CN115987727B - Signal transmission methods and devices - Google Patents

The application provides a signal transmission method and a signal transmission device, which can improve the accuracy of training a decision feedback equalizer, thereby improving the communication quality. The method comprises the following steps: receiving a signal from a transmitting end, wherein the signal comprises an actual receiving signal of a sample signal and a service signal; training a decision feedback equalizer based on the actual received signal and the sample signal; in the training process, according to a first change trend of an error between a processing result of the actual received signal by the decision feedback equalizer and a sample signal and a first corresponding relation, determining an adjustment coefficient of a parameter of the decision feedback equalizer, wherein the first corresponding relation comprises a plurality of change trends and a corresponding relation between a plurality of adjustment coefficients, and the plurality of change trends comprise a first change trend; based on the adjustment coefficient, adjusting the parameters of the decision feedback equalizer, and continuously training the decision feedback equalizer; and carrying out interference elimination processing on the service signal by utilizing the trained decision feedback equalizer.

信号传输方法和装置Signal transmission methods and devices

技术领域Technical field

本申请涉及通信技术领域，尤其涉及一种信号传输方法和装置。The present application relates to the field of communication technology, and in particular, to a signal transmission method and device.

背景技术Background technique

发送端向接收端传输信号的过程中，例如802.11b规定的基带信号，存在多径信号码间干扰。接收端通过判决反馈均衡器，能够减小该多径信号码间干扰，从而提高发送端和接收端之间的通信质量。接收端通过判决反馈均衡器消除多径信号码间干扰前，需要通过样本信号对判决反馈均衡器进行训练，从而确定判决反馈均衡器的参数取值。In the process of transmitting signals from the transmitting end to the receiving end, such as the baseband signal specified by 802.11b, there is multipath signal inter-code interference. The receiving end can reduce the inter-code interference of the multipath signal through the decision feedback equalizer, thereby improving the communication quality between the sending end and the receiving end. Before the receiving end uses the decision feedback equalizer to eliminate multipath signal inter-code interference, it needs to train the decision feedback equalizer through sample signals to determine the parameter values of the decision feedback equalizer.

目前，判决反馈均衡器训练过程中，判决反馈均衡器的参数取值会根据判决反馈均衡器的输出值和期望值之间的误差不断改变，直至判决反馈均衡器的输出值和期望值之间的误差趋近于0。Currently, during the training process of the decision feedback equalizer, the parameter values of the decision feedback equalizer will continue to change according to the error between the output value of the decision feedback equalizer and the expected value, until the error between the output value of the decision feedback equalizer and the expected value approaches 0.

然而，目前判决反馈均衡器训练的准确率较低，接收端接收的数据包的误包率较高，导致发送端和接收端之间的通信质量较差，影响用户体验。However, the current accuracy of decision feedback equalizer training is low, and the packet error rate of data packets received by the receiving end is high, resulting in poor communication quality between the sending end and the receiving end, affecting the user experience.

发明内容Contents of the invention

本申请提供一种信号传输方法和装置，能够提高判决反馈均衡器训练的准确率，降低接收端接收的数据包的误包率，从而提高发送端和接收端之间的通信质量，提高用户体验感。This application provides a signal transmission method and device that can improve the accuracy of decision feedback equalizer training and reduce the packet error rate of data packets received by the receiving end, thereby improving the communication quality between the sending end and the receiving end and improving the user experience. feel.

第一方面，提供一种信号传输方法，包括：接收来自发送端的信号，所述信号包括样本信号的实际接收信号和业务信号；基于所述实际接收信号和所述样本信号，对判决反馈均衡器进行训练；在训练过程中，根据所述判决反馈均衡器对所述实际接收信号的处理结果和所述样本信号之间误差的第一变化趋势和第一对应关系，确定所述判决反馈均衡器的参数的调整系数，所述第一对应关系包括多个变化趋势和多个调整系数之间的对应关系，所述多个变化趋势包括所述第一变化趋势；基于所述调整系数，对所述判决反馈均衡器的参数进行调整，并继续对所述判决反馈均衡器进行训练；利用训练完成的所述判决反馈均衡器，对所述业务信号进行干扰消除处理。In a first aspect, a signal transmission method is provided, including: receiving a signal from a transmitting end, the signal including an actual received signal of a sample signal and a service signal; based on the actual received signal and the sample signal, a decision feedback equalizer is Perform training; during the training process, determine the decision feedback equalizer according to the first changing trend and the first correspondence relationship between the processing result of the actual received signal by the decision feedback equalizer and the error between the sample signal The adjustment coefficient of the parameter, the first correspondence relationship includes a correspondence relationship between a plurality of change trends and a plurality of adjustment coefficients, the plurality of change trends include the first change trend; based on the adjustment coefficient, the Adjust the parameters of the decision feedback equalizer and continue to train the decision feedback equalizer; use the trained decision feedback equalizer to perform interference elimination processing on the service signal.

本申请的信号传输方法，通过在判决反馈均衡器的训练过程中，不断根据累计预设数量的判决反馈均衡器对实际接收信号的处理结果和样本信号之间的误差，确定误差的变化趋势，并进一步根据该变化趋势调整判决反馈均衡器的参数的调整系数，使得接收端能够根据误差的变化趋势实时调整判决反馈均衡器的参数，这样，在判决反馈均衡器的实际接收信号的数量相同的情况下，能够降低判决反馈均衡器对实际接收信号的处理结果和样本信号之间的误差，提高判决反馈均衡器的准确率，从而提高发送端和接收端之间的通信质量，提高用户体验感。The signal transmission method of this application continuously determines the changing trend of the error based on the error between the actual received signal processing results of the cumulative preset number of decision feedback equalizers and the sample signal during the training process of the decision feedback equalizer. And further adjust the adjustment coefficients of the parameters of the decision feedback equalizer according to the changing trend, so that the receiving end can adjust the parameters of the decision feedback equalizer in real time according to the changing trend of the error. In this way, when the number of actual received signals of the decision feedback equalizer is the same In this case, the error between the processing result of the actual received signal by the decision feedback equalizer and the sample signal can be reduced, and the accuracy of the decision feedback equalizer can be improved, thereby improving the communication quality between the sending end and the receiving end and improving the user experience. .

应理解，发送端向接收端发送的信号可以为802.11b所规定的基带信号。样本信号可以指发送端和接收端约定的用于接收端对判决反馈均衡器进行训练的数据信息，即发送端向接收端发送的信号中包括样本信号。样本信号的实际接收信号指终端设备实际接收到的样本信号。判决反馈均衡器在对接收端实际接收信号进行干扰消除处理后，得到的输出结果与样本信号之间存在误差，基于该误差对判决反馈均衡器进行训练。对判决反馈均衡器进行训练的过程即不断调整判决反馈均衡器的参数过程。It should be understood that the signal sent by the transmitting end to the receiving end may be a baseband signal specified by 802.11b. The sample signal may refer to the data information agreed upon by the transmitting end and the receiving end for the receiving end to train the decision feedback equalizer, that is, the signal sent by the transmitting end to the receiving end includes the sample signal. The actual received signal of the sample signal refers to the sample signal actually received by the terminal device. After the decision feedback equalizer performs interference elimination processing on the actual received signal at the receiving end, there is an error between the output result and the sample signal. Based on this error, the decision feedback equalizer is trained. The process of training the decision feedback equalizer is the process of continuously adjusting the parameters of the decision feedback equalizer.

在第一方面的某些实现方式中，所述方法还包括：将所述实际接收信号输入至所述判决反馈均衡器，得到所述实际接收信号的处理结果；确定所述实际接收信号的处理结果和所述样本信号之间的误差；基于所述误差，确定所述第一变化趋势。In some implementations of the first aspect, the method further includes: inputting the actual received signal to the decision feedback equalizer to obtain a processing result of the actual received signal; determining the processing of the actual received signal The error between the result and the sample signal; based on the error, the first change trend is determined.

应理解，实际接收信号的处理结果和样本信号之间的误差可以指实际接收信号的处理结果和样本信号之间的差值。第一变化趋势指误差的变化趋势，因此，第一变化趋势是根据至少两个误差确定的。It should be understood that the error between the processing result of the actual received signal and the sample signal may refer to the difference between the processing result of the actual received signal and the sample signal. The first change trend refers to the change trend of errors. Therefore, the first change trend is determined based on at least two errors.

在第一方面的某些实现方式中，所述基于所述误差，确定所述第一变化趋势，包括：每当所述误差的数量积累到第一预设数量时，对所述第一预设数量的所述误差进行均值滤波处理，得到多个平滑误差；根据所述多个平滑误差中每两个相邻平滑误差之间的差值，确定所述多个平滑误差中每两个相邻平滑误差的局部变化趋势，所述局部变化趋势包括上升趋势和下降趋势；根据所述上升趋势的数量和所述下降趋势的数量，确定所述第一变化趋势。In some implementations of the first aspect, determining the first change trend based on the error includes: whenever the number of errors accumulates to a first preset number, Suppose that a number of the errors are subjected to mean filtering processing to obtain a plurality of smoothing errors; according to the difference between every two adjacent smoothing errors in the plurality of smoothing errors, each two phase-matching errors in the plurality of smoothing errors are determined. The local change trend of the adjacent smoothing error, the local change trend includes an upward trend and a downward trend; the first change trend is determined according to the number of the upward trends and the number of the downward trends.

应理解，第一预设数量可以为任意正整数，例如5个、10个等。对第一预设数量的误差进行均值滤波处理可以指将第一预设数量的误差取平均值，该平均值即为平滑误差。在接收端开始判决反馈均衡器的训练后，接收端每向判决反馈均衡器输入一次实际接收信号，接收端均会有相应的处理结果，根据处理结果和样本信号，能够确定一个误差。判决反馈均衡器的训练过程中，接收端不断将实际接收信号输入判决反馈均衡器，会不断的得到误差。每当误差的数量积累到第一预设数量时，接收端均会确定该第一预设数量的误差的平均值，从而得到一个平滑误差。随着误差的积累数量的进一步增多，平滑误差的数量也会不断增长。It should be understood that the first preset number can be any positive integer, such as 5, 10, etc. Performing mean filtering on the first preset number of errors may refer to averaging the first preset number of errors, and the average is the smoothing error. After the receiving end starts training the decision feedback equalizer, every time the receiving end inputs an actual received signal to the decision feedback equalizer, the receiving end will have corresponding processing results. Based on the processing results and sample signals, an error can be determined. During the training process of the decision feedback equalizer, the receiving end continuously inputs the actual received signal into the decision feedback equalizer, and errors will continue to be obtained. Whenever the number of errors accumulates to a first preset number, the receiving end determines the average value of the first preset number of errors, thereby obtaining a smooth error. As the accumulated number of errors further increases, the number of smoothing errors will also continue to grow.

在第一方面的某些实现方式中，所述根据所述上升趋势的数量和所述下降趋势的数量，确定所述第一变化趋势，包括：若所述上升趋势的数量大于所述下降趋势的数量，则将所述第一变化趋势确定为上升趋势；或者，若所述上升趋势的数量等于所述下降趋势的数量，则将所述第一变化趋势确定为稳定趋势；或者，若所述上升趋势的数量小于所述下降趋势的数量，则将所述第一变化趋势确定为下降趋势。In some implementations of the first aspect, determining the first change trend based on the number of the upward trends and the number of the downward trends includes: if the number of the upward trends is greater than the number of the downward trends The number of the first change trend is determined to be an upward trend; or, if the number of the upward trends is equal to the number of the downward trends, the first change trend is determined to be a stable trend; or, if the number of the upward trends is equal to the number of the downward trends, the first change trend is determined to be a stable trend; or, if If the number of the upward trends is less than the number of the downward trends, the first change trend is determined as a downward trend.

应理解，第一变化趋势包括上升趋势、下降趋势和稳定趋势。第一变化趋势是根据局部变化趋势中的上升趋势和下降趋势的数量确定的，这样，能够更高效的确定误差的变化趋势，从而有助于提高判决反馈均衡器训练的效率和准确率。It should be understood that the first change trend includes an upward trend, a downward trend and a stable trend. The first change trend is determined based on the number of upward trends and downward trends in the local change trend. In this way, the change trend of the error can be determined more efficiently, thereby helping to improve the efficiency and accuracy of decision feedback equalizer training.

在第一方面的某些实现方式中，所述根据所述上升趋势的数量和所述下降趋势的数量，确定所述第一变化趋势，包括：当所述多个平滑误差的数量积累到第二预设数量时，根据所述上升趋势的数量和所述下降趋势的数量，确定所述第一变化趋势。In some implementations of the first aspect, determining the first change trend according to the number of the upward trends and the number of the downward trends includes: when the number of the plurality of smoothing errors accumulates to a third When there are two preset numbers, the first change trend is determined based on the number of upward trends and the number of downward trends.

应理解，第二预设数量可以为任意正整数，例如可以为3个、9个等。示例性地，第二预设数量为6个，则接收端每确定6个平滑误差后，根据该6个平滑误差中每两个相邻平滑误差确定5个局部变化趋势，在该5个局部变化趋势中，根据上升趋势的数量和下降趋势的数量，确定第一变化趋势。It should be understood that the second preset number can be any positive integer, for example, it can be 3, 9, etc. For example, if the second preset number is 6, then every time the receiving end determines 6 smoothing errors, it will determine 5 local changing trends based on each two adjacent smoothing errors among the 6 smoothing errors. Among the changing trends, the first changing trend is determined based on the number of upward trends and the number of downward trends.

在第一方面的某些实现方式中，所述第一变化趋势是基于所述实际接收信号中的第一部分信号得到的；在所述基于所述调整系数，对所述判决反馈均衡器的参数进行调整之后，所述方法还包括：确定调整后的所述判决反馈均衡器对所述实际接收信号中的第二部分信号的处理结果和所述样本信号之间误差的第二变化趋势；基于所述第二变化趋势和所述第一对应关系，确定所述判决反馈均衡器的参数的再次调整系数；基于所述再次调整系数，对所述判决反馈均衡器的参数进行再次调整，并继续对所述判决反馈均衡器进行训练。In some implementations of the first aspect, the first change trend is obtained based on the first part of the actual received signal; based on the adjustment coefficient, the parameters of the decision feedback equalizer are After the adjustment, the method further includes: determining a second changing trend of the error between the adjusted processing result of the second part of the signal in the actual received signal by the decision feedback equalizer and the sample signal; based on The second changing trend and the first corresponding relationship determine the re-adjustment coefficient of the parameters of the decision feedback equalizer; based on the re-adjustment coefficient, re-adjust the parameters of the decision feedback equalizer, and continue The decision feedback equalizer is trained.

应理解，实际接收信号中的第一部分信号、第二部分信号可以为实际接收信号中的部分信号，也可以为实际接收信号中的全部信号。在第一部分信号、第二部分信号为实际接收信号中的部分信号时，实际接收信号还可以包括第三部分信号、第四部分信号等。第二变化趋势也可以为上升趋势、下降趋势或稳定趋势中的一个。接收端可以根据与确定第一变化趋势相同的方法确定第二变化趋势。上述步骤是不断循环进行的，直至满足预设停止条件。It should be understood that the first part signal and the second part signal in the actual received signal may be part of the actual received signal, or may be all signals in the actual received signal. When the first part signal and the second part signal are part of the actual received signal, the actual received signal may also include a third part signal, a fourth part signal, etc. The second change trend can also be one of an upward trend, a downward trend or a stable trend. The receiving end may determine the second change trend according to the same method as determining the first change trend. The above steps are performed continuously in a loop until the preset stopping conditions are met.

第二方面，提供了一种信号传输装置，用于执行上述第一方面中任一种可能的实现方式中的方法。具体地，该装置包括用于执行上述第一方面中任一种可能的实现方式中的方法的模块。A second aspect provides a signal transmission device for performing the method in any possible implementation of the first aspect. Specifically, the device includes a module for executing the method in any possible implementation of the first aspect.

第三方面，本申请提供了又一种信号传输装置，包括处理器，该处理器与存储器耦合，可用于执行存储器中的指令，以实现上述第一方面中任一种可能实现方式中的方法。可选地，该装置还包括存储器。可选地，该装置还包括通信接口，处理器与通信接口耦合。In a third aspect, the present application provides yet another signal transmission device, including a processor, which is coupled to a memory and can be used to execute instructions in the memory to implement the method in any of the possible implementations of the first aspect. . Optionally, the device further includes memory. Optionally, the device further includes a communication interface, and the processor is coupled to the communication interface.

在一种实现方式中，该装置为终端设备。当该装置为终端设备时，上述通信接口可以是收发器，或，输入/输出接口。In one implementation, the device is a terminal device. When the device is a terminal device, the communication interface may be a transceiver, or an input/output interface.

在另一种实现方式中，该装置为配置于终端设备中的芯片。当该装置为配置于终端设备中的芯片时，上述通信接口可以是输入/输出接口。In another implementation, the device is a chip configured in a terminal device. When the device is a chip configured in a terminal device, the communication interface may be an input/output interface.

第四方面，提供了一种处理器，包括：输入电路、输出电路和处理电路。所述处理电路用于通过所述输入电路接收信号，并通过所述输出电路发射信号，使得所述处理器执行上述第一方面中任一种可能实现方式中的方法。In the fourth aspect, a processor is provided, including: an input circuit, an output circuit and a processing circuit. The processing circuit is configured to receive a signal through the input circuit and transmit a signal through the output circuit, so that the processor executes the method in any of the possible implementations of the first aspect.

在具体实现流程中，上述处理器可以为芯片，输入电路可以为输入管脚，输出电路可以为输出管脚，处理电路可以为晶体管、门电路、触发器和各种逻辑电路等。输入电路所接收的输入的信号可以是由例如但不限于接收器接收并输入的，输出电路所输出的信号可以是例如但不限于输出给发射器并由发射器发射的，且输入电路和输出电路可以是同一电路，该电路在不同的时刻分别用作输入电路和输出电路。本申请实施例对处理器及各种电路的具体实现方式不做限定。In the specific implementation process, the above-mentioned processor can be a chip, the input circuit can be an input pin, the output circuit can be an output pin, and the processing circuit can be a transistor, a gate circuit, a flip-flop, and various logic circuits. The input signal received by the input circuit may be received and input by, for example, but not limited to, the receiver, and the signal output by the output circuit may be, for example, but not limited to, output to and transmitted by the transmitter, and the input circuit and the output A circuit may be the same circuit that functions as an input circuit and an output circuit at different times. The embodiments of this application do not limit the specific implementation methods of the processor and various circuits.

第五方面，提供了一种处理装置，包括处理器和存储器。该处理器用于读取存储器中存储的指令，并可通过接收器接收信号，通过发射器发射信号，以执行上述第一方面中任一种可能实现方式中的方法。In a fifth aspect, a processing device is provided, including a processor and a memory. The processor is used to read instructions stored in the memory, and can receive signals through a receiver and transmit signals through a transmitter to execute the method in any of the possible implementations of the first aspect.

可选地，所述处理器为一个或多个，所述存储器为一个或多个。Optionally, there are one or more processors and one or more memories.

可选地，所述存储器可以与所述处理器集成在一起，或者所述存储器与处理器分离设置。Alternatively, the memory may be integrated with the processor, or the memory may be provided separately from the processor.

在具体实现流程中，存储器可以为非瞬时性（non-transitory）存储器，例如只读存储器（read only memory，ROM），其可以与处理器集成在同一块芯片上，也可以分别设置在不同的芯片上，本申请对存储器的类型以及存储器与处理器的设置方式不做限定。In the specific implementation process, the memory can be a non-transitory memory, such as a read only memory (ROM), which can be integrated on the same chip as the processor, or can be set in different On the chip, this application does not limit the type of memory and the arrangement of the memory and the processor.

应理解，相关的数据交互流程例如发送指示信息可以为从处理器输出指示信息的流程，接收能力信息可以为处理器接收输入能力信息的流程。具体地，处理输出的数据可以输出给发射器，处理器接收的输入数据可以来自接收器。其中，发射器和接收器可以统称为收发器。It should be understood that the relevant data interaction process, for example, sending instruction information may be a process of outputting instruction information from the processor, and receiving capability information may be a process of the processor receiving input capability information. Specifically, the data output by the processing can be output to the transmitter, and the input data received by the processor can come from the receiver. Among them, the transmitter and receiver can be collectively called a transceiver.

上述第五方面中的处理装置可以是一个芯片，该处理器可以通过硬件来实现也可以通过软件来实现，当通过硬件实现时，该处理器可以是逻辑电路、集成电路等；当通过软件来实现时，该处理器可以是一个通用处理器，通过读取存储器中存储的软件代码来实现，该存储器可以集成在处理器中，可以位于该处理器之外，独立存在。The processing device in the above fifth aspect can be a chip, and the processor can be implemented by hardware or software. When implemented by hardware, the processor can be a logic circuit, an integrated circuit, etc.; when implemented by software, When implemented, the processor can be a general-purpose processor, which is implemented by reading the software code stored in the memory. The memory can be integrated in the processor, or can be located outside the processor and exist independently.

第六方面，提供了一种计算机程序产品，所述计算机程序产品包括：计算机程序（也可以称为代码，或指令），当所述计算机程序被运行时，使得计算机执行上述第一方面中任一种可能实现方式中的方法。In a sixth aspect, a computer program product is provided. The computer program product includes: a computer program (which may also be called a code, or an instruction). When the computer program is run, it causes the computer to execute any of the above-mentioned aspects of the first aspect. A method among possible implementations.

第七方面，提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序（也可以称为代码，或指令）当其在计算机上运行时，使得计算机执行上述第一方面中任一种可能实现方式中的方法。In a seventh aspect, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program (which may also be called a code, or an instruction), and when run on a computer, causes the computer to execute the above-mentioned first aspect. method in any of the possible implementations.

附图说明Description of the drawings

图1为本申请实施例应用的一种通信系统；Figure 1 is a communication system applied in the embodiment of the present application;

图2为判决反馈均衡器进行干扰消除处理的过程示意图；Figure 2 is a schematic diagram of the process of interference elimination processing by the decision feedback equalizer;

图3为判决反馈均衡器的训练过程示意图；Figure 3 is a schematic diagram of the training process of the decision feedback equalizer;

图4为判决反馈均衡器训练过程中的误差的收敛趋势示意图；Figure 4 is a schematic diagram of the convergence trend of the error during the training process of the decision feedback equalizer;

图5为本申请实施例提供的信号传输方法的流程示意图；Figure 5 is a schematic flowchart of a signal transmission method provided by an embodiment of the present application;

图6为本申请实施例提供的均值滤波处理前后误差的收敛趋势示意图；Figure 6 is a schematic diagram of the convergence trend of errors before and after mean filtering provided by the embodiment of the present application;

图7为本申请实施例提供的一种调整系数适应性调整和无调整系数时对应的误差收敛的对比示意图；Figure 7 is a schematic diagram comparing the adaptive adjustment of an adjustment coefficient and the corresponding error convergence when there is no adjustment coefficient provided by the embodiment of the present application;

图8为本申请实施例提供的另一种调整系数适应性调整和无调整系数时对应的平滑误差收敛的对比示意图；Figure 8 is a schematic diagram comparing the adaptive adjustment of another adjustment coefficient and the corresponding smoothing error convergence when there is no adjustment coefficient provided by the embodiment of the present application;

图9为本申请实施例提供的又一种调整系数适应性调整和无调整系数时对应的平滑误差收敛的对比示意图；Figure 9 is a comparative schematic diagram of another adaptive adjustment of the adjustment coefficient and the corresponding smoothing error convergence when there is no adjustment coefficient provided by the embodiment of the present application;

图10为本申请实施例提供的不同样本信号下调整系数适应性调整和无调整系数时对应的平滑误差收敛的对比示意图；Figure 10 is a schematic diagram comparing the adaptive adjustment of the adjustment coefficient and the corresponding smoothing error convergence when there is no adjustment coefficient under different sample signals provided by the embodiment of the present application;

图11为本申请实施例提供的调整系数适应性调整和无调整系数时对应的误包率和信噪比的关系曲线示意图；Figure 11 is a schematic diagram of the relationship curve between the packet error rate and the signal-to-noise ratio when the adjustment coefficient is adaptively adjusted and when there is no adjustment coefficient provided by the embodiment of the present application;

图12为本申请实施例提供的一种信号传输装置的结构示意图；Figure 12 is a schematic structural diagram of a signal transmission device provided by an embodiment of the present application;

图13为本申请实施例提供的另一种信号传输装置的结构示意图。Figure 13 is a schematic structural diagram of another signal transmission device provided by an embodiment of the present application.

具体实施方式Detailed ways

下面将结合附图，对本申请中的技术方案进行描述。The technical solutions in this application will be described below with reference to the accompanying drawings.

在本申请的实施例中，采用了“第一”、“第二”等字样对功能和作用基本相同的相同项或相似项进行区分。例如，第一数值和第二数值仅仅是为了区分不同的数值，并不对其先后顺序进行限定。本领域技术人员可以理解“第一”、“第二”等字样并不对数量和执行次序进行限定，并且“第一”、“第二”等字样也并不限定一定不同。In the embodiments of the present application, words such as “first” and “second” are used to distinguish identical or similar items with basically the same functions and effects. For example, the first numerical value and the second numerical value are only used to distinguish different numerical values, and their order is not limited. Those skilled in the art can understand that words such as "first" and "second" do not limit the number and execution order, and words such as "first" and "second" do not limit the number and execution order.

需要说明的是，本申请实施例中，“示例性地”或者“例如”等词用于表示作例子、例证或说明。本申请中被描述为“示例性地”或者“例如”的任何实施例或设计方案不应被解释为比其他实施例或设计方案更优选或更具优势。确切而言，使用“示例性地”或者“例如”等词旨在以具体方式呈现相关概念。It should be noted that in the embodiments of this application, words such as "exemplarily" or "for example" are used to represent examples, illustrations or explanations. Any embodiment or design described herein as "exemplary" or "such as" is not intended to be construed as preferred or advantageous over other embodiments or designs. Rather, the use of the words "exemplarily" or "for example" is intended to present the relevant concepts in a concrete manner.

本申请实施例中，“至少一个”是指一个或者多个，“多个”是指两个或两个以上。“和/或”，描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B的情况，其中A，B可以是单数或者复数。字符“/”一般表示前后关联对象是一种“或”的关系。“以下至少一项（个）”或其类似表达，是指的这些项中的任意组合，包括单项（个）或复数项（个）的任意组合。例如，a，b，或c中的至少一项（个），可以表示：a，b，c，a-b，a--c，b-c，或a-b-c，其中a，b，c可以是单个，也可以是多个。In the embodiments of this application, "at least one" refers to one or more, and "multiple" refers to two or more. "And/or" describes the association of associated objects, indicating that there can be three relationships, for example, A and/or B, which can mean: A exists alone, A and B exist simultaneously, and B exists alone, where A, B can be singular or plural. The character "/" generally indicates that the related objects are in an "or" relationship. “At least one of the following” or similar expressions refers to any combination of these items, including any combination of single items (items) or plural items (items). For example, at least one of a, b, or c can mean: a, b, c, a-b, a--c, b-c, or a-b-c, where a, b, c can be single, or It's multiple.

本申请实施例的技术方案可以应用于各种通信系统，例如：长期演进（long termevolution，LTE）系统、LTE频分双工（frequency division duplex，FDD）系统、LTE时分双工（time division duplex，TDD）、通用移动通信系统（universalmobile telecommunicationsystem，UMTS）、全球互联微波接入（worldwide interoperability for microwaveaccess，WiMAX）通信系统、第五代（5th generation，5G）系统或新无线（new radio，NR）、802.11b规定的无线局域网通信系统、未来可能出现的新系统等。The technical solutions of the embodiments of the present application can be applied to various communication systems, such as: long term evolution (LTE) system, LTE frequency division duplex (FDD) system, LTE time division duplex (time division duplex, TDD), universal mobile telecommunication system (UMTS), global interoperability for microwave access (WiMAX) communication system, fifth generation (5th generation, 5G) system or new radio (NR), Wireless LAN communication systems specified by 802.11b, new systems that may appear in the future, etc.

本申请实施例中的终端设备也可以称为：用户设备（user equipment，UE）、移动台（mobile station，MS）、移动终端（mobile terminal，MT）、接入终端、用户单元、用户站、移动站、移动台、远方站、远程终端、移动设备、用户终端、终端、无线通信设备、用户代理或用户装置等。The terminal equipment in the embodiment of this application may also be called: user equipment (UE), mobile station (MS), mobile terminal (MT), access terminal, user unit, user station, Mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication equipment, user agent or user device, etc.

终端设备可以是一种向用户提供语音/数据连通性的设备，例如，具有无线连接功能的手持式设备、车载设备等。目前，一些终端设备的举例包括：手机（mobile phone）、平板电脑、笔记本电脑、掌上电脑、移动互联网设备（mobile internetdevice，MID）、可穿戴设备，虚拟现实（virtual reality，VR）设备、增强现实（augmentedreality，AR）设备、工业控制（industrial control）中的无线终端、无人驾驶（self driving）中的无线终端、远程手术（remote medical surgery）中的无线终端、智能电网（smartgrid）中的无线终端、运输安全（transportation safety）中的无线终端、智慧城市（smart city）中的无线终端、智慧家庭（smart home）中的无线终端、蜂窝电话、无绳电话、会话启动协议（sessioninitiationprotocol，SIP）电话、无线本地环路（wireless local loop，WLL）站、个人数字助理（personal digital assistant，PDA）、具有无线通信功能的手持设备、计算设备或连接到无线调制解调器的其它处理设备、车载设备、可穿戴设备，5G网络中的终端设备或者未来演进的公用陆地移动通信网络（public land mobile network，PLMN）中的终端设备等，本申请对此并不限定。The terminal device may be a device that provides voice/data connectivity to the user, such as a handheld device, a vehicle-mounted device, etc. with wireless connectivity capabilities. Currently, some examples of terminal devices include: mobile phones, tablets, laptops, PDAs, mobile internet devices (MID), wearable devices, virtual reality (VR) devices, augmented reality (augmentedreality, AR) equipment, wireless terminals in industrial control (industrial control), wireless terminals in self-driving (self driving), wireless terminals in remote medical surgery, wireless terminals in smart grids (smartgrid) Terminals, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, cellular phones, cordless phones, session initiation protocol (SIP) phones , wireless local loop (WLL) station, personal digital assistant (PDA), handheld device with wireless communication capabilities, computing device or other processing device connected to a wireless modem, vehicle-mounted device, wearable Equipment, terminal equipment in the 5G network or terminal equipment in the future evolved public land mobile communication network (public land mobile network, PLMN), etc. This application is not limited to this.

作为示例而非限定，在本申请中，终端设备可以是物联网（internet of things，IoT）系统中的终端设备。物联网是未来信息技术发展的重要组成部分，其主要技术特点是将物品通过通信技术与网络连接，从而实现人机互连，物物互连的智能化网络。示例性地，本申请实施例中的终端设备可以是可穿戴设备。可穿戴设备也可以称为穿戴式智能设备，是应用穿戴式技术对日常穿戴进行智能化设计、开发出可以穿戴的设备的总称，如眼镜、手套、手表、服饰及鞋等。可穿戴设备是可以直接穿在身上，或是整合到用户的衣服或配件的一种便携式设备。可穿戴设备不仅仅是一种硬件设备，更可以通过软件支持以及数据交互、云端交互来实现强大的功能。广义穿戴式智能设备包括功能全、尺寸大、可不依赖智能手机实现完整或者部分的功能，例如：智能手表或智能眼镜等，以及只专注于某一类应用功能，需要和其它设备如智能手机配合使用，如各类进行体征监测的智能手环、智能首饰等。As an example and not a limitation, in this application, the terminal device may be a terminal device in an Internet of Things (IoT) system. The Internet of Things is an important part of the future development of information technology. Its main technical feature is to connect objects to the network through communication technology, thereby realizing an intelligent network of human-computer interconnection and object-object interconnection. For example, the terminal device in the embodiment of the present application may be a wearable device. Wearable devices can also be called wearable smart devices. It is a general term for applying wearable technology to intelligently design daily wear and develop wearable devices, such as glasses, gloves, watches, clothing and shoes, etc. A wearable device is a portable device that can be worn directly on the body or integrated into the user's clothing or accessories. Wearable devices are not just hardware devices, but can also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly defined wearable smart devices include full-featured, large-sized devices that can achieve complete or partial functions without relying on smartphones, such as smart watches or smart glasses, and those that only focus on a certain type of application function and need to cooperate with other devices such as smartphones. Use, such as various types of smart bracelets, smart jewelry, etc. for physical sign monitoring.

作为示例而非限定，在本申请实施例中，终端设备还可以是机器类型通信（machine type communication，MTC）中的终端设备。此外，终端设备还可以是作为一个或多个部件或者单元而内置于车辆的车载模块、车载模组、车载部件、车载芯片或者车载单元等，车辆通过内置的所述车载模块、车载模组、车载部件、车载芯片或者车载单元等可以实施本申请提供的方法。因此，本申请实施例也可以应用于车联网，例如车辆外联（vehicleto everything，V2X）、车间通信长期演进技术（longterm evolution-vehicle，LTE-V）、车到车（vehicle-to-vehicle，V2V）技术等。As an example and not a limitation, in the embodiment of the present application, the terminal device may also be a terminal device in machine type communication (machine type communication, MTC). In addition, the terminal device may also be a vehicle-mounted module, vehicle-mounted module, vehicle-mounted component, vehicle-mounted chip or vehicle-mounted unit that is built into the vehicle as one or more components or units. The vehicle uses the built-in vehicle-mounted module, vehicle-mounted module, Vehicle-mounted components, vehicle-mounted chips, or vehicle-mounted units can implement the method provided by this application. Therefore, the embodiments of the present application can also be applied to the Internet of Vehicles, such as vehicle to everything (V2X), vehicle-to-vehicle communication long-term evolution technology (longterm evolution-vehicle, LTE-V), vehicle-to-vehicle (vehicle-to-vehicle, V2V) technology, etc.

本申请涉及的网络设备可以是与终端设备通信的设备，该网络设备也可以称为接入网设备或无线接入网设备，它可以是传输接收点（transmission reception point，TRP），还可以是LTE系统中的演进型基站（evolved NodeB，eNB或eNodeB），还可以是家庭基站（例如，home evolved NodeB，或homeNode B，HNB）、基带单元（base band unit，BBU），还可以是云无线接入网络（cloudradio access network，CRAN）场景下的无线控制器，或者该网络设备可以为中继站、接入点、车载设备、可穿戴设备以及5G网络中的网络设备或者未来演进的PLMN网络中的网络设备等，还可以是WLAN中的接入点（access point，AP），还可以是NR系统中的gNB，上述网络设备还可以是城市基站、微基站、微微基站、毫微微基站等等，本申请对此不做限定。The network device involved in this application may be a device that communicates with a terminal device. The network device may also be called an access network device or a wireless access network device. It may be a transmission reception point (TRP), or it may be The evolved base station (evolved NodeB, eNB or eNodeB) in the LTE system can also be a home base station (for example, home evolved NodeB, or homeNode B, HNB), a base band unit (BBU), or a cloud wireless Wireless controller in the access network (cloudradio access network, CRAN) scenario, or the network device can be a relay station, access point, vehicle-mounted device, wearable device, network device in the 5G network or in the future evolved PLMN network Network equipment, etc., can also be access point (AP) in WLAN, or gNB in NR system. The above network equipment can also be urban base station, micro base station, pico base station, femto base station, etc. This application does not limit this.

在一种网络结构中，网络设备可以包括集中单元（centralized unit，CU）节点、或分布单元（distributed unit，DU）节点、或包括CU节点和DU节点的RAN设备、或者控制面CU节点（CU-CP节点)和用户面CU节点（CU-UP节点）以及DU节点的RAN设备。In a network structure, the network device may include a centralized unit (CU) node, a distributed unit (DU) node, or a RAN device including a CU node and a DU node, or a control plane CU node (CU). -CP node) and user plane CU node (CU-UP node) and RAN equipment of DU node.

网络设备为小区提供服务，终端设备通过网络设备分配的传输资源（例如，频域资源，或者说，频谱资源）与小区进行通信，该小区可以属于宏基站（例如，宏eNB或宏gNB等），也可以属于小小区（small cell）对应的基站，这里的小小区可以包括：城市小区（metrocell）、微小区（micro cell）、微微小区（pico cell）、毫微微小区（femtocell）等，这些小小区具有覆盖范围小、发射功率低的特点，适用于提供高速率的数据传输服务。The network equipment provides services for the cell, and the terminal equipment communicates with the cell through the transmission resources (for example, frequency domain resources, or spectrum resources) allocated by the network equipment. The cell can belong to a macro base station (for example, macro eNB or macro gNB, etc.) , or it can belong to the base station corresponding to a small cell. The small cell here can include: urban cell (metrocell), micro cell (micro cell), pico cell (pico cell), femtocell (femtocell), etc., these Small cells have the characteristics of small coverage and low transmission power, and are suitable for providing high-rate data transmission services.

为便于理解本申请实施例，首先结合图1对适用于本申请实施例的通信系统进行详细说明。In order to facilitate understanding of the embodiments of the present application, the communication system applicable to the embodiments of the present application is first described in detail with reference to FIG. 1 .

图1示出了本申请实施例应用的一种通信系统100。通信系统100可以包括至少一个网络设备，例如图1所示网络设备110；该通信系统100还可以包括至少一个终端设备，例如图1所示的终端设备120。网络设备110与终端设备120可通过无线链路通信。在一种可能的情况下，网络设备110可以作为发送端，终端设备120可以作为接收端，网络设备110向终端设备120发送信号；在另一种可能的情况下，网络设备110可以作为接收端，终端设备120可以作为发送端，终端设备120向网络设备110发送信号。Figure 1 shows a communication system 100 applied in the embodiment of the present application. The communication system 100 may include at least one network device, such as the network device 110 shown in FIG. 1 ; the communication system 100 may also include at least one terminal device, such as the terminal device 120 shown in FIG. 1 . The network device 110 and the terminal device 120 may communicate through wireless links. In one possible case, the network device 110 can serve as the sending end, and the terminal device 120 can serve as the receiving end. The network device 110 sends a signal to the terminal device 120; in another possible case, the network device 110 can serve as the receiving end. , the terminal device 120 can serve as a sending end, and the terminal device 120 sends a signal to the network device 110.

图1示例性地示出了一个网络设备110和一个终端设备120。可选地，该通信系统100还可以包括多个网络设备和/或多个终端设备。网络设备110可以为路由器、基站等，终端设备120可以为手机、平板电脑、智能手环等，本申请实施例对此不做限定。Figure 1 illustrates a network device 110 and a terminal device 120. Optionally, the communication system 100 may also include multiple network devices and/or multiple terminal devices. The network device 110 may be a router, a base station, etc., and the terminal device 120 may be a mobile phone, a tablet computer, a smart bracelet, etc., which are not limited in the embodiments of the present application.

上述各个通信设备，如图1中的网络设备110或终端设备120，可以配置多个天线。该多个天线可以包括至少一个用于发送信号的发射天线和至少一个用于接收信号的接收天线。另外，各通信设备还附加地包括发射机链和接收机链，本领域普通技术人员可以理解，它们均可包括与信号发送和接收相关的多个部件（例如处理器、调制器、复用器、解调器、解复用器或天线等）。因此，网络设备110与终端设备120之间可通过多天线技术通信。Each of the above communication devices, such as the network device 110 or the terminal device 120 in Figure 1, can be configured with multiple antennas. The plurality of antennas may include at least one transmit antenna for transmitting signals and at least one receive antenna for receiving signals. In addition, each communication device additionally includes a transmitter chain and a receiver chain. Those of ordinary skill in the art can understand that they may include multiple components related to signal transmission and reception (such as processors, modulators, multiplexers). , demodulator, demultiplexer or antenna, etc.). Therefore, the network device 110 and the terminal device 120 can communicate through the multi-antenna technology.

可选地，上述通信系统100还可以包括网络控制器、移动管理实体等其他网络实体，本申请实施例不限于此。Optionally, the above-mentioned communication system 100 may also include other network entities such as a network controller and a mobility management entity, and the embodiments of the present application are not limited thereto.

发送端与接收端之间的信号传输质量将直接影响终端用户的体验。由于发送端向接收端发送的信号，例如802.11b规定的基带信号，受到多径信号码间干扰，使得接收端的误包率较高，影响用户体验。示例性地，发送端为WiFi路由器，接收端为手机，手机接收来自WiFi路由器的WiFi信号，在手机接收的WiFi信号受到干扰的情况下，手机与路由器之间的通信质量较差，将影响手机用户的上网体验。The quality of signal transmission between the sender and the receiver will directly affect the end user experience. Since the signal sent from the transmitter to the receiver, such as the baseband signal specified by 802.11b, is subject to multipath signal inter-code interference, the packet error rate at the receiver is high, which affects the user experience. For example, the sending end is a WiFi router and the receiving end is a mobile phone. The mobile phone receives the WiFi signal from the WiFi router. When the WiFi signal received by the mobile phone is interfered, the communication quality between the mobile phone and the router is poor, which will affect the mobile phone. User’s online experience.

为了消除多径信号码间干扰，接收端通常通过判决反馈均衡器，将接收到的混叠的信号恢复成近似单径信号，提高信号传输的准确率，从而降低接收端的误包率。在判决反馈均衡器每次对接收的业务信号进行干扰消除处理前，接收端均会通过样本信号对判决反馈均衡器进行训练。在接收端判决反馈均衡器进行训练的过程中，判决反馈均衡器的参数取值会根据判决反馈均衡器的输出值和期望值之间的误差不断改变，以提高判决反馈均衡器的准确率。In order to eliminate inter-code interference of multipath signals, the receiving end usually uses a decision feedback equalizer to restore the received aliased signal to an approximate single-path signal, thereby improving the accuracy of signal transmission and thereby reducing the packet error rate at the receiving end. Before the decision feedback equalizer performs interference cancellation processing on the received service signal each time, the receiving end will train the decision feedback equalizer through sample signals. During the training process of the decision feedback equalizer at the receiving end, the parameter values of the decision feedback equalizer will continuously change according to the error between the output value of the decision feedback equalizer and the expected value, so as to improve the accuracy of the decision feedback equalizer.

为了便于理解本申请实施例，下面先结合图2至图4对判决反馈均衡器进行干扰消除处理的过程以及判决反馈均衡器的训练过程进行详细说明。In order to facilitate understanding of the embodiments of the present application, the process of interference elimination processing by the decision feedback equalizer and the training process of the decision feedback equalizer will be described in detail below with reference to FIGS. 2 to 4 .

图2为判决反馈均衡器进行干扰消除处理的过程示意图，如图2所示，判决反馈均衡器包括前馈滤波器、反馈滤波器和判决器；干扰消除处理的过程包括过程1、过程2和过程3。Figure 2 is a schematic diagram of the process of interference elimination processing by the decision feedback equalizer. As shown in Figure 2, the decision feedback equalizer includes a feedforward filter, a feedback filter and a decider; the interference elimination process includes process 1, process 2 and Process 3.

过程1中，接收端将n至n+L时刻的离散数据x[n]~x[n+L]输入前馈滤波器中。其中，n为时刻，n≥0；n+L为n时刻之后的时刻，n+L＞n，L为正整数；x[n]~x[n+L]依次分别为n至n+L时刻的离散数据，x[n]~x[n+L]为复数。x[n]~x[n+L]中每个时刻的离散数据分别对应一个参数（W₀~W_-L），例如，x[n]对应的参数为W₀，x[n+L]对应的参数为W_-L，W₀~W_-L为任意有理数。通过前馈滤波器，将x[n]~x[n+L]和W₀~W_-L进行加权求和，消除x[n+1]~x[n+L]对x[n]的串扰，加权求和的公式为x[n]*W₀+x[n+1]*W_-1+x[n+2]*W_-2+…+x[n+L]*W_-L。反馈滤波器存储有n-1至n-M时刻的判决后离散数据d[n-1]~d[n-M]，其中，M为正整数，n-1至n-M均小于n；d[n-1]~d[n-M]依次分别为n-1至n-M时刻的判决后离散数据；d[n-1]~d[n-M]依次分别对应一个参数（W₁~W_M），通过反馈滤波器，将d[n-1]~d[n-M]和W₁~W_M进行加权求和，消除d[n-1]~d[n-M]造成的串扰，该加权求和的公式为d[n-1]*W₁+d[n-2]*W₂+d[n-3]*W₃+…+d[n-M]*W_M。将x[n]~x[n+L]和W₀~W_-L加权求和得到的和与d[n-1]~d[n-M]和W₁~W_M加权求和得到的和进行求和，得到消除码间干扰后的[n]时刻离散数据y[n]。y[n]经过判决器的硬判决处理后，得到n时刻的判决后离散数据d[n]。In process 1, the receiving end inputs the discrete data x[n]~x[n+L] from n to n+L into the feedforward filter. Among them, n is the moment, n≥0; n+L is the moment after n moment, n+L>n, L is a positive integer; x[n]~x[n+L] are n to n+L respectively. Discrete data at time, x[n]~x[n+L] are complex numbers. The discrete data at each moment in x[n]~x[n+L] corresponds to a parameter (W ₀ ~W _-L ). For example, the parameters corresponding to x[n] are W ₀ , x[n+L] The corresponding parameter is W _-L , and W ₀ ~W _-L are any rational numbers. Through the feedforward filter, perform a weighted sum of x[n]~x[n+L] and W ₀ ~W _-L to eliminate the influence of x[n+1]~x[n+L] on x[n] Crosstalk, the formula of weighted summation is x[n]*W ₀ +x[n+1]*W _-1 +x[n+2]*W _-2 +…+x[n+L]*W _-L . The feedback filter stores post-decision discrete data d[n-1]~d[nM] from n-1 to nM moments, where M is a positive integer, n-1 to nM are all less than n; d[n-1] ~d[nM] are respectively the post-decision discrete data at moments n-1 to nM; d[n-1]~d[nM] are respectively corresponding to one parameter (W ₁ ~W _M ) in turn. Through the feedback filter, d[n-1]~d[nM] and W ₁ ~W _M perform weighted summation to eliminate the crosstalk caused by d[n-1]~d[nM]. The formula of the weighted summation is d[n-1 ]*W ₁ +d[n-2]*W ₂ +d[n-3]*W ₃ +…+d[nM]*W _M . The sum obtained by the weighted sum of x[n]~x[n+L] and W ₀ ~W _-L is compared with the sum obtained by the weighted sum of d[n-1]~d[nM] and W ₁ ~W _M Sum up to obtain the discrete data y[n] at time [n] after eliminating inter-code interference. After y[n] undergoes hard decision processing by the decider, the post-decision discrete data d[n] at time n is obtained.

过程2中，接收端将d[n]输入反馈滤波器，并将d[n-1]~d[n-M]向右移位，用于对n+1时刻的离散数据x[n+1]进行干扰消除处理。同时接收端将n+L+1时刻的离散数据x[n+L+1]输入前馈滤波器，并将x[n]~x[n+L]向右移位。In process 2, the receiving end inputs d[n] into the feedback filter and shifts d[n-1]~d[n-M] to the right for discrete data x[n+1] at time n+1 Perform interference elimination processing. At the same time, the receiving end inputs the discrete data x[n+L+1] at time n+L+1 into the feedforward filter, and shifts x[n]~x[n+L] to the right.

过程3中，对n+1时刻的离散数据x[n+1]进行干扰消除处理，得到消除码间干扰后的[n+1]时刻离散数据y[n+1]。y[n+1]经过判决器的硬判决处理后，得到[n+1]时刻的判决后离散数据d[n+1]。d[n+1]输入反馈滤波器后，用于对x[n+2]及n+2时刻之后的离散数据进行干扰消除处理。In process 3, the interference elimination process is performed on the discrete data x[n+1] at time n+1 to obtain the discrete data y[n+1] at time [n+1] after eliminating inter-symbol interference. After y[n+1] undergoes hard decision processing by the decider, the post-decision discrete data d[n+1] at time [n+1] is obtained. After d[n+1] is input into the feedback filter, it is used to perform interference elimination processing on x[n+2] and the discrete data after n+2 time.

图3为判决反馈均衡器的训练过程示意图。如图3所示，判决反馈均衡器在对n时刻的离散数据x[n]进行干扰消除处理后，得到消除码间干扰后的[n]时刻离散数据y[n]。根据消除码间干扰后的n时刻离散数据y[n]和n时刻的样本数据y[n，e]，接收端能够确定一个误差。接收端根据误差可以调整判决反馈均衡器的参数。Figure 3 is a schematic diagram of the training process of the decision feedback equalizer. As shown in Figure 3, after the decision feedback equalizer performs interference elimination processing on the discrete data x[n] at time n, it obtains the discrete data y[n] at time [n] after eliminating inter-symbol interference. Based on the discrete data y[n] at time n and the sample data y[n, e] at time n after eliminating inter-symbol interference, the receiving end can determine an error. The receiving end can adjust the parameters of the decision feedback equalizer based on the error.

可以理解，误差（e_n）=y[n]-y[n，e]，其中，y[n，e]为n时刻的样本数据，e_n为判决反馈均衡器对n时刻的离散数据x[n]进行消除码间干扰后的得到的离散数据y[n]与n时刻的样本数据y[n，e]的差值。It can be understood that error ( _en ) = y[n]-y[n, e], where y[n, e] is the sample data at time n, and e _n is the discrete data x at time n by the decision feedback equalizer [n] The difference between the discrete data y[n] obtained after eliminating inter-symbol interference and the sample data y[n, e] at time n.

根据判决反馈均衡器在对x[n]进行干扰消除的过程，可以得出：According to the process of interference elimination of x[n] by the decision feedback equalizer, it can be concluded that:

。最小均方误差（least-mean-square，LMS）为/>，其中，E_n为最小均方误差，e_n ^H 与e_n为共轭复数。 . The least-mean-square error (LMS) is/> , where E _n is the minimum mean square error, and e _n ^H and e _n are conjugate complex numbers.

根据梯度下降法，前馈滤波器中W₀~W_-L的更新公式为：，其中，W_f为前馈滤波器中的参数W₀~W_-L，W_f,update为更新后的W_f，β为学习率，1＞β＞0。反馈滤波器中的W₁~W_M的更新公式为：/>，其中，W_b为反馈滤波器中的参数W₁~W_M，W_b,update为更新后的W_b，β为学习率，1＞β＞0。According to the gradient descent method, the update formula of W ₀ ~W _-L in the feedforward filter is: , where W _f is the parameter W ₀ ~W _-L in the feedforward filter, W _{f, update} is the updated W _f , β is the learning rate, 1＞ β ＞0. The update formula of W ₁ ~W _M in the feedback filter is:/> , where W _b is the parameter W ₁ ~W _M in the feedback filter, W _{b, update} is the updated W _b , β is the learning rate, 1＞ β ＞0.

可以理解，判决反馈均衡器训练过程中，前馈滤波器中的参数W₀~W_-L和反馈滤波器中的参数W₁~W_M会不断更新。判决反馈均衡器的训练过程即为确定前馈滤波器中的参数W₀~W_-L和反馈滤波器中的参数W₁~W_M的过程。并且，β也可以称为收敛步长，β的取值将能够决定判决反馈均衡器训练过程中产生的误差的收敛速度。误差的收敛指判决反馈均衡器的训练过程中得到的误差动态减小并趋于动态平稳的状态。It can be understood that during the training process of the decision feedback equalizer, the parameters W ₀ ~W _-L in the feedforward filter and the parameters W ₁ ~W _M in the feedback filter will be continuously updated. The training process of the decision feedback equalizer is the process of determining the parameters W ₀ ~W _-L in the feedforward filter and the parameters W ₁ ~W _M in the feedback filter. Moreover, β can also be called the convergence step size, and the value of β will determine the convergence speed of the error generated during the training process of the decision feedback equalizer. The convergence of the error refers to the dynamic reduction of the error obtained during the training process of the decision feedback equalizer and tends to a dynamically stable state.

下面结合图4对判决反馈均衡器的训练过程中误差的收敛趋势进行详细说明。The convergence trend of the error during the training process of the decision feedback equalizer will be described in detail below with reference to Figure 4.

图4为判决反馈均衡器训练过程中的误差的收敛趋势示意图。如图4所示，在该三个收敛趋势的示意图中，横坐标为误差的数量，即判决反馈均衡器的训练过程中的迭代次数，或者样本信号的数量，纵坐标为误差。在样本信号的数量均为1330的情况下，收敛步长不同，误差的收敛速度也不同。如图4中的收敛趋势（a）所示，在收敛步长适中的情况下，误差的收敛速度也适中；如图4中的收敛趋势（b）所示，在收敛步长较小的情况下，误差的收敛速度也较慢；如图4中的收敛趋势（c）所示，在收敛步长较快的情况下，误差的收敛速度也较快。然而，在误差收敛速度较慢时，误差仍有下降趋势，说明误差仍存在收敛空间。在误差收敛速度较快的情况下，误差的收敛趋势很快达到平稳，但是收敛误差有较大的震荡，容易导致训练精度不佳。Figure 4 is a schematic diagram of the convergence trend of the error during the training process of the decision feedback equalizer. As shown in Figure 4, in the schematic diagram of the three convergence trends, the abscissa is the number of errors, that is, the number of iterations in the training process of the decision feedback equalizer, or the number of sample signals, and the ordinate is the error. When the number of sample signals is 1330, the convergence step size is different, and the error convergence speed is also different. As shown in the convergence trend (a) in Figure 4, when the convergence step size is moderate, the convergence speed of the error is also moderate; as shown in the convergence trend (b) in Figure 4, when the convergence step size is small , the convergence speed of the error is also slower; as shown in the convergence trend (c) in Figure 4, when the convergence step size is faster, the convergence speed of the error is also faster. However, when the error converges slowly, the error still has a downward trend, indicating that there is still room for convergence of the error. When the error converges quickly, the convergence trend of the error quickly reaches a plateau, but the convergence error fluctuates greatly, which can easily lead to poor training accuracy.

然而，目前判决反馈均衡器的训练效果较差，使得接收端接收的数据包的误包率较高，导致发送端和接收端之间的通信质量较差，影响用户体验。However, the current training effect of the decision feedback equalizer is poor, resulting in a high packet error rate of data packets received by the receiving end, resulting in poor communication quality between the sending end and the receiving end, affecting the user experience.

为了解决上述技术问题，本申请提供一种信号传输方法和装置，通过在判决反馈均衡器的训练过程中，不断根据累计预设数量的判决反馈均衡器对实际接收信号的处理结果和样本信号之间的误差，确定误差的变化趋势，并进一步根据该变化趋势调整判决反馈均衡器的参数的调整系数，使得接收端能够根据误差的变化趋势实时调整判决反馈均衡器的参数，这样，在判决反馈均衡器的实际接收信号的数量相同的情况下，有助于降低判决反馈均衡器对实际接收信号的处理结果和样本信号之间的误差，能够提高判决反馈均衡器的准确率，从而提高发送端和接收端之间的通信质量，提高用户体验感。In order to solve the above technical problems, the present application provides a signal transmission method and device. During the training process of the decision feedback equalizer, the processing result of the actual received signal and the sample signal are continuously processed by the decision feedback equalizer based on the accumulated preset number. error between the errors, determine the changing trend of the error, and further adjust the adjustment coefficients of the parameters of the decision feedback equalizer according to the changing trend, so that the receiving end can adjust the parameters of the decision feedback equalizer in real time according to the changing trend of the error. In this way, during the decision feedback When the number of actual received signals of the equalizer is the same, it helps to reduce the error between the processing result of the actual received signal by the decision feedback equalizer and the sample signal, and can improve the accuracy of the decision feedback equalizer, thus improving the transmitting end. The communication quality between the device and the receiving end improves the user experience.

下面结合图5至图11对本申请的信号传输方法进行详细介绍。本申请所示出的实施例从设备交互的角度示出了本申请提供的信息传输方法。其中所示的各设备的具体形态和数量仅为示例，不应对本申请提供的方法的实施构成任何限定。下面，以发送端和接收端为执行主体为例，对本申请实施例的信息传输方法进行详细说明。The signal transmission method of the present application will be introduced in detail below with reference to Figures 5 to 11. The embodiments shown in this application illustrate the information transmission method provided by this application from the perspective of device interaction. The specific shapes and quantities of each equipment shown therein are only examples and should not constitute any limitation on the implementation of the method provided in this application. Next, taking the sending end and the receiving end as execution subjects as an example, the information transmission method in the embodiment of the present application will be described in detail.

应理解，本申请实施例中的发送端为发送信号的设备，可以是终端设备或网络设备本身，也可以为支持终端设备或网络设备实现信号传输方法的芯片、芯片系统或处理器，还可以是能实现全部或部分终端设备或网络设备的逻辑模块或软件；本申请实施例中的接收端为接收信号的设备，可以是终端设备或网络设备本身，也可以为支持终端设备或网络设备实现信号传输方法的芯片、芯片系统或处理器，还可以是能实现全部或部分终端设备或网络设备的逻辑模块或软件；本申请对此不做具体限制。It should be understood that the sending end in the embodiment of the present application is a device that sends signals, which can be a terminal device or a network device itself, or a chip, chip system or processor that supports the terminal device or network device to implement a signal transmission method, or it can be It is a logical module or software that can realize all or part of the terminal equipment or network equipment; the receiving end in the embodiment of the present application is a device that receives signals, which can be the terminal equipment or network equipment itself, or can also be implemented to support terminal equipment or network equipment. The chip, chip system or processor of the signal transmission method can also be a logic module or software that can implement all or part of the terminal equipment or network equipment; this application does not specifically limit this.

图5为本申请实施例提供的信号传输方法500的流程示意图。方法500适用于通信系统100，方法500包括下列步骤：Figure 5 is a schematic flowchart of a signal transmission method 500 provided by an embodiment of the present application. The method 500 is applicable to the communication system 100. The method 500 includes the following steps:

S501、发送端向接收端发送信号，信号包括样本信号的实际接收信号和业务信号。对应地，接收端接收来自发送端的信号。S501. The transmitting end sends a signal to the receiving end. The signal includes the actual received signal of the sample signal and the service signal. Correspondingly, the receiving end receives the signal from the transmitting end.

应理解，接收端可以为设置有判决反馈均衡器的网络设备或者终端设备，例如手机、智能手环、WiFi路由器等。发送端向接收端发送的信号可以为802.11b所规定的基带信号。样本信号可以指发送端和接收端约定的用于接收端对判决反馈均衡器进行训练的数据信息，即发送端向接收端发送的信号中包括样本信号。样本信号的实际接收信号指终端设备实际接收到的样本信号。可以理解，样本信号经发送端向接收端传输后，受到多径信号码间干扰等影响，接收端实际接收的样本信号会发生变化，即接收端接收到的样本信号的实际接收信号与样本信号可能不同。示例性地，发送端向接收端发送的样本信号为“1234”，接收端接收的样本信号的实际接收信号为受到多径信号码间干扰的样本信号，例如可以为“2224”。业务信号为接收端需要获取的业务数据，然而，接收端需要获取的业务数据在由发送端传输至接收端的过程中，受到多径信号码间干扰等影响，使得接收端需要获取的业务数据会发生变化，即接收端接收的业务信号。在接收端需要获取正确的业务信号的情况下，接收端可以通过训练好的判决反馈均衡器对实际接收的业务信号进行干扰消除处理。It should be understood that the receiving end can be a network device or terminal device equipped with a decision feedback equalizer, such as a mobile phone, a smart bracelet, a WiFi router, etc. The signal sent by the transmitting end to the receiving end may be a baseband signal specified by 802.11b. The sample signal may refer to the data information agreed upon by the transmitting end and the receiving end for the receiving end to train the decision feedback equalizer, that is, the signal sent by the transmitting end to the receiving end includes the sample signal. The actual received signal of the sample signal refers to the sample signal actually received by the terminal device. It can be understood that after the sample signal is transmitted from the transmitting end to the receiving end, it will be affected by multipath signal inter-code interference, etc., and the sample signal actually received by the receiving end will change, that is, the actual received signal of the sample signal received by the receiving end is different from the sample signal. May be different. For example, the sample signal sent by the transmitting end to the receiving end is "1234", and the actual received signal of the sample signal received by the receiving end is a sample signal subject to multipath signal intercode interference, which may be "2224", for example. The service signal is the service data that the receiving end needs to obtain. However, in the process of being transmitted from the sending end to the receiving end, the service data that the receiving end needs to obtain is affected by multipath signal inter-code interference, so that the service data that the receiving end needs to obtain will be affected. Changes occur, that is, the service signal received by the receiving end. When the receiving end needs to obtain the correct service signal, the receiving end can perform interference cancellation processing on the actually received service signal through a well-trained decision feedback equalizer.

在一个可能的实施方式中，信号包括头部信息（header）和物理层服务数据单元（physical service data unit，PSDU），其中，头部信息为样本信号的实际接收信号，PSDU为业务信号。In a possible implementation, the signal includes header information (header) and a physical service data unit (PSDU), where the header information is the actual received signal of the sample signal and the PSDU is the service signal.

S502、基于实际接收信号和样本信号，对判决反馈均衡器进行训练。S502. Based on the actual received signal and sample signal, train the decision feedback equalizer.

应理解，样本信号为发送端与接收端约定好的准确信号，实际接收信号为接收端实际接收信号。判决反馈均衡器在对接收端实际接收信号进行干扰消除处理后，得到的输出结果与样本信号之间存在误差（error），基于该误差对判决反馈均衡器进行训练。对判决反馈均衡器进行训练的过程即不断调整判决反馈均衡器的参数的过程。It should be understood that the sample signal is the accurate signal agreed between the sending end and the receiving end, and the actual received signal is the signal actually received by the receiving end. After the decision feedback equalizer performs interference elimination processing on the actual received signal at the receiving end, there is an error (error) between the output result and the sample signal. The decision feedback equalizer is trained based on this error. The process of training the decision feedback equalizer is the process of continuously adjusting the parameters of the decision feedback equalizer.

S503、在训练过程中，根据判决反馈均衡器对实际接收信号的处理结果和样本信号之间误差的第一变化趋势和第一对应关系，确定判决反馈均衡器的参数的调整系数，第一对应关系包括多个变化趋势和多个调整系数之间的对应关系，多个变化趋势包括第一变化趋势。S503. During the training process, determine the adjustment coefficients of the parameters of the decision feedback equalizer based on the first changing trend and the first correspondence between the error between the actual received signal processing result of the decision feedback equalizer and the sample signal. The first correspondence The relationship includes correspondence between multiple change trends and multiple adjustment coefficients, and the multiple change trends include a first change trend.

应理解，判决反馈均衡器对实际接收信号的处理结果和样本信号之间误差可以指处理结果和样本信号之间的差值。第一变化趋势可以指至少两个误差的变化趋势。示例性地，接收端连续得到三个误差，可以根据该三个误差，确定第一变化趋势。It should be understood that the error between the processing result of the actual received signal by the decision feedback equalizer and the sample signal may refer to the difference between the processing result and the sample signal. The first change trend may refer to the change trend of at least two errors. For example, the receiving end obtains three errors in succession, and the first change trend can be determined based on the three errors.

判决反馈均衡器的参数指前馈滤波器中的参数和反馈滤波器中的参数，例如图2中所示的过程1中的W₀~W_-L和W₁~W_M。判决反馈均衡器的参数的调整系数为用于调整判决反馈均衡器的参数的系数。The parameters of the decision feedback equalizer refer to the parameters in the feedforward filter and the parameters in the feedback filter, such as W ₀ ~W _-L and W ₁ ~W _M in process 1 shown in Figure 2. The adjustment coefficient of the parameter of the decision feedback equalizer is a coefficient used to adjust the parameter of the decision feedback equalizer.

第一对应关系包括多个变化趋势和多个调整系数之间的对应关系，示例性地，第一对应关系包括变化趋势1、变化趋势2和变化趋势3；还包括调整系数1、调整系数2和调整系数3。其中，变化趋势1对应于调整系数1，变化趋势2对应于调整系数2，变化趋势3对应于调整系数3。在第一变化趋势为变化趋势1的情况下，接收端可以确定调整系数为调整系数1。The first correspondence relationship includes correspondence relationships between multiple change trends and multiple adjustment coefficients. For example, the first correspondence relationship includes change trend 1, change trend 2, and change trend 3; it also includes adjustment coefficient 1 and adjustment coefficient 2. and adjustment factor 3. Among them, change trend 1 corresponds to adjustment coefficient 1, change trend 2 corresponds to adjustment coefficient 2, and change trend 3 corresponds to adjustment coefficient 3. In the case where the first change trend is change trend 1, the receiving end may determine the adjustment coefficient to be adjustment coefficient 1.

S504、基于调整系数，对判决反馈均衡器的参数进行调整，并继续对判决反馈均衡器进行训练。S504. Based on the adjustment coefficient, adjust the parameters of the decision feedback equalizer, and continue training the decision feedback equalizer.

应理解，判决反馈均衡器训练过程中会不断的得到的判决反馈均衡器对实际接收信号的处理结果和样本信号之间的误差，误差的个数为样本信号的数量。并且，判决反馈均衡器训练过程中，判决反馈均衡器的参数是不断调整的。继续对判决反馈均衡器进行训练是指，在调整判决反馈均衡器的参数后，继续重复S503，对判决反馈均衡器进行训练，直至满足停止条件。It should be understood that during the training process of the decision feedback equalizer, the error between the processing result of the actual received signal by the decision feedback equalizer and the sample signal will be continuously obtained, and the number of errors is the number of sample signals. Moreover, during the training process of the decision feedback equalizer, the parameters of the decision feedback equalizer are continuously adjusted. Continuing to train the decision feedback equalizer means that after adjusting the parameters of the decision feedback equalizer, continue to repeat S503 to train the decision feedback equalizer until the stopping condition is met.

在一种可能的实施方式中，停止条件可以为判决反馈均衡器的迭代次数等于实际接收信号的数量的情况下，判决反馈均衡器训练完成。示例性地，实际接收信号包括第一信号、第二信号和第三信号，则判决反馈均衡器分别通过第一信号、第二信号和第三信号迭代训练三次，此时判决反馈均衡器的训练完成。In a possible implementation, the stopping condition may be that when the number of iterations of the decision feedback equalizer is equal to the number of actual received signals, the training of the decision feedback equalizer is completed. For example, if the actual received signal includes the first signal, the second signal and the third signal, then the decision feedback equalizer is iteratively trained three times through the first signal, the second signal and the third signal respectively. At this time, the training of the decision feedback equalizer is Finish.

在一个具体的示例中，实际接收信号包括第一信号、第二信号和第三信号；样本信号包括第一样本信号、第二样本信号和第三样本信号。第一信号为第一样本信号的实际接收信号；第二信号为第二样本信号的实际接收信号；第三信号为第三样本信号的实际接收信号。判决反馈均衡器的参数初始状态为a，接收端将第一信号输入判决反馈均衡器后，得到第一处理结果，根据第一处理结果和第一样本信号，确定第一误差；根据第一误差调整判决反馈均衡器的参数，此时第一误差调整判决反馈均衡器的参数为a₁。接收端将第二信号输入参数为a₁的判决反馈均衡器，得到第二处理结果，根据第二处理结果和第二样本信号，确定第二误差。接收端根据第二误差和第一误差能够确定第一变化趋势，再根据第一变化趋势和第一对应关系，确定调整系数，通过调整系数，调整判决反馈均衡器的参数为a₂。接收端将第三信号输入参数为a₂的判决反馈均衡器，得到第三处理结果，根据第三处理结果和第三样本信号，确定第三误差。接收端根据第三误差和第二误差能够确定第二变化趋势，再根据第二变化趋势和第一对应关系，确定调整系数，通过调整系数，调整判决反馈均衡器的系数为a₃。In a specific example, the actual received signal includes a first signal, a second signal and a third signal; the sample signal includes a first sample signal, a second sample signal and a third sample signal. The first signal is the actual received signal of the first sample signal; the second signal is the actual received signal of the second sample signal; and the third signal is the actual received signal of the third sample signal. The parameter initial state of the decision feedback equalizer is a. After the receiving end inputs the first signal into the decision feedback equalizer, the first processing result is obtained, and the first error is determined according to the first processing result and the first sample signal; according to the first The error adjusts the parameters of the decision feedback equalizer. At this time, the parameter of the first error adjustment decision feedback equalizer is a ₁ . The receiving end inputs the second signal into the decision feedback equalizer with parameter a ₁ to obtain the second processing result, and determines the second error based on the second processing result and the second sample signal. The receiving end can determine the first change trend based on the second error and the first error, and then determine the adjustment coefficient based on the first change trend and the first correspondence. Through the adjustment coefficient, the parameter of the decision feedback equalizer is adjusted to a ₂ . The receiving end inputs the third signal into the decision feedback equalizer with parameter a ₂ to obtain the third processing result, and determines the third error based on the third processing result and the third sample signal. The receiving end can determine the second change trend based on the third error and the second error, and then determine the adjustment coefficient based on the second change trend and the first correspondence. By adjusting the coefficient, the coefficient of the decision feedback equalizer is adjusted to a ₃ .

在一种可能的实施方式中，判决反馈均衡器的参数是根据实际接收信号的处理结果和样本信号之间误差、调整系数和学习率确定的。可选地，调整系数与判决反馈均衡器的参数的关系如以下公式所示：；/>，其中，R为调整系数，也可以用ratio表示；W_f为前馈滤波器中的参数W₀~W_-L，W_f,update为更新后的W_f，W_b为反馈滤波器中的参数W₁~W_M，W_b,update为更新后的W_b，β为学习率，1＞β＞0。In a possible implementation, the parameters of the decision feedback equalizer are determined based on the error between the processing result of the actual received signal and the sample signal, the adjustment coefficient and the learning rate. Optionally, the relationship between the adjustment coefficient and the parameters of the decision feedback equalizer is as shown in the following formula: ;/> , where R is the adjustment coefficient, which can also be expressed as ratio; W _f is the parameter W ₀ ~W _-L in the feedforward filter, W _{f, update} is the updated W _f , and W _b is the parameter in the feedback filter Parameters W ₁ ~W _M , W _{b, update} is the updated W _b , β is the learning rate, 1> β >0.

应理解，接收端通过误差的第一变化趋势确定调整系数，使得判决反馈均衡器的参数能够根据误差实时变化，从而能够判决反馈均衡器训练效率，提高判决反馈均衡器训练效果，降低接收端的误包率，提高发送端和接收端的通信质量，提高用户体验感。It should be understood that the receiving end determines the adjustment coefficient through the first change trend of the error, so that the parameters of the decision feedback equalizer can change in real time according to the error, so that the training efficiency of the decision feedback equalizer can be improved, the training effect of the decision feedback equalizer can be improved, and the error of the receiving end can be reduced. packet rate, improve the communication quality between the sending end and the receiving end, and improve the user experience.

S505、利用训练完成的判决反馈均衡器，对业务信号进行干扰消除处理。S505: Use the trained decision feedback equalizer to perform interference elimination processing on the service signal.

应理解，训练完成的判决反馈均衡器即确定好参数的判决反馈均衡器。一种可能的实施方式中，接收端包括一个判决反馈均衡器，在接收端通过样本信号对该判决反馈均衡器训练完成后，则得到训练完成的判决反馈均衡器。在另一个可能的实施方式中，接收端包括一个用于训练的判决反馈均衡器和一个用于干扰消除处理的判决反馈均衡器，在接收端通过样本信号对用于训练的判决反馈均衡器训练完成后，用于训练的判决反馈均衡器将确定好的参数发送至用于干扰消除处理的判决反馈均衡器，用于干扰消除处理的判决反馈均衡器在采用用于训练的判决反馈均衡器的参数后，即为训练完成的判决反馈均衡器。It should be understood that the decision feedback equalizer that has been trained is the decision feedback equalizer with determined parameters. In a possible implementation, the receiving end includes a decision feedback equalizer. After the receiving end completes training of the decision feedback equalizer through sample signals, the trained decision feedback equalizer is obtained. In another possible implementation, the receiving end includes a decision feedback equalizer for training and a decision feedback equalizer for interference cancellation processing, and the decision feedback equalizer for training is trained at the receiving end through sample signals. After completion, the decision feedback equalizer used for training sends the determined parameters to the decision feedback equalizer used for interference cancellation processing. The decision feedback equalizer used for interference cancellation processing uses the decision feedback equalizer used for training. After the parameters, it is the decision feedback equalizer that has been trained.

在一种可能的实施方式中，训练好的判决反馈均衡器的参数可以为训练过程中，判决反馈均衡器对实际接收信号的处理结果和样本信号之间误差最小时对应的参数。示例性地，判决反馈均衡器的参数为c₁时，得到的处理结果和样本信号之间误差为g₁；判决反馈均衡器的参数为c₂时，得到的处理结果和样本信号之间误差为g₂；判决反馈均衡器的参数为c₃时，得到的处理结果和样本信号之间误差为g₃。在g₁＞g₂＞g₃的情况下，接收端可以确定训练完成的判决反馈均衡器的参数为c₃。In a possible implementation, the parameters of the trained decision feedback equalizer may be parameters corresponding to the minimum error between the processing result of the decision feedback equalizer on the actual received signal and the sample signal during the training process. For example, when the parameter of the decision feedback equalizer is c ₁ , the error between the obtained processing result and the sample signal is g ₁ ; when the parameter of the decision feedback equalizer is c ₂ , the error between the obtained processing result and the sample signal is g ₂ ; when the parameter of the decision feedback equalizer is c ₃ , the error between the obtained processing result and the sample signal is g ₃ . In the case of g ₁ > g ₂ > g ₃ , the receiving end can determine that the parameter of the trained decision feedback equalizer is c ₃ .

在另一种可能的实施方式中，训练好的判决反馈均衡器的参数也可以为判决反馈均衡器最后一次迭代时所采用的参数。示例性地，判决反馈均衡器的参数为c₁时，得到的处理结果和样本信号之间误差为g₁；判决反馈均衡器的参数为c₂时，得到的处理结果和样本信号之间误差为g₂；判决反馈均衡器的参数为c₃时，得到的处理结果和样本信号之间误差为g₃，在g₁＞g₃＞g₂的情况下，接收端可以确定训练完成的判决反馈均衡器的参数为c₃。In another possible implementation, the parameters of the trained decision feedback equalizer may also be the parameters used in the last iteration of the decision feedback equalizer. For example, when the parameter of the decision feedback equalizer is c ₁ , the error between the obtained processing result and the sample signal is g ₁ ; when the parameter of the decision feedback equalizer is c ₂ , the error between the obtained processing result and the sample signal is g ₂ ; when the parameter of the decision feedback equalizer is c ₃ , the error between the obtained processing result and the sample signal is g _3. When g ₁ > g ₃ > g ₂ , the receiving end can determine the decision after training. The parameter of the feedback equalizer is c ₃ .

本申请的信号传输方法，通过在判决反馈均衡器的训练过程中，根据累计预设数量的判决反馈均衡器对实际接收信号的处理结果和样本信号之间的误差，确定误差的变化趋势，并进一步根据该变化趋势调整判决反馈均衡器的参数的调整系数，使得接收端能够根据误差的变化趋势实时调整判决反馈均衡器的参数，这样，在判决反馈均衡器的实际接收信号的数量相同的情况下，能够降低判决反馈均衡器对实际接收信号的处理结果和样本信号之间的误差，提高判决反馈均衡器的准确率，从而提高发送端和接收端之间的通信质量，提高用户体验感。The signal transmission method of this application determines the changing trend of the error based on the error between the actual received signal processing results of the cumulative preset number of decision feedback equalizers and the sample signal during the training process of the decision feedback equalizer, and Further adjust the adjustment coefficients of the parameters of the decision feedback equalizer according to the changing trend, so that the receiving end can adjust the parameters of the decision feedback equalizer in real time according to the changing trend of the error. In this way, when the number of actual received signals of the decision feedback equalizer is the same Under this method, the error between the processing result of the actual received signal by the decision feedback equalizer and the sample signal can be reduced, and the accuracy of the decision feedback equalizer can be improved, thereby improving the communication quality between the sending end and the receiving end and improving the user experience.

作为一个可选的实施例，方法500还包括：接收端将实际接收信号输入至判决反馈均衡器，得到实际接收信号的处理结果；确定实际接收信号的处理结果和样本信号之间的误差；基于误差，确定第一变化趋势。As an optional embodiment, method 500 also includes: the receiving end inputs the actual received signal into the decision feedback equalizer to obtain the processing result of the actual received signal; determines the error between the processing result of the actual received signal and the sample signal; based on error to determine the first change trend.

应理解，实际接收信号的处理结果和样本信号之间的误差可以指实际接收信号的处理结果和样本信号之间的差值。第一变化趋势指误差的变化趋势，因此，第一变化趋势是根据至少两个误差确定的。It should be understood that the error between the processing result of the actual received signal and the sample signal may refer to the difference between the processing result of the actual received signal and the sample signal. The first change trend refers to the change trend of errors. Therefore, the first change trend is determined based on at least two errors.

在一种可能的实施方式中，基于误差，确定第一变化趋势，包括：每当误差的数量积累到第一预设数量时，对第一预设数量的误差进行均值滤波处理，得到多个平滑误差；根据多个平滑误差中每两个相邻平滑误差之间的差值，确定多个平滑误差中每两个相邻平滑误差的局部变化趋势，局部变化趋势包括上升趋势和下降趋势；根据上升趋势的数量和下降趋势的数量，确定第一变化趋势。In a possible implementation, determining the first change trend based on the errors includes: whenever the number of errors accumulates to a first preset number, performing mean filtering processing on the first preset number of errors to obtain a plurality of Smoothing error; based on the difference between each two adjacent smoothing errors in multiple smoothing errors, determine the local change trend of each two adjacent smoothing errors in multiple smoothing errors. The local change trend includes an upward trend and a downward trend; The first change trend is determined based on the number of upward trends and the number of downward trends.

应理解，第一预设数量可以为任意正整数，例如5个、10个等。可选地，第一预设数量也可以用窗口长度（window length）表示。对第一预设数量的误差进行均值滤波处理可以指将第一预设数量的误差取平均值，该平均值即为平滑误差（smoothed error）。在接收端开始判决反馈均衡器的训练后，接收端每向判决反馈均衡器输入一次实际接收信号，接收端均会有相应的处理结果，根据处理结果和样本信号，能够确定一个误差。判决反馈均衡器的训练过程中，接收端不断将实际接收信号输入判决反馈均衡器，会不断的得到误差。每当误差的数量积累到第一预设数量时，接收端均会确定该第一预设数量的误差的平均值，从而得到一个平滑误差。随着误差的积累数量的进一步增多，平滑误差的数量也会不断增长。It should be understood that the first preset number can be any positive integer, such as 5, 10, etc. Optionally, the first preset number may also be represented by window length (window length). Performing mean filtering on the first preset number of errors may refer to averaging the first preset number of errors, and the average is the smoothed error. After the receiving end starts training the decision feedback equalizer, every time the receiving end inputs an actual received signal to the decision feedback equalizer, the receiving end will have corresponding processing results. Based on the processing results and sample signals, an error can be determined. During the training process of the decision feedback equalizer, the receiving end continuously inputs the actual received signal into the decision feedback equalizer, and errors will continue to be obtained. Whenever the number of errors accumulates to a first preset number, the receiving end determines the average value of the first preset number of errors, thereby obtaining a smooth error. As the accumulated number of errors further increases, the number of smoothing errors will also continue to grow.

下面结合图6对均值滤波处理进行进一步说明。The mean filtering process will be further explained below in conjunction with Figure 6 .

图6为本申请实施例提供的均值滤波处理前后误差的收敛趋势示意图。如图6中的误差的收敛趋势（a）所示，误差数量为1365个，即判决反馈均衡器训练过程中，共迭代1365次。第一预设数量为21，即在判决反馈均衡器训练过程中，每得到21个误差，均会对该21个误差进行均值滤波处理，得到一个平滑误差，在判决反馈均衡器训练结束后，共得到65个平滑误差，该65个平滑误差的收敛趋势如图6中的收敛趋势（b）所示。通过图6可以看出，通过对第一预设数量的误差进行均值滤波处理，有助于接收端确定误差的变化趋势，这样，有助于提高误差的收敛效率，提高判决反馈均衡器的训练效果。Figure 6 is a schematic diagram of the convergence trend of errors before and after mean filtering provided by the embodiment of the present application. As shown in the error convergence trend (a) in Figure 6, the number of errors is 1365, that is, during the training process of the decision feedback equalizer, a total of 1365 iterations were performed. The first preset number is 21, that is, during the training process of the decision feedback equalizer, for every 21 errors obtained, the 21 errors will be average filtered to obtain a smooth error. After the training of the decision feedback equalizer is completed, A total of 65 smoothing errors are obtained, and the convergence trend of these 65 smoothing errors is shown in the convergence trend (b) in Figure 6. It can be seen from Figure 6 that by performing mean filtering on the first preset number of errors, it helps the receiving end determine the changing trend of the errors. This helps improve the convergence efficiency of the errors and improves the training of the decision feedback equalizer. Effect.

相邻平滑误差指接收端连续确定的两个平滑误差，确定相邻平滑误差的多个误差是判决反馈均衡器连续输出的。示例性地，在如图6中的收敛趋势（b）中，每相邻的两个点均为相邻平滑误差，例如点A对应的平滑误差和点B对应的平滑误差为相邻平滑误差。局部变化趋势可以根据相邻B对应的平滑误差和点C对应的平滑误差为相邻平滑误差。局部变化趋势可以根据相邻平滑误差的差值确定，在相邻平滑误差中后一个平滑误差大于前一个平滑误差的情况下，接收端可以确定局部变化趋势为下降趋势；在相邻平滑误差中后一个平滑误差小于前一个平滑误差的情况下，接收端可以确定局部变化趋势为上升趋势。示例性地，在如图6中的收敛趋势（b）中，点A对应的平滑误差为1.1，点B对应的平滑误差为0.8，点C对应的平滑误差为0.9。点A和点B为相邻平滑误差，其中，点B为该两个相邻平滑误差中的后一个平滑误差，点A为前一个平滑误差，由于点B对应的平滑误差小于点A对应的平滑误差，因此，接收端根据该相邻平滑误差确定的一个局部变化趋势为下降趋势。类似地，点B和点C为相邻平滑误差，根据该两个相邻平滑误差，接收端能够确定一个局部变化趋势为上升趋势。Adjacent smoothing errors refer to two smoothing errors that are continuously determined by the receiving end. Multiple errors that determine adjacent smoothing errors are continuously output by the decision feedback equalizer. For example, in the convergence trend (b) as shown in Figure 6, every two adjacent points are adjacent smoothing errors. For example, the smoothing error corresponding to point A and the smoothing error corresponding to point B are adjacent smoothing errors. . The local change trend can be determined as the adjacent smoothing error based on the smoothing error corresponding to adjacent B and the smoothing error corresponding to point C. The local change trend can be determined based on the difference between adjacent smoothing errors. In the case where the latter smoothing error is greater than the previous smoothing error, the receiving end can determine that the local change trend is a downward trend; in the adjacent smoothing errors When the latter smoothing error is smaller than the previous smoothing error, the receiving end can determine that the local change trend is an upward trend. For example, in the convergence trend (b) as shown in Figure 6, the smoothing error corresponding to point A is 1.1, the smoothing error corresponding to point B is 0.8, and the smoothing error corresponding to point C is 0.9. Point A and point B are adjacent smoothing errors, where point B is the latter smoothing error of the two adjacent smoothing errors, and point A is the previous smoothing error. Since the smoothing error corresponding to point B is smaller than that corresponding to point A, Smoothing error, therefore, a local change trend determined by the receiving end based on the adjacent smoothing error is a downward trend. Similarly, point B and point C are adjacent smoothing errors. Based on these two adjacent smoothing errors, the receiving end can determine a local change trend as an upward trend.

在一种可能的实施方式中，局部变化趋势还包括稳定趋势，在相邻平滑误差之间的差值小于或者等于第一预设阈值的情况下，确定该相邻平滑误差的局部变化趋势为稳定趋势；在相邻平滑误差之间的差值大于第一预设阈值，并且该相邻平滑误差中后一个平滑误差大于前一个平滑误差的情况下，确定该相邻平滑误差的局部变化趋势为上升趋势；在相邻平滑误差之间的差值大于第一预设阈值，并且该相邻平滑误差中后一个平滑误差小于前一个平滑误差的情况下，确定该相邻平滑误差的局部变化趋势为下降趋势。In a possible implementation, the local change trend also includes a stable trend. When the difference between adjacent smoothing errors is less than or equal to the first preset threshold, the local change trend of the adjacent smoothing errors is determined to be Stable trend; when the difference between adjacent smoothing errors is greater than the first preset threshold, and the latter smoothing error among the adjacent smoothing errors is greater than the previous smoothing error, determine the local change trend of the adjacent smoothing errors. is an upward trend; when the difference between adjacent smoothing errors is greater than the first preset threshold, and the latter smoothing error among the adjacent smoothing errors is less than the previous smoothing error, determine the local change of the adjacent smoothing errors. The trend is downward.

应理解，第一预设阈值为任意大于或者等于0的值，例如可以为0、0.01等。在相邻平滑误差之间的差值小于或者等于第一预设阈值时，说明该两个相邻平滑误差接近，可以确定局部变化趋势为稳定趋势。示例性地，第一平滑误差和第二平滑误差为相邻平滑误差，第二平滑误差和第三平滑误差为相邻平滑误差，第一平滑误差为1.0，第二平滑误差为0.9，第三平滑误差为0.91，第一预设阈值为0.02，则根据第一平滑误差和第二平滑误差，接收端可以确定一个局部变化趋势为下降趋势；根据第二平滑误差和第三平滑误差，接收端可以确定一个局部变化趋势为稳定趋势。It should be understood that the first preset threshold is any value greater than or equal to 0, such as 0, 0.01, etc. When the difference between adjacent smoothing errors is less than or equal to the first preset threshold, it means that the two adjacent smoothing errors are close, and the local change trend can be determined to be a stable trend. For example, the first smoothing error and the second smoothing error are adjacent smoothing errors, the second smoothing error and the third smoothing error are adjacent smoothing errors, the first smoothing error is 1.0, the second smoothing error is 0.9, and the third smoothing error is 0.9. The smoothing error is 0.91 and the first preset threshold is 0.02. According to the first smoothing error and the second smoothing error, the receiving end can determine a local change trend as a downward trend; according to the second smoothing error and the third smoothing error, the receiving end A local change trend can be determined as a stable trend.

在一种可能的实施方式中，根据上升趋势的数量和下降趋势的数量，确定第一变化趋势，包括：若上升趋势的数量大于下降趋势的数量，则将第一变化趋势确定为上升趋势；或者，若上升趋势的数量等于下降趋势的数量，则将第一变化趋势确定为稳定趋势；或者，若上升趋势的数量小于下降趋势的数量，则将第一变化趋势确定为下降趋势。In a possible implementation, determining the first change trend based on the number of upward trends and the number of downward trends includes: if the number of upward trends is greater than the number of downward trends, determining the first change trend as an upward trend; Alternatively, if the number of upward trends is equal to the number of downward trends, the first change trend is determined to be a stable trend; or, if the number of upward trends is less than the number of downward trends, the first change trend is determined to be a downward trend.

应理解，第一变化趋势包括上升趋势、下降趋势和稳定趋势。第一变化趋势是根据局部变化趋势中的上升趋势和下降趋势的数量确定的，这样，能够更高效的确定误差的变化趋势，从而有助于提高判决反馈均衡器训练的效率和准确率。It should be understood that the first change trend includes an upward trend, a downward trend and a stable trend. The first change trend is determined based on the number of upward trends and downward trends in the local change trend. In this way, the change trend of the error can be determined more efficiently, thereby helping to improve the efficiency and accuracy of decision feedback equalizer training.

在另一种可能的实施方式中，根据上升趋势的数量和下降趋势的数量，确定第一变化趋势，包括：当多个平滑误差的数量积累到第二预设数量时，根据上升趋势的数量和下降趋势的数量，确定第一变化趋势。可选地，第二预设数量也可以用计数数量（count_num）表示。In another possible implementation, determining the first change trend according to the number of upward trends and the number of downward trends includes: when the number of multiple smoothing errors accumulates to a second preset number, according to the number of upward trends and the number of downward trends determine the first change trend. Optionally, the second preset number can also be represented by a count number (count_num).

应理解，第二预设数量可以为任意正整数，例如可以为3个、9个等。示例性地，第二预设数量为6个，则接收端每确定6个平滑误差后，根据该6个平滑误差中每两个相邻平滑误差确定5个局部变化趋势，在该5个局部变化趋势中，根据上升趋势的数量和下降趋势的数量，确定第一变化趋势。It should be understood that the second preset number can be any positive integer, for example, it can be 3, 9, etc. For example, if the second preset number is 6, then every time the receiving end determines 6 smoothing errors, it will determine 5 local changing trends based on each two adjacent smoothing errors among the 6 smoothing errors. Among the changing trends, the first changing trend is determined based on the number of upward trends and the number of downward trends.

可选地，根据上升趋势的数量和下降趋势的数量，确定第一变化趋势，包括：当多个平滑误差的数量积累到第二预设数量时，若上升趋势的数量大于下降趋势的数量，并且上升趋势的数量与下降趋势的数量之间的差值大于或者等于第二预设阈值，则将第一变化趋势确定为上升趋势；或者，若上升趋势的数量小于下降趋势的数量，并且下降趋势的数量与上升趋势的数量之间的差值大于或者等于第三预设阈值，则将第一变化趋势确定为下降趋势；否则，则将第一变化趋势确定为稳定趋势。Optionally, determining the first change trend based on the number of upward trends and the number of downward trends includes: when the number of multiple smoothing errors accumulates to a second preset number, if the number of upward trends is greater than the number of downward trends, And the difference between the number of upward trends and the number of downward trends is greater than or equal to the second preset threshold, then the first change trend is determined as an upward trend; or, if the number of upward trends is less than the number of downward trends, and the first change trend is If the difference between the number of trends and the number of upward trends is greater than or equal to the third preset threshold, the first change trend is determined as a downward trend; otherwise, the first change trend is determined as a stable trend.

应理解，第二预设阈值、第三预设阈值均为预设的任意正整数。第一变化趋势可以为上升趋势、下降趋势或者稳定趋势，在第一变化趋势不是上升趋势或下降趋势的情况下，第一变化趋势为稳定趋势。示例性地，第二预设阈值为2，第三预设阈值为3，在局部变化趋势中上升趋势的数量比下降趋势的数量多3个的情况下，接收端确定第一变化趋势为上升趋势；在局部变化趋势中下降趋势的数量比上升趋势的数量多3个的情况下，接收端确定第一变化趋势为下降趋势；在局部变化趋势中上升趋势的数量比下降趋势的数量多1个的情况下，接收端确定第一变化趋势为稳定趋势。It should be understood that the second preset threshold and the third preset threshold are both preset arbitrary positive integers. The first changing trend may be an upward trend, a downward trend or a stable trend. If the first changing trend is not an upward trend or a downward trend, the first changing trend is a stable trend. For example, the second preset threshold is 2 and the third preset threshold is 3. When the number of upward trends in the local change trend is 3 more than the number of downward trends, the receiving end determines that the first change trend is upward. Trend; when the number of downward trends in the local change trend is 3 more than the number of upward trends, the receiving end determines the first change trend as a downward trend; in the local change trend, the number of upward trends is 1 more than the number of downward trends. In this case, the receiving end determines that the first changing trend is a stable trend.

在一种可能的实施方式中，判决反馈均衡器包括上升累计器和下降累计器，根据上升趋势的数量和下降趋势的数量，确定第一变化趋势，包括：接收端每确定一个上升趋势，上升累计器累计一个+1；接收端每确定一个下降趋势，下降累计器累计一个-1，当多个平滑误差的数量积累到第三预设数量时，根据上升累计器累计的数值与下降累计器累计的数值的和，确定第一变化趋势。在上升累计器累计的数值与下降累计器累计的数值的和，大于或者等于第四预设阈值时，确定第一变化趋势为上升趋势；在上升累计器累计的数值与下降累计器累计的数值的和小于或者等于第五预设阈值时，确定第一变化趋势为下降趋势；否则，确定第一变化趋势为稳定趋势。可选地，上升累计器累计的数值可以用flag_up表示，即上升累计器每累计一个局部变化趋势为上升趋势，flag_up均加+1；下降累计器累计的数值可以用flag_down表示，即上升累计器每累计一个局部变化趋势为下降趋势，flag_down均加-1。可选地，第四预设阈值也可以用up_thr表示，第五预设阈值也可以用down_thr表示。In a possible implementation, the decision feedback equalizer includes a rising accumulator and a falling accumulator, and determines the first change trend according to the number of rising trends and the number of falling trends, including: each time the receiving end determines an rising trend, the rising trend The accumulator accumulates a +1; every time the receiving end determines a downward trend, the descending accumulator accumulates a -1. When the number of multiple smoothing errors accumulates to the third preset number, the value accumulated by the ascending accumulator is the same as the descending accumulator. The sum of the accumulated values determines the first change trend. When the sum of the value accumulated by the rising accumulator and the value accumulated by the falling accumulator is greater than or equal to the fourth preset threshold, the first change trend is determined to be an upward trend; When the sum of is less than or equal to the fifth preset threshold, the first changing trend is determined to be a downward trend; otherwise, the first changing trend is determined to be a stable trend. Optionally, the value accumulated by the rising accumulator can be represented by flag_up, that is, every time the rising accumulator accumulates a local change trend, flag_up is increased by +1; the value accumulated by the falling accumulator can be represented by flag_down, that is, by the rising accumulator For every cumulative local change trend that is a downward trend, flag_down is increased by -1. Optionally, the fourth preset threshold can also be expressed as up_thr, and the fifth preset threshold can also be expressed as down_thr.

在一个具体的示例中，第三预设数量为6，第四预设阈值为2，第五预设阈值为-3，在接收端确定6个平滑误差后，局部变化趋势包括3个上升趋势，则上升累计器累计的数值为+3；局部变化趋势包括2个上升趋势，则下降累计器累计的数值为-2，上升累计器累计的数值和下降累计器累计的数值的和为-1，则接收端确定第一变化趋势为稳定趋势。In a specific example, the third preset number is 6, the fourth preset threshold is 2, and the fifth preset threshold is -3. After the receiving end determines 6 smoothing errors, the local change trend includes 3 upward trends. , then the accumulated value of the rising totalizer is +3; the local change trend includes 2 rising trends, then the accumulated value of the falling totalizer is -2, and the sum of the accumulated value of the rising totalizer and the accumulated value of the falling totalizer is -1 , then the receiving end determines that the first changing trend is a stable trend.

若上升趋势的数量大于下降趋势的数量，并且上升趋势的数量与下降趋势的数量之间的差值大于或者等于第二预设阈值，则将第一变化趋势确定为上升趋势；或者，若上升趋势的数量小于下降趋势的数量，并且下降趋势的数量与上升趋势的数量之间的差值大于或者等于第三预设阈值，则将第一变化趋势确定为下降趋势；否则，则将第一变化趋势确定为稳定趋势。If the number of upward trends is greater than the number of downward trends, and the difference between the number of upward trends and the number of downward trends is greater than or equal to the second preset threshold, the first change trend is determined as an upward trend; or, if the number of upward trends is greater than or equal to the second preset threshold, If the number of trends is less than the number of downward trends, and the difference between the number of downward trends and the number of upward trends is greater than or equal to the third preset threshold, then the first change trend is determined as a downward trend; otherwise, the first change trend is determined as a downward trend; otherwise, the first change trend is determined as a downward trend. The changing trend is determined to be a stable trend.

在一种可能的实施方式中，多个变化趋势包括上升趋势、下降趋势和稳定趋势，第一对应关系包括：在第一变化趋势为上升趋势的情况下，调整系数为初始调整系数的p倍；在第一变化趋势为下降趋势的情况下，调整系数为初始调整系数的q倍；在第一变化趋势为稳定趋势的情况下，调整系数为初始调整系数的s倍；p、q和s均为任意大于0的值。初始调整系数为根据第一变化趋势和第一对应关系调整之前的调整系数。In a possible implementation, the multiple change trends include an upward trend, a downward trend and a stable trend, and the first corresponding relationship includes: when the first change trend is an upward trend, the adjustment coefficient is p times the initial adjustment coefficient. ; When the first change trend is a downward trend, the adjustment coefficient is q times the initial adjustment coefficient; when the first change trend is a stable trend, the adjustment coefficient is s times the initial adjustment coefficient; p, q and s are any values greater than 0. The initial adjustment coefficient is the adjustment coefficient before adjustment based on the first change trend and the first correspondence relationship.

在一个具体的示例中，p为0.65，q为1.5，s为0.85。在调整系数为2的情况下，接收端确定了6个平滑误差，根据该6个平滑误差确定的5个局部变化趋势中，上升趋势的数量大于下降趋势的数量，在接收端确定第一变化趋势为上升趋势，则调整系数变化为1.3。然后，接收端根据变化后的调整系数，确定判决反馈均衡器的参数，并基于新确定的判决反馈均衡器的参数，继续对判决反馈均衡器进行训练。In a specific example, p is 0.65, q is 1.5, and s is 0.85. When the adjustment coefficient is 2, the receiving end determines 6 smoothing errors. Among the 5 local change trends determined based on the 6 smoothing errors, the number of upward trends is greater than the number of downward trends. The first change is determined at the receiving end. If the trend is an upward trend, the adjustment coefficient changes to 1.3. Then, the receiving end determines the parameters of the decision feedback equalizer based on the changed adjustment coefficient, and continues to train the decision feedback equalizer based on the newly determined parameters of the decision feedback equalizer.

作为一个可选的实施例，第一变化趋势是基于实际接收信号中的第一部分信号得到的；在基于调整系数，对判决反馈均衡器的参数进行调整之后，方法500还包括：确定调整后的判决反馈均衡器对实际接收信号中的第二部分信号的处理结果和样本信号之间误差的第二变化趋势；基于第二变化趋势和第一对应关系，确定判决反馈均衡器的参数的再次调整系数；基于再次调整系数，对判决反馈均衡器的参数进行再次调整，并继续对判决反馈均衡器进行训练。As an optional embodiment, the first change trend is obtained based on the first part of the actual received signal; after adjusting the parameters of the decision feedback equalizer based on the adjustment coefficient, the method 500 further includes: determining the adjusted The second changing trend of the error between the processing result of the second part of the signal in the actual received signal by the decision feedback equalizer and the sample signal; based on the second changing trend and the first correspondence, determine the readjustment of the parameters of the decision feedback equalizer coefficient; based on the readjustment of the coefficient, the parameters of the decision feedback equalizer are readjusted, and the decision feedback equalizer is continued to be trained.

应理解，实际接收信号中的第一部分信号、第二部分信号可以为实际接收信号中的部分信号，也可以为实际接收信号中的全部信号。在第一部分信号、第二部分信号为实际接收信号中的部分信号时，实际接收信号还可以包括第三部分信号、第四部分信号等。第二变化趋势也可以为上升趋势、下降趋势或稳定趋势中的一个。接收端可以根据与确定第一变化趋势相同的方法确定第二变化趋势。上述步骤是不断循环进行的，直至满足预设停止条件。It should be understood that the first part signal and the second part signal in the actual received signal may be part of the actual received signal, or may be all signals in the actual received signal. When the first part signal and the second part signal are part of the actual received signal, the actual received signal may also include a third part signal, a fourth part signal, etc. The second change trend can also be one of an upward trend, a downward trend or a stable trend. The receiving end may determine the second change trend according to the same method as determining the first change trend. The above steps are performed continuously in a loop until the preset stopping conditions are met.

下面结合图7至图10和具体的示例对本申请的信号传输方法进行进一步介绍。The signal transmission method of the present application will be further introduced below with reference to Figures 7 to 10 and specific examples.

图7为本申请实施例提供的一种调整系数适应性调整和无调整系数时对应的误差收敛的对比示意图。如图7所示，在样本信号的数量均为1330的情况下，判决反馈均衡器训练过程迭代次数和得到的误差的数量也均为1330。目前的信号传输方法中，无调整系数，即收敛步长始终为1，误差的收敛速度较慢，确定的误差的收敛趋势如图7中的误差的变化趋势（a）所示。通过本申请的信号传输方法对判决反馈均衡器进行训练，调整系数会根据第一变化趋势和第一对应关系不断的进行适应性调整。在判决反馈均衡器训练过程中，初始调整系数为2.5，上文中的第一预设数量为11，上文中的第二预设数量为6，上文中的第四预设阈值为2，上文中的第五预设阈值为-3，确定的误差的收敛趋势如图7中的变化趋势（b）所示。将无调整系数时得到的1330个误差进行均值滤波处理，得到65个平滑误差，该65个平滑误差的变化趋势如图7中的701所示；将调整系数不断适应性调整时得到的1330个误差进行均值滤波处理，得到65个平滑误差，该65个平滑误差的变化趋势如图7中的702所示。在判决反馈均衡器训练过程中，每得到5个平滑误差，接收端会根据该5个平滑误差中任意两个相邻平滑误差，确定4个局部变化趋势，在上升趋势的数量比下降趋势的数量大于或者等于2的情况下，确定第一变化趋势为上升趋势，将调整系数调整为初始调整系数的0.65倍；在下降趋势的数量比上升趋势的数量大于或者等于3的情况下，确定第一变化趋势为下降趋势，将调整系数调整为初始调整系数的1.5倍；否则，确定第一变化趋势为稳定趋势，将调整系数调整为初始调整系数的0.85倍。这样，使得调整系数的变化过程如图7中的变化过程（d）所示。FIG. 7 is a schematic diagram comparing the adaptive adjustment of the adjustment coefficient and the corresponding error convergence when there is no adjustment coefficient according to the embodiment of the present application. As shown in Figure 7, when the number of sample signals is 1330, the number of iterations of the decision feedback equalizer training process and the number of errors obtained are also 1330. In the current signal transmission method, there is no adjustment coefficient, that is, the convergence step is always 1, and the convergence speed of the error is slow. The determined convergence trend of the error is shown in the error change trend (a) in Figure 7. The decision feedback equalizer is trained through the signal transmission method of the present application, and the adjustment coefficient will be continuously adjusted adaptively according to the first change trend and the first correspondence relationship. During the training process of the decision feedback equalizer, the initial adjustment coefficient is 2.5, the first preset number above is 11, the second preset number above is 6, the fourth preset threshold above is 2, and the above The fifth preset threshold is -3, and the convergence trend of the determined error is shown in the change trend (b) in Figure 7. The 1330 errors obtained when there is no adjustment coefficient are subjected to mean filtering processing, and 65 smooth errors are obtained. The changing trend of the 65 smooth errors is shown as 701 in Figure 7; the 1330 errors obtained when the adjustment coefficient is continuously adaptively adjusted The errors are subjected to mean filtering to obtain 65 smooth errors. The changing trend of these 65 smooth errors is shown as 702 in Figure 7. During the training process of the decision feedback equalizer, every time 5 smoothing errors are obtained, the receiving end will determine 4 local changing trends based on any two adjacent smoothing errors among the 5 smoothing errors. When the number of upward trends is greater than that of downward trends, If the number is greater than or equal to 2, determine the first change trend to be an upward trend, and adjust the adjustment coefficient to 0.65 times the initial adjustment coefficient; if the number of downward trends is greater than or equal to 3 than the number of upward trends, determine the first change trend. If the first change trend is a downward trend, adjust the adjustment coefficient to 1.5 times the initial adjustment coefficient; otherwise, determine that the first change trend is a stable trend, and adjust the adjustment coefficient to 0.85 times the initial adjustment coefficient. In this way, the change process of the adjustment coefficient is shown in the change process (d) in Figure 7.

将701和702进行对比，可以看出，通过本申请的信号传输方法，能够提高误差的收敛效率，从而在样本信号数量确定的情况下，能够提高判决反馈均衡器训练的准确率，这样，通过准确率更高的判决反馈均衡器，能够降低接收端的误包率，提高发送端和接收端之间的通信质量，提高用户体验感。Comparing 701 and 702, it can be seen that the signal transmission method of the present application can improve the convergence efficiency of the error, thereby improving the accuracy of the decision feedback equalizer training when the number of sample signals is determined. In this way, through A decision feedback equalizer with higher accuracy can reduce the packet error rate at the receiving end, improve the communication quality between the sending end and the receiving end, and improve the user experience.

图8为本申请实施例提供的另一种调整系数适应性调整和无调整系数时对应的平滑误差收敛的对比示意图。如图8所示，接收端的实际接收信号来自B信道，接收端共确定50个平滑误差，在接收端的判决反馈均衡器训练过程中，无调整系数的情况下，平滑误差的收敛趋势如801所示，在35个平滑误差时，平滑误差趋于收敛；在接收端的判决反馈均衡器训练过程中，调整系数适应性调整的情况下，上文中的第一预设数量为11，平滑误差的收敛趋势如802所示，在10个平滑误差时，平滑误差趋于收敛。将801和802进行对比，可以看出，本申请的信号传输方法使得判决反馈均衡器训练的收敛时间缩短为无调整系数时判决反馈均衡器训练的收敛时间的27%。由此可见，本申请的信号传输方法，在判决反馈均衡器训练过程中，适应性调整调整系数，这样，能够提高判决反馈均衡器的训练效率和准确率，从而提高判决反馈均衡器的均衡结果的准确率。FIG. 8 is a comparative schematic diagram of the adaptive adjustment of another adjustment coefficient and the corresponding smoothing error convergence when there is no adjustment coefficient provided by the embodiment of the present application. As shown in Figure 8, the actual received signal at the receiving end comes from the B channel. The receiving end determines a total of 50 smoothing errors. During the training process of the decision feedback equalizer at the receiving end, without adjustment coefficients, the convergence trend of the smoothing errors is as shown in 801 shows that at 35 smoothing errors, the smoothing errors tend to converge; in the decision feedback equalizer training process at the receiving end, when the adjustment coefficient is adaptively adjusted, the first preset number above is 11, and the smoothing errors converge The trend is shown in 802. At 10 smoothing errors, the smoothing errors tend to converge. Comparing 801 and 802, it can be seen that the signal transmission method of the present application shortens the convergence time of decision feedback equalizer training to 27% of the convergence time of decision feedback equalizer training without adjustment coefficients. It can be seen that the signal transmission method of the present application adaptively adjusts the adjustment coefficient during the training process of the decision feedback equalizer. In this way, the training efficiency and accuracy of the decision feedback equalizer can be improved, thereby improving the equalization results of the decision feedback equalizer. accuracy.

图9为本申请实施例提供的又一种调整系数适应性调整和无调整系数时对应的平滑误差收敛的对比示意图。如图9所示，接收端共确定75个平滑误差，在接收端的判决反馈均衡器训练过程中，无调整系数的情况下，平滑误差的收敛趋势如901所示；在接收端的判决反馈均衡器训练过程中，调整系数适应性调整的情况下，上文中的第一预设数量为11，平滑误差的收敛趋势如902所示。将901和902进行对比，可以看出，通过本申请实施例的信号传输方法，能够提高判决反馈均衡器的训练效率。将图9中的平滑误差的收敛趋势（a）中的区域903部分放大，可以看出，在平滑误差收敛后，在无调整系数时，平滑误差的收敛趋势如904所示；在平滑误差收敛后，调整系数适应性调整的情况下，平滑误差的收敛趋势如904所示。FIG. 9 is a comparative schematic diagram of another adaptive adjustment of the adjustment coefficient and the corresponding smoothing error convergence when there is no adjustment coefficient provided by the embodiment of the present application. As shown in Figure 9, a total of 75 smoothing errors are determined at the receiving end. During the training process of the decision feedback equalizer at the receiving end, without adjustment coefficients, the convergence trend of the smoothing error is shown in 901; in the decision feedback equalizer at the receiving end During the training process, when the adjustment coefficient is adaptively adjusted, the first preset number mentioned above is 11, and the convergence trend of the smoothing error is as shown in 902. Comparing 901 and 902, it can be seen that the training efficiency of the decision feedback equalizer can be improved through the signal transmission method of the embodiment of the present application. Enlarging the area 903 in the convergence trend (a) of the smoothing error in Figure 9, it can be seen that after the smoothing error converges, when there is no adjustment coefficient, the convergence trend of the smoothing error is as shown in 904; after the smoothing error converges Finally, when the adjustment coefficient is adaptively adjusted, the convergence trend of the smoothing error is shown in 904.

示例性地，在本申请实施例中，接收端的实际接收信号可以来自B信道、C信道、D信道、E信道和F信道中的一个或者多个信道。B信道、C信道、D信道、E信道和F信道为通过矩阵实验室（matrix laboratory，MATLAB）的模拟的5种模拟信道，该5种信道分别存在不同程度的符号间干扰，使得在样本信号由发送端传输至接收端的过程中，样本信号会收到不同程度的符号间干扰。因此，接收端在接收来自该5种信道的实际接收信号后，接收端会基于实际接收信号对判决反馈均衡器进行训练，并通过训练好的判决反馈均衡器对业务信号进行干扰消除处理。For example, in this embodiment of the present application, the actual received signal at the receiving end may come from one or more channels among B channel, C channel, D channel, E channel and F channel. B channel, C channel, D channel, E channel and F channel are five types of analog channels simulated by the matrix laboratory (MATLAB). The five channels have different degrees of inter-symbol interference, making the sample signal During the process of transmission from the transmitter to the receiver, the sample signal will receive varying degrees of inter-symbol interference. Therefore, after receiving the actual received signals from the five channels, the receiving end will train the decision feedback equalizer based on the actual received signals, and perform interference cancellation processing on the service signal through the trained decision feedback equalizer.

图10为本申请实施例提供的不同样本信号下调整系数适应性调整和无调整系数时对应的平滑误差收敛的对比示意图。如图10所示，接收端确定的平滑误差的数量均为50。此外，图10中的（a）至（e）中所示的分别为判决反馈均衡器根据来自B信道、C信道、D信道、E信道和F信道的实际接收信号进行训练时的平滑误差的收敛趋势的示意图。在接收端实际接收信号均来自B信道时，在无调整系数的情况下，平滑误差的收敛趋势如1001所示；在调整系数适应性调整的情况下，上文中的第一预设数量为11，平滑误差的收敛趋势如1002所示。在接收端实际接收信号均来自C信道时，在无调整系数的情况下，平滑误差的收敛趋势如1003所示；在调整系数适应性调整的情况下，上文中的第一预设数量为11，平滑误差的收敛趋势如1004所示。在接收端实际接收信号均来自D信道时，在无调整系数的情况下，平滑误差的收敛趋势如1005所示；在调整系数适应性调整的情况下，上文中的第一预设数量为11，平滑误差的收敛趋势如1006所示。在接收端实际接收信号均来自E信道时，在无调整系数的情况下，平滑误差的收敛趋势如1007所示；在调整系数适应性调整的情况下，上文中的第一预设数量为11，平滑误差的收敛趋势如1008所示。在接收端实际接收信号均来自F信道时，在无调整系数的情况下，平滑误差的收敛趋势如1009所示；在调整系数适应性调整的情况下，上文中的第一预设数量为11，平滑误差的收敛趋势如1010所示。分别将收敛趋势1001和收敛趋势1002、收敛趋势1003和收敛趋势1004、收敛趋势1005和收敛趋势1006、收敛趋势1007和收敛趋势1008、收敛趋势1009和收敛趋势1010进行对比，可以看出，本申请的信号传输方法，在判决反馈均衡器训练过程中，适应性调整调整系数，这样，对于不同的在实际接收信号，均能够提高判决反馈均衡器的训练效率和准确率，从而提高判决反馈均衡器的均衡结果的准确率。FIG. 10 is a comparative schematic diagram of the smoothing error convergence when the adjustment coefficient is adaptively adjusted and when there is no adjustment coefficient under different sample signals provided by the embodiment of the present application. As shown in Figure 10, the number of smoothing errors determined by the receiving end is all 50. In addition, shown in (a) to (e) in Figure 10 are smooth errors when the decision feedback equalizer is trained based on actual received signals from the B channel, C channel, D channel, E channel, and F channel, respectively. Schematic diagram of the convergence trend. When the actual received signals at the receiving end are all from the B channel, in the absence of adjustment coefficients, the convergence trend of the smoothing error is as shown in 1001; in the case of adaptive adjustment of the adjustment coefficients, the first preset number above is 11 , the convergence trend of the smoothing error is shown in 1002. When the actual received signals at the receiving end are all from the C channel, in the absence of adjustment coefficients, the convergence trend of the smoothing error is as shown in 1003; in the case of adaptive adjustment of the adjustment coefficients, the first preset number above is 11 , the convergence trend of the smoothing error is shown in 1004. When the actual received signals at the receiving end are all from the D channel, in the absence of adjustment coefficients, the convergence trend of the smoothing error is as shown in 1005; in the case of adaptive adjustment of the adjustment coefficients, the first preset number above is 11 , the convergence trend of the smoothing error is shown in 1006. When the actual received signals at the receiving end are all from the E channel, in the absence of adjustment coefficients, the convergence trend of the smoothing error is as shown in 1007; in the case of adaptive adjustment of the adjustment coefficients, the first preset number above is 11 , the convergence trend of the smoothing error is shown in 1008. When the actual received signals at the receiving end are all from the F channel, in the absence of adjustment coefficients, the convergence trend of the smoothing error is as shown in 1009; in the case of adaptive adjustment of the adjustment coefficients, the first preset number above is 11 , the convergence trend of the smoothing error is shown in 1010. Comparing the convergence trend 1001 with the convergence trend 1002, the convergence trend 1003 with the convergence trend 1004, the convergence trend 1005 with the convergence trend 1006, the convergence trend 1007 with the convergence trend 1008, the convergence trend 1009 with the convergence trend 1010, it can be seen that this application In the signal transmission method, during the training process of the decision feedback equalizer, the adjustment coefficient is adaptively adjusted. In this way, for different actual received signals, the training efficiency and accuracy of the decision feedback equalizer can be improved, thereby improving the decision feedback equalizer. The accuracy of the balanced result.

图11为本申请实施例提供的调整系数适应性调整和无调整系数时对应的误包率和信噪比的关系曲线示意图。如图11所示，无论调整系数是否适应性调整，误包率（PER-PSDU）均随着信噪比（signal to noise ratio，SNR）的增大而呈现降低的趋势。在无调整系数的情况下，误包率和信噪比的关系曲线如1101所示，在适应性基于调整系数调整反馈均衡器的参数的情况下，误包率和信噪比的关系曲线如1102所示。将1101和1102进行对比，在信噪比相同的情况下，1102中对应的误包率更低。示例性地，在信噪比为32dB时，1101中对应的误包率为0.173，1102中对应的误包率为0.112，通过本申请实施例的信号传输方法，使得接收端的误包率降低约35%。Figure 11 is a schematic diagram of the relationship curve between the packet error rate and the signal-to-noise ratio when the adjustment coefficient is adaptively adjusted and when there is no adjustment coefficient provided by the embodiment of the present application. As shown in Figure 11, regardless of whether the adjustment coefficient is adaptively adjusted or not, the packet error rate (PER-PSDU) shows a decreasing trend as the signal to noise ratio (SNR) increases. In the case of no adjustment coefficient, the relationship curve between the packet error rate and the signal-to-noise ratio is as shown in 1101. When the parameters of the feedback equalizer are adjusted adaptively based on the adjustment coefficient, the relationship curve between the packet error rate and the signal-to-noise ratio is as follows 1102 shown. Comparing 1101 and 1102, when the signal-to-noise ratio is the same, the corresponding packet error rate in 1102 is lower. For example, when the signal-to-noise ratio is 32dB, the corresponding packet error rate in 1101 is 0.173, and the corresponding packet error rate in 1102 is 0.112. Through the signal transmission method of the embodiment of the present application, the packet error rate at the receiving end is reduced by approximately 35%.

应理解，上述各方法的序号的大小并不意味着执行顺序的先后，各方法的执行顺序应以其功能和内在逻辑确定。It should be understood that the size of the serial numbers of the above methods does not mean the order of execution. The execution order of each method should be determined by its functions and internal logic.

上文结合图2至图11，详细描述了本申请实施例的信号传输方法，下面结合图12和图13，详细描述本申请实施例的信号传输装置。The signal transmission method according to the embodiment of the present application is described in detail above with reference to FIGS. 2 to 11 . Next, the signal transmission device according to the embodiment of the present application is described in detail with reference to FIGS. 12 and 13 .

图12为本申请实施例提供的一种信号传输装置1200的结构示意图。如图12所示，装置1200包括：收发模块1201和处理模块1202。Figure 12 is a schematic structural diagram of a signal transmission device 1200 provided by an embodiment of the present application. As shown in Figure 12, the device 1200 includes: a transceiver module 1201 and a processing module 1202.

装置1200用于实现上述方法实施例中接收端对应的步骤。The device 1200 is used to implement the steps corresponding to the receiving end in the above method embodiment.

收发模块1201，用于接收来自发送端的信号，信号包括样本信号的实际接收信号和业务信号；The transceiver module 1201 is used to receive signals from the sending end. The signals include the actual received signal of the sample signal and the service signal;

处理模块1202，用于基于实际接收信号和样本信号，对判决反馈均衡器进行训练；在训练过程中，根据判决反馈均衡器对实际接收信号的处理结果和样本信号之间误差的第一变化趋势和第一对应关系，确定判决反馈均衡器的参数的调整系数，第一对应关系包括多个变化趋势和多个调整系数之间的对应关系，多个变化趋势包括第一变化趋势；基于调整系数，对判决反馈均衡器的参数进行调整，并继续对判决反馈均衡器进行训练；利用训练完成的判决反馈均衡器，对业务信号进行干扰消除处理。The processing module 1202 is used to train the decision feedback equalizer based on the actual received signal and the sample signal; during the training process, according to the first changing trend of the error between the processing result of the actual received signal and the sample signal by the decision feedback equalizer and a first correspondence relationship, determining the adjustment coefficient of the parameter of the decision feedback equalizer, the first correspondence relationship includes a correspondence relationship between a plurality of change trends and a plurality of adjustment coefficients, the plurality of change trends include a first change trend; based on the adjustment coefficient , adjust the parameters of the decision feedback equalizer, and continue to train the decision feedback equalizer; use the trained decision feedback equalizer to perform interference elimination processing on the service signal.

可选地，处理模块1202还用于：将实际接收信号输入至判决反馈均衡器，得到实际接收信号的处理结果；确定实际接收信号的处理结果和样本信号之间的误差；基于误差，确定第一变化趋势。Optionally, the processing module 1202 is also used to: input the actual received signal into the decision feedback equalizer to obtain the processing result of the actual received signal; determine the error between the processing result of the actual received signal and the sample signal; based on the error, determine the third A changing trend.

可选地，处理模块1202具体用于：每当误差的数量积累到第一预设数量时，对第一预设数量的误差进行均值滤波处理，得到多个平滑误差；根据多个平滑误差中每两个相邻平滑误差之间的差值，确定多个平滑误差中每两个相邻平滑误差的局部变化趋势，局部变化趋势包括上升趋势和下降趋势；根据上升趋势的数量和下降趋势的数量，确定第一变化趋势。Optionally, the processing module 1202 is specifically configured to: whenever the number of errors accumulates to a first preset number, perform mean filtering on the first preset number of errors to obtain multiple smooth errors; according to the multiple smooth errors The difference between each two adjacent smoothing errors determines the local changing trend of each two adjacent smoothing errors in multiple smoothing errors. The local changing trend includes an upward trend and a downward trend; according to the number of upward trends and the number of downward trends quantity to determine the first change trend.

可选地，处理模块1202具体用于：若上升趋势的数量大于下降趋势的数量，则将第一变化趋势确定为上升趋势；或者，若上升趋势的数量等于下降趋势的数量，则将第一变化趋势确定为稳定趋势；或者，若上升趋势的数量小于下降趋势的数量，则将第一变化趋势确定为下降趋势。Optionally, the processing module 1202 is specifically configured to: if the number of upward trends is greater than the number of downward trends, determine the first change trend as an upward trend; or, if the number of upward trends is equal to the number of downward trends, determine the first change trend as an upward trend; The changing trend is determined as a stable trend; or, if the number of upward trends is less than the number of downward trends, the first changing trend is determined as a downward trend.

可选地，处理模块1202具体用于：当多个平滑误差的数量积累到第二预设数量时，根据上升趋势的数量和下降趋势的数量，确定第一变化趋势。Optionally, the processing module 1202 is specifically configured to: when the number of multiple smoothing errors accumulates to a second preset number, determine the first change trend based on the number of upward trends and the number of downward trends.

可选地，第一变化趋势是基于实际接收信号中的第一部分信号得到的；处理模块1202还用于：确定调整后的判决反馈均衡器对实际接收信号中的第二部分信号的处理结果和样本信号之间误差的第二变化趋势；基于第二变化趋势和第一对应关系，确定判决反馈均衡器的参数的再次调整系数；基于再次调整系数，对判决反馈均衡器的参数进行再次调整，并继续对判决反馈均衡器进行训练。Optionally, the first change trend is obtained based on the first part of the signal in the actual received signal; the processing module 1202 is also used to: determine the processing result of the adjusted decision feedback equalizer on the second part of the signal in the actual received signal and The second changing trend of the error between the sample signals; based on the second changing trend and the first corresponding relationship, determine the re-adjustment coefficient of the parameters of the decision feedback equalizer; based on the re-adjustment coefficient, re-adjust the parameters of the decision feedback equalizer, And continue to train the decision feedback equalizer.

应理解，这里的装置1200以功能模块的形式体现。这里的术语“模块”可以指应用特有集成电路（application specific integrated circuit，ASIC）、电子电路、用于执行一个或多个软件或固件程序的处理器（例如共享处理器、专有处理器或组处理器等）和存储器、合并逻辑电路和/或其它支持所描述的功能的合适组件。在一个可选的例子中，本领域技术人员可以理解，装置1200可以具体为上述实施例中的接收端，装置1200可以用于执行上述方法实施例中与接收端对应的各个流程和/或步骤，为避免重复，在此不再赘述。It should be understood that the device 1200 here is embodied in the form of a functional module. The term "module" as used herein may refer to an application specific integrated circuit (ASIC), an electronic circuit, a processor (such as a shared processor, a proprietary processor, or a group of processors) used to execute one or more software or firmware programs. processor, etc.) and memory, incorporated logic circuitry, and/or other suitable components to support the described functionality. In an optional example, those skilled in the art can understand that the device 1200 can be specifically the receiving end in the above embodiment, and the device 1200 can be used to perform various processes and/or steps corresponding to the receiving end in the above method embodiment. , to avoid repetition, will not be repeated here.

上述装置1200具有实现上述方法中接收端执行的相应步骤的功能；上述功能可以通过硬件实现，也可以通过硬件执行相应的软件实现。该硬件或软件包括一个或多个与上述功能相对应的模块。The above-mentioned device 1200 has the function of realizing the corresponding steps performed by the receiving end in the above-mentioned method; the above-mentioned functions can be realized by hardware, or can also be realized by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions.

在本申请的实施例，图12中的装置1200也可以是芯片，例如：SOC。对应地，处理模块1202可以是该芯片的收发电路，在此不做限定。In this embodiment of the present application, the device 1200 in Figure 12 may also be a chip, such as a SOC. Correspondingly, the processing module 1202 may be the transceiver circuit of the chip, which is not limited here.

图13为本申请实施例提供的一种信号传输装置1300的结构示意图。该装置1300包括处理器1301、收发器1302和存储器1303。其中，处理器1301、收发器1302和存储器1303通过内部连接通路互相通信，该存储器1303用于存储指令，该处理器1301用于执行该存储器1303存储的指令，以控制该收发器1302发送信号和/或接收信号。Figure 13 is a schematic structural diagram of a signal transmission device 1300 provided by an embodiment of the present application. The device 1300 includes a processor 1301, a transceiver 1302 and a memory 1303. Among them, the processor 1301, the transceiver 1302 and the memory 1303 communicate with each other through internal connection paths. The memory 1303 is used to store instructions. The processor 1301 is used to execute the instructions stored in the memory 1303 to control the transceiver 1302 to send signals and /or receive a signal.

应理解，装置1300可以具体为上述实施例中的接收端，并且可以用于执行上述方法实施例中与接收端对应的各个步骤和/或流程。可选地，该存储器1303可以包括只读存储器和随机存取存储器，并向处理器提供指令和数据。存储器的一部分还可以包括非易失性随机存取存储器。例如，存储器还可以存储设备类型的信息。该处理器1301可以用于执行存储器中存储的指令，并且当该处理器1301执行存储器中存储的指令时，该处理器1301用于执行上述方法实施例的各个步骤和/或流程。该收发器1302可以包括发射器和接收器，该发射器可以用于实现上述收发器对应的用于执行发送动作的各个步骤和/或流程，该接收器可以用于实现上述收发器对应的用于执行接收动作的各个步骤和/或流程。It should be understood that the device 1300 may be specifically a receiving end in the above embodiments, and may be used to perform various steps and/or processes corresponding to the receiving end in the above method embodiments. Optionally, the memory 1303 may include read-only memory and random access memory and provide instructions and data to the processor. A portion of the memory may also include non-volatile random access memory. For example, the memory may also store device type information. The processor 1301 may be used to execute instructions stored in the memory, and when the processor 1301 executes the instructions stored in the memory, the processor 1301 is used to execute various steps and/or processes of the above method embodiments. The transceiver 1302 may include a transmitter and a receiver. The transmitter may be used to implement the steps and/or processes corresponding to the above-mentioned transceiver for performing sending actions. The receiver may be used to implement the functions corresponding to the above-mentioned transceiver. To perform various steps and/or processes of receiving actions.

应理解，在本申请实施例中，该处理器可以是中央处理单元（central processingunit，CPU），该处理器还可以是其他通用处理器、数字信号处理器（DSP）、专用集成电路（ASIC）、现场可编程门阵列（FPGA）或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。It should be understood that in the embodiment of the present application, the processor may be a central processing unit (CPU), or other general-purpose processor, digital signal processor (DSP), or application specific integrated circuit (ASIC). , field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

在实现过程中，上述方法的各步骤可以通过处理器中的硬件的集成逻辑电路或者软件形式的指令完成。结合本申请实施例所公开的方法的步骤可以直接体现为硬件处理器执行完成，或者用处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器，闪存、只读存储器，可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器，处理器执行存储器中的指令，结合其硬件完成上述方法的步骤。为避免重复，这里不再详细描述。During the implementation process, each step of the above method can be completed by instructions in the form of hardware integrated logic circuits or software in the processor. The steps of the methods disclosed in conjunction with the embodiments of the present application can be directly implemented by a hardware processor for execution, or can be executed by a combination of hardware and software modules in the processor. The software module can be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other mature storage media in this field. The storage medium is located in the memory, and the processor executes the instructions in the memory and completes the steps of the above method in combination with its hardware. To avoid repetition, it will not be described in detail here.

本申请还提供了一种计算机可读存储介质，该计算机可读存储介质用于存储计算机程序，该计算机程序用于实现上述方法实施例中所示的方法。This application also provides a computer-readable storage medium, which is used to store a computer program, and the computer program is used to implement the method shown in the above method embodiment.

本申请还提供了一种计算机程序产品，该计算机程序产品包括计算机程序（也可以称为代码，或指令），当该计算机程序在计算机上运行时，该计算机可以执行上述方法实施例所示的方法。This application also provides a computer program product. The computer program product includes a computer program (which can also be called code, or instructions). When the computer program is run on a computer, the computer can execute the steps shown in the above method embodiments. method.

本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的模块及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。Those of ordinary skill in the art can appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each specific application, but such implementations should not be considered beyond the scope of this application.

所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统、装置和模块的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, devices and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be described again here.

在本申请所提供的几个实施例中，应该理解到，所揭露的系统、装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述模块的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个模块或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或模块的间接耦合或通信连接，可以是电性，机械或其它的形式。In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple modules or components may be combined or can be integrated into another system, or some features can be ignored, or not implemented. On the other hand, the coupling or direct coupling or communication connection between each other shown or discussed may be through some interfaces, indirect coupling or communication connection of devices or modules, and may be in electrical, mechanical or other forms.

所述作为分离部件说明的模块可以是或者也可以不是物理上分开的，作为模块显示的部件可以是或者也可以不是物理模块，即可以位于一个地方，或者也可以分布到多个网络模块上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

另外，在本申请各个实施例中的各功能模块可以集成在一个处理模块中，也可以是各个模块单独物理存在，也可以两个或两个以上模块集成在一个模块中。In addition, each functional module in each embodiment of the present application can be integrated into one processing module, or each module can exist physically alone, or two or more modules can be integrated into one module.

所述功能如果以软件功能模块的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备（可以是个人计算机，服务器，或者网络设备等）执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器（read-only memory，ROM）、随机存取存储器（random access memory，RAM）、磁碟或者光盘等各种可以存储程序代码的介质。If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the existing technology or the part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk and other media that can store program code. .

以上所述，仅为本申请的具体实施方式，但本申请实施例的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请实施例揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请实施例的保护范围之内。因此，本申请实施例的保护范围应所述以权利要求的保护范围为准。The above are only specific implementation modes of the present application, but the protection scope of the embodiments of the present application is not limited thereto. Any person familiar with the technical field can easily think of changes within the technical scope disclosed in the embodiments of the present application. or replacement, all should be covered by the protection scope of the embodiments of this application. Therefore, the protection scope of the embodiments of the present application shall be subject to the protection scope of the claims.