CN103067320A - Mesh ad-hoc network channel adaptive automatic equalizer - Google Patents
- ️Wed Apr 24 2013
CN103067320A - Mesh ad-hoc network channel adaptive automatic equalizer - Google Patents
Mesh ad-hoc network channel adaptive automatic equalizer Download PDFInfo
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- CN103067320A CN103067320A CN 201210582470 CN201210582470A CN103067320A CN 103067320 A CN103067320 A CN 103067320A CN 201210582470 CN201210582470 CN 201210582470 CN 201210582470 A CN201210582470 A CN 201210582470A CN 103067320 A CN103067320 A CN 103067320A Authority
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L25/03012—Arrangements for removing intersymbol interference operating in the time domain
- H04L25/03019—Arrangements for removing intersymbol interference operating in the time domain adaptive, i.e. capable of adjustment during data reception
- H04L25/03057—Arrangements for removing intersymbol interference operating in the time domain adaptive, i.e. capable of adjustment during data reception with a recursive structure
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L2025/03433—Arrangements for removing intersymbol interference characterised by equaliser structure
- H04L2025/03439—Fixed structures
- H04L2025/03445—Time domain
- H04L2025/03471—Tapped delay lines
- H04L2025/03484—Tapped delay lines time-recursive
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L2025/03592—Adaptation methods
- H04L2025/03598—Algorithms
- H04L2025/03611—Iterative algorithms
- H04L2025/03636—Algorithms using least mean square [LMS]
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Abstract
The invention discloses a Mesh ad-hoc network channel adaptive automatic equalizer which comprises a linear equalizer and a decision feedback equalizer. The linear equalizer is composed of a delayed unit, tap coefficient units, a summing device and a sampling decision device, the tap coefficient unit consists of a noise producing module and a multiplier, outputs of all tap coefficient units are connected with the summing device, and a balance output of the summing device is connected with the sampling decision device. The decision feedback equalizer is composed of a forward direction filter and a feedback filter, the feedback filter consists of a tap coefficient unit and a delayed unit, a balance output of the equalizer is connected with an input of the delayed unit, an output of the delayed unit is connected with an input of the tap coefficient unit, and the outputs of the tap coefficient units are connected with the summing device. When tracking time-variable characteristics of a communication channel in real time, the Mesh ad-hoc network channel adaptive automatic equalizer overcomes the disturbance among symbols, can effectively prevent from producing signal distortion or producing error code on a receiving end in the process of information transport, and improves communication quality of Mesh ad-hoc network.
Description
Technical field
The present invention relates to a kind of Mesh MANET channel adaptive equalization device.
Background technology
Along with the develop rapidly of science and technology, the continuous propelling of information age, means of communication is also to diversified development.But still there are some drawbacks in the means of communication that generally adopts of people in fact, at present.The below is deficiency and the shortcoming of present several means of communication of generally using and their existence:
(1) cellular mobile communication networks
1. rely on infrastructure: need between the portable terminal could realize communication by fixed base stations, the base station links to each other with key switching network by Wireline, has increased communications cost;
2. portable terminal does not possess routing function, and portable terminal can only carry out data transmit-receive by fixed base stations, uses constraint larger;
3. star topology, certain bar link breaks down, and service on a large scale will be interrupted, and Survivabilities of Networks is poor;
4. build, expansion, maintenance cost be high;
Message transmission rate can reach 2Mbit/s when 5. portable terminal was static, but message transmission rate only has 144kbit/s during the portable terminal high-speed mobile.
(2) trunked communication system
1. similar with cellular mobile communication networks, belong to the network that connection is arranged, rely on infrastructure;
2. generally be dedicated network, take speech business as main.
(3) WLAN (wireless local area network) WLAN
1. mobile node is equipped with wireless network card, is connected with fixed network by the AP access point, depends on the network infrastructure of similar base station or access point;
2. concerning network layer, be single-hop networks, can not forwarding data;
3. can realize high-speed communication (802.11b:11M or 802.11a:54M) in the limited coverage (hundreds of rice), but coverage is comparatively limited.
(4) VSAT satellite communication system
1. coverage is the widest, but cost is high, transmission bandwidth is limited, transmission delay is large.
(5) communication in moving
1. rely on satellite, when rainy day or cloud layer are thick and heavy, or just lost efficacy easily in the place that particular surroundings and existence are blocked, communication failure occurs;
2. antenna is too heavy, uses and carries all very inconveniently, must be placed on the mobile devices such as automobile, steamer;
3. have the star process of seeking of one period long period, can't drop into fast application, the use of a lot of occasions all is restricted.
In sum, present existing communication network mostly is based on the reliable and stable communications infrastructure, in case these communications infrastructures are destroyed, conventional means of communication is all no longer feasible.And often be exactly in such, keeping reliably, communication seems particularly important.Trunked communication system also has considerable restraint on the network bandwidth except relying on infrastructure, use the arrowband technology more, and about bandwidth 30K, about message transmission rate 16Kbps, this is just so that its data transmission capabilities is greatly limited.Therefore, under some special occasions, existing means of communication can't satisfy the demand of communication, and maximum problem is exactly that survival ability is too poor, is destroyed fast easily.
Mesh self-organized network communication system has following characteristic:
1) without the center: the status of all nodes all is equality in the MANET, it is a peer to peer network, node can add and deviated from network at any time, when arbitrary relay nodes disconnects, communication terminal or the repeater of Automatic-searching minimum distance remedy, the fault of any node can not affect the normal operation of whole network, has very strong survivability.
2) self-organizing: the cloth of network is if launch to need not to rely on any default basic communications facility, just can form quickly and automatically after the node start one independently network launch communication work, communication efficiency is high and build, expansion, safeguard and the cost of use low.
3) multi-hop route: when node will with its coverage outside node when communicating, can transmit and can realize by the multi-hop of intermediate node (communication terminal or repeater).
4) dynamic topology: the wireless self-assembly system allows the topological structure of dynamic change oneself, and topology of networks can constantly change to adapt to the conversation needs along with the variation of handheld terminal.
5) smart terminal: communication terminal is portable hand-held machine or vehicle-mounted machine, carries with easy to use; For conserve energy, each communication terminal can be selected best working method automatically, and it only keeps in touch to reduce communication energy consumption with nearest node.
6) communication quality: it is strong that MANET has adaptive capacity to environment, and can with outer Network Communication, obtain abundant data service; The characteristics such as its transfer of data has the speed height, it is wide to be with, time-delay is little and network coverage is wide.
In the wireless communication system of Mesh MANET, reliability is a very important index.In the channel of band limit and time diffusion, the intersymbol interference meeting that causes owing to multi-path influence makes the signal of transmission produce distortion, thereby produces easily error code in receiving terminal, and the balanced a kind of technology that overcomes just intersymbol interference.Because randomness and the time variation of wireless channel, just require the time-varying characteristics of the tracking communication channel that equalizer can be real-time, this equalizer is called adaptive equalizer.
Summary of the invention
The object of the invention is to overcome the deficiencies in the prior art, a kind of time-varying characteristics of real-time tracking communication channel are provided, overcome intersymbol interference, the Mesh MANET channel adaptive equalization device of avoiding producing distorted signals in the message transmitting procedure or producing error code at receiving terminal.
The objective of the invention is to be achieved through the following technical solutions: Mesh MANET channel adaptive equalization device, it is made of linear equalizer and DFF, by model selection, between linear equalization and decision feedback equalization, automatically switch, and automatically select the algorithm of best results;
Described linear equalizer comprises 2N delay unit, 2N+1 tap coefficient unit, an adder and a sampling decision device, the tap coefficient unit is comprised of noise producing module and multiplier, input signal respectively with the first delay unit be connected the input of tap coefficient unit and be connected, one tunnel output of the first delay unit is connected with the input of the second delay unit, another road output links to each other with the second tap coefficient unit, the output of final stage delay unit is connected with the input of final stage tap coefficient unit, the output of each tap coefficient unit connects adder, and the equilibrium output of adder is connected with the sampling decision device;
Described DFF comprises forward-direction filter and feedback filter, the structure of forward-direction filter is identical with the structure of linear equalizer, feedback filter comprises at least one tap coefficient unit and the identical delay unit of quantity with it, the equilibrium output of adder links to each other with the input of delay unit, the output of delay unit is connected with the input of tap coefficient unit, and the output of each tap coefficient unit all connects adder.
Linear equalizer of the present invention is linear LMS equalizer.
Further, linear LMS equalizer comprises the weight setting unit, delay unit, the tap coefficient unit, adder, decision unit and mistake in computation feedback unit, input signal respectively with delay unit, the weight setting unit links to each other, the output of delay unit and weight setting unit all links to each other with the tap coefficient unit, the output of tap coefficient unit connects adder, a road of adder is exported direct output signal output, the the second tunnel output of adder is connected with one tunnel input of mistake in computation feedback unit with training unit by decision unit successively, the Third Road output of adder links to each other the output connection weight setting unit of mistake in computation feedback unit with another road input of mistake in computation feedback unit.
DFF of the present invention is decision-feedback LMS equalizer.
Further, decision-feedback LMS equalizer comprises the weight setting unit, the forward direction delay unit, the forward taps coefficient elements, the delay of feedback unit, the feedback tap coefficient elements, adder, decision unit and mistake in computation feedback unit, input signal respectively with the forward direction delay unit, the weight setting unit links to each other, the output of forward direction delay unit and weight setting unit all links to each other with the forward taps coefficient elements, the output of forward taps coefficient elements connects adder, a road of adder is exported direct output signal output, the the second tunnel output of adder is connected with training unit by decision unit, one tunnel output of training unit connects the mistake in computation feedback unit, another road output of training unit is connected with the input of delay of feedback unit, the delay of feedback unit is connected with the feedback tap coefficient elements, and the output of feedback tap coefficient elements all connects adder; The Third Road output of adder links to each other the output connection weight setting unit of mistake in computation feedback unit with the mistake in computation feedback unit.
The invention has the beneficial effects as follows:
(1) time-varying characteristics of real-time tracking communication channel have overcome intersymbol interference, can effectively avoid producing in the message transmitting procedure distorted signals or produce error code at receiving terminal, have improved the communication quality of Mesh MANET;
(2) based on the communication channel adaptive equalization of LMS algorithm, the LMS algorithm is algorithms most in use, and is simple in structure, and operand is moderate, and stability does not rely on input data and only relevant with step-length, and the tracking characteristics of time varying channel is better than the RLS algorithm.
Description of drawings
Fig. 1 is the linear equalizer structural representation;
Fig. 2 is the Structure of Decision-feedback Equalization schematic diagram;
Fig. 3 is linear LMS equaliser structure schematic diagram;
Fig. 4 is decision-feedback LMS equaliser structure schematic diagram.
Embodiment
Below in conjunction with accompanying drawing technical scheme of the present invention is described in further detail, but protection scope of the present invention is not limited to the following stated.
Mesh MANET channel adaptive equalization device, it is made of linear equalizer and DFF, by model selection, automaticallyes switch between linear equalization and decision feedback equalization, and automatically selects the algorithm of best results.
As shown in Figure 1, linear equalizer comprises 2N delay unit, 2N+1 tap coefficient unit, an adder and a sampling decision device, the tap coefficient unit is comprised of noise producing module and multiplier, input signal respectively with the first delay unit be connected the input of tap coefficient unit and be connected, one tunnel output of the first delay unit is connected with the input of the second delay unit, another road output links to each other with the second tap coefficient unit, the output of final stage delay unit is connected with the input of final stage tap coefficient unit, the output of each tap coefficient unit connects adder, and the equilibrium output of adder is connected with the sampling decision device.Input signal with each respective taps multiplication (being linear, additive), then in the adder addition, is delivered to the sampling decision device respectively at last through behind the delay unit.
Linear equalizer can be realized by the FIR filter, and linear equalizer is done that linear superposition generates with past value by filter coefficient the currency of received signal and as exporting.
When difficult processing of the serious consequently linear equalizer of channel distortion, when the decline of degree of depth frequency spectrum is arranged in the channel, linear equalizer can not obtain satisfied effect, just need this time to adopt nonlinear equalizer, nonlinear equalizer to comprise DFF, maximum likelihood sign equalizer and maximum-likelihood sequence estimation equalizer.
As shown in Figure 2, DFF comprises forward-direction filter and feedback filter, the structure of forward-direction filter is identical with the structure of linear equalizer, feedback filter comprises at least one tap coefficient unit and the identical delay unit of quantity with it, the equilibrium output of adder links to each other with the input of delay unit, the output of delay unit is connected with the input of tap coefficient unit, and the output of each tap coefficient unit all connects adder.
In case the basic ideas of DFF are after detecting and judging a signal code, just can predict and eliminate the intersymbol interference that this symbol brings before detecting successive character.
The filter that becomes when adaptive equalizer is one, its parameter need constantly to adjust.General adaptive algorithm is controlled by error, by error signal e cost function is minimized, and namely the weight with iterative manner renewal equalizer makes cost function be tending towards minimum.In actual applications, coefficient of equalizing wave filter can be determined by various algorithms.These algorithms mainly contain: zero forcing algorithm, LMS algorithm, RLS algorithm etc.Wherein the criterion of LMS algorithm is desired output and the minimum of the mean square error between the real output value that makes equalizer.Seek filter weight optimum or that approach optimum by carrying out the following formula iterative operation: new weight=original weight+current input vector of constant * predicated error *; Wherein, predicated error=pre-enter desired value-real output value.For better real-time change of following the tracks of channel, the training sequence that the transmission of system cycle is known, equilibrium is estimated channel, constantly adjusts filter coefficient, makes mean square error minimum.
As shown in Figure 3, linear equalizer adopts linear LMS equalizer.Linear LMS equalizer comprises the weight setting unit, delay unit, the tap coefficient unit, adder, decision unit and mistake in computation feedback unit, input signal respectively with delay unit, the weight setting unit links to each other, the output of delay unit and weight setting unit all links to each other with the tap coefficient unit, the output of tap coefficient unit connects adder, a road of adder is exported direct output signal output, the the second tunnel output of adder is connected with one tunnel input of mistake in computation feedback unit with training unit by decision unit successively, the Third Road output of adder links to each other the output connection weight setting unit of mistake in computation feedback unit with another road input of mistake in computation feedback unit.
As shown in Figure 4, DFF is decision-feedback LMS equalizer.Decision-feedback LMS equalizer comprises the weight setting unit, the forward direction delay unit, the forward taps coefficient elements, the delay of feedback unit, the feedback tap coefficient elements, adder, decision unit and mistake in computation feedback unit, input signal respectively with the forward direction delay unit, the weight setting unit links to each other, the output of forward direction delay unit and weight setting unit all links to each other with the forward taps coefficient elements, the output of forward taps coefficient elements connects adder, a road of adder is exported direct output signal output, the the second tunnel output of adder is connected with training unit by decision unit, one tunnel output of training unit connects the mistake in computation feedback unit, another road output of training unit is connected with the input of delay of feedback unit, the delay of feedback unit is connected with the feedback tap coefficient elements, and the output of feedback tap coefficient elements all connects adder; The Third Road output of adder links to each other the output connection weight setting unit of mistake in computation feedback unit with the mistake in computation feedback unit.
Because become when channel is, making a start periodically sends training sequence, follow the tracks of the variation of channel to help equalizer.In MESH, the frame head of every frame data can comprise the pseudo random sequence (training sequence) of a regular length.Equalizer has training mode and two kinds of operating states of tracing mode.At the work initial stage, the tap coefficient of sef-adapting filter is initialized as null vector.Data communication device is sent into adaptive equalizer after crossing the receiver reception ﹠ disposal, and the tap coefficient of equalizer is adjusted under the error control that receives signal and training sequence automatically.Through after the iteration of certain number of times, the filter factor of equalizer can approach the optimum value that can obtain and no longer significantly change, and this state of equalizer is called as convergence.This moment, equalizer was in tracing mode (also being decision pattern), and under this pattern, the tap coefficient of equalizer is adjusted under the error control that receives signal and signal constellation (in digital modulation) figure automatically.Equalizer is placed on after the frame synchronization, and equalizer automaticallyes switch in training mode and tracing mode according to frame synchronizing signal and training sequence length.
Zero forcing algorithm has amplified noise, is difficult to adapt to deep fading's channel.The RLS algorithm performance is better, but algorithm is complicated, and operand is large, be not suitable for integrated, and its stability dependency in the input data.LMS is the algorithm of commonly using the most, and is simple in structure, and operand is moderate, and stability does not rely on input data and only relevant with step-length, and is good than RLS algorithm to the tracking characteristics of time varying channel yet, thus in MESH choice for use LMS algorithm.
Claims (5)
1.Mesh MANET channel adaptive equalization device is characterized in that: it is made of linear equalizer and DFF, by model selection, automaticallyes switch between linear equalization and decision feedback equalization, and automatically selects the algorithm of best results;
Described linear equalizer comprises 2N delay unit, 2N+1 tap coefficient unit, an adder and a sampling decision device, the tap coefficient unit is comprised of noise producing module and multiplier, input signal respectively with the first delay unit be connected the input of tap coefficient unit and be connected, one tunnel output of the first delay unit is connected with the input of the second delay unit, another road output links to each other with the second tap coefficient unit, the output of final stage delay unit is connected with the input of final stage tap coefficient unit, the output of each tap coefficient unit connects adder, and the equilibrium output of adder is connected with the sampling decision device;
Described DFF comprises forward-direction filter and feedback filter, the structure of forward-direction filter is identical with the structure of linear equalizer, feedback filter comprises at least one tap coefficient unit and the identical delay unit of quantity with it, the equilibrium output of adder links to each other with the input of delay unit, the output of delay unit is connected with the input of tap coefficient unit, and the output of each tap coefficient unit all connects adder.
2. Mesh MANET channel adaptive equalization device according to claim 1, it is characterized in that: described linear equalizer is linear LMS equalizer.
3. Mesh MANET channel adaptive equalization device according to claim 2, it is characterized in that: described linear LMS equalizer comprises the weight setting unit, delay unit, the tap coefficient unit, adder, decision unit and mistake in computation feedback unit, input signal respectively with delay unit, the weight setting unit links to each other, the output of delay unit and weight setting unit all links to each other with the tap coefficient unit, the output of tap coefficient unit connects adder, a road of adder is exported direct output signal output, the the second tunnel output of adder is connected with one tunnel input of mistake in computation feedback unit with training unit by decision unit successively, the Third Road output of adder links to each other the output connection weight setting unit of mistake in computation feedback unit with another road input of mistake in computation feedback unit.
4. Mesh MANET channel adaptive equalization device according to claim 1, it is characterized in that: described DFF is decision-feedback LMS equalizer.
5. Mesh MANET channel adaptive equalization device according to claim 4, it is characterized in that: described decision-feedback LMS equalizer comprises the weight setting unit, the forward direction delay unit, the forward taps coefficient elements, the delay of feedback unit, the feedback tap coefficient elements, adder, decision unit and mistake in computation feedback unit, input signal respectively with the forward direction delay unit, the weight setting unit links to each other, the output of forward direction delay unit and weight setting unit all links to each other with the forward taps coefficient elements, the output of forward taps coefficient elements connects adder, a road of adder is exported direct output signal output, the the second tunnel output of adder is connected with training unit by decision unit, one tunnel output of training unit connects the mistake in computation feedback unit, another road output of training unit is connected with the input of delay of feedback unit, the delay of feedback unit is connected with the feedback tap coefficient elements, and the output of feedback tap coefficient elements all connects adder; The Third Road output of adder links to each other the output connection weight setting unit of mistake in computation feedback unit with the mistake in computation feedback unit.
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| CN105450566A (en) * | 2014-09-30 | 2016-03-30 | 展讯通信（上海）有限公司 | Balancing method and balancer |
| CN105827557A (en) * | 2016-05-24 | 2016-08-03 | 桂林市思奇通信设备有限公司 | Time-domain equalizer based on MIMO (Multiple-Input Multiple-Output) |
| CN107005307A (en) * | 2014-12-09 | 2017-08-01 | 华为技术有限公司 | The method and balancer of a kind of setting balancer |
| CN107733821A (en) * | 2017-09-26 | 2018-02-23 | 北京集创北方科技股份有限公司 | Channel compensating method and device |
| CN108574475A (en) * | 2017-03-08 | 2018-09-25 | 默升科技集团有限公司 | Receiving filter is simulated in finite impulse response (FIR) with the delay chain based on amplifier |
| CN108616276A (en) * | 2016-12-12 | 2018-10-02 | 中国航空工业集团公司西安航空计算技术研究所 | Simulation decision feedback equalization circuit for high speed SerDes |
| CN113992485A (en) * | 2021-10-27 | 2022-01-28 | 西安微电子技术研究所 | Decision feedback equalization circuit and high-speed signal channel transmission structure |
| CN114710212A (en) * | 2022-05-06 | 2022-07-05 | 成都天奥测控技术有限公司 | IQ correction method, module, equipment and system based on decision feedback |
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| US7027503B2 (en) * | 2002-06-04 | 2006-04-11 | Qualcomm Incorporated | Receiver with a decision feedback equalizer and a linear equalizer |
| JP4822946B2 (en) * | 2006-06-16 | 2011-11-24 | 日本無線株式会社 | Adaptive equalizer |
| CN100562076C (en) * | 2006-06-29 | 2009-11-18 | 上海高清数字科技产业有限公司 | Time-domain adaptive equalizer and the decision feedback filter device that comprises thereof |
| CN102790734B (en) * | 2011-05-18 | 2014-12-31 | 中国科学院声学研究所 | A Linear Adaptive Equalizer Based on Channel Estimation |
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| CN105450566A (en) * | 2014-09-30 | 2016-03-30 | 展讯通信（上海）有限公司 | Balancing method and balancer |
| CN105450566B (en) * | 2014-09-30 | 2019-04-30 | 展讯通信（上海）有限公司 | Equalization methods and balanced device |
| CN107005307B (en) * | 2014-12-09 | 2019-06-28 | 华为技术有限公司 | A kind of method and balancer that balancer is set |
| CN107005307A (en) * | 2014-12-09 | 2017-08-01 | 华为技术有限公司 | The method and balancer of a kind of setting balancer |
| CN105827557A (en) * | 2016-05-24 | 2016-08-03 | 桂林市思奇通信设备有限公司 | Time-domain equalizer based on MIMO (Multiple-Input Multiple-Output) |
| CN108616276A (en) * | 2016-12-12 | 2018-10-02 | 中国航空工业集团公司西安航空计算技术研究所 | Simulation decision feedback equalization circuit for high speed SerDes |
| CN108574475A (en) * | 2017-03-08 | 2018-09-25 | 默升科技集团有限公司 | Receiving filter is simulated in finite impulse response (FIR) with the delay chain based on amplifier |
| CN107733821A (en) * | 2017-09-26 | 2018-02-23 | 北京集创北方科技股份有限公司 | Channel compensating method and device |
| CN113992485A (en) * | 2021-10-27 | 2022-01-28 | 西安微电子技术研究所 | Decision feedback equalization circuit and high-speed signal channel transmission structure |
| CN113992485B (en) * | 2021-10-27 | 2023-05-30 | 西安微电子技术研究所 | Decision feedback equalization circuit and high-speed signal channel transmission system |
| CN114710212A (en) * | 2022-05-06 | 2022-07-05 | 成都天奥测控技术有限公司 | IQ correction method, module, equipment and system based on decision feedback |
| CN114710212B (en) * | 2022-05-06 | 2023-10-31 | 成都天奥测控技术有限公司 | IQ correction method, module, device and system based on decision feedback |
| CN115987727A (en) * | 2023-03-21 | 2023-04-18 | 荣耀终端有限公司 | Signal transmission method and device |
| CN115987727B (en) * | 2023-03-21 | 2023-09-26 | 荣耀终端有限公司 | Signal transmission methods and devices |
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| WO2014101341A1 (en) | 2014-07-03 |
| CN103067320B (en) | 2015-09-16 |
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