CN108923887A - Soft decision decoder structure of multi-system partial response CPM signal - Google Patents
Soft decision decoder structure of multi-system partial response CPM signal Download PDFInfo
- Publication number
- CN108923887A CN108923887A CN201810671401.8A CN201810671401A CN108923887A CN 108923887 A CN108923887 A CN 108923887A CN 201810671401 A CN201810671401 A CN 201810671401A CN 108923887 A CN108923887 A CN 108923887A
- Authority
- CN
- China
- Prior art keywords
- state
- module
- path
- reliability matrix
- reliability
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
- H04L1/0045—Arrangements at the receiver end
- H04L1/0054—Maximum-likelihood or sequential decoding, e.g. Viterbi, Fano, ZJ algorithms
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
- H04L1/0045—Arrangements at the receiver end
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
- H04L1/0056—Systems characterized by the type of code used
- H04L1/0061—Error detection codes
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
- H04L1/0056—Systems characterized by the type of code used
- H04L1/0064—Concatenated codes
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/18—Phase-modulated carrier systems, i.e. using phase-shift keying
- H04L27/22—Demodulator circuits; Receiver circuits
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Artificial Intelligence (AREA)
- Error Detection And Correction (AREA)
Abstract
The invention provides a soft-decision decoder for a multi-system partial response CPM signal. The method comprises the following steps: the device comprises an adding and comparing module, a reliability matrix updating unit, a state selecting module, a first delay module, a second delay module and a soft decision output module. The branch measurement and modulation index synchronous signals of all paths are input into an addition and comparison module, the addition and comparison module calculates the survivor path serial number and the competition path serial number of each state and the measurement difference (path measurement difference for short) of the survivor path and the competition path and outputs the measurement difference to a reliability matrix updating unit, and the accumulated measurement of each state is calculated and output to a state selection module. The state picking module finds the state with the largest cumulative metric among all the states. The soft decision output module calculates the likelihood ratio (multi-system likelihood information) of all the symbols and outputs the likelihood ratio. The decoder can be suitable for soft decision decoding of a multilevel CPM signal; is suitable for high-speed decoding.
Description
Technical field
The present invention relates to wireless communication and telemetry remote control technology fields, provide a kind of for multi-system part response CPM
The soft decision decoder structure of (Continuous Phase Modulation, Continuous Phase Modulation) signal.
Background technique
CPM signal has the characteristics that Phase Continuation, other opposite modulation systems all have on power efficiency, bandwidth efficiency
Very big advantage is with a wide range of applications in satellite communication, remote measuring and controlling field.According to the part response length of CPM signal
Whether L, which is greater than 1, can be divided into CPM signal total regression CPM signal and part response CPM signal, and part, which responds CPM signal, to be had
Memorability, waveform is not only related with the symbol in current symbol period in current symbol period, also and preceding several code-element periods
Symbol is related.Part response CPM can obtain better bandwidth availability ratio.CPM signal is processed into during general demodulation
For hard-decision values (i.e. 0 or 1), a large amount of average informations are during which had lost.If each decision value generated in demodulating process is seemingly
Right information carrys out auxiliary channel decoding, then can obtain better error-resilient performance.SOVA (Soft-output Viterbi, it is soft
Output Viterbi) it is a kind of soft-decision algorithm that likelihood information is exported on the basis of exporting Viterbi hard-decision values
(Hagenauer J,Hoeher P.A Viterbi Algorithm with Soft-Decision Outputs and its
Applications[C]//Global Telecommunications Conference,1989,and
Exhibition.Communications Technology for the 1990s and Beyond.GLOBECOM'
89.IEEE.IEEE Xplore,1989:1680-1686 vol.3.).Soft decision decoder currently based on SOVA algorithm is big
It is mostly Two-Step SOVA structure (Joeressen O J, Meyr H.A 40Mbit/s soft-output Viterbi
decoder[J].IEEE Journal of Solid-State Circuits,1995,30(7):812-818.) succession and
Development.As shown in Figure 1, this structure, by Gabi selection module, survivor path memory module measures quantizing, normalization, delay mould
Block, path comparison module, likelihood value update module, time delay module and selecting module composition.The branch metric in all paths inputs
The metric of the path candidate of each state relatively and is selected the survivor path, competing of each state by Gabi selection module, Gabi selection module
Path is striven, the cumulative metric of each state is updated, gives the serial number of the survivor path of each state, contended path to survivor path
Memory module gives the survivor path of each state after delay, the serial number of contended path to path comparison module, will
The survivor path of each state, the metric difference of contended path, which are given, measures quantizing, normalization, time delay module；Survivor path is deposited
Storage module is recalled according to the state transfer indicating vector sent, survivor path that backtracking is obtained, correspondence in contended path
Symbol give path comparison module, the serial number for the state view that survivor path passes through gives that quantizing measurement, normalization, be delayed mould
Block.Measure quantizing, normalization, time delay module is passed through by the survivor path that the number of state indexes that survivor path passes through selects
The corresponding metric difference of state, and given likelihood value update module；Path comparison module one side output hard-decision values, one
Aspect finds out survivor path, corresponds to the unequal position of symbol in contended path, gives likelihood value update module；Likelihood value updates
Module is according to the corresponding measurement of state for corresponding to the unequal position of symbol and survivor path process in survivor path, contended path
Difference, the metric difference picked out survivor path, correspond to the unequal position of symbol in contended path, is minimized as likelihood information
Output.It is exactly soft-decision that hard decision and likelihood information, which combine,.The algorithm itself that this structure is based on not is optimal
SOVA algorithm, performance can not (maximal posterior probability algorithm be in log-domain with close Max-Log-MAP algorithm ideally
Approximate algorithm), and improved and performance can be worse under the application scenarios of multi-system.The present invention provide it is a kind of mostly into
System part responds the soft decision decoder structure of CPM signal, and this structure is based on a kind of multi-system part and responds Multi-h CPM
Soft output Viterbi algorithm (Lai Penghui, Ma Yanmin, Wang Shilian, Xie Shunqin, high triumphant multi-system part respond Multi-h
Soft output Viterbi algorithm [J] the Terahertz science and electronic information journal .20148.16 (2) of CPM:277-292), performance
It is greatly enhanced.
Summary of the invention
It is this to translate the object of the present invention is to provide a kind of soft decision decoder structure of multi-system part response CPM signal
Code device structure can be suitable for the Soft decision decoding of multi-system CPM signal；The performance of the algorithm of realization and ideally
Max-Log-MAP algorithm is close；The processing clock that each symbol needs is few, is suitble to high-speed coding.
As shown in Fig. 2, a kind of soft decision decoder of multi-system part response CPM signal, is typically characterized by, including：
Gabi selection module, reliability matrix updating unit, state Choosing module, the first time delay module, the second time delay module, soft-decision are defeated
Module out.The branch metric in all paths, modulation index synchronization signal (not needed when for single index CPM application scenarios) input
Gabi selection module, Gabi selection module execute the Gabi selection operation of existing SOVA decoder, calculate the survivor path of each state
The metric difference (abbreviation path metric difference) of serial number and contended path serial number and survivor path and contended path is simultaneously exported to reliable
Property matrix update unit, calculate the cumulative metric of each state and export to state Choosing module.Modulation index synchronization signal is same
When be input to the first time delay module, the first time delay module will be exported by the modulation index synchronization signal of delay to reliability matrix
Updating unit.Reliability matrix updating unit is used to update the reliability matrix of each state, and by the reliability of each state
The first row of matrix is exported to soft-decision output module.State Choosing module finds out the stateful middle maximum shape of cumulative metric of institute
State, and the serial number of the state is exported to the second time delay module.Second time delay module is by the serial number of the maximum state of cumulative metric
It is delayed, the serial number of the maximum state of cumulative metric by delay is exported to soft-decision output module.Soft-decision output
Module calculates the likelihood ratio (likelihood information of multi-system) of all symbols and exports.
Further, the reliability matrix updating unit, including：One reliability matrix mapping block, several are reliable
Property matrix update module, the number of reliability matrix update module corresponds to the state number of CPM signal.At current time,
The input of reliability matrix mapping block is the survivor path serial number and contended path serial number of current time each state；Reliability
Matrix mapping block is according to the survivor path serial number and contended path serial number of each state, survivor path to each state and competing
It strives path to be recalled, finds state and contended path previous moment process that the survivor path previous moment of each state is passed through
State, then the reliability matrix of the corresponding previous moment of state that the survivor path previous moment of each state is passed through exports
To the corresponding reliability matrix update module of the state, corresponding previous moment in the state that contended path previous moment is passed through
Reliability matrix export reliability matrix update module corresponding to the state.Meanwhile each reliability matrix update module
Input the path metric difference of the module corresponding states obtained in Gabi selection module.The corresponding reliability matrix of each state updates
Module calculates the corresponding reliability matrix of the state for updating current time, and reliability matrix first row is exported to soft-decision
Output module.
The beneficial effects of the invention are as follows：A kind of completely new SOVA decoder architecture is proposed, is constantly updated under this structure
The reliability matrix for indicating multi-system reliability, can export the likelihood information of multi-system；The algorithm performance of realization can approach
Max-Log-MAP algorithm ideally；The reliability matrix update that reliability matrix updating unit is realized can be in 1 clock
Interior completion is suitble to realization of High Speed.
Detailed description of the invention
Fig. 1 is the schematic diagram of SOVA decoder in the prior art；
Fig. 2 is the soft decision decoder structural schematic diagram of response CPM signal in multi-system part of the present invention；
Fig. 3 is the state transition network lattice of multi-system part response CPM signal；
Fig. 4 is that reliability matrix updates list in the soft decision decoder of response CPM signal in multi-system part of the present invention
Meta structure schematic diagram；
Fig. 5 is using the more modulation index CPM system structure charts of cascade LDPC of the invention；
Fig. 6 is using the more modulation index CPM system error performance figures of cascade LDPC of the invention；
Table 1 is the occupation condition that the present invention realizes on FPGA；
Specific embodiment
To be more easily understood the present invention, with reference to the accompanying drawing, with status number for 8, the part of system number M=4 is responded
The soft decision decoder of CPM is realized on FPGA (Field Programmable Gate Array, field programmable gate array)
For, the present invention is described in further detail.
Status number is 8, and the state transition network lattice of the part response CPM of system number M=4 are as shown in Figure 3.Wherein S0~S7For
Corresponding 8 states of CPM signal.Lines indicate state transition path, and wherein solid line indicates that symbol is 0 transfer path, closeer
The dashed bars of collection indicate that symbol is 1 transfer path, and sparse dashed bars line indicates that symbol is 2 transfer path, dotted line table
Show that symbol is 3 transfer path.(CPM state transition network lattice are to see document Anderson J B, Aulin T known in the field CPM,
Sundberg C E.Digital Phase Modulation[J].Applications of Communications
Theory,1986:412-412.)
Gabi selection module of the invention and the Gabi selection modular structure of existing SOVA decoder are similar with function.Difference
It is, each state of 4 ary CPM signals has 4 path candidates (with reference to Fig. 3), and each state of binary system CPM signal is only
Want two path candidates.Therefore the present invention and the difference of existing SOVA decoder are that existing SOVA decoder only need to be from two
The biggish path of cumulative metric is selected in path candidate and is considered as survivor path, and another is contended path, and the present invention need to be from M item
The maximum path of cumulative metric is selected in path candidate, is regarded as survivor path, it is second largest to select cumulative metric, depending on
For contended path.
Modulation index synchronization signal inputs the first time delay module simultaneously.First time delay module to modulation Exponential Synchronization signal into
Line delay is aligned the modulation index synchronization signal by delay of output in time with the output of Gabi selection module, and will
It is exported to reliability matrix update module.The processing time of usual Gabi selection module is 3 or 4 clocks, therefore first prolongs
When module delay time be 3 or 4 clocks.
As shown in figure 4, reliability matrix updating unit includes：One reliability matrix mapping block, several reliabilities
Matrix update module.At current time, the input of reliability matrix mapping block is the survival road of current time each state
Diameter serial number and contended path serial number；Reliability matrix mapping block is according to the survivor path serial number and contended path sequence of each state
Number, the survivor path and contended path of each state are recalled, the survivor path previous moment for finding each state is passed through
State and contended path previous moment pass through state；The state pair that the survivor path previous moment of each state is passed through again
The reliability matrix for the previous moment answered exports reliability matrix update module corresponding to the state, when contended path is previous
The reliability matrix for carving corresponding previous moment in the state passed through exports reliability matrix update module corresponding to the state.
Meanwhile the path metric difference of the module corresponding states obtained in each reliability matrix update module input Gabi selection module.
The corresponding reliability matrix update module of each state calculates the corresponding reliability matrix of the state for updating current time, and will
Reliability matrix first row is exported to soft-decision output module.
Corresponding reliability matrix is the matrix of 4 row δ column in each state.Wherein δ is positive integer, and size is according to reality
Border situation determines that the precision of the bigger reliability matrix of the value of δ is higher, and the value of general δ is less than 30.For ease of illustration of reliability square
The renewal process of element in battle array, by k moment state SiCorresponding reliability matrix is expressed as in (0≤i≤7, i are integer)By k+1 moment state SiSurvivor path in the state that the k moment passes through the corresponding k moment can
It is expressed as by property matrixBy k+1 moment state SiContended path pass through at the k moment
The reliability matrix at corresponding k moment is expressed as in stateWherein j, μ are whole
Number, and 0≤j≤δ -1,0≤μ≤3.
Element in reliability matrix initializes rule：
When 0 moment, state SiIn corresponding reliability matrix last columnMiddle element assignment as the following formula：
Wherein v is into state SiThe corresponding symbol of path candidate.
State SiIn other elements (i.e. except the other elements in last column element external reliability matrix) be initialized as+
∞ (just infinite), in practice twice of available path metric difference maximum value substitute+∞, such as when path metric difference is 5 quantizations
When, path metric difference maximum value is 31, with 63 substitution+∞.
It is to the rule of reliability matrix update in reliability matrix update module：
When the k+1 moment, last column in reliability matrix still press the regular value of initialization, and other elements update rule
Then it is：
Wherein 0≤l≤δ -2, min indicate minimizing operation, diffk+1(Si) indicate k+1 moment state SiPath metric difference.
When the k moment, after the completion of reliability matrix updates, state SiCorresponding reliability matrix update module is by the state pair
First column element of the reliability matrix answered, i.e.,It exports to soft-decision output module.
State Choosing module stateful middle maximum state of cumulative metric for finding out, and the serial number of the state is exported
To the second time delay module.
The serial number of the maximum state of cumulative metric is delayed by the second time delay module, itself and reliability matrix is made to update mould
The first row of corresponding reliability matrix is aligned in time in each state of block output, and outputs this to soft-decision output
Module.
If inputting the serial number c of the maximum state of cumulative metric of soft-decision output module.Soft-decision output module is selected
Do well ScThe first row of corresponding reliability matrix (indicates a possibility that+1 moment of k- δ each symbol occurs size, is worth smaller
A possibility that appearance, is bigger), calculate the likelihood ratio of all symbols and output.The likelihood ratio of k- δ+1 moment symbol μMeter
Calculation method is：
Wherein μ=0,1,2,3.
The subsequent likelihood ratio that can whether convert the likelihood ratio of symbol to bit according to actual needs.
Apply the invention to cascade LDPC (Low Density Parity Check Codes, low-density checksum
Code) more modulation index CPM systems in, system structure as shown in figure 5, transmitting terminal by the information sequence that need to be sent by LDPC volume
Code, then CPM modulation is carried out, finally obtained intermediate frequency CPM signal is sent by channel.Digital Down Convert is passed through in receiving end
It after synchronous, input decoder provided by the invention and carries out Soft decision decoding, convert bit log likelihood ratio for decoder output
LDPC decoding, the information sequence that can be sent are carried out afterwards.The modulation index h=[5,6]/16 of CPM, system number M=4, portion
Dividing response length L=3, LDPC is CCSDS (Consultative Committee for Space Data Systems, sky
Between data Advisory Board) standard recommendation code word, code length 8176, code rate 7/8, δ=20.Error performance is as shown in fig. 6, figure
In the curve with five-pointed star indicate decoder (FPGA realizations) performance provided by the invention, the curve expression Max- with diamond shape
Log-MAP algorithm (MTLAB emulation) performance, they are 10 in the bit error rate as seen from the figure-5In the case of, Eb/No (energy per bit with
The ratio between noise power spectral density) differ only by 0.2dB.It is realized on XC7VX690T (FPGA development board), transmitted bit rate is
60M bit/s, processing clock are 120MHz, and maximum clock 120MHz, main resource occupancy situation is as shown in table 1, from table
As can be seen that soft decision decoder occupancy resource proposed by the present invention is less, it is suitble to high-speed transfer.
Table 1
Claims (2)
1. a kind of soft decision decoder of multi-system part response CPM signal, CPM refer to Continuous Phase Modulation, which is characterized in that
Including：Gabi selection module, reliability matrix updating unit, state Choosing module, the first time delay module, the second time delay module are soft
Adjudicate output module；The branch metric in all paths, modulation index synchronization signal input Gabi selection module, and Gabi selection module calculates
Out the metric difference of the survivor path serial number of each state and contended path serial number and survivor path and contended path and export extremely
Reliability matrix updating unit；Gabi selection module calculates the cumulative metric of each state and exports to state Choosing module；Modulation
Exponential Synchronization signal is input to the first time delay module simultaneously, and the first time delay module is defeated by the modulation index synchronization signal by delay
Out to reliability matrix updating unit；Reliability matrix updating unit is used to update the reliability matrix of each state, and will be every
The first row of the reliability matrix of a state is exported to soft-decision output module；State Choosing module finds out the stateful middle accumulation of institute
Maximum state is measured, and the serial number of the state is exported to the second time delay module；Second time delay module is maximum by cumulative metric
The serial number of state be delayed, the serial number of the maximum state of cumulative metric by delay is exported to soft-decision and exports mould
Block；Soft-decision output module calculates the likelihood ratio of all symbols and output.
2. the soft decision decoder of response CPM signal in multi-system part according to claim 1, which is characterized in that described
Reliability matrix updating unit includes：One reliability matrix mapping block, several reliability matrix update modules, reliability
The number of matrix update module corresponds to the state number of CPM signal；At current time, reliability matrix mapping block it is defeated
Enter be current time each state survivor path serial number and contended path serial number；Reliability matrix mapping block is according to each shape
The survivor path serial number and contended path serial number of state, recall the survivor path and contended path of each state, find every
The state that the state and contended path previous moment that the survivor path previous moment of a state is passed through are passed through, then by each state
The reliability matrix for the corresponding previous moment of state that survivor path previous moment is passed through exports reliability corresponding to the state
Matrix update module exports the reliability matrix of corresponding previous moment in state that contended path previous moment is passed through to this
The corresponding reliability matrix update module of state；Meanwhile it being obtained in each reliability matrix update module input Gabi selection module
The module corresponding states path metric difference；The corresponding reliability matrix update module of each state, which calculates, updates current time
The corresponding reliability matrix of the state, and reliability matrix first row is exported to soft-decision output module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810671401.8A CN108923887B (en) | 2018-06-26 | 2018-06-26 | Soft decision decoder structure of multi-system partial response CPM signal |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810671401.8A CN108923887B (en) | 2018-06-26 | 2018-06-26 | Soft decision decoder structure of multi-system partial response CPM signal |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108923887A true CN108923887A (en) | 2018-11-30 |
| CN108923887B CN108923887B (en) | 2021-01-15 |
Family
ID=64422606
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810671401.8A Active CN108923887B (en) | 2018-06-26 | 2018-06-26 | Soft decision decoder structure of multi-system partial response CPM signal |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108923887B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113973037A (en) * | 2020-07-24 | 2022-01-25 | 晶晨半导体(上海)股份有限公司 | Demodulation method, apparatus, device and computer readable storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1151669A (en) * | 1995-09-04 | 1997-06-11 | 冲电气工业株式会社 | Signal determination, receiving device and method of signal determination, channel state inference |
| CN101517901A (en) * | 2006-09-13 | 2009-08-26 | 哈里公司 | Programmable Continuous Phase Modulation (CPM) decoder and associated methods |
| CN102148681A (en) * | 2011-05-19 | 2011-08-10 | 北京邮电大学 | System and method for realizing iterative timing synchronization of continuous phase modulation signal |
| CN102523076A (en) * | 2012-01-04 | 2012-06-27 | 西安电子科技大学 | Universal and configurable high-speed Turbo code decoding system and method thereof |
| WO2017032255A1 (en) * | 2015-08-24 | 2017-03-02 | Beihang University | System and method for data decoding |
-
2018
- 2018-06-26 CN CN201810671401.8A patent/CN108923887B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1151669A (en) * | 1995-09-04 | 1997-06-11 | 冲电气工业株式会社 | Signal determination, receiving device and method of signal determination, channel state inference |
| CN101517901A (en) * | 2006-09-13 | 2009-08-26 | 哈里公司 | Programmable Continuous Phase Modulation (CPM) decoder and associated methods |
| CN102148681A (en) * | 2011-05-19 | 2011-08-10 | 北京邮电大学 | System and method for realizing iterative timing synchronization of continuous phase modulation signal |
| CN102523076A (en) * | 2012-01-04 | 2012-06-27 | 西安电子科技大学 | Universal and configurable high-speed Turbo code decoding system and method thereof |
| WO2017032255A1 (en) * | 2015-08-24 | 2017-03-02 | Beihang University | System and method for data decoding |
| CN106487392A (en) * | 2015-08-24 | 2017-03-08 | 北京航空航天大学 | Down-sampled interpretation method and device |
Non-Patent Citations (2)
| Title |
|---|
| 傅蕾: ""水声跳频通信的信道估计与CPM解调算法研究"", 《中国优秀硕士学位论文全文数据库》 * |
| 赖鹏辉等: ""多进制部分响应Multi-h CPM的软输出维特比算法"", 《太赫兹科学与电子信息学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113973037A (en) * | 2020-07-24 | 2022-01-25 | 晶晨半导体(上海)股份有限公司 | Demodulation method, apparatus, device and computer readable storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108923887B (en) | 2021-01-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| AU751391B2 (en) | Coding and modulation method and apparatus for its implementation | |
| US5414738A (en) | Maximum likelihood paths comparison decoder | |
| US7360040B2 (en) | Interleaver for iterative decoder | |
| KR102684139B1 (en) | Error correction coding method and apparatus using triangular factorization of generator matrix | |
| JP2004528747A (en) | Method and system for iterative encoding / decoding for digital data streams encoded by space-time combinations in multiplexing transmission and reception | |
| EP0937336A1 (en) | Soft decision output decoder for decoding convolutionally encoded codewords | |
| US9059829B2 (en) | Receiver and received signal decoding method | |
| US11082147B2 (en) | Processing method, device and system for overlap multiplexing system | |
| Yu et al. | FPGA implementation of rate-adaptable prefix-free code distribution matching for probabilistic constellation shaping | |
| KR20110031148A (en) | Method for transmitting a digital signal between at least two transmitters and at least one receiver, using at least one relay, and corresponding program product and relay device | |
| CN112332864A (en) | Polar code decoding method and system for self-adaptive ordered mobile pruning list | |
| US7062700B2 (en) | 16 QAM and 16 APSK TTCM (Turbo Trellis Coded Modulation) with minimum bandwidth efficiency of 3 bit/s/Hz using a rate 2/4 constituent encoder | |
| US20030226096A1 (en) | True bit level decoding of TTCM (Turbo Trellis Code Modulation ) | |
| KR100515472B1 (en) | Channel coding and decoding method and multiple-antenna communication systems performing the same | |
| CN108923887A (en) | Soft decision decoder structure of multi-system partial response CPM signal | |
| KR100809551B1 (en) | An apparatus and a method for transmission which encoding a message with spact-time turbo code using feedback bit in mobile communication system | |
| CN111130572A (en) | Turbo code quick realizing method | |
| Wang et al. | Parallel decoding for non-recursive convolutional codes and its enhancement through artificial neural networks | |
| US10958488B2 (en) | Signal transmission method and system | |
| Sánchez et al. | High speed low complexity radix-16 max-log-MAP SISO decoder | |
| CN109995465B (en) | Overlapping multiplexing system and processing method and device thereof | |
| US20070044001A1 (en) | Single stage implementation of min*, max*, min and/or max to perform state metric calculation in SISO decoder | |
| JP2001168738A (en) | Soft judgment information output method, decoding/error correction device and data receiver | |
| Zolotarev et al. | The performance of multithreshold decoder over fading channels | |
| Chhabra et al. | An efficient high performance turbo code implementation in Rayleigh fading channel |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |