CN109639301B - Confidence estimation-based FTN (fiber to the home) equalization method - Google Patents

Confidence estimation-based FTN (fiber to the home) equalization method Download PDF

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CN109639301B
CN109639301B CN201811441024.5A CN201811441024A CN109639301B CN 109639301 B CN109639301 B CN 109639301B CN 201811441024 A CN201811441024 A CN 201811441024A CN 109639301 B CN109639301 B CN 109639301B
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刘光辉
文山
李林洲
朱志鹏
陈强
夏延山
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University of Electronic Science and Technology of China
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/06—Receivers
    • H04B1/10—Means associated with receiver for limiting or suppressing noise or interference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/38—Transceivers, i.e. devices in which transmitter and receiver form a structural unit and in which at least one part is used for functions of transmitting and receiving
    • H04B1/40—Circuits
    • 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
    • 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
    • H04L25/03178—Arrangements involving sequence estimation techniques
    • H04L25/03305—Joint sequence estimation and interference removal
    • 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

Abstract

The invention discloses an FTN (fiber to the home) equalization method based on confidence estimation, belonging to the field of wireless communication. The technical scheme of the invention is as follows: and setting a threshold in the iterative process of the SIC equalizer and the decoder, and judging that the bit is reliable when the log-likelihood ratio LLR output by the decoder is greater than the threshold, otherwise, the bit is unreliable. And when all bits in one symbol are reliable bits, judging the symbol to be reliable, otherwise, judging the symbol to be unreliable. For the symbol judged as a reliable symbol, directly carrying out hard decision when estimating ISI; for unreliable symbols, the ISI cancellation is updated once with the SIC method. The symbol sequence obtained by the soft symbol mapping at the decoding end is obtained by the above operation and is used for estimating the ISI and then iterating back to the SIC equalizer. The invention obtains better decoding performance at the cost of lower complexity, thereby realizing the requirement of improving the data transmission rate.

Description

Confidence estimation-based FTN (fiber to the home) equalization method
Technical Field
The invention belongs to the field of wireless communication, and particularly relates to SIC (successive Interference cancellation) iterative equalization technology of an FTN (fast peak) communication transmission system receiver.
Background
With the explosive increase of data flow, the massive access of equipment, the continuous development of various new services and various application scenes, the requirement of users on data transmission rate is higher and higher. Increasing bandwidth is a solution for increasing system capacity, however, spectrum resources of wireless communication are very scarce and increasingly scarce, and in order to achieve the purpose of greatly increasing system capacity under the premise of limited spectrum resources, a new transmission technology is urgently needed to be proposed, so as to fundamentally solve the problem. FTN transmission techniques, which achieve higher data transmission rates through compression of the intervals of the shaped waveform, can well address this problem.
As known from Nyquist transmission criterion without intersymbol interference (ISI), if the data transmission rate exceeds the Nyquist rate, intersymbol interference (ISI) is inevitably caused, thereby reducing the transmission reliability of the communication system. As early as 1975, however, Mazo proposed the Nyquist transmission theorem and has theoretically demonstrated that selecting a sinc pulse shaping filter in the time domain does not change the minimum euclidean distance of the signal at symbol rates that exceed the Nyquist rate by 25%, which means that the error performance of the communication system is not affected. This conclusion sets forth the possibility of non-orthogonal transmission and thus yields a technique of faster-than-nyquist (FTN) transmission. The FTN transmission technique allows signals to be transmitted at a data rate higher than the Nyquist symbol rate, and by combining the precoding at the transmitting end and the interference cancellation technique at the receiving end, it is possible to achieve an error rate performance equivalent to that of orthogonal transmission. Since the transmission rate is higher than the Nyquist symbol rate, the FTN transmission technique has a higher throughput rate and system capacity than the conventional transmission technique. With the continuous increase of the processing speed of digital chips, the FTN technology is becoming one of the hot topics of current wireless communication technology research and new core technologies in future wireless communication systems.
FTN transmission also artificially introduces inter-symbol interference while increasing the data transmission rate, which requires the receiver to be designed to cancel this interference. However, most of the receivers designed at present have the problems of poor error code performance or high complexity, and cannot be realized. It is of great significance to the development of FTN technology if a new FTN receiver architecture can be designed that can achieve more excellent error rate performance and relatively low complexity.
The literature "Liveris A D, Georghiades C N. explicit failure-than-Nyquist signaling J. Communications IEEE Transactions on,2003,51(9): 1502-1511" proposes a scheme for iteratively eliminating ISI through SISO and BCJR equalizers, but the BCJR algorithm has high processing complexity and is difficult to realize. In the document "Prlja, a. (2013). Reduced Receivers for fast-than-Nyquist signalling and General Linear Channels tryckey iE-hue, Lunds unitselet", the author proposes an improved algorithm M-BCJR of the BCJR algorithm, which obviously reduces the complexity of the receiver, but at the same time has the problem that high-order modulation cannot be iterated. The complexity of the nonlinear equalization algorithm is too high, and the nonlinear equalization algorithm still seems to be a problem which is difficult to process at present. In view of this, the present invention designs an iterative equalization processing scheme of Successive Interference Cancellation (SIC) based on confidence estimation, and obtains better decoding performance under the condition of lower complexity.
Disclosure of Invention
The invention aims to: aiming at the technical problem of poor elimination performance of introduced interference signals at a receiving end, an FTN (fiber to the home) equalization method based on confidence estimation is disclosed.
The invention discloses an FTN equalization method based on confidence estimation, which comprises the following steps:
ISI (inter symbol interference) based on current intersymbol interference at receiving endesSequence of symbols S to be subjected to iterative equalizationobAnd (3) carrying out intersymbol interference processing: by a sequence of symbols SobSubtracting intersymbol interference ISIesObtaining the symbol sequence after removing the inter-symbol interference
Figure BDA0001884715050000021
The intersymbol interference ISIesIs a preset value, and inter-symbol interference ISI is acquired based on the following processingesCurrent value of (a):
a sequence of symbols
Figure BDA0001884715050000022
As the prior information of the decoder at the receiving end
Figure BDA0001884715050000023
And obtaining a posteriori information of the bits based on the decoder output
Figure BDA0001884715050000024
Posterior information based on preset threshold pair bit
Figure BDA0001884715050000025
And the judgment is carried out, if the judgment is larger than the threshold,the corresponding bit mapped symbol is treated as a reliable symbol; otherwise, the symbol is regarded as an unreliable symbol;
for reliable symbols, the posterior information of the reliable symbol position is directly used
Figure BDA0001884715050000026
After hard decision is carried out to obtain bits 0 and 1, mapping the bits into hard symbols, updating the reliable symbols into corresponding hard symbols to obtain an updated symbol sequence S'ob；
For unreliable symbols, the sequence of symbols S is usedobSubtracting the parameters
Figure BDA0001884715050000027
Obtaining an updated symbol sequence S'ob；
The updated symbol sequence S'obMultiplying by an intersymbol interference matrix to obtain intersymbol interference ISIesThe current value of (a);
wherein, the parameter
Figure BDA0001884715050000028
The acquisition mode is as follows: a posteriori information to decoder output
Figure BDA0001884715050000029
Performing soft symbol mapping processing to obtain a soft symbol sequence
Figure BDA00018847150500000210
Then the soft symbol sequence is decoded
Figure BDA00018847150500000211
Multiplying by an intersymbol interference matrix to obtain a parameter
Figure BDA00018847150500000212
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that: the invention adds threshold judgment operation to the confidence coefficient output by the decoder to process the technical problem of interference elimination by improving the SIC iterative equalization structure of the receiving end, and obtains better decoding performance at the cost of lower complexity, thereby realizing the requirement of improving the data transmission rate.
Drawings
Fig. 1 is a block diagram of a FTN transmission transceiving system.
FIG. 2 is a flow diagram of a confidence estimation scheme.
Fig. 3 is a graph comparing Nyquist orthogonal transmission and FTN non-orthogonal transmission of signals.
Fig. 4 is a bit error rate curve of a conventional SIC iterative equalization scheme with a compression ratio of 0.8, QPSK modulation, an LDPC code length of 1024 code rates of 0.5, 20 iterations, and an improved SIC iterative equalization scheme based on confidence estimation.
Fig. 5 is a bit error rate curve of a conventional SIC iterative equalization scheme with a compression ratio of 0.8, 16QAM modulation, an LDPC code length of 1024 code rates of 0.5, 20 iterations, and an improved SIC iterative equalization scheme based on confidence estimation.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the following embodiments and accompanying drawings.
Aiming at the technical problem of poor elimination performance of introduced interference signals at a receiving end, the SIC iterative equalization structure is improved, threshold judgment operation is added to confidence coefficient output by a decoder, the technical problem of interference elimination is solved, better decoding performance is obtained at the cost of lower complexity, and finally the requirement of improving data transmission rate is met.
The technical scheme of the invention is as follows: and setting a threshold in the iterative process of the SIC equalizer and the decoder, and judging that the bit is reliable when the log-likelihood ratio LLR output by the decoder is greater than the threshold, otherwise, the bit is unreliable. And when all bits in one symbol are reliable bits, judging the symbol to be reliable, otherwise, judging the symbol to be unreliable. For the symbol judged as a reliable symbol, directly carrying out hard decision when estimating ISI; for unreliable symbols, the ISI cancellation is updated once with the SIC method. The symbol sequence obtained by the soft symbol mapping at the decoding end is obtained by the above operation and is used for estimating the ISI and then iterating back to the SIC equalizer.
FTN transmission systems boost the data transmission rate by compressing the spacing between the shaped waveforms. When the signal is subjected to Nyquist transmission, the symbol pulses h (t) are orthogonal with respect to the symbol period, and the FTN technique breaks the orthogonality to increase the symbol transmission rate.
The FTN transmission time domain waveform can be represented as:
Figure BDA0001884715050000031
wherein, anThe symbol sequence of the sending filter is represented, n is a waveform identifier, namely n waveforms are superposed to obtain corresponding time domain waveforms; τ represents the time domain acceleration factor, which is the key point for the difference between FTN transmission and Nyquist transmission, and the symbol rate of FTN transmission at this time is 1/τ times the symbol rate of Nyquist transmission. It can be seen that the FTN signal increases the data transmission rate by reducing the time domain spacing between adjacent pulses.
Due to the non-orthogonality of the shaped pulses in the FTN system, there is significant intersymbol interference (ISI), but this artificially introduced ISI is well-defined and can be removed by iterative equalization and decoding operations at the receiving end.
In this embodiment, LDPC encoding is used to encode a plurality of frames of transmitted bits, which are mapped to symbols, and then transmitted to an Additive White Gaussian Noise (AWGN) channel via FTN modulation. Iterative equalization and decoding with Turbo structure are adopted at a receiving end for decoding and interference elimination, a successive interference elimination (SIC) equalizer and an LDPC decoder (decoder) are connected in series, a threshold is set for confidence coefficient output by the decoder, and iteration is realized by continuously exchanging soft information between the SIC equalizer and the LDPC decoder, so that intersymbol interference elimination and Gaussian white noise resistance are realized. Referring to fig. 1 and 2, the specific steps are as follows:
the transmitting end processing step:
step A: coding and symbol mapping: inputting binary bit sequence U, with a code length and a code rate of RcThe LDPC code is coded to obtain a bit sequence V, and then symbol sequence S is obtained through QPSK/QAM symbol mapping. The LDPC encoding employed in this embodiment is of quasi-cyclicLDPC codes (QC-LDPC) generate check matrices from a given base matrix cyclic extension.
And B: simulation processing based on FTN transmission:
FTN modulation: and controlling the up-down sampling multiple to compress the formed waveform interval, thereby obtaining a signal X transmitted by a channel. In the actual processing, the signal reaches the receiving end after passing through the channel, and the signal reaching the receiving end after passing through the transmission channel is represented as Y.
Down sampling the received signal Y and then obtaining a symbol sequence S by matched filteringobI.e. symbol sequence observations, which contain not only the useful signal term W but also intersymbol interference ISI and noise interference.
In this embodiment, the received signal Y is obtained by performing simulation processing for an appropriate number of times under the condition of an Additive White Gaussian Noise (AWGN) channel at different signal-to-noise ratios.
And C: the receiving end processes ISI and white noise:
step C1: SIC equalization with received symbol sequence SobSubtracting the estimated intersymbol interference ISIesObtaining the symbol sequence after removing ISI
Figure BDA0001884715050000041
The estimate of the intersymbol interference is given by the following step C3.
Step C2: LDPC decoding of symbol sequences
Figure BDA0001884715050000042
Performing symbol soft demodulation, and using the demodulation result as the prior information of LDPC decoder
Figure BDA0001884715050000043
Obtaining a soft demodulation result of each bit, namely log-likelihood ratio (LLR), through symbol soft demodulation; and obtaining a posteriori information of bits based on decoder output
Figure BDA0001884715050000044
Step C3: setting threshold and estimation symbolInter-symbol interference ISIes: for the obtained bit posterior information output by the LDPC decoder
Figure BDA0001884715050000045
And judging according to the set threshold, wherein all symbols mapped by bits larger than the threshold are regarded as reliable symbols, and otherwise, the symbols are regarded as unreliable symbols. Traditional SIC algorithm directly uses SobMultiplying ISI matrix (ISI _ mat) to estimate ISI, the present invention updates original S with reliable and unreliable symbols in different waysobThe symbol is updated S'obThen, this S 'is reused'obMultiplying the ISI matrix to obtain an estimated ISI for the intersymbol interference ISIesThe whole flow is as shown in FIG. 2, and this estimation is used in SIC equalizer in step C1.
And C1-C3 steps are iterated circularly until a certain iteration number is stopped.
Specifically, in step C3, for the reliable symbol, the posterior information of the reliable symbol position is directly used
Figure BDA0001884715050000051
After hard decision is carried out to bits 0 and 1, mapping is carried out to hard symbols, the reliable symbols are updated to corresponding hard symbols, and updated S 'is obtained'ob(ii) a Unreliable symbol, then SobMinus
Figure BDA0001884715050000052
To obtain updated S'obHere, the
Figure BDA0001884715050000053
Is extrinsic information output by the LDPC decoder
Figure BDA0001884715050000054
The symbol sequence obtained by soft symbol mapping is multiplied by the ISI matrix.
Wherein the LDPC decoder output is utilized as an input
Figure BDA0001884715050000055
Estimating soft symbol vectors
Figure BDA0001884715050000056
The method comprises the following steps:
Figure BDA0001884715050000057
wherein, Pr () represents the probability,
Figure BDA0001884715050000058
representing a vector
Figure BDA0001884715050000059
N-1, N represents the number of symbols in the received frame, i.e., the number of symbols in a received frame (the frame length of the received frame).
By the symbol S 'obtained by a thresholding method'obEstimating ISI signalesThe method comprises the following steps:
Figure BDA00018847150500000510
and then demodulating the symbol S fromobMidamble ISI interference
Figure BDA00018847150500000511
In which ISI ises,nIndicating ISIesThe (n) th element of (a),
Figure BDA00018847150500000512
as a sequence of soft symbols
Figure BDA00018847150500000513
H () denotes a symbol pulse, N-0, 1, …, N-1, k-0, 1, …, N-1 and k ≠ N, and T denotes a symbol period.
Using interference cancellation symbols
Figure BDA00018847150500000514
Performing PSK/QAM soft demodulation to compute a priori information input to an LDPC decoder
Figure BDA00018847150500000515
The method comprises the following steps:
Figure BDA00018847150500000516
wherein the content of the first and second substances,
Figure BDA00018847150500000517
representing a vector
Figure BDA00018847150500000518
The N-th (N-0, 1.., N-1) element of (a), b,
Figure BDA00018847150500000519
variance representing noise + interference:
Figure BDA00018847150500000520
wherein var (·) represents the variance calculation, and the average power of the symbol vector S at the transmitting end is normalized to 1.
Example (b):
the embodiment adopts an LDPC coding mode, the code length is 1024, the code rate is 0.5, the symbol mapping mode is QPSK/16QAM, the compression factor is α is 4/5, the iteration times are 20, a traditional SIC iteration equalization scheme and an SIC iteration equalization scheme improved based on a confidence estimation method are respectively adopted for simulation, one with the minimum log-likelihood ratio of all correct bits is selected as a threshold, Monte-Carlo simulation of the suitable times is carried out under the condition of AWGN channel for each signal-to-noise ratio Eb/N0, and the Bit Error Rate (BER) output by the decoding of a receiver is counted.
Fig. 3 is a comparison graph of a signal changing from orthogonal transmission to non-orthogonal transmission when FTN technology is used (discrete time symbol sequences are sent as {1, -1,1, -1, -1 }). It can be seen that in the orthogonal transmission, there is no intersymbol interference ISI between the pulse waveforms at the sampling points, and it is easy to obtain the output symbols correctly. For FTN transmission with an acceleration factor τ of 0.8, the pulse waveforms are advanced compared to quadrature transmission, with sampling times of 0s, 0.8s, 1.6s, 2.4s, and 3.2s, respectively. And intersymbol interference ISI exists between each waveform when sampling points, and the baseband composite waveform is also distorted.
Fig. 4 is a bit error rate curve under the conventional SIC iterative equalization scheme and the SIC iterative equalization scheme improved based on confidence estimation when the compression ratio is 4/5, QPSK modulation, LDPC code length is 1024, code rate is 0.5, and the number of iterations is 20. It can be seen that the difference between the conventional SIC iterative equalization scheme and the Nyquist transmission is about 0.8dB around the error rate of 1e-5, the difference between the improved SIC iterative equalization scheme based on confidence coefficient estimation and the Nyquist transmission is about 0.5dB around the error rate of 1e-5, and the confidence coefficient estimation scheme has about 0.3dB performance gain compared with the conventional SIC scheme.
Fig. 5 is a bit error rate curve under a conventional SIC iterative equalization scheme and a SIC iterative equalization scheme improved based on confidence estimation when the compression ratio is 4/5, 16QAM modulation, LDPC code length is 1024, code rate is 0.5, and the number of iterations is 20. It can be seen that the error rate curve of the traditional SIC equalization iterative scheme is far from the Nyquist transmission error rate curve, and the error rate curve simulated by the improved SIC iterative equalization scheme based on confidence estimation is 2dB away from the Nyquist transmission error rate curve in the vicinity of the error rate of 1 e-4.
While the invention has been described with reference to specific embodiments, any feature disclosed in this specification may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise; all of the disclosed features, or all of the method or process steps, may be combined in any combination, except mutually exclusive features and/or steps.

Claims (4)

1. An FTN equalization method based on confidence estimation comprises the following steps:
ISI (inter symbol interference) based on current intersymbol interference at receiving endesSequence of symbols S to be subjected to iterative equalizationobAnd (3) carrying out intersymbol interference processing: by a sequence of symbols SobSubtracting intersymbol interference ISIesObtaining the symbol sequence after removing the inter-symbol interference
Figure FDA0002383137910000011
Characterized in that the intersymbol interference ISIesIs a preset value, and inter-symbol interference ISI is acquired based on the following processingesCurrent value of (a):
a sequence of symbols
Figure FDA0002383137910000012
As the prior information of the decoder at the receiving end
Figure FDA0002383137910000013
And obtaining a posteriori information of the bits based on the decoder output
Figure FDA0002383137910000014
Posterior information based on preset threshold pair bit
Figure FDA0002383137910000015
Judging, if the symbol is greater than the threshold, regarding the symbol of the corresponding bit mapping as a reliable symbol; otherwise, the symbol is regarded as an unreliable symbol;
for reliable symbols, the posterior information of the reliable symbol position is directly used
Figure FDA0002383137910000016
After hard decision is carried out to obtain bits 0 and 1, mapping the bits into hard symbols, updating the reliable symbols into corresponding hard symbols to obtain an updated symbol sequence S'ob；
For unreliable symbols, the sequence of symbols S is usedobSubtracting the parameters
Figure FDA0002383137910000017
Obtaining an updated symbol sequence S'ob；
The updated symbol sequence S'obMultiplying by an intersymbol interference matrix to obtain intersymbol interference ISIesThe current value of (a);
wherein, the parameter
Figure FDA0002383137910000018
The acquisition mode is as follows: a posteriori information to decoder output
Figure FDA0002383137910000019
Performing soft symbol mapping processing to obtain a soft symbol sequence
Figure FDA00023831379100000110
Then the soft symbol sequence is decoded
Figure FDA00023831379100000111
Multiplying by an intersymbol interference matrix to obtain a parameter
Figure FDA00023831379100000112
2. The method of claim 1, wherein inter-symbol interference (ISI)esIs an N-dimensional vector with the value ISI of each elementes,nComprises the following steps:
Figure FDA00023831379100000113
wherein ISIes,nIndicating ISIesThe (n) th element of (a),
Figure FDA00023831379100000114
for the k-th symbol observation, h () represents a symbol pulse, N is 0,1, …, N-1, k is 0,1, …, N-1, and k ≠ N, N represents the number of symbols of a received frame, and T represents a symbol period.
3. The method of claim 1, wherein a sequence of soft symbols
Figure FDA00023831379100000115
Is an N-dimensional vector, the value of each element of which
Figure FDA00023831379100000116
Comprises the following steps:
Figure FDA00023831379100000117
wherein the content of the first and second substances,
Figure FDA00023831379100000118
to represent
Figure FDA00023831379100000119
N-th element of (1), N is 0,1, …, N-1, N represents the number of symbols of the received frame.
4. The method of claim 1, in which the a priori information
Figure FDA00023831379100000120
Is an N-dimensional vector, the value of each element of which
Figure FDA00023831379100000121
Comprises the following steps:
Figure FDA00023831379100000122
wherein the content of the first and second substances,
Figure FDA0002383137910000021
representing a sequence of symbols
Figure FDA0002383137910000022
N-th element of (1) 0, …, N-1,
Figure FDA0002383137910000023
represents the variance of noise + interference, and
Figure FDA0002383137910000024
n denotes the number of symbols of the received frame.
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