A novel approach to soft decision decoding of threshold decodable codes (Corresp.)

A new method of soft-decision decoding of threshold decodable codes is presented. Excellent error performance, comparable to or better than that of other known practical schemes, is demonstrated by computer simulation and error analysis. The method is an approximate realization, without undue deterioration in performance, of the optimum {em a posteriori} probability (APP) decoding and has a much simpler structure.     

基于前向多层神经网络的分组码译码器设计

把最大相关译码与神经网络神经元的内积特性及吸引域有机地联系起来,连接权决定译码码字,阈值设定决定神经元的纠错范围,从而形成一种可用于硬判决及软判决译码的神经译码器,并在理论上证明了此译码器可在ＤＭＣ信道的纠错能力范围内实现零错误概率硬判决译码,也可实现与最小欧几里德距离译码相当的软判决译码,并能在检错范围内检错。     

乘积码基于相关运算的迭代译码

乘积码是一种能以Turbo码的思想实现译码的级联码，具有一般编码无法达到的纠错能力。本文提出一种新的乘积码迭代译码算法，其核心思想是通过输出软信息与接收软信息进行线性迭加的方式来实现反馈，此时只须提供-1和1组成的软输出矩阵就能获得很高的编码增益，仿真表明，将子译码器译码后的结果再进行一次相关运算作为软输出，译码性能可以得到进一步的提高。     

Joint Source and Channel Coding using Punctured Ring Convolutional Coded CPM

In this paper, a novel trellis source encoding scheme based on punctured ring convolutional codes is presented. Joint source and channel coding (JSCC) using trellis coded continuous phase modulation (CPM) with punctured convolutional codes over rings is investigated. The channels considered are the additive white gaussian noise (AWGN) channel and the Rayleigh fading channel. Optimal soft decoding for the proposed JSCC scheme is studied. The soft decoder is based on the a posteriori probability (APP) algorithm for trellis coded CPM with punctured ring convolutional codes. It is shown that these systems with soft decoding outperform the same systems with hard decoding especially when the systems operate at low to medium signal-to-noise ratio (SNR). Furthermore, adaptive JSCC approaches based on the proposed source coding scheme are investigated. Compared with JSCC schemes with fixed source coding rates, the proposed adaptive approaches can achieve much better performance in the high SNR region. The novelties of this work are the development of a trellis source encoding method based on punctured ring convolutional codes, the use of a soft decoder, the APP algorithm for the combined systems and the adaptive approaches to the JSCC problem.     

On the decoder error probability of block codes

By using coding and combinational techniques, an explicit formula is derived which enumerates the complete weight distribution of decodable words of block codes using partially known weight distributions. Also, an approximation formula for nonbinary block codes is obtained. These results give exact and approximate expressions for the decoder error probability P_E(u) of block codes     

Low complexity concatenated coding schemes for digital satellite communications

A study of reduced complexity concatenated coding schemes, for commercial digital satellite systems with low-cost earth terminals, is reported. The study explored trade-offs between coding gain, overall rate and decoder complexity, and compared concatenated schemes with single codes. It concentrated on short block and constraint length inner codes, with soft decision decoding, concatenated with a range of Reed-Solomon outer codes. The dimension of the inner code was matched to the outer code symbol size, and appropriate interleaving between the inner and outer codes was used. Very useful coding gains were achieved with relatively high-rate, low-complexity schemes. For example, concatenating the soft decision decoded (9,8) single parity check inner code with the CCSDS recommended standard Reed-Solomon outer code gives a coding gain of 4.8dB at a bit error probability of 10^?5, with an overall rate of 0-78.     

Decoder error and failure probabilities for Reed-Solomon codes:decodable vectors method

In this letter, formulas for the total number of decodable and undecodable vectors are derived for a general (n,k) q-ary linear block code. These formulas are used to find the probabilities of decoder error and decoder failure for Reed-Solomon codes under errors-and-erasures decoding. The resulting analytical expressions are computationally efficient and allow accurate calculation of very small values of decoder failure probabilities. The formulas are used to analyze the performance of type-I hybrid automatic-repeat-request (HARQ) protocols with two decoding diameters     

Neural network decoding of the block Markov superposition transmission

A neural network (NN)-based decoding algorithm of block Markov superposition transmission (BMST) was researched.The decoders of the basic code with different network structures and representations of training data were implemented using NN.Integrating the NN-based decoder of the basic code in an iterative manner,a sliding window decoding algorithm was presented.To analyze the bit error rate (BER) performance,the genie-aided (GA) lower bounds were presented.The NN-based decoding algorithm of the BMST provides a possible way to apply NN to decode long codes.That means the part of the conventional decoder could be replaced by the NN.Numerical results show that the NN-based decoder of basic code can achieve the BER performance of the maximum likelihood (ML) decoder.For the BMST codes,BER performance of the NN-based decoding algorithm matches well with the GA lower bound and exhibits an extra coding gain.     

Complexity Reduction in SISO Decoding of Block Codes

SISO decoding for block codes can be carried out based on a trellis representation of the code. However, the complexity entailed by such decoding is most often prohibitive and thus prevents practical implementation. This paper examines a new decoding scheme based on the soft-output Viterbi algorithm (SOVA) applied to a sectionalized trellis for linear block codes. The computational complexities of the new SOVA decoder and of the conventional SOVA decoder, based on a bit-level trellis, are theoretically analyzed and derived for different linear block codes. These results are used to obtain optimum sectionalizations of a trellis for SOVA. For comparisons, the optimum sectionalizations for Maximum A Posteriori (MAP) and Maximum Logarithm MAP (Max-Log-MAP) algorithms, and their corresponding computational complexities are included. The results confirm that the new SOVA decoder is the most computationally efficient SISO decoder, in comparisons to MAP and Max-Log-MAP algorithms. The simulation results of the bit error rate (BER) performance, assuming binary phase -- shift keying (BPSK) and additive white Gaussian noise (AWGN) channel, demonstrate that the performance of the new decoding scheme is not degraded. The BER performance of iterative SOVA decoding of serially concatenated block codes shows no difference in the quality of the soft outputs of the new decoding scheme and of the conventional SOVA.     

Low complexity soft-input soft-output block decision feedback equalization

A low complexity soft-input soft-output (SISO) block decision feedback equalizer (BDFE) is presented for turbo equalization. The proposed method employs a sub-optimum sequence-based detection, where the soft-output of the equalizer is calculated by evaluating an approximation of the sequence-based a posteriori probability (APP) of the data symbol. The sequence-based APP approximation is enabled by the adoption of both soft a priori information and soft decision feedback, and it leads to better performance and faster convergence compared to symbol-based detection methods as used by most other low complexity equalizers. The performance and convergence property of the proposed algorithm is analyzed by using extrinsic information transfer (EXIT) chart. Both analytical and simulation results show that the new equalizer can achieve a performance similar to that of trellis-based equalization algorithms, with a complexity similar to linear SISO minimum mean square error equalizers.     

Space–Time Codes From Structured Lattices

We present constructions of space–time (ST) codes based on lattice coset coding. First, we focus on ST code constructions for the short block-length case, i.e., when the block length is equal to or slightly larger than the number of transmit antennas. We present constructions based on dense lattice packings and nested lattice (Voronoi) shaping. Our codes achieve the optimal diversity–multiplexing tradeoff (DMT) of quasi-static multiple-input multiple-output (MIMO) fading channels for any fading statistics, and perform very well also at practical, moderate values of signal-to-noise ratios (SNR). Then, we extend the construction to the case of large block lengths, by using trellis coset coding. We provide constructions of trellis coded modulation (TCM) schemes that are endowed with good packing and shaping properties. Both short-block and trellis constructions allow for a reduced complexity decoding algorithm based on minimum mean-squared error generalized decision feedback equalizer (MMSE-GDFE) lattice decoding and a combination of this with a Viterbi TCM decoder for the TCM case. Beyond the interesting algebraic structure, we exhibit codes whose performance is among the state-of-the art considering codes with similar encoding/decoding complexity.      

Rayleigh衰落信道中分组码最大似然译码的性能

摆脱了传统代数译码方法,对分组码进行基于广义阵列码（ＧＡＣ）结构的网格译码（Ｔｒｅｌｌｉｓ ｄｅｃｏｄｉｎｇ）,研究了Ｒａｙｌｅｉｇｈ衰落信道中分组码与这种软判决最大似然译码方法相结合的性能。模拟结果显示。分组码采用网格译码,可为移动衰落信道带来显著的性能改善。     

DSD (double soft decision) concatenated FEC scheme in mobilesatellite communication systems

In order to realize a higher-code-gain forward error correction scheme in mobile satellite communication systems, a novel concatenated coding scheme employing soft decision decoding for not only inner codes but also outer codes (double soft decision, or DSD, concatenated forward error correction scheme) is proposed. Soft-decision outer decoding can improve the bit error probability of inner decoded data. In this scheme, likelihood information from an inner Viterbi decoder is used in the decoding of outer codes. A technique using the path memory circuit status 1.0 ratio for likelihood information is proposed, and is shown to be the most reliable even though it requires the simplest hardware among the alternative methods. A computer simulation clarifies that the DSD scheme improves Pe performance to one-third of that of the conventional hard-decision outer decoding. Moreover, to reduce the interleaving delay time in fading channels or inner decoded data of concatenated codes, a parallel forward error correction scheme is proposed     

Modified majority logic decoding of cyclic codes in hybrid-ARQsystems

Reliability information provided by sets of orthogonal check sums in a majority logic decoder for block codes is used in a type-I hybrid automatic-repeat-request (ARQ) error control scheme. The reliability information is obtained through a simple modification of the majority logic decoding rule. It is shown that the reliability performance of Reed-Muller and other majority logic decodable codes can be substantially improved at the expense of a very small reduction in throughput. The simplicity of the decoding circuit permits implementation in systems with very high data rates     

Reconfigurable Hardware Architectures for Sequential and Hybrid Decoding

A novel reconfigurable sequential decoder architecture based on the Fano algorithm is presented in which the constraint length, the threshold spacing, and the time-out threshold are all run time reconfigurable. To maximize decoding performance, a maximum possible backward depth (of a whole frame) is performed. This is achieved by using shift registers combined with memory to store the information of an entire visited path. A field-programmable gate array) prototype of the decoder is built and actual hardware decoding performances in terms of decoding speeds, bit error rates (BERs), and buffer overflow rates, are obtained and comparisons made. To overcome the decoding delay that is inherent in sequential decoders, a hybrid scheme, including simple block codes and cyclic redundancy check is proposed to limit the number of backward search operations that the sequential decoder has to execute. As a result, a significant reduction in decoding delay and buffer overflow rate is achieved while maintaining comparative decoding performance in terms of BER     

Error-propagation properties of uniform codes

The problem of error propagation in uniform codes is investigated using the concept of parity-parallelogram submatrices and the threshold-decoding algorithm. A set of optimum orthogonalization rules is presented and it is shown that if these rules are incorporated into the decoder, then sufficient conditions can be found for the return of the decoder to correct operation following a decoding error. These conditions are considerably less stringent than the requirement that the channel be completely free of errors following a decoding error. However, this is not the case if the prescribed orthogonalization rules are not followed, as is demonstrated with a simple example. It is also shown that the syndrome memory required with Massey's orthogonalization procedure for definite decoding of uniform codes is the lowest possible. The results of simulation of the ratefrac{1}{4}andfrac{1}{8}uniform codes are presented, and these codes are seen to make fewer decoding errors with feedback decoding than with definite decoding. Comparison of the performance of an ordinary feedback decoder with a genie-aided feedback decoder, which never propagates errors, indicates that error propagation with uniform codes is a minor problem if the optimum orthogonalization rules are used, but that the situation is somewhat worse with nonoptimum orthogonalization.     

Iterative decoding of binary block and convolutional codes

Iterative decoding of two-dimensional systematic convolutional codes has been termed “turbo” (de)coding. Using log-likelihood algebra, we show that any decoder can be used which accepts soft inputs-including a priori values-and delivers soft outputs that can be split into three terms: the soft channel and a priori inputs, and the extrinsic value. The extrinsic value is used as an a priori value for the next iteration. Decoding algorithms in the log-likelihood domain are given not only for convolutional codes but also for any linear binary systematic block code. The iteration is controlled by a stop criterion derived from cross entropy, which results in a minimal number of iterations. Optimal and suboptimal decoders with reduced complexity are presented. Simulation results show that very simple component codes are sufficient, block codes are appropriate for high rates and convolutional codes for lower rates less than 2/3. Any combination of block and convolutional component codes is possible. Several interleaving techniques are described. At a bit error rate (BER) of 10^-4 the performance is slightly above or around the bounds given by the cutoff rate for reasonably simple block/convolutional component codes, interleaver sizes less than 1000 and for three to six iterations     

A CASCADABLE PRAGMATIC BLOCK DECODING ALGORITHM EXPLOITING CHANNEL MEASUREMENT INFORMATION

The complexity of algorithms to perform soft decision decoding on block codes has impeded their inclusion in practical systems. A well-known class of algorithms for decoding block codes utilizing channel measurement information along with the algebraic properties of the code are the Chase algorithms.¹ In this paper a decoding method similar to Chase's third algorithm is presented. However, in this method, a single test pattern or alternate codeword makes up one stage of the decoder. The method uses information from the previous decoding(s) to assist in generating a test pattern. This single stage ‘Second Chance Algorithm’ can then be extended to a ‘Third Chance Algorithm’ (and beyond) to enhance performance. The method does not invoke the hard decision decoder as often as the Chase algorithms.     

Critical point for maximum likelihood decoding of linear block codes

In this letter, the SNR value at which the error performance curve of a soft decision maximum likelihood decoder reaches the slope corresponding to the code minimum distance is determined for a random code. Based on this value, referred to as the critical point, new insight about soft bounded distance decoding of random-like codes (and particularly Reed-Solomon codes) is provided.     

完美空时分组码及其高性能解码算法

根据完美空时分组码（STBC）的结构特点提出了等效的垂直-贝尔实验室空时（V-BLAST）模型，在对该模型进行最小均方误差-判决反馈均衡（MMS-DFE）预处理之后，提出一种有边界约束的Fano解码器。该解码器可达到几乎最大似然（ML）性能，在很大的信噪比区域范围内其复杂度比目前典型的解码器低，而且该解码器可用于发射天线数大于接收天线数的系统。直接在复数域计算和处理，该解码器适用于任何星座形式。该解码器可用于任何能等效成V-BLAST模型的空时系统。仿真结果表明了该解码器的有效性。