Low-complexity ML decoding for convolutional tail-biting codes

Recently, a maximum-likelihood (ML) decoding algorithm with two phases has been proposed for convolutional tailbiting codes [1]. The first phase applies the Viterbi algorithm to obtain the trellis information, and then the second phase employs the algorithm A* to find the ML solution. In this work, we improve the complexity of the algorithm A* by using a new evaluation function. Simulations showed that the improved A* algorithm has over 5 times less average decoding complexity in the second phase when E_b/N₀? 4 dB.     

An efficiently implementable maximum likelihood decoding algorithm for tailbiting codes

Convolutional tailbiting codes are widely used in mobile systems to perform error-correcting strategies of data and control information. Unlike zero tail codes, tailbiting codes do not reset the encoder memory at the end of each data block, improving the code efficiency for short block lengths. The objective of this work is to propose a low-complexity maximum likelihood decoding algorithm for convolutional tailbiting codes based on the Viterbi algorithm. The performance of the proposed solution is compared to that of another maximum likelihood decoding strategy which is based on the A* algorithm. The computational load and the memory requirements of both algorithms are also analysed in order to perform a fair comparison between them. Numerical results considering realistic transmission conditions show the lower memory requirements of the proposed solution, which makes its implementation more suitable for devices with limited resources.     

On decoding unequal error protection product codes

The decoding of unequal error protection product codes, which are a combination of linear unequal error protection (UEP) codes and product codes, is addressed. A nonconstructive proof of the existence of a good error-erasure-decoding algorithm is presented; however, obtaining the decoding procedure is still an open research problem. A particular subclass of UEP product codes is considered, including a decoding algorithm that is an extension of the Blokh-Zyablov decoding algorithm for product codes. For this particular subclass the decoding problem is solved     

Novel Generalized max* Approximation Method for Simplified Decoding of Turbo and TTCM Codes

A novel method for approximating the optimal max* operator used in Log- MAP decoding of turbo and turbo trellis-coded modulation (TTCM) codes is proposed being derived from a well-known inequality, which has not been published before. The max* operation is generalized, for the first time, and performed on n > 2 rather than n = 2 arguments, as it is the conventional approach. Complexity comparisons reveal a significant reduction in the number of operations required per decoding step for the proposed approximation, as compared with the optimal Log-MAP algorithm. Performance evaluation results are presented for both turbo and TTCM codes, showing the near optimal performance of the novel approximation method in both the additive white Gaussian noise (AWGN) and uncorrelated, i.e. fully interleaved, Rayleigh fading channels.     

Decoding spherical codes for the Gaussian channel

A decoding algorithm for permutation codes that is equivalent to maximum-likelihood decoding, but less complex than the correlation decoder, is presented. A general construction for iteratively maximum-likelihood decodable (IMLD) codes is proved and used to construct IMLD codes for every dimension n. D. Slepian (1965) defined permutation modulation codes and presented an efficient algorithm for their decoding. Slepian's decoding scheme is one of the principal components of the permutation code decoding algorithm presented     

Achieving the designed error capacity in decodingalgebraic-geometric codes

A decoding algorithm for codes arising from algebraic curves explicitly constructable by Goppa's construction is presented. Any configuration up to the greatest integer less than or equal to (d *-1)/2 errors is corrected by the algorithm whenever d*⩾6g, where d* is the designed minimum distance of the code and g is the genus of the curve. The algorithm's complexity is at most O((d*)² n), where n denotes the length of the code. Application to Hermitian codes and connections with well-known algorithms are explained     

一种低复杂度的Log-MAP译码器结构

根据实际中Turbo译码器硬件实现的重要性,提出了一种适合于并行计算的改进Log-MAP译码算法,即在其译码计算中间参数的过程中,将具有n个输入变量的最大近似算法max*运算简化为取最大值的max运算和相关函数的计算,减少了存储量,有效实现了低复杂度的Turbo译码器的硬件结构。将此改进的算法应用于CCSDS标准和Wi MAX标准中,仿真结果表明,所提出的简化的近似算法与传统的Log-MAP算法对比,有效降低了译码复杂度和时延,而且纠错性能接近Log-MAP算法,便于实际工程应用。     

Hard- and soft-decision decoding beyond the half minimum distance---An algorithm for linear codes (Corresp.)

A decoding algorithm for linear codes that uses the minimum weight words of the dual code as parity checks is defined. This algorithm is able to correct beyond the half minimum distance and has the capability of including soft-decision decoding. Results on applying this algorithm to quadratic residue (QR) codes, BCH codes, and the Golay codes (with and without soft-decision decoding) are presented.     

Efficient heuristic search algorithms for soft-decision decoding oflinear block codes

Efficient new algorithms are presented for maximum-likelihood and suboptimal soft-decision decoding algorithms for linear block codes. The first algorithm, MA*, improves the efficiency of the A* decoding algorithm, conducting the heuristic search through a code tree while exploiting code-specific properties. The second algorithm, H*, reduces search space by successively estimating the cost of the minimum-cost codeword with a fixed value at each of the most reliable and linearly independent components of the received message. The third algorithm, directed search, finds the codeword closest to the received vector by exploring a continuous search space. The strengths of these three algorithms are combined in a hybrid algorithm, applied to the (128,64), the (256,131), and the (256,139) binary-extended Bose-Chaudhuri-Hocquenghem (BCH) codes. Simulation results show that this hybrid algorithm can efficiently decode the (128,64) code for any signal-to-noise ratio, with near-optimal performance. Previously, no practical decoder could have decoded this code with such a performance for all ranges of signal-to-noise ratio     

Soft-decision decoding of Reed-Muller codes: a simplified algorithm

Soft-decision decoding is considered for general Reed-Muller (RM) codes of length n and distance d used over a memoryless channel. A recursive decoding algorithm is designed and its decoding threshold is derived for long RM codes. The algorithm has complexity of order nlnn and corrects most error patterns of the Euclidean weight of order radicn/lnn, instead of the decoding threshold radicd/2 of the bounded distance decoding. Also, for long RM codes of fixed rate R, the new algorithm increases 4/pi times the decoding threshold of its hard-decision counterpart     

New decoding algorithm for Reed - Muller codes (Corresp.)

We interpret Reed-Muller codes in terms of superimposition and present a new decoding algorithm for Reed-Muller codes. Before presenting this algorithm, we propose a decoding algorithm for a class of simple iterated codes (SI codes) that will play an important role in our new decoding algorithm. Finally, we compare our algorithm with the conventional algorithm for the cyclic Reed-Muller codes from the standpoint of decoding delay.     

一种基于奇偶校验码级联极化码的低复杂度译码算法

极化码作为一种纠错码,具有较好的编译码性能,已成为5G短码控制信道的标准编码方案.但在码长较短时,其性能不够优异.作为一种新型级联极化码,奇偶校验码与极化码的级联方案提高了有限码长的性能,但是其译码算法有着较高的复杂度.该文针对这一问题,提出一种基于奇偶校验码级联极化码的串行抵消局部列表译码(PC-PSCL)算法,该算...     

Generalized tensor product codes

A class of binary error-correcting codes, called generalized tensor product codes, is presented with their decoding algorithm. These codes are constructed by combining a number of codes on various extension fields with shorter binary codes. A general algorithm is provided to do bounded distance decoding for these codes. Simply decodable codes such as Wolf's tensor product codes are shown to be special cases of this class of codes. Simply decodable and more efficient codes than Wolf's codes are also included as special cases.     

Decoding algebraic-geometric codes up to the designed minimumdistance

A simple decoding procedure for algebraic-geometric codes C _Ω(D,G) is presented. This decoding procedure is a generalization of Peterson's decoding procedure for the BCH codes. It can be used to correct any [(d*-1)/2] or fewer errors with complexity O(n³), where d * is the designed minimum distance of the algebraic-geometric code and n is the codelength     

Class of majority decodable real-number codes

A majority decoding algorithm for a class of real-number codes is presented. Majority decoding has been a relatively simple and fast decoding technique for codes over finite fields. When applied to decode real-number codes, the robustness of the majority decoding to the presence of background noise, which is usually an annoying problem for existing decoding algorithms for real-number codes, is its most prominent property. The presented class of real-number codes has generator matrices similar to those of the binary Reed-Muller codes and is decoded by similar majority logic     

基于串行消息传递机制的QC-LDPC码快速译码算法研究

针对准循环LDPC(QC-LDPC)码基于洪水消息传递机制译码算法的不足,该文提出了一种快速的分组串行译码算法。该算法通过将LDPC码的校验节点(或变量节点)按一定规则划分成若干个子集,在每一轮迭代过程中,依次对各个子集中的校验节点(或变量节点)并行地进行消息更新,提高了译码速度。同时根据分组规则,提出了一种有效的分组方法,并通过分析发现基于循环置换阵的准循环LDPC码非常适合采用这种分组译码算法进行译码。通过对不同消息传递机制下准循环LDPC码译码算法性能的仿真比较,验证了在复杂度不增加的情况下,该译码算法在继承了串行译码算法性能优异和迭代收敛快等优点的同时,极大地提高了准循环LDPC码的译码速度。分析表明,分组串行译码算法译码速度至少为串行译码算法的p倍(p为准循环LDPC码校验矩阵中循环置换阵的行数或列数)。     

Symbol-by-symbol MAP decoding algorithm for high-rate convolutionalcodes that use reciprocal dual codes

A symbol-by-symbol maximum a posteriori (MAP) decoding algorithm for high-rate convolutional codes applying reciprocal dual convolutional codes is presented. The advantage of this approach is a reduction of the computational complexity since the number of codewords to consider is decreased. All requirements for iterative decoding schemes are fulfilled. Since tail-biting convolutional codes are equivalent to quasi-cyclic block codes, the decoding algorithm for truncated or terminated convolutional codes is modified to obtain a soft-in/soft-out decoder for high-rate quasi-cyclic block codes which also uses the dual code because of complexity reasons. Additionally, quasi-cyclic block codes are investigated as component codes for parallel concatenation. Simulation results obtained by iterative decoding are compared with union bounds for maximum likelihood decoding. The results of a search for high-rate quasi-cyclic block codes are given in the appendix     

TRELLIS STRUCTURES OF BLOCK CODES AND THEIR DECODING

Trellis structures of block codes are discussed. L-section trellis structures of some BCH codes are presented. A fast maximum likelihood decoding algorithm for BCH codes is proposed correspondingly, the decoding problem of q-ary images of qm-ary block codes is also discussed. The direct-sum partition and the associated decoding algorithms are given for the images.     

Estimation of the exponent of the decoding error probability for a special generalized LDPC code

A special construction of a generalized low-density parity-check (LDPC) code and a low-complexity algorithm for his code decoding are proposed. A lower estimate of the exponent of the decoding error probability is obtained for the considered code and the decoding algorithm. This estimate leads the conclusion that, in an ensemble of considered LDPC codes, there are codes with rates as high as the code capacity and the exponent of the decoding error probability exceeds zero.     

A construction technique for random-error-correcting convolutional codes

A simple algorithm is presented for finding rate1/nrandom-error-correcting convolutional codes. Good codes considerably longer than any now known are obtained. A discussion of a new distance measure for convolutional codes, called the free distance, is included. Free distance is particularly useful when considering decoding schemes, such as sequential decoding, which are not restricted to a fixed constraint length. It is shown how the above algorithm can be modified slightly to produce codes with known free distance. A comparison of probability of error with sequential decoding is made among the best known constructive codes of constraint length36.