Iterative Biased Reliability-Based Decoding of Binary Linear Codes

Miodrag J. Mihaljević

Marc P.C. Foss Rier, Shu Lin

Kenny Barrese

Madamsetti, Kalyani, M, Suseela

In the information theory , the non- binary low density parity check  (NB-LDPC) code is a  linear error correcting code , a method of transmitting message over a  noisy transmission channel. LDPCcodes are  capacity-approaching codes , which  means  that  practical constructions exist  that allow the noise threshold to be set very close to the theoretical maximum for a symmetric memory less channel.Using iterative  belief propagation techniques, NB-LDPC codes can be decoded in time linear to their block length. Non-binary low-density parity-check codes can achieve higher performance than their binary counterparts. Recently, two algorithms were developed for decoding NB-LDPC codes: iterative hard reliability-based majority-logic decoding (IHRB-MLGD) and iterative soft reliability-based majority-logic decoding (ISRB-MLGD has better performance-complexity tradeoffs than previous algorithms. This paper first proposes message-passing in such a way that we can reduce the memory consumption to a greater extent at the same time there should not be performance loss. By using enhanced iterative reliability-based majority-logic decoding algorithms we can achieve effective complexity-performance and noise free design. Compared to previous designs, our proposed decoders have at least tens of times lower complexity with moderate coding gain loss.

Chenrong Xiong, Zhiyuan Yan

Non-binary low-density parity-check (LDPC) codes have some advantages as opposed to their binary counterparts, but unfortunately their decoding complexity is a significant challenge. Hence, the iterative soft-reliability-based (ISRB) majority-logic decoding algorithm is attractive for non-binary LDPC codes, since it involves only finite field additions and multiplications as well as integer additions and comparisons. In this paper, we propose an improved ISRB majority-logic decoding algorithm by using a new reliability update. Our improved algorithm achieves better error performance and faster convergence, while further reducing the computational complexity. For instance, for a (16, 16)-regular (255, 175) cyclic Euclidean geometry LDPC code over GF(28), the proposed algorithm achieves a 0.15 dB coding gain and improves the convergence speed by 10% at a block error rate of 10-4versus the ISRB majority-logic decoding algorithm. Compared with the ISRB majority-logic decoding algorithm, the proposed algorithm requires the same numbers of finite field additions and multiplications but fewer integer additions and comparisons. Furthermore, the ISRB majority-logic decoding algorithm is based on the accumulation of reliability information, and hence the numerical range of the reliability information increases with iterations. In contrast, the proposed reliability update has a fixed numerical range and thus simplifies hardware implementations.

Hiroshi Kamabe, Shusaku Kobota