Efficient Inplementation of the Sum-Product Algorithm for Decoding LDPC Codes

양경철

Stylianos Papaharalabos, F. Lazarakis

The problem of how to approximate effectively the box-plus operation used in sum-product algorithm (SPA) decoding of low-density parity-check (LDPC) codes has been widely investigated over the past years of research. This letter deals, for the first time, with a totally different approach where a very simple, yet efficient, decoding algorithm for LDPC codes is proposed. The tremendous savings, in terms of required number of operations, offered by the proposed algorithm and its near optimal SPA performance are making it appealing in practical applications requiring very low complexity LDPC decoding architectures.

Yuki Kawauchi, Hiroshi Enoki, Kohtaro Watanabe +1 more

Chirag Dadlani, Ranjan Bose

Low-Density Parity-Check (LDPC) codes have gained significant popularity recently and have been recommended for various wireless standards of the future. Non-binary LDPC codes provide all the well-known advantages of binary LDPC codes but allow for much shorter block lengths. The sum-product decoding algorithm for non-binary LDPC codes is too complex for efficient implementation. Hence, we have represented the sum-product algorithm in a novel log-domain form in terms of operators defined earlier in literature. This form greatly simplifies the key step in the check-node processing and allows us to replace a max* operation in the decoder by a max operation. This leads to a sub-optimal decoding algorithm which we propose in this paper.

H. Sankar, Krishna R. Narayanan

Low-density parity-check (LDPC) codes perform very close to capacity for long lengths on several channels. However, the amount of memory (fixed-point numbers that need to be stored) required for implementing the message-passing algorithm increases linearly as the number of edges in the graph increases. In this letter, we propose a decoding algorithm for decoding LDPC codes that reduces the memory requirement at the decoder. The proposed decoding algorithm can be analyzed using density evolution; further, we show how to design good LDPC codes using this. Results show that this algorithm provides almost the same performance as the conventional sum-product decoding of LDPC codes.

Juntan Zhang, M.P.C. Fossorier, Daqing Gu +1 more