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Low Complexity Soft Decision Circuit for LDPC decoders

Meer Sakib, Venkatesan Mahalingam, Andrew J. Wong, Warren J. Gross, Odile Liboiron-Ladouceur

Published Jan 1, 2011• 1 citation
Publisher

Abstract

A reduced complexity implementation is proposed of an optical receiver for the soft decoding of low density parity check codes. Coding gain of 9.4 dB is achieved using 20 % of the incoming optical signal.
DOI
10.1364/cleo_at.2011.jwa18

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Very powerful long low-density parity-check (LDPC) codes, such as the ITU G.975.1 Standard (32643, 30592) LDPC Code [1], have been considered for optical communications. Traditional implementations of such long codes result in circuits requiring millions of interconnections, which are not affordable. This thesis investigates the performance of the hard-decision differential decoding with binary message-passing (DD-BMP) algorithm [2], a low-complexity algorithm requiring a minimal number of wires due to its binary messages. Our simulation results for the ITU G.975.1 standard demonstrate that hard-decision DD-BMP algorithm outperforms the results provided in the standard, and that the gap between the decoding performance of hard-decision DD-BMP and hard-decision sum-product is small at high signal-to-noise ratios (SNR). We also present a novel design methodology for implementing a soft-decision decoder by exploiting the code's structure. An implementation-efficient architecture is presented using a partially-parallel adaptation of the min-sum algorithm known as the line-passing algorithm. The line-passing algorithm makes soft-decision decoding available while requiring a minimal number of interconnections, which is attractive for long-haul optical communication systems.
In this paper, a low complexity algorithm for binary linear block codes is applied to low-density parity-check (LDPC) codes and improvements are described, namely an extension to soft-decision decoding and a loop detection mechanism. For soft decoding, only one real-valued addition per code symbol is needed, while the remaining operations are only binary as in the hard decision case. The decoding performance is considerably increased by the loop detection. Simulation results are used to compare the performance with other known decoding strategies for LDPC codes, with the result that the presented algorithms offer excellent performance at smaller complexity.
Low-density parity check (LDPC) codes are gaining increased attention in information theory field. However one of the main problems facing usage of these codes in communication systems is its high complexity decoding scheme that results in high decoding delay. Such a delay is not acceptable in many applications. This paper presents, a new hybrid decoding scheme. The proposed scheme mixes between soft-decision and hard-decision algorithms and provides a good tradeoff between error performance and decoding delay as proved by simulation results.
Low Density Parity Check Codes (LDPC) is a class of linear block codes best suited for forward error control in communication systems. When compared with other codes, LDPC codes have significant performance gain, which can be turned to an increase of the coverage range or a reduction of transmission power. Hence a convenient and practical receiver is obtained. The analysis done in this paper is based on the Bit Error Rate of the decoded output. The factors considered for the analysis are multiple code rate, different number of iterations and various decoding schemes. For lower code rate, soft decision decoding and increased number of iterations LDPC codes yields a better performance.
In this letter, a low complexity decoding algorithm for binary linear block codes is applied to low-density paritycheck (LDPC) codes and improvements are described, namely an extension to soft-decision decoding and a loop detection mechanism. For soft decoding, only one real-valued addition per code symbol is needed, while the remaining operations are only binary as in the hard decision case. The decoding performance is considerably increased by the loop detection. Simulation results are used to compare the performance with other known decoding strategies for LDPC codes, with the result that the presented algorithms offer excellent performances at smaller complexity.