Abstract
In this paper, two-dimensional (2-D) correction scheme is proposed to improve the performance of conventional Min-Sum (MS) decoding of regular low density parity check codes. The adopted algorithm to obtain the correction factors is simply based on estimating the mean square difference (MSD) between the transmitted codeword and the posteriori information of both bit and check node that produced at the MS decoder. Semi-practical tests using software-defined radio (SDR) and specific code simulations show that the proposed quasi-optimal algorithm provides a comparable error performance as Sum-Product (SP) decoding while requiring less complexity.
Highlights
Due to its exceptional error performance, low density parity check code (LDPC) [1] has received significant attention recently
The adopted algorithm to obtain the correction factors is based on estimating the mean square difference (MSD) between the transmitted codeword and the posteriori information of both bit and check node that produced at the MS decoder
Semi-practical tests using software-defined radio (SDR) and specific code simulations show that the proposed quasi-optimal algorithm provides a comparable error performance as Sum-Product (SP) decoding while requiring less complexity
Summary
Due to its exceptional error performance, low density parity check code (LDPC) [1] has received significant attention recently. It is adopted by many new generation communication standards, such as wireless LAN (IEEE 802.11n) [2], WiMax (IEEE 802.16e) [3] and DVB-S2 [4]. Sub-optimal algorithms like Min-Sum (MS) [6] can significantly reduce the hardware complexity of SP at the cost of performance degradation. A simple algorithm is presented to estimate the optimal correction factors for 2-D corrected MS decoding of regular LDPC codes.
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