Abstract
Abstract A word error rate (WER) reducing approach for a hybrid iterative error and erasure decoding algorithm for low-density parity-check codes is described. A lower WER is achieved when the maximum number of iterations of the min-sum belief propagation decoder stage is set to certain specific values which are code dependent. By proper choice of decoder parameters, this approach reduces WER by about 2 orders of magnitude for an equivalent decoding complexity. Computer simulation results are given for the efficient use of this hybrid decoding technique in the presence of additive white Gaussian noise.
Highlights
Low-density parity-check (LDPC) codes were first introduced by Gallager in 1963 [1] and rediscovered by Mackay [2] in late 1990s
In the error-floor region, where LDPC codes exhibit a sudden saturation in word error rate (WER) for a sufficiently high signal-to-noise ratio (SNR), the bit errors are primarily caused by trapping sets ([3], p. 225)
As an alternative to the usual computer simulation, we develop an error event analysis, which has a much lower computational cost, and apply it to two LDPC codes of the IEEE802.11n standard used as examples in this article
Summary
Low-density parity-check (LDPC) codes were first introduced by Gallager in 1963 [1] and rediscovered by Mackay [2] in late 1990s. LDPC codes are characterized by a sparse parity-check matrix H, for which an iterative decoder becomes an attractive option. A new material has been added to explain the estimation of the number of bits to be erased at the end of an unsuccessful BP decoding, and computer simulations were performed to investigate the behavior of certain LDPC codes in the presence of AWGN by analyzing the following:. Impact on the performance of HD systems caused by setting a specific number of iterations in a min-sum BP decoder, such that the cardinality of the remaining bit error pattern is small in case of unsuccessful BP decoding;. As mentioned in [9], there are three main approaches to reduce the complexity of LDPC decoding, namely
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