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Noise Adaptive LDPC Decoding Using Particle Filtering
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DOI：10.1109/TCOMM.2011.011811.090309.png)
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Abstract
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Belief propagation (BP) is a powerful algorithm to decode low-density parity check (LDPC) codes over additive white Gaussian noise (AWGN) channels. However, the traditional BP algorithm cannot adapt efficiently to the statistical change of SNR in an AWGN channel. This paper proposes an adaptive scheme that incorporates a particle filtering (PF) algorithm into the BP based LDPC decoding process. The proposed scheme is capable to perform online estimation of time-varying SNR at the bit-level and enhance the BP decoding performance simultaneously.
Keywords:
Signal processing
channel coding
estimation
adaptive decoding
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