Robust Low Density Parity Check Decoding over Markov Gaussian Channels

Communications systems suffer from impulsive in- terference, generally modeled as a memory channel to account for the inherent bursts of impulse even though conventional receivers take into account the additive white Gaussian noise only. In this paper, finite- field based constructions of Low Density Parity Check (LDPC) coding over the Markov Gaussian channel are investigated. In contrast with existing approaches assuming the impulse noise statistics, this paper proposes a modified maximum- a-priori method, which forfeits using the statistical knowledge of impulse, to estimate whether or not each transmitted symbol is corrupted by impulse noise. Subsequently, the sum-product algorithm LDPC decoder invokes a clipper to diminish impulsive interference when the channel state is identified to be impulse- corrupted. The bit error rate (BER) performance versus the signal-to-noise ratio for the proposed decoder is conducted using computer simulation. The experimental results in terms of the BER performance justified the robustness of our proposed receiver and also revealed its competitiveness with the optimal benchmark decoder in the hostile environment. Moreover, using the proposed receiver, our calibrated quasi-cyclic LDPC code is shown to slightly outperform its 5G New Radio counterpart under certain circumstances.