Abstract

In this paper, we investigate memory based Luby transform (LT) encoders (MBLTEs) over binary input additive white Gaussian noise (BIAWGN) channels. We analyze the performance of MBLTEs by characterizing the expected probability at each decoding round that a variable node has not yet received any nonzero message. Simulation results verify our analysis and show that MBLTEs outperform the regular LT encoder over BIAWGN channels in terms of bit error rate (BER)/frame error rate (FER) and error floor.

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