Reduced Complexity Maximum Likelihood Decoding of Linear Block Codes
نویسندگان
چکیده
This paper proposes a reduced complexity Maximum-Likelihood (ML) decoding Algorithm for Linear Block Codes based on the Kaneko decoder and incorporating ruling out conditions for useless iteration steps. The proposed decoding scheme is evaluated over the Additive White Gaussian Noise (AGWN) channel using Binary Phase Shift Key (BPSK) signalling by simulation. Simulations results show that for negligible performance loss, there is significant reduction in the complexity of decoding.
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تاریخ انتشار 2007