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Near-Maximum-Likelihood Decoding for Convolutionally Coded Physical-Layer Network Coding Over the Full-Duplex Two-Way Relay Channel
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DOI：10.1109/TVT.2018.2841990.png)
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Abstract
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The full duplex (FD) two-way relay channel (TWRC) has recently been shown to be a feasible way to improve the network throughput in practical communications. In this correspondence, we consider the convolutionally coded physical-layer network coding over the TWRC in which two sources work in the FD mode and there exists a direct link between them. Every source receives two packets, one packet from the other source and one network coded packet from the relay. A near-maximum-likelihood decoding algorithm for the sources is proposed. A salient feature of the proposed algorithm is that it exploits the code structure to mitigate the error propagation induced by the relay. Furthermore, we derive the near maximum-likelihood decoding bound on end-to-end BER for the system. Simulation results indicate that the performance of the proposed algorithm matches well the bound.
Keywords:
Two-way relay channel
full duplex
error propagation
physical-layer network coding
convolutional code
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