Abstract

Recently, in multi-way relay systems employing physical-layer network coding (PNC), channel condition-based pair selection for pairwise information exchange has drawn increased attention as it provides improved performance over the alternative approaches such as round-robin scheduling of node pairs. With pairwise information exchange, there is additional time diversity available due to transmission of the same coded information block of most of the nodes twice in two adjacent time slots. This additional time diversity can be exploited to further enhance the system performance by means of joint channel decoding-network coding. To this end, a joint belief propagation (BP)-based channel decoding-network coding algorithm was proposed by us in [9] for the relay node of low density parity check (LDPC)-coded multi-way relay systems. Even though the algorithm of [9] offers much superior performance over separate channel decoding, it is highly computational expensive and may not be suitable for applications in wireless sensor networks. Alternatively, bit-flipping (BF)-based LDPC decoding can be adopted at much lower computational complexity. In this paper, we develop a low complexity joint bit-flipping (BF)-based channel decoding and network coding algorithm for LDPC-based multi-way relay systems. The BER performance of the proposed algorithm is investigated using computer simulation for two commonly used LDPC codes. The simulation results demonstrate that superior BER performance can be achieved using the proposed joint decoding algorithm over separate and independent bit-flipping-based LDPC channel decoding at the relay. The simulation results also verify that our proposed algorithm is capable of harnessing the aforesaid additional time diversity available. Though the performance of the proposed joint decoding algorithm is inferior to the BP-based algorithm of [9], due to its low computationally complexity, this algorithm may be appealing for applications in relay nodes with low computational capabilities and memory constraints.

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