A Low Complexity SCMA Decoder Based on List Sphere Decoding

Non-orthogonal multiple access is one of the key techniques developed for the future 5G communication systems among which, the recent proposed sparse code multiple access (SCMA) has attracted a lots of researchers' interests. By exploring the shaping gain of the multi-dimensional complex codewords, SCMA is shown to have a better performance compared with some other non-orthogonal schemes such as low density signature (LDS). However, although the sparsity of the codewords makes the near optimal message passing algorithm (MPA) possible, the decoding complexity is still very high. In this paper, we propose a low complexity decoding algorithm based on list sphere decoding. Complexity analysis and simulation results show that the proposed algorithm can reduce the computational complexity substantially while achieve the near maximum likelihood (ML) performance.