Low complexity sparse code multiple access decoder based on tree pruned method

Abstract

With the requirement of rapid traffic growth and tremendous access, non-orthogonal multiple access becoming a prominent technology in the current 5G research area. The sparse code multiple access (SCMA) scheme is one of the most promising technology among the non-orthogonal technologies. In this work, we propose a tree pruned method based on MAX log-message decoding algorithm (MPA) to reduce the decoding complexity of SCMA significantly. We first formulate the decoding problem to a tree updating process. By using the tree pruned method, the sub nodes with lower weight can be updated by low complexity arithmetic operations. According to the simulation result, the proposed tree pruned method reduces 30% computation complexity compared with existing methods. The results provide in this paper indicates the potential practical application of SCMA decoder.