Unified Iterative Receiver Design in Uplink Grant-Free Massive MIMO SCMA Systems

In machine-type communication scenarios, sparse code multiple access (SCMA) is a promising non-orthogonal multiple access (NOMA) scheme owing to shaping gain by combining constellation modulation and spreading patterns together. In this paper, to fully exploit the channel knowledge contained in received data sequences, we propose the joint active user detection (AUD), channel estimation (CE), multi-user detection (MUD), and decoding receiver without knowing users' activity parameters in uplink grant-free massive multiple-input multiple-output (MIMO) SCMA systems. To avoid the permutation and scaling ambiguities of estimation results, the proposed receiver estimates channel based on both received short pilot and data sequences. We introduce auxiliary active state indicators in AUD to describe the sporadic transmission feature. The joint CE and MUD module is constructed as a bilinear inference problem with joint column-wise sparsity. Furthermore, we exploit the SCMA codewords sparsity feature and put Gaussian approximations on modulated symbols in joint CE and MUD module to reduce the receiver complexity. Simulation results show that the proposed unified receiver has substantial performance improvement and lower computational complexity than the conventional two-stage receiver and joint receiver in the literature.