Low Complexity Detection Based on Dynamic Factor Graph for SCMA Systems

Abstract

Sparse code multiple access (SCMA) has been proposed to support massive connections, and becomes a promising non-orthogonal multiple access in future fifth generation wireless communication systems. In SCMA, message passing algorithm (MPA) is utilized to achieve nearly optimal multiuser detection, but the high complexity of MPA detector still makes it hard to implement in practice. To tackle this issue, we present a low complexity MPA detector based on the dynamic factor graph, named DFG-MPA, in which the branches with large belief values in the factor graph model do not participate in the message propagation in current and later iterations. Moreover, choosing the number of partial branches with large belief values for each iteration adaptively depends on practical application scenarios. Numerical results show that the proposed detection scheme provides a commendable tradeoff between bit-error-rate (BER) performance and computational complexity compared with some existing MPA schemes.