A low-complexity tree search based quasi-ML receiver for SCMA system

Sparse code multiple access (SCMA) which is overloaded by carrying more users than its resource blocks, is different from conventional multiple access method. It can improve spectrum efficiency to solve the problem of large amounts of telecommunication data. Conventional message passing algorithm (MPA) receiver has been used in SCMA, but it has a relatively high complexity. In this paper, we propose a new low-complexity quasi maximum likelihood (quasi-ML) receiver to further reduce the complexity. Quasi-ML receiver is improved for the specific characteristic of SCMA. Numerical results demonstrate that the quasi-ML detector achieves significantly less computational complexity than the classic MPA detector, with a little performance loss. The superior performance of the proposed algorithm is demonstrated by theoretic analysis as well as simulation results.