Error Performance of Sparse Code Multiple Access Networks with Joint ML Detection

Abstract

This paper investigates error performance of sparse code multiple access (SCMA) networks with multiple access channels (MAC) and broadcast channels (BC).We give the closed-form expression for the pairwise error probability (PEP) of joint maximum likelihood (ML) detection for multiuser signals over additive white Gaussian noise (AWGN) and Rayleigh fading channels with an arbitrary number of users and multidimensional codebooks. An upper bound for the average symbol error rate (SER) is calculated. The bound is tight in both AWGN channel and Rayleigh fading channels for high SNR regions. The analytical bounds are compared with simulations, and the results confirm the effectiveness of the analysis for both AWGN and Rayleigh fading channels.