Success Probability and Area Spectral Efficiency in SCMA Wireless Networks

Sparse code multiple access (SCMA) is emerging as a promising multiple access technology for the fifth-generation wireless networks. By leveraging user-specific SCMA codebooks, SCMA possesses the potential to enable non-orthogonal resource access, and thus leading to the overloading gain. Benefiting from this, SCMA can accommodate more users and achieve a higher throughput than orthogonal frequency division multiple access. In this correspondence, we propose a tractable analytical framework using tools from stochastic geometry to investigate the performance of SCMA wireless networks. In particular, we obtain explicit closed-form expressions for the success probability and the area spectral efficiency (ASE). Based on the derived results, we prove that the ASE is a quasi-concave function of the transmitter density. Moreover, we shed light on the impact of SCMA codeword dimension
$K$
and the number of non-zero entries in SCMA codeword
$N$
on the network performance. Specifically, we demonstrate that the optimal transmitter density and the maximum ASE scale super-linearly with rate
$K^{N}$
. Simulation results validate the accuracy of the presented analysis and exhibit the superiority of SCMA.