Sparse Code Multiple Access (SCMA) is a disruptive code-domain non-orthogonal multiple access (NOMA) scheme to enable future massive machine-type communication networks. As an evolved variant of code division multiple access (CDMA), multiple users in SCMA are separated by assigning distinctive sparse codebooks (CBs). Efficient multiuser detection is carried out at the receiver by employing the message passing algorithm (MPA) that exploits the sparsity of CBs to achieve error performance approaching to that of the maximum likelihood receiver. In spite of numerous research efforts in recent years, a comprehensive one-stop tutorial of SCMA covering the background, the basic principles, and new advances, is still missing, to the best of our knowledge. To fill this gap and to stimulate more forthcoming research, we provide a holistic introduction to the principles of SCMA encoding, CB design, and MPA based decoding in a self-contained manner. As an ambitious paper aiming to push the limits of SCMA, we present a survey of advanced decoding techniques with brief algorithmic descriptions as well as several promising directions.

Sparse code multiple access (SCMA), as a code-domain non-orthogonal multiple access (NOMA) scheme, has received considerable research attention for enabling massive connectivity in future wireless communication systems. In this paper, we present a novel codebook (CB) design for SCMA based visible light communication (VLC) system, which suffers from shot noise. In particular, we introduce an iterative algorithm for designing and optimizing CB by considering the impact of shot noise at the VLC receiver. Based on the proposed CB, we derive and analyze the theoretical bit error rate (BER) expression for the resultant SCMA-VLC system. The simulation results show that our proposed CBs outperform CBs in the existing literature for different loading factors with much less complexity. Further, the derived analytical BER expression well aligns with simulated results, especially in high signal power regions.

We study an intelligent reflecting surface (IRS)aided downlink sparse code multiple access (SCMA) system for massive connectivity in future machine-type communication networks. Our objective is to maximize the system sum-rate subject to the constraint of minimum user data rate, the total power of base station, SCMA codebook structure, and IRS channel coefficients. To this end, a joint optimization problem involving IRS phase vector, factor graph matrix assignment, and power allocation problem is formulated, which is non-convex in nature. This problem is solved by developing an alternating optimization (AO) algorithm. A key idea is to first divide the formulated non-convex problem into three subproblems (i.e., factor graph matrix assignment, power allocation, and phase vector of IRS) and then tackle them iteratively. The validity of the proposed schemes is shown using the simulation results. Moreover, compared to the SCMA system without IRS, a significant performance improvement in the IRS-aided SCMA system is shown in terms of achievable sum-rate.