Capacity Analysis and Sum Rate Maximization for the SCMA Cellular Network Coexisting with D2D Communications

TL;DR

This paper analyzes the capacity and proposes a power allocation algorithm to maximize the sum rate in a hybrid SCMA cellular network coexisting with D2D communications, enhancing spectral efficiency for IoT connectivity.

Contribution

It derives the capacity bounds considering interference and introduces a geometric programming-based iterative algorithm for joint power optimization.

Findings

The proposed algorithm converges quickly.

Significant sum rate improvement demonstrated in simulations.

Capacity bounds effectively model interference effects.

Abstract

Sparse code multiple access (SCMA) is the most concerning scheme among non-orthogonal multiple access (NOMA) technologies for 5G wireless communication new interface. Another efficient technique in 5G aimed to improve spectral efficiency for local communications is device-to-device (D2D) communications. Therefore, we utilize the SCMA cellular network coexisting with D2D communications for the connection demand of the Internet of things (IOT), and improve the system sum rate performance of the hybrid network. We first derive the information-theoretic expression of the capacity for all users and find the capacity bound of cellular users based on the mutual interference between cellular users and D2D users. Then we consider the power optimization problem for the cellular users and D2D users jointly to maximize the system sum rate. To tackle the non-convex optimization problem, we propose a geometric programming (GP) based iterative power allocation algorithm. Simulation results demonstrate that the proposed algorithm converges fast and well improves the sum rate performance.