Energy Efficiency Maximization for Uplink SCMA System Using CCPSO

Abstract

This paper considers an energy efficiency (EE) maximization problem with minimal sum rate requirement in an uplink multi-user sparse code multiple access (SCMA) system. SCMA allows overloading with a large number of SCMA layers to enable massive connectivity. A linear sparse sequence modeling is utilized to obtain the upper bound of the sum rate. The EE maximization problem is then formulated to obtain the optimal power and resource element (RE) allocation. In general, the EE maximization problem is a non-convex problem. It is also a large-scale optimization problem, i.e., the optimization variable is high-dimensional, since massive connectivity needs a large number of SCMA layers. A novel method, namely cooperative coevolutionary particle swarm optimization (CCPSO), is applied to solve the EE maximization problem. Simulation results show the validity of CCPSO to solve the problem. It also implies that the SCMA scheme outperforms the traditional OFDMA in terms of EE under the same minimal sum rate requirement, mainly owing to its dramatic gain in sum rate due to the overloading gain.