Joint user grouping and power control using whale optimization algorithm for NOMA uplink systems

The non-orthogonal multiple access (NOMA) scheme has proven to be a potential candidate to enhance spectral potency and massive connectivity for 5G wireless networks. To achieve effective system performance, user grouping, power control, and decoding order are considered to be fundamental factors. In this regard, a joint combinatorial problem consisting of user grouping and power control is considered, to obtain high spectral-efficiency for NOMA uplink system with lower computational complexity. To solve the joint problem of power control and user grouping, for Uplink NOMA, we have used a newly developed meta-heuristicnature-inspired optimization algorithm i.e., whale optimization algorithm (WOA), for the first time. Furthermore, for comparison, a recently initiated grey wolf optimizer (GWO) and the well-known particle swarm optimization (PSO) algorithms were applied for the same joint issue. To attain optimal and sub-optimal solutions, a NOMA-based model was used to evaluate the potential of the proposed algorithm. Numerical results validate that proposed WOA outperforms GWO, PSO and existing literature reported for NOMA uplink systems interms of spectral performance. In addition, WOA attains improved results in terms of joint user grouping and power control with lower system-complexity when compared to GWO and PSO algorithms. The proposed work is a novel enhancement for 5G uplink applications of NOMA systems.