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