Energy-efficient resource optimization using game theory in hybrid NOMA assisted cognitive radio networks

Abstract

Presently, Secondary Networks (SNs) are gleaned from rising capacity with reducing interference together instead of making them energy-efficient for green communication. This paper proposes an energy-efficient optimization for resources using game in Hybrid Non-orthogonal Multiple Access (HNOMA) based Cognitive Radio Networks (CRNs). For this, also proposes SUs clustering and energy-efficient Power Allocation (PA) scheme together to enhance the throughput. Whereas, clustering and PA schemes together are incorporated to broken SUs in distinct coalitions and allocating efficient powers to them simultaneously over various Frequency Bands (FBs). In addition, PA to users happens in a distributed manner (without communicating other BSs) in which each BS is updating PA strategies for its utility maximization. The stability, existence and uniqueness of both schemes are being derived and proved. Simulations are taken out with various channel gains to evaluate analytical outcome, and uphold the success of both schemes together over existing ones.