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Energy-efficient resource optimization using game theory in hybrid NOMA assisted cognitive radio networks
Physical Communication ( IF 2.2 ) Pub Date : 2021-06-01 , DOI: 10.1016/j.phycom.2021.101382
Ashok Kumar , Krishan Kumar

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.



中文翻译:

在混合 NOMA 辅助认知无线电网络中使用博弈论进行节能资源优化

目前,辅助网络 (SN) 是从容量增加和干扰减少中收集的,而不是使其节能以实现绿色通信。本文提出了一种在基于混合非正交多址 (HNOMA) 的认知无线电网络 (CRN) 中使用游戏的资源的节能优化。为此,还提出了 SUs 集群和节能功率分配 (PA) 方案,以提高吞吐量。而集群和 PA 方案一起被合并到不同联盟中的破碎 SU 中,并在不同的频段 (FB) 上同时为它们分配有效的功率。此外,对用户的 PA 以分布式方式(不与其他 BS 通信)发生,其中每个 BS 正在更新 PA 策略以实现其效用最大化。稳定性,正在推导和证明这两种方案的存在性和唯一性。使用各种信道增益进行模拟以评估分析结果,并支持两种方案相较于现有方案的成功。

更新日期:2021-06-17
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