利用粒子群算法和遗传算法实现基于CR的物联网系统的能效最大化

J. Ramesh, Ajay Thammana, V. Sudha
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引用次数: 0

摘要

物联网系统与5G无线通信系统的兼容性更高。物联网具有共享大量数据的能力,因此物联网网络存在一定的开销。克服这个问题的更好的解决方案是结合合适的路由和最佳的能量转换方法。认知无线电由于其智能,是路由和节能方法的最佳解决方案。但在认知无线电网络中,频谱感知时间和能量消耗之间存在交换。为了克服这种权衡,必须在认知无线电中包含优化,以获得更好的物联网服务。本文尝试利用遗传算法(GA)和粒子群算法(PSO)解决协同通信场景下认知无线网络中感知时间和能量消耗的联合优化问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Maximization of Energy Efficiency in CR Based IoT Systems Using PSO and GA Algorithms
IOT systems are more compatible with 5G wireless communication systems. Internet of things has the capability of sharing large amount of data, due to which there is an overhead on the IOT network. The better solution to overcome this problem is by incorporating suitable routing and best energy conversation methods. Cognitive radio is the best solution for routing and energy conservation methods due to its intelligence. But there is swap between spectrum sensing time and energy consumption in cognitive radio networks. To overcome the trade-off, the inclusion of Optimization in cognitive radio is must for better IOT services. In this paper, we try to resolve joint optimization of sensing time and energy consumption by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in cognitive radio network under Co-operative communication scenario.
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