Energy Consumption Saving in 5G Network Based on Artificial Intelligence

Debarun Ghosh, S. Bharathi
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Abstract

Fifth generation (5G) technology is tasked with tackling the challenge of energy efficiency. As a result, the problem of selecting the optimal set of cells to be turned OFF is nondeterministic polynomial time hard. 5G is more than just a generational step; it opens a new world of possibilities. There are several ways to develop a nation, and Information and Communication Technology will be the best enabler toward realizing this challenge. The exponential increase in network traffic and the number of connected devices make energy efficiency an increasingly important concern for the entire technological ecosystem. With that in mind, we shall discuss some of the proven works related to the topic, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithms, controlling PDCCH channel skipping in sectors of IIoT (3GPP of 5G), and many other related solutions to the most vital element of concern.
基于人工智能的5G网络节能
第五代(5G)技术的任务是解决能源效率的挑战。因此,选择要关闭的最优单元格集的问题是非确定性多项式时间困难的。5G不仅仅是一代人的进步;它开启了一个充满可能性的新世界。一个国家的发展有多种方式,信息和通信技术将是实现这一挑战的最佳推动者。网络流量和连接设备数量的指数级增长使得能源效率成为整个技术生态系统日益关注的问题。考虑到这一点,我们将讨论一些与该主题相关的成熟工作,例如遗传算法(GA),粒子群优化(PSO)算法,控制工业物联网(5G的3GPP)部门中的PDCCH信道跳变,以及许多其他相关的解决方案,以解决最重要的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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