NOMA using AI for 5G and Future Generation: A Comprehensive Analysis

Abstract

Wireless mobile communication is an essential part of modern life. In wireless communication the issues related   to requirement of increased data rate, increased sum rate, increased SNR   , and increased throughput, increased security decrement in latency must be meet. This requirement arises due to rapidly growing machines, digitalization of most of the services and devices engaging the insufficient radio spectrum. The coming decades also will be of the advanced machines, IoT based application, mobile application etc. with great efficiency. The demand of such huge bandwidth cannot be supported by the existing technology. Because of this reason it is essential to increase the frequency band as well as to use these frequency bands effectively and efficiently. In this context NOMA is a potential technology which uses frequency bands effectively and efficiently. To take the advantages in optimum manner of NOMA as power allocation can be used with different deep learning algorithms. With large number of communicating devices the overall performance of wireless network can be achieved better by integrating the two techniques NOMA and DL/ML techniques. DL is advantageous for changing channel conditions detection effectively and training input signals. Researchers already proved The usage of techniques based on artifial intelligence researchers already used for  beam forming ,resource allocation, clustering of users in NOMA is paramount for the 5G system and B5G wireless communication system. In paper a detailed Analysis is done on various techniques of AI (Artificial Intelligence) aided NOMA system which is advantageous for the future wireless communication.