Incorporation of Deep Learning (DL) Techniques to make Intelligent and Adaptable Wireless Communication Systems

The emergence of Deep Learning (DL) was a response to the widespread availability of mobile data and the growing complexity of wireless networks. It is a subfield of Machine learning that has been proposed in academic literature. This technology is regarded as a breakthrough in the management of mobile data traffic. Wireless systems generate a significant amount of varied data, which presents computational issues. In order to tackle this problem, a variety of optimization methodologies are being investigated. DL increases wireless communication by enhancing its intelligence and adaptability. This paper offers an overview of the DL platform and several methodologies employed to enable deep learning in wireless communications. Wireless networking involves various disciplines, including networking, routing, and scheduling, all of which incorporate DL. This text encompasses a comprehensive range of topics. The topic encompassed several optimization methodologies and the latest breakthroughs in this domain.