Application of Deep Learning Techniques to Modulation and Detection for 5G and Beyond Wireless Systems

Abstract

In modern society, wireless communication systems play a very crucial role in entertainment, business, commercial, health, and safety applications. These systems keep evolving from one generation to next generation, and currently we are seeing the deployment of the fifth generation (5G) wireless systems around the world. Academics and industries are already discussing beyond 5G wireless systems, which will be sixth generation (6G) of the evolution. One of the key components of 6G systems will be the use of artificial intelligence (AI) and machine learning (ML) for such wireless networks. Every component and building block of a wireless system that we currently are familiar with from our knowledge of wireless technologies up to 5G, such as physical, network, and application layers, will involve AI/ML techniques. Sixth generation (6G) is a new wireless technology that many academics and researchers are embarking on. The main promises of 6G are to extend AI and ML benefits in the wireless networks and to the users. The 6G technology also will provide advances in technical metrics such as high throughput, supporting new high-demand applications, improved usage of radio-frequency bands, and many more using AI and ML techniques. One of the major ML technologies envisioned as a key technology for 6G will be deep learning (DL) because of its strong applications in achieving learning from scenarios that are more close to human. This chapter presents an up-to-date review of future wireless system concepts such as 6G and role of ML techniques in the modulation and detection of signals.