It is a technique of using Neural Networks to implement complex iterative signal processing approaches in a simplified way especially at the physical layer.
Published in Chapter:
AI-Based Wireless Communication
Sanjana T, (BMS College of Engineering, India), Lalitha S. (BMS College of Engineering, India), Surendra H. H. (BMS College of Engineering, India), and Madhusudhan .. K. N. (BMS College of Engineering, India)
Copyright: © 2022
|Pages: 19
DOI: 10.4018/978-1-6684-3804-6.ch004
Abstract
Artificial intelligence (AI) is one of the key enablers among quantum technology, smart meta-surfaces, dense antenna arrays, and mobile edge communication in 6G. The level of maturity achieved in the field of AI and development of computationally efficient hardware architectures with reduced costs have powered up the use of AI in different layers of wireless communication. Based on the learning, reasoning, and decision-making capability of AI, performance of wireless communication can be optimized. In addition, a whole new range of smart applications such as augmented reality (AR), virtual reality (VR), unmanned aerial vehicle (UAV), extended reality (XR) and holography, and autonomous driving, which demands high precision and low latency, can easily be accomplished by integrating AI into wireless communication. This chapter covers the role of AI in different layers, utilization of deep unfolding in physical layer, AI in mobile edge computing, explainable AI, federated learning, and AI for energy-efficient communication. The chapter concludes with research challenges and opportunities.