AI-Driven Signal Processing for Mobile Communications

Authors

Niranjana Gurushankar

Abstract

The relentless demand for higher data rates, lower latency, and massive connectivity in next-generation mobile networks (beyond 5G) necessitates innovative signal processing techniques. This paper delves into the intricacies of AI-driven signal processing in mobile communications, addressing challenges, solutions, and future directions. It also explores the transformative role of Artificial Intelligence (AI) in revolutionizing signal processing for future 6G systems. We examine how deep learning, reinforcement learning, and other AI paradigms are being applied to address key challenges such as channel estimation, signal detection, beamforming, interference management, and resource allocation. The integration of AI allows for adaptive and intelligent signal processing, enabling networks to dynamically optimize performance in complex and rapidly changing radio environments. This paper aims to contribute a detailed analysis of AI-driven signal processing in mobile communications, emphasizing not only the theoretical aspects but also the practical implementation and real-world implications.

Keywords

AI, Machine learning, Deep learning, Signal processing, Mobile communications, 5G, 6G, wireless networks, channel estimation, beamforming, modulation.

AI-Driven Signal Processing for Mobile Communications. Niranjana Gurushankar. 2024. IJIRCT, Volume 10, Issue 1. Pages 1-6. https://www.ijirct.org/viewPaper.php?paperId=2412108