Large Artificial Intelligence Models for Future Wireless Communications

TL;DR

This paper explores how large AI models can revolutionize future wireless communications by enhancing data analysis, resource management, and real-time adaptation, while addressing associated challenges and future research directions.

Contribution

It introduces a comprehensive architecture for integrating large AI models into wireless networks and discusses their advantages, challenges, and potential future applications.

Findings

Large AI models can improve resource allocation and real-time network adaptation.

Integration of AI models faces challenges like energy consumption, privacy, and security.

Proposes solutions and future research directions for AI in wireless communications.

Abstract

The anticipated integration of large artificial intelligence (AI) models with wireless communications is estimated to usher a transformative wave in the forthcoming information age. As wireless networks grow in complexity, the traditional methodologies employed for optimization and management face increasingly challenges. Large AI models have extensive parameter spaces and enhanced learning capabilities and can offer innovative solutions to these challenges. They are also capable of learning, adapting and optimizing in real-time. We introduce the potential and challenges of integrating large AI models into wireless communications, highlighting existing AIdriven applications and inherent challenges for future large AI models. In this paper, we propose the architecture of large AI models for future wireless communications, introduce their advantages in data analysis, resource allocation and real-time adaptation, discuss the potential challenges and corresponding solutions of energy, architecture design, privacy, security, ethical and regulatory. In addition, we explore the potential future directions of large AI models in wireless communications, laying the groundwork for forthcoming research in this area.