Autonomous Wireless Systems with Artificial Intelligence

TL;DR

This paper explores how artificial intelligence can be integrated into autonomous wireless systems, emphasizing real-time self-organization, knowledge management, and the distinction between training-based and training-free AI methods.

Contribution

It provides a comprehensive overview of AI methodologies for autonomous wireless systems, highlighting the functions of autonomous agents and the differences in AI training approaches.

Findings

Highlights the importance of AI in real-time self-organization.

Differentiates training-based and training-free AI methods.

Conceptually introduces autonomous agent functions in wireless systems.

Abstract

This paper discusses technology and opportunities to embrace artificial intelligence (AI) in the design of autonomous wireless systems. We aim to provide readers with motivation and general AI methodology of autonomous agents in the context of self-organization in real time by unifying knowledge management with sensing, reasoning and active learning. We highlight differences between training-based methods for matching problems and training-free methods for environment-specific problems. Finally, we conceptually introduce the functions of an autonomous agent with knowledge management.