Multi-Agent Reinforcement Learning in Wireless Distributed Networks for 6G

TL;DR

This paper provides a comprehensive study on MARL-assisted wireless distributed networks for 6G, introducing the basic mathematical background and evolution of wireless distributed networks and MARL, as well as demonstrating their interrelationships.

Abstract

The introduction of intelligent interconnectivity between the physical and human worlds has attracted great attention for future sixth-generation (6G) networks, emphasizing massive capacity, ultra-low latency, and unparalleled reliability. Wireless distributed networks and multi-agent reinforcement learning (MARL), both of which have evolved from centralized paradigms, are two promising solutions for the great attention. Given their distinct capabilities, such as decentralization and collaborative mechanisms, integrating these two paradigms holds great promise for unleashing the full power of 6G, attracting significant research and development attention. This paper provides a comprehensive study on MARL-assisted wireless distributed networks for 6G. In particular, we introduce the basic mathematical background and evolution of wireless distributed networks and MARL, as well as demonstrate their interrelationships. Subsequently, we analyze different structures of wireless distributed networks from the perspectives of homogeneous and heterogeneous. Furthermore, we introduce the basic concepts of MARL and discuss two typical categories, including model-based and model-free. We then present critical challenges faced by MARL-assisted wireless distributed networks, providing important guidance and insights for actual implementation. We also explore an interplay between MARL-assisted wireless distributed networks and emerging techniques, such as information bottleneck and mirror learning, delivering in-depth analyses and application scenarios. Finally, we outline several compelling research directions for future MARL-assisted wireless distributed networks.

Figures (19)

• Figure 1: The development roadmap of wireless distributed networks and MARL from 2002 to Dec 2024. From the perspective of wireless distributed network development, networks have evolved from a single homogeneous type to a complex heterogeneous type of interconnected everything. From the perspective of MARL development, MARL has gradually shifted from a single network architecture to integration with various emerging techniques. Note that "IB" is defined as an "information bottleneck".
• Figure 2: The outline of this tutorial, where we introduce the provisioning of different MARL algorithms on wireless distributed networks for 6G, and highlight some essential implementation challenges about MARL-assisted wireless distributed networks and emerging techniques that can be adopted.
• Figure 3: The connection between wireless distributed networks and MARL reflects the four evolutionary mechanisms of MARL, including high-overhead CTCE, classical CTDE, non-collaborative DTDE, and collaborative DTDE.
• Figure 4: The network architecture and connection of different wireless distributed networks, including homogeneous types (e.g., sharing the same communication modes, hardware, and software) and heterogeneous types (e.g., composed of nodes with different characteristics).
• Figure 5: Two typical heterogeneous distributed networks for 6G, including CF massive MIMO networks and RIS-assisted MIMO networks.