Multi-player Bandits for Distributed Cognitive Radar

TL;DR

This paper explores the use of multi-player bandit algorithms for waveform selection in distributed cognitive radar networks, enabling spectrum sharing and collision avoidance without dedicated communication channels.

Contribution

It introduces a novel approach for radar nodes to coordinate spectrum usage indirectly through actions, addressing coexistence with communication systems without explicit communication.

Findings

Nodes can effectively avoid collisions through indirect communication strategies.

The approach adapts to both homogeneous and heterogeneous channel conditions.

Radar nodes optimize spectrum utilization while coexisting with communication systems.

Abstract

With new applications for radar networks such as automotive control or indoor localization, the need for spectrum sharing and general interoperability is expected to rise. This paper describes the application of multi-player bandit algorithms for waveform selection to a distributed cognitive radar network that must coexist with a communications system. Specifically, we make the assumption that radar nodes in the network have no dedicated communication channel. As we will discuss later, nodes can communicate indirectly by taking actions which intentionally interfere with other nodes and observing the resulting collisions. The radar nodes attempt to optimize their own spectrum utilization while avoiding collisions, not only with each other, but with the communications system. The communications system is assumed to statically occupy some subset of the bands available to the radar network. First, we examine models that assume each node experiences equivalent channel conditions, and later examine a model that relaxes this assumption.