Distributed Average Consensus in Wireless Multi-Agent Systems with Over-the-Air Aggregation

TL;DR

This paper introduces a novel distributed consensus algorithm for wireless multi-agent systems that leverages over-the-air signal superposition to efficiently compute averages, even over time-varying channels.

Contribution

It proposes a modified Ratio Consensus algorithm utilizing over-the-air aggregation with normalization to achieve consensus in wireless networks.

Findings

Algorithm converges asymptotically with negligible noise

Works for both time-invariant and time-varying channels

Numerical simulations validate theoretical results

Abstract

In this paper, we address the average consensus problem of multi-agent systems over wireless networks. We propose a distributed average consensus algorithm by invoking the concept of over-the-air aggregation, which exploits the signal superposition property of wireless multiple-access channels. The proposed algorithm deploys a modified version of the well-known Ratio Consensus algorithm with an additional normalization step for compensating for the arbitrary channel coefficients. We show that, when the noise level at the receivers is negligible, the algorithm converges asymptotically to the average for time-invariant and time-varying channels. Numerical simulations corroborate the validity of our results.