Integrated Sensing and Communication with UAV Swarms via Decentralized Consensus ADMM

TL;DR

This paper introduces a decentralized ADMM-based optimization framework for UAV swarms to collaboratively optimize their positions for enhanced integrated sensing and communication, achieving rapid convergence and superior performance.

Contribution

It develops a novel decentralized consensus ADMM algorithm enabling UAVs to optimize their positions for ISAC without a central controller, balancing communication and sensing objectives.

Findings

The proposed algorithm converges rapidly in simulations.

UAV swarms outperform fixed-array baselines in communication and sensing.

The framework scales well with swarm size.

Abstract

UAV swarms can form virtual antenna arrays to exploit additional spatial degrees of freedom and enhance integrated sensing and communication (ISAC). The optimization of UAV positions is challenging due to the distributed nature of swarms and the lack of a global view at individual UAVs. This paper presents a new decentralized optimization framework that allows UAVs to decide their locations in parallel and reach consensus on a globally optimal swarm geometry for ISAC. Specifically, we derive the achievable uplink rate and Cram\'er-Rao Bound (CRB) as tractable metrics for communication and sensing, respectively. The UAV positions are optimized to balance maximizing the communication rate and minimizing the CRB. To solve this non-convex problem with coupled variables, we develop a decentralized consensus alternating direction method of multipliers (ADMM) algorithm, which enables the UAVs to iteratively align their local updates and reach consensus. The algorithm decomposes the global objective into local projection updates, proxy-assisted consensus coordination, and lightweight dual updates, ensuring scalability and consistency throughout the swarm. Simulations demonstrate that the proposed consensus ADMM algorithm converges rapidly with strong scalability, and that the UAV swarm significantly outperforms fixed-array baselines in both communication and sensing performance.