UAV-Assisted Multi-Cluster Over-the-Air Computation

TL;DR

This paper proposes an optimized UAV-assisted over-the-air computation framework for multi-cluster wireless data aggregation, improving task performance and interference management through joint trajectory and transceiver design.

Contribution

It introduces an iterative algorithm for joint optimization of UAV trajectory, transceiver design, and cluster scheduling in multi-cluster AirComp networks, addressing non-convex challenges.

Findings

Significant performance gains over benchmarks.

Multiple UAVs increase task throughput.

Reduced access delays with optimized deployment.

Abstract

In this paper, we study unmanned aerial vehicles (UAVs) assisted wireless data aggregation (WDA) in multicluster networks, where multiple UAVs simultaneously perform different WDA tasks via over-the-air computation (AirComp) without terrestrial base stations. This work focuses on maximizing the minimum amount of WDA tasks performed among all clusters by optimizing the UAV's trajectory and transceiver design as well as cluster scheduling and association, while considering the WDA accuracy requirement. Such a joint design is critical for interference management in multi-cluster AirComp networks, via enhancing the signal quality between each UAV and its associated cluster for signal alignment and meanwhile reducing the inter-cluster interference between each UAV and its nonassociated clusters. Although it is generally challenging to optimally solve the formulated non-convex mixed-integer nonlinear programming, an efficient iterative algorithm as a compromise approach is developed by exploiting bisection and block coordinate descent methods, yielding an optimal transceiver solution in each iteration. The optimal binary variables and a suboptimal trajectory are obtained by using the dual method and successive convex approximation, respectively. Simulations show the considerable performance gains of the proposed design over benchmarks and the superiority of deploying multiple UAVs in increasing the number of performed tasks while reducing access delays.