Beamforming-based Achievable Rate Maximization in ISAC System for Multi-UAV Networking

TL;DR

This paper proposes a beamforming-based scheme for multi-UAV networks to maximize achievable communication rates in ISAC systems, integrating advanced optimization and filtering techniques for emergency scenarios.

Contribution

It introduces a novel joint optimization framework for UAV beamforming, load management, and direction planning using robust algorithms, enhancing system performance in emergency communication.

Findings

Improved achievable communication rate and fairness.

Enhanced sensing accuracy and system robustness.

Effective distributed optimization for UAV networks.

Abstract

Airborne mobile Integrated Sensing and Communication (ISAC) base stations have garnered significant attention recently, with ISAC technology being a crucial application for 6G networks. Since ISAC can sense potential mobile communication users, this paper studies an effective scheme for a multi-UAV network tailored for emergency communication. In this paper, we develop a temporal-assisted frame structure utilizing integrated omnidirectional and directional beampattern to facilitate efficient and frequent searching, with extended Kalman filtering (EKF) as an aid to beam alignment. Further, we address an optimization problem to maximize the total achievable rate per slot by jointly designing UAV beamforming, load management, and UAV direction planning, all while adhering to the constraints of the predicted beam coverage. Given the problem NP-hard, we introduce three robust mechanisms for its resolution: an enhanced distributed Successive Convex Approximation (SCA)-Iterative Rank Minimization (IRM) algorithm, an coalition game approach, and a Fermat point search method. In particular, the proposed SCA-IRM algorithm decomposes the original complex optimization problem into several sub-problems and assigns them equally to each UAV, so as to realize distributed computing and improve computational efficiency. Our proposed simulations demonstrate the improved system performance in terms of communication rate, fairness, and sensing accuracy, providing design guidelines of UAV-assisted emergency communication networking.