Large Language Model Based Multi-Objective Optimization for Integrated Sensing and Communications in UAV Networks

作     者：Li, Haoyun Xiao, Ming Wang, Kezhi Kim, Dong In Debbah, Merouane 

作者机构：Division of Information Science and Engineering KTH Royal Institute of Technology Stockholm10044 Sweden Department of Computer Science Brunel University London Middlesex UxbridgeUB8 3PH United Kingdom Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Department of Electrical Engineering and Computer Science KU 6G Center Khalifa University Abu Dhabi127788 United Arab Emirates CentraleSupelec University Paris-Saclay Gif-sur-Yvette91192 France 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2024年

核心收录：

主　　题：Cramer Rao bounds 

摘      要：This letter investigates an unmanned aerial vehicle (UAV) network with integrated sensing and communication (ISAC) systems, where multiple UAVs simultaneously sense the locations of ground users and provide communication services with radars. To find the trade-off between communication and sensing (C&S) in the system, we formulate a multi-objective optimization problem (MOP) to maximize the total network utility and the localization Cramér-Rao bounds (CRB) of ground users, which jointly optimizes the deployment and power control of UAVs. Inspired by the huge potential of large language models (LLM) for prediction and inference, we propose an LLM-enabled decomposition-based multi-objective evolutionary algorithm (LEDMA) for solving the highly non-convex MOP. We first adopt a decomposition-based scheme to decompose the MOP into a series of optimization sub-problems. We second integrate LLMs as black-box search operators with MOP-specifically designed prompt engineering into the framework of MOEA to solve optimization sub-problems simultaneously. Numerical results demonstrate that the proposed LEDMA can find the clear trade-off between C&S and outperforms baseline MOEAs in terms of obtained Pareto fronts and convergence. Copyright © 2024, The Authors. All rights reserved.