Energy Efficiency Maximization for Integrated Sensing and Communications in Satellite-UAV MIMO Systems

2026-03-02

AI Summary

This work addresses the trade-off between energy efficiency and integrated sensing and communication (ISAC) performance in satellite–UAV MIMO systems by proposing a distributed MIMO ISAC framework under a hybrid high- and low-altitude channel model that accounts for both line-of-sight (LoS) and non-LoS components. The framework jointly optimizes beamforming and power allocation, incorporating—for the first time—a constraint on sensing beampattern gain into the energy efficiency maximization problem to ensure multi-user quality-of-service requirements and multi-target radar sensing accuracy. Leveraging a uniform planar array and a probabilistic LoS channel model, the resulting non-convex problem is solved via an alternating optimization algorithm. Simulation results demonstrate that the proposed method significantly enhances energy efficiency in multi-user, multi-target scenarios while simultaneously meeting communication throughput and sensing precision requirements.

Technology Category

• Search and Optimization: Distributed Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

This paper investigates energy efficiency maximization in an integrated sensing and communication framework for satellite-UAV MIMO systems, where a LEO satellite and a UAV simultaneously serve ground users and perform target sensing. Both the satellite and UAV are equipped with uniform planar arrays of transmit antennas, enabling a distributed multi-user and multi-target architecture. We derive the achievable downlink throughput by considering that the high-altitude satellite maintains a line-of-sight (LoS) link with users, while adopting a probabilistic model for the UAV that accounts for the likelihood of both LoS and non-line-of-sight conditions. The energy efficiency maximization problem is formulated as a complex non-convex optimization problem, subject to power constraints, quality of service (QoS) requirements, and beampattern gain constraints for accurate sensing. To tackle this challenge, we propose an efficient alternating optimization algorithm capable of handling the complex search space and QoS guarantees. Numerical results across diverse scenarios with multiple users demonstrate that the proposed method achieves high energy efficiency while meeting both communication and sensing performance targets.

Problem

• Energy Efficiency
• Integrated Sensing and Communications
• Satellite-UAV MIMO
• Non-convex Optimization
• Beampattern Gain

Innovation

• Integrated Sensing and Communications
• Energy Efficiency Maximization
• Satellite-UAV MIMO
• Alternating Optimization
• Beampattern Design