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

Ngo Tran Anh Thu, Pham Dang Anh Duc, Bui Trong Duc, Nguyen Minh Quan, Trinh Van Chien, Hoang D. Le

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.

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

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.
Paper Structure (12 sections, 25 equations, 2 figures, 1 table, 1 algorithm)

This paper contains 12 sections, 25 equations, 2 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. Satellite-UAV-assisted Integrated Sensing and Communications Model
  3. Multi-user Downlink Communication Network
  4. Communication Model for Rural Users
  5. Communication Model for Urban Users
  6. Downlink Transmission Rate
  7. Multi-target Sensing Network
  8. Joint Optimization of Communication and Sensing Energy Efficiency
  9. Problem Formulation
  10. Alternating Optimization
  11. Numerical Results
  12. Conclusion

Figures (2)

  • Figure 1: Illustration of an ISAC Satellite-UAV wireless network: (a) Integrated space-aerial-terrestrial scenario with multi-functional sensing and communication links, (b) Geographical coverage of satellite-UAV platforms in a 3D coordinate system.
  • Figure 2: Overall system performance across sensing and communication tasks: (a) Convergence behavior of Algorithm \ref{['alg:convex']} over iterations; (b) Impact of increasing the number of sensing targets on the achieved EE for various user densities; (c) Comparison of EE achieved by proposed AO algorithms with other algorithms; (d) EE performance as a function of the beampattern threshold.

Theorems & Definitions (1)

  • Remark 1