Throughput Maximization for UAV-Enabled Integrated Periodic Sensing and Communication

2022-03-12

IEEE Transactions on Wireless Communications

AI Summary

This paper addresses the design of unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC) systems, where joint optimization of UAV trajectory, user association, target selection, and beamforming must satisfy sensing periodicity and beam gain constraints while maximizing achievable rate. Method: We propose a periodic sensing-communication coordination mechanism and uncover an inter-frame decoupled symmetric structure inherent in ISAC signaling. Leveraging this structure, we derive a closed-form optimal beamformer and construct a tight lower bound on the achievable rate. Non-convexity and discrete integer variables are handled via continuous relaxation, penalty-based optimization, and large-scale MIMO asymptotic analysis. Contribution/Results: The proposed framework significantly improves system throughput over benchmark schemes and enables flexible trade-offs between sensing accuracy and communication rate, demonstrating superior performance in UAV-ISAC co-design.

Abstract

Driven by unmanned aerial vehicle (UAV)’s advantages of flexible observation and enhanced communication capability, it is expected to revolutionize the existing integrated sensing and communication (ISAC) system and promise a more flexible joint design. Nevertheless, the existing works on ISAC mainly focus on exploring the performance of both functionalities simultaneously during the entire considered period, which may ignore the practical asymmetric sensing and communication requirements. In particular, always forcing sensing along with communication may make it is harder to balance between these two functionalities due to shared spectrum resources and limited transmit power. To address this issue, we propose a new integrated periodic sensing and communication (IPSAC) mechanism for the UAV-enabled ISAC system to provide a more flexible trade-off between two integrated functionalities. Specifically, the system achievable rate is maximized via jointly optimizing UAV trajectory, user association, target sensing selection, and transmit beamforming, while meeting the sensing frequency and beam pattern gain requirement for the given targets. Despite that this problem is highly non-convex and involves closely coupled integer variables, we derive the closed-form optimal beamforming vector to dramatically reduce the complexity of beamforming design, and present a tight lower bound of the achievable rate to facilitate UAV trajectory design. Based on the above results, we propose a two-layer penalty-based algorithm to efficiently solve the considered problem. To draw more important insights, the optimal achievable rate and the optimal UAV location are analyzed under a special case of infinity number of antennas. Furthermore, we prove the structural symmetry between the optimal solutions in different ISAC frames without location constraints in our considered UAV-enabled ISAC system. Based on this, we propose an efficient algorithm for solving the problem with location constraints. Numerical results validate the effectiveness of our proposed designs and also unveil a more flexible trade-off in ISAC systems over benchmark schemes.

Problem

• Drone ISAC System
• Optimization Mechanism
• Perception-Communication Tradeoff

Innovation

• Optimized Path Planning
• ISAC System
• Symmetrical Solution Design