Resilient Full-Duplex ISAC in the Face of Imperfect SI Cancellation: Globally Optimal Timeslot Allocation and Beam Selection

2025-10-17

AI Summary

This paper addresses the resource management challenge in downlink full-duplex integrated sensing and communication (ISAC) systems under residual self-interference (RSI). Method: We jointly optimize time-slot allocation and beam selection. To overcome the computational intractability of the original semi-infinite non-convex mixed-integer nonlinear programming (MINLP) formulation, we propose a customized problem reformulation that equivalently transforms it into a globally optimizable mixed-integer linear program (MILP). The reformulation integrates RSI-aware modeling, adaptive beamforming, and fine-grained time-slot scheduling. Contribution/Results: To the best of our knowledge, this is the first work achieving strong robustness against imperfect self-interference cancellation while guaranteeing joint sensing-communication performance. Simulation results demonstrate significant improvements in spectral and energy efficiency, along with a theoretically guaranteed global optimum.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

This work addresses the radio resource management (RRM) design in downlink full-duplex integrated sensing and communications (ISAC) systems, jointly optimizing timeslot allocation and beam selection under imperfect self-interference cancellation. Timeslot allocation governs the distribution of discrete channel uses between sensing and communication tasks, while beam selection determines transmit and receive directions along with adaptive beamwidths. The joint design leads to a semi-infinite, nonconvex mixed-integer nonlinear program (MINLP), which is difficult to solve. To overcome this, we develop a tailored reformulation strategy that transforms the problem into a tractable mixed-integer linear program (MILP), enabling globally optimal solutions. Our approach provides insights into the coordinated optimization of timeslot allocation and beam selection, enhancing the efficiency of full-duplex ISAC systems while ensuring resilience against residual self-interference.

Problem

• Optimizing timeslot allocation and beam selection in full-duplex ISAC systems
• Addressing imperfect self-interference cancellation in radio resource management
• Transforming complex MINLP into tractable MILP for optimal solutions

Innovation

• Transforms MINLP into tractable MILP for solutions
• Globally optimizes timeslot allocation and beam selection
• Enhances full-duplex ISAC resilience to self-interference