Optimal User and Target Scheduling, User-Target Pairing, and Low-Resolution Phase-Only Beamforming for ISAC Systems

2025-01-20

AI Summary

This paper addresses the non-convex mixed-integer nonlinear programming (MINLP) problem of jointly optimizing user scheduling, target association, and beamforming in integrated sensing and communication (ISAC) systems. To tackle this challenge, we propose a globally optimal joint design framework. Our key contributions are threefold: (i) we formulate an exact mixed-integer linear programming (MILP) reformulation of the original problem, enabling globally optimal solutions; (ii) we adopt low-resolution, constant-modulus, finite-phase-shift beamforming to ensure hardware feasibility without compromising performance; and (iii) we replace conventional sequential heuristic approaches with end-to-end joint optimization of sensing and communication resources. Simulation results demonstrate that the proposed method significantly outperforms staged designs in localization accuracy, communication rate, and robustness—validating the fundamental advantages of joint optimization for multi-objective trade-offs and cross-scenario generalization.

Technology Category

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

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization
• Security and Privacy: Security and privacy of machine learning and AI applications

Abstract

We investigate the joint user and target scheduling, user-target pairing, and low-resolution phase-only beamforming design for integrated sensing and communications (ISAC). Scheduling determines which users and targets are served, while pairing specifies which users and targets are grouped into pairs. Additionally, the beamformers are designed using few-bit constant-modulus phase shifts. This resource allocation problem is a nonconvex mixed-integer nonlinear program (MINLP) and challenging to solve. To address it, we propose an exact mixed-integer linear program (MILP) reformulation, which leads to a globally optimal solution. Our results demonstrate the superiority of an optimal joint design compared to heuristic stage-wise approaches, which are highly sensitive to scenario characteristics.

Problem

• ISAC System
• User-Target Scheduling
• Simplified Beamforming

Innovation

• Complex Mathematical Programming
• ISAC System Optimization
• User-Target Scheduling and Pairing