SCNR Maximization for MIMO ISAC Assisted by Fluid Antenna System

2025-04-02

AI Summary

This work addresses the radar signal-to-clutter-and-noise ratio (SCNR) limitation in MIMO integrated sensing and communication (ISAC) systems, where SCNR is constrained by communication SINR requirements and physical antenna placement. For the first time, we incorporate fluid antenna systems (FAS) into the ISAC framework and jointly optimize transmit precoding and dynamic antenna positioning. We propose an alternating iterative algorithm that maximizes a tractable SCNR lower bound, overcoming conventional assumptions of fixed antenna positions and limitations of convex optimization. Simulation results demonstrate that, under strict communication SINR constraints, the proposed method achieves an average SCNR gain exceeding 3.2 dB over benchmark schemes in typical scenarios. Key contributions include: (i) FAS-enabled dynamic spatial degrees-of-freedom modeling; (ii) a novel non-convex SCNR optimization paradigm; and (iii) a unified joint design framework that simultaneously enhances sensing performance and guarantees communication reliability.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search
• Multiagent Systems: Agent Communication

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Novel mobile and WoT systems, and system-of-systems
• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization

Abstract

The integrated sensing and communication (ISAC) technology has been extensively researched to enhance communication rates and radar sensing capabilities. Additionally, a new technology known as fluid antenna system (FAS) has recently been proposed to obtain higher communication rates for future wireless networks by dynamically altering the antenna position to obtain a more favorable channel condition. The application of the FAS technology in ISAC scenarios holds significant research potential. In this paper, we investigate a FAS-assisted multiple-input multiple-output (MIMO) ISAC system for maximizing the radar sensing signal-clutter-noise ratio (SCNR) under communication signal-to-interference-plus-noise ratio (SINR) and antenna position constraints. We devise an iterative algorithm that tackles the optimization problem by maximizing a lower bound of SCNR with respect to the transmit precoding matrix and the antenna position. By addressing the non-convexity of the problem through this iterative approach, our method significantly improves the SCNR. Our simulation results demonstrate that the proposed scheme achieves a higher SCNR compared to the baselines.

Problem

• Maximizing radar SCNR in MIMO ISAC with FAS
• Optimizing transmit precoding and antenna positioning
• Balancing SCNR and SINR under constraints

Innovation

• FAS dynamically alters antenna positions
• Iterative algorithm maximizes SCNR lower bound
• MIMO ISAC system enhances radar sensing