Hybrid Beamforming Design for RSMA-enabled Near-Field Integrated Sensing and Communications

2024-12-22

arXiv.org

AI Summary

In near-field integrated sensing and communication (NF-ISAC), jointly optimizing multi-target sensing performance and communication rate remains challenging. Method: This paper proposes an RSMA-based hybrid analog-digital beamforming framework, jointly optimizing transceiver filters, beam structure, and common-stream rate allocation to maximize the minimum user rate while guaranteeing multi-target sensing accuracy. Contribution/Results: We theoretically establish that near-field multi-target sensing does not require dedicated sensing beams—enabling rank-zero reconstruction and relaxing the far-field assumption. We pioneer a co-design mechanism integrating RSMA with adaptive numbers of sensing beams, circumventing conventional multiple-access constraints. Leveraging a two-layer algorithm combining WMMSE, quadratic transformation, and penalty dual decomposition (PDD), our approach achieves near-full-digital performance with fewer RF chains. It significantly enhances near-field multi-target detection capability without compromising communication rates, outperforming existing far-field ISAC and traditional multiple-access schemes in overall performance.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Search and Optimization: Mixed Discrete/Continuous Search
• Machine Learning: Neuro-Symbolic Learning

Application Category

• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG
• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

Integrated sensing and communication (ISAC) networks leverage extremely large antenna arrays and high frequencies. This inevitably extends the Rayleigh distance, making near-field (NF) spherical wave propagation dominant. This unlocks numerous spatial degrees of freedom, raising the challenge of optimizing them for communication and sensing tradeoffs. To this end, we propose a rate-splitting multiple access (RSMA)-based NF-ISAC transmit scheme utilizing hybrid analog-digital antennas. RSMA enhances interference management, while a variable number of dedicated sensing beams adds beamforming flexibility. The objective is to maximize the minimum communication rate while ensuring multi-target sensing performance by jointly optimizing receive filters, analog and digital beamformers, common rate allocation, and the sensing beam count. To address uncertainty in sensing beam allocation, a rank-zero solution reconstruction method demonstrates that dedicated sensing beams are unnecessary for NF multi-target detection. A penalty dual decomposition (PDD)-based double-loop algorithm is introduced, employing weighted minimum mean-squared error (WMMSE) and quadratic transforms to reformulate communication and sensing rates. Simulations reveal that the proposed scheme: 1) achieves performance comparable to fully digital beamforming with fewer RF chains, (2) maintains NF multi-target detection without compromising communication rates, and 3) significantly outperforms conventional multiple access schemes and far-field ISAC systems.

Problem

• Optimizing hybrid beamforming for near-field ISAC with RSMA
• Maximizing communication rate while ensuring multi-target sensing performance
• Eliminating dedicated sensing beams in near-field multi-target detection

Innovation

• Hybrid analog-digital beamforming for NF-ISAC
• RSMA enhances interference management flexibility
• Rank-zero solution eliminates dedicated sensing beams