Tri-Hybrid Beamforming Design for Large-Scale MIMO ISAC Systems

2026-09-17

AI Summary

研究通过设计一种基于三混合波束成形架构的方法，旨在大规模MIMO通感一体系统中同时提高通信速率和感知信息量，以解决能效问题。

Abstract

Tri-hybrid multiple-input multiple-output (MIMO) architectures have been proposed as a promising solution for enabling energy-efficient communications systems in large-scale antenna arrays by replacing conventional antenna arrays in hybrid beamforming (HBF) systems with low-cost dynamic metasurface antennas (DMAs). In this work, we investigate beamforming design for integrated sensing and communications (ISAC) systems based on tri-HBF architectures, with the objective of jointly enhancing the communications sum rate and sensing sum mutual information. Specifically, we formulate a weighted multi-objective optimization problem that balances communications throughput and sensing mutual information, subject to a total transmit power consumption constraint and the physical limitations inherent to tri-HBF architectures. By exploiting the problem structure, we develop an efficient iterative algorithm with closed-form updates to solve the non-convex optimization problem with low complexity. Numerical results are provided to evaluate the performance of the proposed tri-HBF architecture in various setups. The results demonstrate that the proposed tri-HBF architecture can achieve significant improvement in energy efficiency (EE) compared to the conventional hybrid MIMO and DMA-only configurations, at the cost of minor degradations in sum rate and sensing mutual information.

Problem

• Tri-Hybrid Beamforming
• MIMO ISAC Systems
• Sum Rate
• Sensing Mutual Information
• Energy Efficiency

Innovation

• Tri-hybrid Beamforming
• Dynamic Metasurface Antennas
• Integrated Sensing and Communications
• Energy Efficiency
• Multi-objective Optimization