发表机构
University of Oulu; Korea University; Korea Advanced Institute of Science and Technology（奥卢大学; 高丽大学; 韩国科学技术院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对大规模MIMO ISAC系统，提出三混合波束成形架构，通过加权多目标优化联合提升通信和速率与感知互信息，以低复杂度迭代算法求解，显著提高能效，仅轻微牺牲性能。
AI 中文摘要
三混合多输入多输出（MIMO）架构已被提出作为一种有前景的解决方案，通过在混合波束成形（HBF）系统中用低成本动态超表面天线（DMAs）替代传统天线阵列，实现大规模天线阵列中的节能通信系统。在本工作中，我们研究了基于三混合波束成形（tri-HBF）架构的集成感知与通信（ISAC）系统的波束成形设计，目标是联合提升通信和速率与感知和互信息。具体而言，我们构建了一个加权多目标优化问题，在总发射功率约束和tri-HBF架构固有的物理限制下，平衡通信吞吐量与感知互信息。通过利用问题结构，我们开发了一种具有闭式更新的高效迭代算法，以低复杂度求解该非凸优化问题。提供了数值结果以评估所提出的tri-HBF架构在不同设置下的性能。结果表明，与传统的混合MIMO和仅DMA配置相比，所提出的tri-HBF架构能够实现能效（EE）的显著提升，代价是求和速率和感知互信息的轻微下降。
英文摘要
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.
Comments13 pages, journal extention of our previous conference work
