Problem
Research questions and friction points this paper is trying to address.
Smart Reflecting Surface (IRS)
Energy Consumption
Distributed Multi-Input Multi-Output (D-MIMO)
Static IRS Meets Distributed MIMO: A New Architecture for Dynamic Beamforming
🤖 AI Summary
Dynamic intelligent reflecting surfaces (IRSs) in distributed multiple-input multiple-output (D-MIMO) systems incur high energy consumption and complex real-time control overhead.
Method: This paper proposes a novel static-IRS-assisted D-MIMO architecture: IRS reflection coefficients are fixed offline, while access points (APs) collaboratively serve user subregions to achieve wide-area coverage enhancement with low operational overhead. A two-stage algorithm jointly optimizes static IRS beamforming and AP–subregion association, maximizing the worst-case channel power to exploit spatial diversity.
Contribution/Results: We theoretically establish, for the first time, that static IRSs can still achieve asymptotic square-power gain; we further quantify the performance gap between static and dynamic IRSs. Simulation results demonstrate that, without any real-time IRS reconfiguration, the proposed scheme significantly improves the global worst-case received power—approaching the performance of dynamic IRSs—while drastically reducing signaling and computational complexity.
📝 Abstract
Intelligent reflecting surface (IRS) has been considered as a revolutionary technology to enhance the wireless communication performance. To cater for multiple mobile users, adjusting IRS beamforming patterns over time, i.e., dynamic IRS beamforming (DIBF), is generally needed for achieving satisfactory performance, which results in high controlling power consumption and overhead. To avoid such cost, we propose a new architecture based on the static regulated IRS for wireless coverage enhancement, where the principle of distributed multiple-input multiple-output (D-MIMO) is integrated into the system to exploite the diversity of spatial directions provided by multiple access points (APs). For this new D-MIMO empowered static IRS architecture, the total target area is partitioned into several subareas and each subarea is served by an assigned AP. We consider to maximize the worst-case received power over all locations in the target area by jointly optimizing a single set of IRS beamforming pattern and AP-subarea association. Then, a two-step algorithm is proposed to obtain its high-quality solution. Theoretical analysis unveils that the fundamental squared power gain can still be achieved over all locations in the target area. The performance gap relative to the DIBF scheme is also analytically quantified. Numerical results validate our theoretical findings and demonstrate the effectiveness of our proposed design over benchmark schemes.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Intelligent Reflecting Surface (IRS)
Distributed Multiple-Input Multiple-Output (D-MIMO)
Two-step Optimization Algorithm
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