Fundamental Limits of Intelligent Reflecting Surface Aided Multiuser Broadcast Channel
Guangji Chen, Qingqing Wu

TL;DR
This paper characterizes the fundamental capacity limits of IRS-aided multi-user broadcast channels, demonstrating how IRS can reduce the need for complex beamforming and approach optimal sum-rate performance.
Contribution
It introduces a capacity region characterization framework for IRS-aided MISO broadcast channels and analyzes the impact of IRS on beamforming strategies and achievable rates.
Findings
Dynamic beamforming enlarges the rate region when IRS phase-shifts are limited.
IRS can reduce the necessity for complex beamforming schemes.
IRS-assisted ZF can approach DPC sum-rate with large IRS.
Abstract
Intelligent reflecting surface (IRS) has recently received significant attention in wireless networks owing to its ability to smartly control the wireless propagation through passive reflection. Although prior works have employed the IRS to enhance the system performance under various setups, the fundamental capacity limits of an IRS aided multi-antenna multi-user system have not yet been characterized. Motivated by this, we investigate an IRS aided multiple-input single-output (MISO) broadcast channel by considering the capacity-achieving dirty paper coding (DPC) scheme and dynamic beamforming configurations. We first propose a bisection based framework to characterize its capacity region by optimally solving the sum-rate maximization problem under a set of rate constraints, which is also applicable to characterize the achievable rate region with the zero-forcing (ZF) scheme.…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Antenna Design and Analysis · Underwater Vehicles and Communication Systems
