Massive MIMO Communication with Intelligent Reflecting Surface
Zhaorui Wang, Liang Liu, Shuowen Zhang, and Shuguang Cui

TL;DR
This paper explores the integration of intelligent reflecting surfaces (IRSs) into massive MIMO systems to enhance user performance, proposing a low-overhead protocol and analyzing asymptotic behavior for effective channel estimation and rate optimization.
Contribution
It introduces a novel IRS-assisted massive MIMO protocol that reduces training overhead and provides a theoretical analysis of user rates with fixed channel covariance matrices.
Findings
Channel hardening and favorable propagation still hold with IRS.
Satisfactory user rates achievable with simple beamforming.
Proposed low-complexity IRS reflection optimization algorithm.
Abstract
This paper studies the feasibility of deploying intelligent reflecting surfaces (IRSs) in massive MIMO (multiple-input multiple-output) systems to improve the performance of users in the service dead zone. To reduce the channel training overhead, we advocate a novel protocol for the uplink communication in the IRS-assisted massive MIMO systems. Under this protocol, the IRS reflection coefficients are optimized based on the channel covariance matrices, which are generally fixed for many coherence blocks, to boost the long-term performance. Then, given the IRS reflecting coefficients, the BS beamforming vectors are designed in each coherence block based on the effective channel of each user, which is the superposition of its direct and reflected user-IRS-BS channels, to improve the instantaneous performance. Since merely the user effective channels are estimated in each coherence block,…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Satellite Communication Systems · Indoor and Outdoor Localization Technologies
