Intelligent Reflecting Surface Assisted Massive MIMO Communications
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In a practical massive MIMO (multiple-input multiple-output) system, the number of antennas at a base station (BS) is constrained by the space and cost factors, which limits the throughput gain promised by theoretical analysis. This paper studies the feasibility of adopting intelligent reflecting surface (IRS) for further improving the beamforming gain and throughput of the uplink communications in a massive MIMO system. Specifically, we show that the favorable propagation property for the conventional massive MIMO system without IRS, i.e., the channels of arbitrary two users are orthogonal, no longer holds for the IRS-assisted massive MIMO system, because of the correlated user channels arising from the fact that each IRS element reflects the signals from all the users to the BS via the same channel. As a result, the maximal-ratio combining (MRC) receive beamforming strategy leads to strong inter-user interference and thus low user rates. To tackle this challenge, we propose a novel zero-forcing (ZF) beamforming strategy to efficiently null the interference, under which the user achievable signal-to-interference-plus-noise ratios (SINRs) are characterized in closed-form and shown to be significantly larger than those achieved by the conventional massive MIMO system without IRS. Despite the increased channel estimation overhead and thus reduced data transmission time, numerical results show that the IRS-assisted massive MIMO system can achieve higher throughput compared to its counterpart without IRS thanks to the substantial SINR gain.
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