Two-Timescale Design for Reconfigurable Intelligent Surface-Aided Massive MIMO Systems with Imperfect CSI

Abstract

This paper investigates the two-timescale transmission design for reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) systems, where the beamforming at the base station (BS) is adapted to the rapidly-changing instantaneous channel state information (CSI), while the passive beamforming at the RIS is adapted to the slowly-changing statistical CSI. Specifically, we first propose a linear minimum mean square error (LMMSE) estimator to obtain the aggregated channel from the users to the BS in each channel coherence interval. Based on the estimated channel, we apply the low-complexity maximal ratio combining (MRC) beamforming at the BS, and then derive the ergodic achievable rate in a closed form expression. To draw design insights, we perform a detailed theoretical analysis departing from the derived ergodic achievable rate. If the BS-RIS channel is Rician distributed, we prove that the transmit power can be scaled proportionally to $1/M$, as the number of BS antennas, $M$, grows to infinity while maintaining a non-zero rate. If the BS-RIS channel is Rayleigh distributed, the transmit power can be scaled either proportionally to $1/\sqrt{M}$ as $M$ grows large, or proportionally to $1/N$ as the number of reflecting elements, $N$, grows large, while still maintaining a non-zero rate. By capitalizing on the derived expression of the data rate under the statistical knowledge of the CSI, we maximize the minimum user rate by designing the passive beamforming at the RIS. Numerical results confirm that, even in the presence of imperfect CSI, the integration of an RIS in massive MIMO systems results in promising performance gains. In addition, the obtained results reveal that it is favorable to place the RIS close to the users rather than close to the BS.

arXiv commentRevision in IEEE TIT. Keywords: Reconfigurable Intelligent Surface, Intelligent Reflecting Surface, Massive MIMO, Channel estimation, etc

References in corpus (11)

• Wireless Communications with Reconfigurable Intelligent Surface: Path Loss Modeling and Experimental Measurement
• Power Scaling of Uplink Massive MIMO Systems with Arbitrary-Rank Channel Means
• A Framework of Robust Transmission Design for IRS-aided MISO Communications with Imperfect Cascaded Channels
• Intelligent Reflecting Surface Enhanced Wireless Network: Two-timescale Beamforming Optimization
• Intelligent Reflecting Surface Aided MIMO Broadcasting for Simultaneous Wireless Information and Power Transfer
• Massive MIMO with Spatially Correlated Rician Fading Channels
• Joint Transceiver and Large Intelligent Surface Design for Massive MIMO MmWave Systems
• Moments and Absolute Moments of the Normal Distribution
• Two-timescale Beamforming Optimization for Intelligent Reflecting Surface Aided Multiuser Communication with QoS Constraints
• Intelligent Reflecting Surfaces: Sum-Rate Optimization Based on Statistical CSI
• Reconfigurable Intelligent Surface-Aided MISO Systems with Statistical CSI: Channel Estimation, Analysis and Optimization

Cited by in corpus (2)

• On the Maximum Achievable Sum-rate of the RIS-aided MIMO Broadcast Channel
• Reconfigurable Intelligent Surface-Aided MISO Systems with Statistical CSI: Channel Estimation, Analysis and Optimization