RIS Configuration, Beamformer Design, and Power Control in Single-Cell and Multi-Cell Wireless Networks
arXiv:2103.11165
Abstract
Reconfigurable Intelligent Surfaces (RISs) are recently attracting a wide interest due to their capability of tuning wireless propagation environments in order to increase the system performance of wireless networks. In this paper, a multiuser wireless network assisted by a RIS is studied and resource allocation algorithms are presented for several scenarios. First of all, the problem of channel estimation is considered, and an algorithm that permits separate estimation of the mobile user-to-RIS and RIS-to-base stations components is proposed. Then, for the special case of a single-user system, three possible approaches are shown in order to optimize the Signal-to-Noise Ratio with respect to the beamformer used at the base station and to the RIS phase shifts. Next, for a multiuser system with two cells, assuming channel-matched beamforming, the geometric mean of the downlink Signal-to-Interference plus Noise Ratios across users is maximized with respect to the base stations transmit powers and RIS phase shifts configurations. In this scenario, the RIS is placed at the cell-edge and some users are jointly served by two base stations to increase the system performance. Numerical results show that the proposed procedures are effective and that the RIS brings substantial performance improvements to wireless system.
Accepted for publication on the IEEE Transactions on Cognitive Communications and Networking, special issue on "Intelligent Surfaces for Smart Wireless Communications". arXiv admin note: text overlap with arXiv:2004.08944
References in corpus (4)
- MISO Wireless Communication Systems via Intelligent Reflecting Surfaces
- Joint Active and Passive Beamforming for Intelligent Reflecting Surface-Assisted Massive MIMO Systems
- Channel Estimation for Wireless Communication Systems Assisted by Large Intelligent Surfaces
- An Efficient CSI Acquisition Method for Intelligent Reflecting Surface-assisted mmWave Networks