MIMO Assisted Networks Relying on Intelligent Reflective Surfaces
arXiv:1910.00959
Abstract
Intelligent reflective surfaces (IRSs) are invoked for improving both spectral efficiency (SE) and energy efficiency (EE). Specifically, an IRS-aided multiple-input multiple-output network is considered, where the performance of randomly roaming users is analyzed by utilizing stochastic geometry tools. As such, to distinguish the superposed signals at each user, the passive beamforming weight at the IRSs and detection weight vectors at the users are jointly designed. As a benefit, by adopting a zero-forcing-based design, the intra-cell interference imposed by the IRS can be suppressed. In order to evaluate the performance of the proposed network, we first derive the approximated channel statistics in the high signal-to-noise-ratio (SNR) regime. Then, we derive the closed-form expressions both for the outage probability and for the ergodic rate of users. Both the high-SNR slopes of ergodic rate and the diversity orders of outage probability are derived for gleaning further insights. The network's SE and EE are also derived. Our numerical results are provided to confirm that: i) the high-SNR slope of the proposed network is one; ii) the SE and EE can be significantly enhanced by increasing the number of IRS elements.
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Cited by in corpus (8)
- RIS-Assisted Coverage Enhancement in Millimeter-Wave Cellular Networks
- Reconfigurable Intelligent Surfaces Aided Multi-Cell NOMA Networks: A Stochastic Geometry Model
- RIS Enhanced Massive Non-orthogonal Multiple Access Networks: Deployment and Passive Beamforming Design
- Modeling RIS Empowered Outdoor-to-Indoor Communication in mmWave Cellular Networks
- Physical Layer Security Enhancement With Reconfigurable Intelligent Surface-Aided Networks
- Modeling and Coverage Analysis for RIS-aided NOMA Transmissions in Heterogeneous Networks
- Multi-User Opportunistic Beamforming using Reconfigurable Surfaces
- Passive Beamforming Design for Intelligent Reflecting Surface Assisted MIMO Systems