[Paper Review] Large Intelligent Surface Assisted MIMO Communications

Qurrat-Ul-Ain Nadeem, Abla Kammoun+3 more|arXiv (Cornell University)|Mar 19, 2019

Advanced Wireless Communication TechnologiesEngineering65 citations

TL;DR

This paper proposes a large intelligent surface (LIS)-assisted MIMO system where a multi-antenna base station communicates with single-antenna users via a passive LIS that reconfigures wireless propagation. It derives optimal linear precoding to maximize the minimum SINR, showing that LIS can achieve Massive MIMO-like spectral efficiency with far fewer active antennas, drastically reducing energy consumption.

ABSTRACT

This work focuses on the downlink of a single-cell multi-user (MU) system in which a base station (BS) equipped with $M$ antennas communicates with $K$ single-antenna users through a large intelligent surface (LIS) installed in the line-of-sight (LoS) of the BS. LIS is envisioned to offer unprecedented massive multiple-input multiple-output (MIMO) like gains by utilizing $N$ passive reflecting elements that induce phase shifts on the impinging electromagnetic waves to smartly reconfigure the signal propagation. We study the minimum signal-to-interference-plus-noise ratio (SINR) achieved by the optimal linear precoder (OLP), that maximizes the minimum SINR subject to a given power constraint for any given LIS phase matrix, for the cases where the LoS channel matrix between the BS and the LIS is of rank-one and of full-rank. In the former scenario, the minimum SINR is bounded by a quantity that goes to zero with $K > 1$. For the high-rank scenario, we develop accurate deterministic approximations for the parameters of the asymptotically OLP, which are then utilized to optimize the LIS phase matrix. Simulation results show that the LIS-assisted system can offer Massive MIMO like gains with a much fewer number of active antennas, thereby significantly reducing the energy consumption at the BS.

Motivation & Objective

• To investigate the performance limits of LIS-assisted downlink MIMO systems in terms of minimum SINR under power constraints.
• To analyze the impact of LIS phase shifts on system spectral efficiency and interference management.
• To develop deterministic approximations for optimal precoding in high-rank LoS channel scenarios.
• To optimize the LIS phase matrix to maximize the minimum user SINR.
• To demonstrate that LIS can achieve Massive MIMO-like performance with significantly reduced active antenna count and energy consumption.

Proposed method

• Formulates the downlink MU-MIMO system with a base station (M antennas), K single-antenna users, and a large intelligent surface (N passive reflecting elements).
• Models the LIS as a passive array that applies controllable phase shifts to reflect signals, enabling smart propagation control.
• Analyzes two channel rank cases: rank-one (LoS-dominated) and full-rank (rich scattering) between BS and LIS.
• Derives the optimal linear precoder (OLP) that maximizes the minimum SINR under a total transmit power constraint.
• Develops accurate deterministic equivalents for the asymptotic OLP parameters in the high-rank scenario using random matrix theory.
• Uses these approximations to optimize the LIS phase matrix to enhance the worst-case user SINR.

Experimental results

Research questions

• RQ1 What is the fundamental limit on the minimum SINR in an LIS-assisted MU-MIMO system when the BS-LIS channel is rank-one?
• RQ2 How does the system performance scale with the number of users K when the BS-LIS channel is rank-one?
• RQ3 Can deterministic approximations of the optimal precoder be derived in the high-rank BS-LIS channel case?
• RQ4 How can the LIS phase shifts be optimized to maximize the minimum user SINR in the high-rank scenario?
• RQ5 To what extent can LIS achieve Massive MIMO-like spectral efficiency with fewer active antennas?

Key findings

• In the rank-one BS-LIS channel case, the minimum SINR is bounded by a value that approaches zero as the number of users K exceeds one.
• For high-rank BS-LIS channels, the proposed deterministic approximations of the optimal precoder parameters are highly accurate in asymptotic regimes.
• The optimized LIS phase matrix significantly enhances the worst-case user SINR, enabling robust multi-user communication.
• Simulation results confirm that the LIS-assisted system achieves spectral efficiency comparable to Massive MIMO but with a much smaller number of active antennas at the base station.
• The system achieves substantial energy savings at the base station due to the use of passive reflecting elements instead of active RF chains.