[Paper Review] Beyond Cell-free MIMO: Energy Efficient Reconfigurable Intelligent Surface Aided Cell-free MIMO Communications

Yutong Zhang, Boya Di+4 more|arXiv (Cornell University)|Nov 17, 2020

Advanced Wireless Communication Technologies33 references7 citations

TL;DR

This paper proposes a reconfigurable intelligent surface (RIS)-assisted cell-free MIMO system to enhance energy efficiency by leveraging RISs for low-cost signal reflection and beamforming. By combining digital beamforming at base stations with RIS-based analog beamforming, the system maximizes energy efficiency through an iterative algorithm, showing that optimal performance depends critically on RIS number and size, with significant gains over conventional cell-free systems.

ABSTRACT

Cell-free systems can effectively eliminate the inter-cell interference by enabling multiple base stations (BSs) to cooperatively serve users without cell boundaries at the expense of high costs of hardware and power sources due to the large-scale deployment of BSs. To tackle this issue, the low-cost reconfigurable intelligent surface (RIS) can serve as a promising technique to improve the energy efficiency of cell-free systems. In this paper, we consider an RIS aided cell-free MIMO system where multiple RISs are deployed around BSs and users to create favorable propagation conditions via reconfigurable reflections in a low-cost way, thereby enhancing cell-free MIMO communications. To maximize the energy efficiency, a hybrid beamforming (HBF) scheme consisting of the digital beamforming at BSs and the RIS-based analog beamforming is proposed. The energy efficiency maximization problem is formulated and an iterative algorithm is designed to solve this problem. The impact of the transmit power, the number of RIS, and the RIS size on energy efficiency are investigated. Both theoretical analysis and simulation results reveal that the optimal energy efficiency depends on the numbers of RISs and the RIS size. Numerical evaluations also show that the proposed system can achieve a higher energy efficiency than conventional ones.

Motivation & Objective

• To address the high energy cost of traditional cell-free MIMO systems due to dense base station deployment.
• To improve energy efficiency by integrating low-cost reconfigurable intelligent surfaces (RISs) into cell-free MIMO architectures.
• To jointly optimize digital beamforming at base stations and phase shifts at RISs for energy efficiency maximization.
• To analyze the impact of RIS number, size, and transmit power on system energy efficiency.

Proposed method

• Proposes a hybrid beamforming (HBF) architecture combining digital beamforming at base stations and RIS-based analog beamforming.
• Models the system with multiple RISs deployed around base stations and users to create favorable propagation via reconfigurable reflections.
• Formulates an energy efficiency maximization problem involving transmit power, RIS configuration, and hardware constraints.
• Designs an iterative algorithm to jointly optimize digital beamformers and RIS phase shifts under practical hardware and power constraints.
• Uses statistical channel models and approximations to derive tractable expressions for sum rate and energy efficiency.
• Applies Jensen’s inequality and asymptotic analysis to prove the negativity of key terms in the energy efficiency derivative, enabling convergence analysis.

Experimental results

Research questions

• RQ1 How does the integration of multiple RISs affect the energy efficiency of cell-free MIMO systems?
• RQ2 What is the optimal number of RISs and RIS size for maximizing energy efficiency in a cell-free MIMO setup?
• RQ3 How does the proposed hybrid beamforming scheme compare to conventional cell-free MIMO in terms of energy efficiency?
• RQ4 What is the impact of transmit power and RIS hardware parameters on system performance?

Key findings

• The optimal energy efficiency is highly sensitive to both the number of RISs and the size of each RIS, with a non-monotonic relationship.
• When the RIS size is small, energy efficiency increases with RIS size, but eventually decreases due to growing RIS hardware power consumption.
• The system achieves higher energy efficiency than conventional cell-free MIMO, especially when the RIS-to-BS power ratio is favorable.
• Theoretical analysis confirms that the energy efficiency derivative is positive for small RIS sizes under the condition that $\mathcal{P}_s / (M \cdot P_R) > \ln(NP_T / (k\sigma^2))$, indicating increasing efficiency before saturation.
• Numerical results validate that the proposed algorithm converges and significantly improves energy efficiency compared to baseline schemes.