Energy Efficiency Maximization in RIS-Aided Cell-Free Network with Limited Backhaul
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Abstract (arXiv)
Integrating the reconfigurable intelligent surface in a cell-free (RIS-CF) network is an effective solution to improve the capacity and coverage of future wireless systems with low cost and power consumption. The reflecting coefficients of RISs can be programmed to enhance signals received at users. This letter addresses a joint design of transmit beamformers at access points and reflecting coefficients at RISs to maximize the energy efficiency (EE) of RIS-CF networks, taking into account the limited backhaul capacity constraints. Due to a very computationally challenging nonconvex problem, we develop a simple yet efficient alternating descent algorithm for its solution. Numerical results verify that the EE of RIS-CF networks is greatly improved, showing the benefit of using RISs.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Dec 2020.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 0; 2026: 2.
4 papers.
- 2023Digital Twin-Aided Learning for Managing Reconfigurable Intelligent Surface-Assisted, Uplink, User-Centric Cell-Free Systemscited by 3
- 2026Auction-Based RIS Allocation With DRL: Controlling the Cost-Performance Trade-Offcited by 1
- 2022Energy Efficiency Maximization in IRS-Aided Cell-Free Massive MIMO Systemcited by 0
- 2026Cooperative Deep Reinforcement Learning for Fair RIS Allocationcited by 0
- 2026Cooperative Deep Reinforcement Learning for Fair RIS Allocation26 Mar 2026
- 2026Auction-Based RIS Allocation With DRL: Controlling the Cost-Performance Trade-Off18 Feb 2026
- 2023Digital Twin-Aided Learning for Managing Reconfigurable Intelligent Surface-Assisted, Uplink, User-Centric Cell-Free Systems10 Feb 2023
- 2022Energy Efficiency Maximization in IRS-Aided Cell-Free Massive MIMO System24 Dec 2022