Radio Environment Map for Energy-Efficient User-Centric Cell-Free M-MIMO Network

2026-04-17

AI Summary

This study addresses the low energy efficiency in service cluster formation within user-centric cell-free massive MIMO networks. To tackle this issue, the paper introduces, for the first time, a radio environment map (REM) into the cluster formation mechanism, integrating user location information with a model of power amplifier nonlinearities. Building upon this integration, the authors propose an energy-efficiency-driven access point selection and cluster optimization method. By accurately characterizing spatial channel conditions and hardware impairments, the approach dynamically constructs high-energy-efficiency service clusters that maintain coverage performance while substantially improving system-wide energy efficiency. Simulation results demonstrate that the proposed method achieves up to a 19% gain in energy efficiency compared to conventional schemes.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Clustering
• Search and Optimization: Applications

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

This paper proposes a Radio Environment Map (REM) for energy-efficient (EE) serving cluster formulation in a user-centric cell-free network. By incorporating the location of the user and the characteristics of the power amplifier, REM enables EE to be improved by up to 19%.

Problem

• Radio Environment Map
• energy-efficient
• cell-free M-MIMO
• serving cluster
• user-centric

Innovation

• Radio Environment Map
• energy efficiency
• cell-free M-MIMO
• user-centric
• serving cluster