Technology Category
Planning, Routing, and Scheduling: Optimization of Spatio-temporal SystemsConstraint Satisfaction and Optimization: Distributed CSP/OptimizationSearch and Optimization: Mixed Discrete/Continuous Search
Energy-Aware Resource Allocation for Multi-Operator Cell-Free Massive MIMO in V-CRAN Architectures
🤖 AI Summary
This work addresses the high energy consumption of cell-free massive MIMO systems in multi-operator virtualized cloud radio access networks (V-CRANs). To minimize the maximum total power consumption (max-TPC) across operators, we propose an energy-aware joint resource allocation framework. Methodologically, we formulate a mixed-integer programming (MIP) model that jointly optimizes access point selection, user equipment association, cloud resource allocation, and user–operator assignment. A key innovation is the introduction of a flexible cross-operator user assignment mechanism, enabling coordinated scheduling of heterogeneous resources. Simulation results demonstrate that the proposed scheme significantly reduces the system’s max-TPC and improves overall energy efficiency. The framework provides a scalable, end-to-end optimization approach for green multi-operator V-CRAN deployment.
Technology Category
Application Category
📝 Abstract
Cell-free massive multiple-input multiple-output (MIMO) implemented in virtualized cloud radio access networks (V-CRAN) has emerged as a promising architecture to enhance spectral efficiency (SE), network flexibility, and energy efficiency (EE) in next-generation wireless systems. In this work, we develop a holistic optimization framework for the efficient deployment of cell-free massive MIMO in V-CRAN with multiple mobile network operators (MNOs). Specifically, we formulate a set of mixed-integer programming (MIP) models to jointly optimize access point (AP) selection, user equipment (UE) association, cloud resource allocation, and MNO assignment while minimizing the maximum total power consumption (TPC) across MNOs. We consider two different scenarios based on whether UEs can be assigned to arbitrary MNOs or not. The numerical results demonstrate the impact of different deployment assumptions on power consumption, highlighting that flexible UE-MNO assignment significantly reduces TPC. The findings provide key insights into optimizing resource management in cell-free massive MIMO V-CRAN, paving the way for energy-efficient wireless network implementations.
Problem
Research questions and friction points this paper is trying to address.
Optimize AP selection and UE association in V-CRAN
Minimize total power consumption across MNOs
Evaluate flexible UE-MNO assignment impact on energy
Innovation
Methods, ideas, or system contributions that make the work stand out.
Joint optimization of AP selection and UE association
MIP models for cloud resource allocation
Flexible UE-MNO assignment reduces power
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2024-03-28Conference on Computer Communications WorkshopsCitations: 0
