Radio Resource Management

Radio Resource Management (RRM) optimizes the allocation of limited wireless resources (bandwidth, power, etc.) to maximize network efficiency and user experience. Current research heavily utilizes machine learning, particularly reinforcement learning (RL) and graph neural networks (GNNs), often employing offline or hybrid training methods to address the challenges of real-world deployment and dynamic environments. These advancements aim to improve network performance, address security concerns like application fingerprinting through side channels, and enable efficient resource sharing in emerging technologies like O-RAN and cell-free networks, ultimately impacting the design and performance of future wireless systems.

Papers

September 25, 2024

Offline and Distributional Reinforcement Learning for Radio Resource Management
Eslam Eldeeb, Hirley Alves
Reinforcement Learning Distributional Reinforcement Learning Action Free Offline Stochastic Environment Radio Resource Management Future Network

July 10, 2024

Characterizing Encrypted Application Traffic through Cellular Radio Interface Protocol
Md Ruman Islam, Raja Hasnain Anwar, Spyridon Mastorakis, Muhammad Taqi Raza
Side Channel Cellular Network Pervasive Computing G Wireless Radio Resource Management Encrypted Traffic

June 7, 2024

Online Frequency Scheduling by Learning Parallel Actions
Anastasios Giovanidis, Mathieu Leconte, Sabrine Aroua, Tor Kvernvik, David Sandberg
Multiple Input Multiple Output Deep Q Learning Parallel Training Radio Resource Management Priority Driven Scheduling Enhancement

May 13, 2024

Radio Resource Management and Path Planning in Intelligent Transportation Systems via Reinforcement Learning for Environmental Sustainability
S. Norouzi, N. Azarasa, M. R. Abedi, N. Mokari, S. E. Seyedabrishami, H. Saeedi, E. A. Jorswieck
Reinforcement Learning Path Planning Intelligent Transportation System Radio Resource Management Vehicle to Infrastructure Vehicle to Everything Environment Optimization C V2x

April 14, 2024

ProSAS: An O-RAN Approach to Spectrum Sharing between NR and LTE
Sneihil Gopal, David Griffith, Richard A. Rouil, Chunmei Liu
Radio Access Network Spectrum Sharing Radio Resource Management Spectrum Management LTE WiFi

March 28, 2024

Tiny Graph Neural Networks for Radio Resource Management
Ahmad Ghasemi, Hossein Pishro-Nik
Neural Network Graph Neural Network Resource Allocation Message Passing Graph Neural Network Radio Resource Management

December 16, 2023

Advancing RAN Slicing with Offline Reinforcement Learning
Kun Yang, Shu-ping Yeh, Menglei Zhang, Jerry Sydir, Jing Yang, Cong Shen
Reinforcement Learning Offline Reinforcement Learning Near Optimal Policy Radio Resource Management Radio Access Network Slicing

October 18, 2023

Flexible Payload Configuration for Satellites using Machine Learning
Marcele O. K. Mendonca, Flor G. Ortiz-Gomez, Jorge Querol, Eva Lagunas, Juan A. Vásquez Peralvo, Victor Monzon Baeza, Symeon Chatzinotas, Bjorn Ottersten
Machine Learning Multiple Satellite Radio Resource Management Satellite Communication Heterogeneous Traffic Payload Transmission Probability Model Spectrum Utilization

September 13, 2023

Safe and Accelerated Deep Reinforcement Learning-based O-RAN Slicing: A Hybrid Transfer Learning Approach
Ahmad M. Nagib, Hatem Abou-Zeid, Hossam S. Hassanein
Reinforcement Learning Deep Reinforcement Learning Radio Access Network Radio Resource Management Radio Access Network Slicing

August 22, 2023

Energy-Efficient On-Board Radio Resource Management for Satellite Communications via Neuromorphic Computing
Flor Ortiz, Nicolas Skatchkovsky, Eva Lagunas, Wallace A. Martins, Geoffrey Eappen, Saed Daoud, Osvaldo Simeone, Bipin Rajendran, Symeon Chatzinotas
Neuromorphic Computing Energy Efficient Radio Resource Management Satellite Communication

July 7, 2023

Federated Learning over a Wireless Network: Distributed User Selection through Random Access
Chen Sun, Shiyao Ma, Ce Zheng, Songtao Wu, Tao Cui, Lingjuan Lyu
Preference Feedback Wireless Network Random Access Multiple Access Radio Resource Management User Selection

April 14, 2023

Synergies Between Federated Learning and O-RAN: Towards an Elastic Virtualized Architecture for Multiple Distributed Machine Learning Services
Payam Abdisarabshali, Nicholas Accurso, Filippo Malandra, Weifeng Su, Seyyedali Hosseinalipour
Wireless Network Architecture Design Radio Resource Management Emerging Synergy

December 20, 2022

Cell-Free Data Power Control Via Scalable Multi-Objective Bayesian Optimisation
Sergey S. Tambovskiy, Gábor Fodor, Hugo Tullberg
Bayesian Optimisation Radio Resource Management Spectral Efficiency Multi Objective Bayesian Optimisation Cell Free

December 14, 2022

ENGNN: A General Edge-Update Empowered GNN Architecture for Radio Resource Management in Wireless Networks
Yunqi Wang, Yang Li, Qingjiang Shi, Yik-Chung Wu
Wireless Network Adaptive Beamforming Power Allocation Radio Resource Management Future Wireless Network

November 21, 2022

TinyQMIX: Distributed Access Control for mMTC via Multi-agent Reinforcement Learning
Tien Thanh Le, Yusheng Ji, John C. S Lui
Reinforcement Learning Multi Agent Reinforcement Learning Radio Resource Management Soft QMIX Dynamic Traffic

October 28, 2022

A State-Augmented Approach for Learning Optimal Resource Management Decisions in Wireless Networks
Yiğit Berkay Uslu, Navid NaderiAlizadeh, Mark Eisen, Alejandro Ribeiro
Wireless Network Power Allocation Utility Maximization Radio Resource Management State Augmentation

September 16, 2022

Toward Safe and Accelerated Deep Reinforcement Learning for Next-Generation Wireless Networks
Ahmad M. Nagib, Hatem Abou-zeid, Hossam S. Hassanein
Reinforcement Learning Deep Reinforcement Learning Radio Resource Management Deep Reinforcement Learning Based Next Generation Wireless Network

July 5, 2022

State-Augmented Learnable Algorithms for Resource Management in Wireless Networks
Navid NaderiAlizadeh, Mark Eisen, Alejandro Ribeiro
Wireless Network Resource Management Utility Maximization Radio Resource Management State Augmentation Learning Augmented

April 16, 2022

Cognitive Radio Resource Scheduling using Multi agent QLearning for LTE
Najem N Sirhan, Manel Martinez-Ramon
Radio Resource Management Optimal Scheduling Multi Agent Q Learning Scheduling Algorithm LTE WiFi

March 7, 2022

Learning Resilient Radio Resource Management Policies with Graph Neural Networks
Navid NaderiAlizadeh, Mark Eisen, Alejandro Ribeiro
Graph Neural Network Radio Resource Management Channel Charting Interference Limited Wireless Network Capacity Constraint

Radio Resource Management

Papers

Offline and Distributional Reinforcement Learning for Radio Resource Management

Characterizing Encrypted Application Traffic through Cellular Radio Interface Protocol

Online Frequency Scheduling by Learning Parallel Actions

Radio Resource Management and Path Planning in Intelligent Transportation Systems via Reinforcement Learning for Environmental Sustainability

ProSAS: An O-RAN Approach to Spectrum Sharing between NR and LTE

Tiny Graph Neural Networks for Radio Resource Management

Advancing RAN Slicing with Offline Reinforcement Learning

Flexible Payload Configuration for Satellites using Machine Learning

Safe and Accelerated Deep Reinforcement Learning-based O-RAN Slicing: A Hybrid Transfer Learning Approach

Energy-Efficient On-Board Radio Resource Management for Satellite Communications via Neuromorphic Computing

Federated Learning over a Wireless Network: Distributed User Selection through Random Access

Synergies Between Federated Learning and O-RAN: Towards an Elastic Virtualized Architecture for Multiple Distributed Machine Learning Services

Cell-Free Data Power Control Via Scalable Multi-Objective Bayesian Optimisation

ENGNN: A General Edge-Update Empowered GNN Architecture for Radio Resource Management in Wireless Networks

TinyQMIX: Distributed Access Control for mMTC via Multi-agent Reinforcement Learning

A State-Augmented Approach for Learning Optimal Resource Management Decisions in Wireless Networks

Toward Safe and Accelerated Deep Reinforcement Learning for Next-Generation Wireless Networks

State-Augmented Learnable Algorithms for Resource Management in Wireless Networks

Cognitive Radio Resource Scheduling using Multi agent QLearning for LTE

Learning Resilient Radio Resource Management Policies with Graph Neural Networks