Base Station

Base stations (BSs) are the fundamental infrastructure of cellular networks, with the primary objective of providing reliable wireless communication to users. Current research focuses on optimizing BS energy efficiency, deployment strategies (including using UAVs and AI-driven siting), and resource allocation through machine learning models like neural networks, reinforcement learning, and federated learning. These advancements aim to improve network performance, reduce operational costs, and enhance the overall sustainability of next-generation cellular networks.

Papers

February 17, 2022

UAV Base Station Trajectory Optimization Based on Reinforcement Learning in Post-disaster Search and Rescue Operations
Shiye Zhao, Kaoru Ota, Mianxiong Dong
Reinforcement Learning Unmanned Aerial Vehicle Q Learning Various Fast Moving Drone Search and Rescue Base Station

February 4, 2022

5G Network on Wings: A Deep Reinforcement Learning Approach to the UAV-based Integrated Access and Backhaul
Hongyi Zhang, Zhiqiang Qi, Jingya Li, Anders Aronsson, Jan Bosch, Helena Holmström Olsson
Unmanned Aerial Vehicle Deep Reinforcement Learning Approach G Network Multi Drone Base Station Dual Purpose WING Aerial Network Backhaul Network

December 29, 2021

Altitude Optimization of UAV Base Stations from Satellite Images Using Deep Neural Network
Ibrahim Shoer, Bahadir K. Gunturk, Hasan F. Ates, Tuncer Baykas
Deep Neural Network Unmanned Aerial Vehicle Satellite Image Base Station Path Loss Altitude Control

December 21, 2021

Aerial Base Station Positioning and Power Control for Securing Communications: A Deep Q-Network Approach
Aly Sabri Abdalla, Ali Behfarnia, Vuk Marojevic
Reinforcement Learning Q Learning Deep Q Network Physical Layer Base Station Power Control Secure Communication

December 14, 2021

Autonomous Navigation and Configuration of Integrated Access Backhauling for UAV Base Station Using Reinforcement Learning
Hongyi Zhang, Jingya Li, Zhiqiang Qi, Xingqin Lin, Anders Aronsson, Jan Bosch, Helena Holmström Olsson
Reinforcement Learning Autonomous Navigation Mobile Network Cellular Network Base Station System Configuration Safety Critical Domain Backhaul Network

Base Station

Papers

UAV Base Station Trajectory Optimization Based on Reinforcement Learning in Post-disaster Search and Rescue Operations

5G Network on Wings: A Deep Reinforcement Learning Approach to the UAV-based Integrated Access and Backhaul

Altitude Optimization of UAV Base Stations from Satellite Images Using Deep Neural Network

Aerial Base Station Positioning and Power Control for Securing Communications: A Deep Q-Network Approach

Autonomous Navigation and Configuration of Integrated Access Backhauling for UAV Base Station Using Reinforcement Learning