Low-complexity Q-learning for Energy-aware Small-cell Networks with Integrated Access and Backhaul
An integrated access and backhaul (IAB)-enabled small-cell network commonly utilizes
frequency channels for access and backhaul links, and thus this network has a chance to …
frequency channels for access and backhaul links, and thus this network has a chance to …
EARNEST: Experimental Analysis of RAN Energy with Open-Source Software Tools
The 5G and Beyond (B5G) networks aim to support diverse use cases—extremely low
latency, high data rates, and dense user connectivity. However, meeting these use cases …
latency, high data rates, and dense user connectivity. However, meeting these use cases …
Federated learning for efficient spectrum allocation in open RAN
In the evolving landscape of Open Radio Access Networks (Open RAN), the dynamic and
unpredictable nature of network conditions presents significant challenges for traditional …
unpredictable nature of network conditions presents significant challenges for traditional …
Strategies for minimization of energy consumption in data Centers
S Friis, LMP Larsen, SR Ruepp - Twenty-Second International …, 2023 - orbit.dtu.dk
Abstract Data Centers (DCs) consume a significant amount of energy, making overall energy
consumption a major concern. The scale of a DC affects its energy efficiency, with larger …
consumption a major concern. The scale of a DC affects its energy efficiency, with larger …
Cost dynamics of converged optical-wireless networks: enabling low-latency xRANs through a reconfigurable hybrid split
M Nooruzzaman, X Fernando - Journal of Optical Communications …, 2024 - opg.optica.org
Future 6G and beyond wireless networks are anticipated to be highly versatile,
accommodating a wide range of services, from ultra-low-latency applications like …
accommodating a wide range of services, from ultra-low-latency applications like …
A supervised active learning method for identifying critical nodes in IoT networks
The energy efficiency of wireless sensor networks (WSNs) as a key feature of the Internet of
Things (IoT) and fifth-generation (5G) mobile networks is determined by several key …
Things (IoT) and fifth-generation (5G) mobile networks is determined by several key …
Maximizing throughput and energy efficiency in 6G based on phone user clustering enabled UAV assisted downlink hybrid multiple access HetNet
U Ghafoor, T Ashraf - Telecommunication Systems, 2024 - Springer
The surge in technology is driving demands for real-time interactive applications and high-
speed transmissions, necessitating improved network throughput and energy efficiency (EE) …
speed transmissions, necessitating improved network throughput and energy efficiency (EE) …
A Multi-Agent Proximal Policy Optimized Joint Mechanism in mmWave HetNets With CoMP Towards Energy Efficiency Maximization
A Lotfolahi, HW Ferng - IEEE Transactions on Green …, 2023 - ieeexplore.ieee.org
A novel cluster-based traffic offloading and user association (UA) algorithm alongside a
multi-agent deep reinforcement learning (DRL) based base station (BS) activation …
multi-agent deep reinforcement learning (DRL) based base station (BS) activation …
An Intelligent Bayesian Inference Based Learning Automaton Approach for Traffic Management in Radio Access Network
Wireless cellular networks can be used to establish machine-to-machine (M2M)
connections, enabling the use of the Internet of Things (IoT). Access class barring (ACB) is …
connections, enabling the use of the Internet of Things (IoT). Access class barring (ACB) is …
Toward Energy-Efficient Massive MIMO: Graph Neural Network Precoding for Mitigating Non-Linear PA Distortion
Massive MIMO systems are typically designed assuming linear power amplifiers (PAs).
However, PAs are most energy efficient close to saturation, where non-linear distortion …
However, PAs are most energy efficient close to saturation, where non-linear distortion …