Results 51 to 60 of about 30,726 (232)
Dynamic Bandwidth Allocation in Heterogeneous OFDMA-PONs Featuring Intelligent LTE-A Traffic Queuing [PDF]
, 2014 This work was supported by the ACCORDANCE project, through the 7th ICT Framework Programme. This is an Accepted Manuscript of an article accepted for publication in Journal of Lightwave Technology following peer review.
Kanonakis, Konstantinos +5 more
core +1 more source
IET Communications, Volume 20, Issue 1, January/December 2026.This paper investigates new radio spectrum coexistence mechanisms, leveraging the currently uninhabited 6 GHz bands and aiming for fair coexistence of Wi‐Fi 6 and 5G new radio unlicensed (NR‐U). A novel two‐stage channel contention mechanism is proposed to explore additional spectrum access opportunities which remain unrealized in the existing channel ...
Md Toufiqur Rahman +2 more
wiley +1 more source
Optimization Framework and Graph-Based Approach for Relay-Assisted Bidirectional OFDMA Cellular Networks [PDF]
, 2010 This paper considers a relay-assisted bidirectional cellular network where the base station (BS) communicates with each mobile station (MS) using OFDMA for both uplink and downlink.
Li, Bin +3 more
core +1 more source
DRL‐Based Joint Clustering and Trajectory Optimization for UAV‐Assisted Emergency Networks
IET Communications, Volume 20, Issue 1, January/December 2026.6G is expected to see unprecedented data traffic surges. UAV‐assisted MEC aids emergency communications but faces challenges from dynamic user mobility and heterogeneous tasks. To address these, the proposed KM‐PPO integrates interference‐aware k‐means clustering (for user aggregation and initial UAV deployment) and PPO (for stable policy updates and ...
Ruirui Xu +4 more
wiley +1 more source
A Comparison of Reinforcement Learning Algorithms in Fairness-Oriented OFDMA Schedulers
Information, 2019 Due to large-scale control problems in 5G access networks, the complexity of radio resource management is expected to increase significantly. Reinforcement learning is seen as a promising solution that can enable intelligent decision-making and reduce ...
Ioan-Sorin Comșa +5 more
doaj +1 more source
IET Communications, Volume 20, Issue 1, January/December 2026.Within the framework of integrated space‐air‐ground edge computing networks, this paper investigates the joint optimization of task allocation, user‐UAV association, UAV deployment, and computation resource allocation between UAVs and the LEO satellite.
Tengda Huang, Tao Hu, Di Wu, Wenzhi Zhao
wiley +1 more source
Communication‐Security Co‐Design for Federated Learning in Grant‐Free NOMA IoT Networks
IET Communications, Volume 20, Issue 1, January/December 2026.This article presents SA‐PPO, a Security‐Aware Proximal Policy Optimisation framework for federated learning over grant‐free NOMA (non‐orthogonal multiple access) in IoT networks. By jointly optimising access control, resource allocation, and trust‐weighted aggregation using cross‐layer indicators, SA‐PPO enhances both communication reliability and ...
Emmanuel Atebawone +5 more
wiley +1 more source
Cooperative Interference Control for Spectrum Sharing in OFDMA Cellular Systems
, 2011 This paper studies cooperative schemes for the inter-cell interference control in orthogonal-frequency-divisionmultiple- access (OFDMA) cellular systems.
Da, Bin, Zhang, Rui
core +1 more source
Layered random beamforming OFDMA with fair scheduling algorithms [PDF]
, 2008 This paper presents performance analysis of layered random beamforming (LRB) - MIMO-OFDMA employing various resource scheduling algorithms with feedback reduction in a realistic outdoor environment.
Armour, SMD +4 more
core +3 more sources
Federated Split Learning for Large Language Models With RSMA
IET Communications, Volume 20, Issue 1, January/December 2026.This study proposes a federated split learning framework for large language models (FedsLLM) integrated with rate‐splitting multiple access (RSMA), aimed at enhancing the efffciency and privacy of LLM training in wireless communication systems. ABSTRACT This study proposes a federated split learning framework for large language models (FedsLLM ...
Jianxin Dai +6 more
wiley +1 more source