Resource allocation trends for ultra dense networks in 5G and beyond networks: A classification and comprehensive survey

N Sharma, K Kumar - Physical Communication, 2021‏ - Elsevier
With an exaggerating upsurge in mobile data traffic, the wireless networks are confronted
with a subtle task of enhancing their network capacity. The shortage of spectrum resources …

Deep Learning Based Energy, Spectrum, and SINR-Margin Tradeoff Enabled Resource Allocation Strategies for 6G

V Pathak, R Chethan, RJ Pandya, S Iyer… - IEEE Access, 2024‏ - ieeexplore.ieee.org
In the rapidly evolving landscape of wireless communication systems, the forthcoming sixth-
generation technology aims to achieve remarkable milestones, including ultra-high data …

Federated learning for resource allocation in vehicular edge computing-enabled moving small cell networks

S Zafar, S Jangsher, A Zafar - Vehicular Communications, 2024‏ - Elsevier
Moving networks comprising of moving small cells (MoSCs) is an emerging technology that
provide ubiquitous connectivity to the cellular users in vehicular environment. MoSCs are …

Energy and spectrum efficient cell switch-off with channel and power allocation in ultra-dense networks: A deep reinforcement learning approach

Z Rezaei, BS Ghahfarokhi - Computer Networks, 2023‏ - Elsevier
The high density of small cells in the Ultra-Dense Network (UDN) has increased the capacity
and the coverage of Fifth Generation (5G) cellular networks. However, with increasing the …

Coexistence scheme for uncoordinated LTE and WiFi networks using experience replay based Q-learning

M Girmay, V Maglogiannis, D Naudts, A Shahid… - Sensors, 2021‏ - mdpi.com
Nowadays, broadband applications that use the licensed spectrum of the cellular network
are growing fast. For this reason, Long-Term Evolution-Unlicensed (LTE-U) technology is …

Energy efficiency and throughput optimization in 5g heterogeneous networks

R Arshad, M Farooq-i-Azam, R Muzzammel, A Ghani… - Electronics, 2023‏ - mdpi.com
Device-to-device communication offers a promising technology for the 5G network that aims
to enhance the data rate, reduce latency and cost, improve energy efficiency, and provide …

Machine learning enabled Wi-Fi saturation sensing for fair coexistence in unlicensed spectrum

M Girmay, A Shahid, V Maglogiannis, D Naudts… - IEEE …, 2021‏ - ieeexplore.ieee.org
In the past few years, machine learning (ML) techniques have been extensively applied to
provide efficient solutions to complex wireless network problems. As such, Convolutional …

Energy efficient train-ground mmWave mobile relay system for high speed railways

L Wang, B Ai, Y Niu, Z Zhong, S Mao… - IEEE Transactions …, 2022‏ - ieeexplore.ieee.org
The rapid development of high-speed railways (HSRs) puts forward high requirements on
the corresponding communication system. Millimeter wave (mmWave) can be a promising …

Federated learning-based trajectory prediction for dynamic resource allocation in moving small cell networks

S Zafar, S Jangsher, A Zafar - Vehicular Communications, 2024‏ - Elsevier
With the evolution of fifth generation (5G) of mobile communication, vehicular edge
computing (VEC) and moving small cell (MSC) network are gaining attention because of …

Evolutionary multi-objective optimization algorithm for resource allocation using deep neural network in ultra-dense networks

N Sharma, K Kumar - IEEE Transactions on Network and …, 2023‏ - ieeexplore.ieee.org
It is certain that in the modern era the ultra-dense network (UDN) structure will play a major
role for the evolution of 5G and beyond wireless communication system, particularly for blind …