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Resource allocation trends for ultra dense networks in 5G and beyond networks: A classification and comprehensive survey
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 …
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
In the rapidly evolving landscape of wireless communication systems, the forthcoming sixth-
generation technology aims to achieve remarkable milestones, including ultra-high data …
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
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 …
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
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 …
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
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 …
are growing fast. For this reason, Long-Term Evolution-Unlicensed (LTE-U) technology is …
Energy efficiency and throughput optimization in 5g heterogeneous networks
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 …
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
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 …
provide efficient solutions to complex wireless network problems. As such, Convolutional …
Energy efficient train-ground mmWave mobile relay system for high speed railways
The rapid development of high-speed railways (HSRs) puts forward high requirements on
the corresponding communication system. Millimeter wave (mmWave) can be a promising …
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
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 …
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
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 …
role for the evolution of 5G and beyond wireless communication system, particularly for blind …