[HTML][HTML] Energy efficiency techniques in ultra-dense wireless heterogeneous networks: An overview and outlook
In wireless heterogeneous networks (HetNets), the spatial densification through small cells
and the application of massive MIMO antenna arrays are key enablers for high data …
and the application of massive MIMO antenna arrays are key enablers for high data …
[HTML][HTML] Handover management over dual connectivity in 5G technology with future ultra-dense mobile heterogeneous networks: A review
Supporting seamless connection through user mobility is a critical challenge that must be
addressed in mobile Heterogeneous Networks (HetNets). The case will become more worse …
addressed in mobile Heterogeneous Networks (HetNets). The case will become more worse …
Distributed deep reinforcement learning-based spectrum and power allocation for heterogeneous networks
This paper investigates the problem of distributed resource management in two-tier
heterogeneous networks, where each cell selects its joint device association, spectrum …
heterogeneous networks, where each cell selects its joint device association, spectrum …
Survey of radio resource management in 5G heterogeneous networks
Radio resource management (RRM) for future fifth-generation (5G) heterogeneous networks
(HetNets) has emerged as a critical area due to the increased density of small-cell networks …
(HetNets) has emerged as a critical area due to the increased density of small-cell networks …
Reinforcement learning for energy-efficient trajectory design of UAVs
Integrating unmanned aerial vehicles (UAVs) as aerial base stations (BSs) into terrestrial
cellular networks has emerged as an effective solution to provide coverage and complement …
cellular networks has emerged as an effective solution to provide coverage and complement …
HAPS-UAV-enabled heterogeneous networks: A deep reinforcement learning approach
The integrated use of non-terrestrial network (NTN) entities such as the high-altitude
platform station (HAPS) and low-altitude platform station (LAPS) has become essential …
platform station (HAPS) and low-altitude platform station (LAPS) has become essential …
Fairness-aware link optimization for space-terrestrial integrated networks: A reinforcement learning framework
The integration of space and air components considering satellites and unmanned aerial
vehicles (UAVs) into terrestrial networks in a space-terrestrial integrated network (STIN) has …
vehicles (UAVs) into terrestrial networks in a space-terrestrial integrated network (STIN) has …
Re-envisioning space-air-ground integrated networks: Reinforcement learning for link optimization
To provide ubiquitous connectivity and achieve high reliability in the under-served and
under-connected areas, the integration of aerial and space communication infrastructures …
under-connected areas, the integration of aerial and space communication infrastructures …
Energy-efficient resource allocation for ultra-dense licensed and unlicensed dual-access small cell networks
In this study, an energy-efficient self-organized framework for sub-channel allocation and
power allocation is presented for ultra-dense small cell networks, which can operate in both …
power allocation is presented for ultra-dense small cell networks, which can operate in both …
Distributed learning-based resource allocation for self-organizing c-v2x communication in cellular networks
In this paper, we investigate a resource allocation problem for a Cellular Vehicle to
Everything (C-V2X) network to improve energy efficiency of the system. To address this …
Everything (C-V2X) network to improve energy efficiency of the system. To address this …