A survey on resource allocation for 5G heterogeneous networks: Current research, future trends, and challenges
In the fifth-generation (5G) mobile communication system, various service requirements of
different communication environments are expected to be satisfied. As a new evolution …
different communication environments are expected to be satisfied. As a new evolution …
Wireless backhaul in 5G and beyond: Issues, challenges and opportunities
B Tezergil, E Onur - IEEE Communications Surveys & Tutorials, 2022 - ieeexplore.ieee.org
With the introduction of new technologies such as Unmanned Aerial Vehicle (UAV), High
Altitude Platform Station (HAPS), Millimeter Wave (mmWave) frequencies, Massive Multiple …
Altitude Platform Station (HAPS), Millimeter Wave (mmWave) frequencies, Massive Multiple …
Robust max-min energy efficiency for RIS-aided HetNets with distortion noises
The energy efficiency (EE) of femtocells is always limited by the surrounding radio
environments in heterogeneous networks (HetNets), such as walls and obstacles. In this …
environments in heterogeneous networks (HetNets), such as walls and obstacles. In this …
DMRO: A deep meta reinforcement learning-based task offloading framework for edge-cloud computing
With the explosive growth of mobile data and the unprecedented demand for computing
power, resource-constrained edge devices cannot effectively meet the requirements of …
power, resource-constrained edge devices cannot effectively meet the requirements of …
Collaborate edge and cloud computing with distributed deep learning for smart city internet of things
City Internet-of-Things (IoT) applications are becoming increasingly complicated and thus
require large amounts of computational resources and strict latency requirements. Mobile …
require large amounts of computational resources and strict latency requirements. Mobile …
Distributed deep learning-based offloading for mobile edge computing networks
This paper studies mobile edge computing (MEC) networks where multiple wireless devices
(WDs) choose to offload their computation tasks to an edge server. To conserve energy and …
(WDs) choose to offload their computation tasks to an edge server. To conserve energy and …
Power control based on deep reinforcement learning for spectrum sharing
In the current researches, artificial intelligence (AI) plays a crucial role in resource
management for the next generation wireless communication network. However, traditional …
management for the next generation wireless communication network. However, traditional …
Energy-efficient resource allocation in NOMA heterogeneous networks
Non-orthogonal multiple access has attracted much recent attention due to its capability of
improving the system spectral efficiency in wireless communications. Deploying NOMA in a …
improving the system spectral efficiency in wireless communications. Deploying NOMA in a …
Energy efficient resource management in SWIPT enabled heterogeneous networks with NOMA
H Zhang, M Feng, K Long… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
Non-orthogonal multiple access (NOMA) in heterogeneous network (HetNet) is a very
promising scheme to meet the exponential growth of mobile data expected in the coming …
promising scheme to meet the exponential growth of mobile data expected in the coming …
MR-DRO: A fast and efficient task offloading algorithm in heterogeneous edge/cloud computing environments
With the rapid development of Internet of Things (IoT) and next-generation communication
technologies, resource-constrained mobile devices (MDs) fail to meet the demand of …
technologies, resource-constrained mobile devices (MDs) fail to meet the demand of …