The frontiers of deep reinforcement learning for resource management in future wireless HetNets: Techniques, challenges, and research directions
Next generation wireless networks are expected to be extremely complex due to their
massive heterogeneity in terms of the types of network architectures they incorporate, the …
massive heterogeneity in terms of the types of network architectures they incorporate, the …
Survey on device to device (D2D) communication for 5GB/6G networks: Concept, applications, challenges, and future directions
Device-to-device (D2D) communication is one of the most promising technologies in
wireless cellular networks that can be employed to improve spectral and energy efficiency …
wireless cellular networks that can be employed to improve spectral and energy efficiency …
Deep reinforcement learning for radio resource allocation and management in next generation heterogeneous wireless networks: A survey
Next generation wireless networks are expected to be extremely complex due to their
massive heterogeneity in terms of the types of network architectures they incorporate, the …
massive heterogeneity in terms of the types of network architectures they incorporate, the …
Collaborative multiagent reinforcement learning aided resource allocation for UAV anti-jamming communication
In this article, we investigate the anti-jamming problem with joint channel and power
allocation for unmanned aerial vehicle (UAV) networks. In particular, we focus on avoiding …
allocation for unmanned aerial vehicle (UAV) networks. In particular, we focus on avoiding …
Research on multi-agent D2D communication resource allocation algorithm based on A2C
X Li, G Chen, G Wu, Z Sun, G Chen - Electronics, 2023 - mdpi.com
Device to device (D2D) communication technology is the main component of future
communication, which greatly improves the utilization of spectrum resources. However, in …
communication, which greatly improves the utilization of spectrum resources. However, in …
[HTML][HTML] Cognitive D2D communication: A comprehensive survey, research challenges, and future directions
The integration of cognitive radio and device-to-device (D2D) communication gives rise to
Cognitive D2D (cD2D) communication, which offers numerous advantages, such as …
Cognitive D2D (cD2D) communication, which offers numerous advantages, such as …
Deep reinforcement learning-based dynamic spectrum access for D2D communication underlay cellular networks
This letter investigates a deep reinforcement learning (DRL)-based spectrum access
scheme for device-to-device (D2D) communication underlay cellular networks. Specifically …
scheme for device-to-device (D2D) communication underlay cellular networks. Specifically …
Dynamic spectrum access for D2D-enabled Internet of Things: A deep reinforcement learning approach
Device-to-device (D2D) communication is regarded as a promising technology to support
spectral-efficient Internet of Things (IoT) in beyond fifth-generation (5G) and sixth-generation …
spectral-efficient Internet of Things (IoT) in beyond fifth-generation (5G) and sixth-generation …
Deep Q-learning based optimal resource allocation method for energy harvested cognitive radio networks
MK Giri, S Majumder - physical communication, 2022 - Elsevier
In this article, we propose a deep Q-learning based algorithm for optimal resource allocation
in energy harvested cognitive radio networks (EH-CRN). In EH-CRN, channel resources of …
in energy harvested cognitive radio networks (EH-CRN). In EH-CRN, channel resources of …
Holistic resource management in UAV-assisted wireless networks: An optimization perspective
S Taimoor, L Ferdouse, W Ejaz - Journal of Network and Computer …, 2022 - Elsevier
Unmanned aerial vehicles (UAVs) are considered as a promising solution to assist terrestrial
networks in future wireless networks (ie, beyond fifth-generation (B5G) and sixth-generation …
networks in future wireless networks (ie, beyond fifth-generation (B5G) and sixth-generation …