Lyapunov optimization machine learning resource allocation approach for uplink underlaid D2D communication in 5G networks

[1]  S. Bhattacharya,et al.  Significance of IoT in India’s E-Medical Framework: A study , 2020, 2020 First International Conference on Power, Control and Computing Technologies (ICPC2T).

[2]  Lin Zhang,et al.  Q-learning based power control algorithm for D2D communication , 2016, 2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[3]  Gang Feng,et al.  Multi-Agent Reinforcement Learning for Efficient Content Caching in Mobile D2D Networks , 2019, IEEE Transactions on Wireless Communications.

[4]  Kai Zhang,et al.  Smart Mode Selection Using Online Reinforcement Learning for VR Broadband Broadcasting in D2D Assisted 5G HetNets , 2020, IEEE Transactions on Broadcasting.

[5]  Ming Chen,et al.  Downlink Resource Allocation and Power Control for Device-to-Device Communication Underlaying Cellular Networks , 2016, IEEE Communications Letters.

[6]  Sandeep Kumar,et al.  Lagrange's multiplier based resource management for energy efficient D2D communication in 5G networks , 2021, International Journal of System Assurance Engineering and Management.

[7]  Hazem H. Refai,et al.  Energy Efficiency Optimization and Dynamic Mode Selection Algorithms for D2D Communication Under HetNet in Downlink Reuse , 2020, IEEE Access.

[8]  Dusit Niyato,et al.  Game Theory and Lyapunov Optimization for Cloud-Based Content Delivery Networks With Device-to-Device and UAV-Enabled Caching , 2019, IEEE Transactions on Vehicular Technology.

[9]  Syed Ali Hassan,et al.  Machine Learning for Resource Management in Cellular and IoT Networks: Potentials, Current Solutions, and Open Challenges , 2019, IEEE Communications Surveys & Tutorials.

[10]  Ming Chen,et al.  Pilot Allocation and Power Control in D2D Underlay Massive MIMO Systems , 2017, IEEE Communications Letters.

[11]  Yan Chen,et al.  Lyapunov Optimization for Energy Harvesting Wireless Sensor Communications , 2018, IEEE Internet of Things Journal.

[12]  Mohamed-Slim Alouini,et al.  Power Control for D2D Underlay Cellular Networks With Channel Uncertainty , 2017, IEEE Transactions on Wireless Communications.

[13]  Chenyang Yang,et al.  Caching Policy Optimization for D2D Communications by Learning User Preference , 2017, 2017 IEEE 85th Vehicular Technology Conference (VTC Spring).

[14]  Lillykutty Jacob,et al.  Utility-Based resource allocation for underlay D2D networks , 2017, 2017 IEEE Region 10 Symposium (TENSYMP).

[15]  Dusit Niyato,et al.  Combining Contract Theory and Lyapunov Optimization for Content Sharing With Edge Caching and Device-to-Device Communications , 2020, IEEE/ACM Transactions on Networking.

[16]  Ehab Mahmoud Mohamed,et al.  Neighbor Discovery and Selection in Millimeter Wave D2D Networks Using Stochastic MAB , 2020, IEEE Communications Letters.

[17]  Geoffrey Y. Li,et al.  Learning to Branch: Accelerating Resource Allocation in Wireless Networks , 2019, IEEE Transactions on Vehicular Technology.

[18]  Gang Feng,et al.  Efficient D2D content caching using multi-agent reinforcement learning , 2018, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[19]  Xuemin Shen,et al.  Device-to-device communication in 5G cellular networks , 2015, IEEE Network.

[20]  Zhu Han,et al.  Distributed Interference and Energy-Aware Power Control for Ultra-Dense D2D Networks: A Mean Field Game , 2017, IEEE Transactions on Wireless Communications.