Optimal resource allocation is a fundamental challenge for dense and heterogeneous wireless networks with massive wireless connections.

Applications, Challenges, and Scenarios in IoT HetNets Fadi Al-Turjman. 38. Su, Q., Li, B., Wang, C., Qin, C., & Wang, W. (2020). A power allocation scheme based on deep reinforcement learning in HetNets. In 2020 international conference ...

... Energy-aware traffic offloading for green heterogeneous networks,” IEEE J. Sel. Areas Commun., 34(5), pp. 1116–1129, 2016. 45. Q. Su, B. Li, C. Wang, C. Qin, and W. Wang, “A power allocation scheme based on deep reinforcement learning in ...

... allocation include Q- learning, Deep Q- Networks (DQN), Proximal Policy Optimization (PPO), or actor- critic methods ... based on the real- time network state and performance feedback. By applying RL to resource allocation in ...

... power allocation based on multi-agent deep reinforcement learning. IEEE Trans. Veh. Technol. 69, 13124–13138 (2020) 18. Wang, D., Sun, Q., Wang, Y., Han, X., Chen, Y.: Network-assisted vertical handover scheme in heterogeneous ...

... learning algorithm which has been tried in the environment to develop the policy. However, this problem is a nonconvex problem. Traditional ... Allocation in HetNets with Green Energy Supply Based on DRL 681 5 Conclusion References.

A comprehensive and invaluable guide to 5G technology, implementation and practice in one single volume. For all things 5G, this book is a must-read.

... reinforcement as well as recurrent learning . This will help us increase detec- tion accuracy for a secured 5G ... allocation in single - RF load - modulated massive MIMO HetNets . IEEE Open J Commun Soc 1 : 1738-1764 2. Lin Y ...