Multiuser Scheduling Algorithm for 5G IoT Systems Based on Reinforcement Learning
Author:
Affiliation:
1. College of Telecommunications & Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China
2. College of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China
Funder
National Natural Science Foundation of China
Postgraduate Research and Practice Innovation Program of Jiangsu Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/25/10104191/09956912.pdf?arnumber=9956912
Reference32 articles.
1. User Scheduling and Resource Allocation in HetNets With Hybrid Energy Supply: An Actor-Critic Reinforcement Learning Approach
2. A User Selection Algorithm Using Angle between Subspaces for Downlink MU-MIMO Systems
3. Low-Complexity Learning for Dynamic Spectrum Access in Multi-User Multi-Channel Networks
4. Reinforcement Learning-Based User Scheduling and Resource Allocation for Massive MU-MIMO System
5. Rethinking energy efficiency models of cellular networks with embodied energy
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