Interference-Aware Based Resource Configuration Optimization for URLLC Grant-Free Transmission
Author:
Affiliation:
1. Beijing University of Posts and Telecommunications (BUPT),Wireless Signal Processing and Networks Laboratory (WSPN)) Key Laboratory of Universal Wireless Communication, Ministry of Education,Beijing,P.R. China,100876
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10118584/10118587/10118859.pdf?arnumber=10118859
Reference18 articles.
1. Regression-Based Uplink Interference Identification and SINR Prediction for 5G Ultra-Dense Network
2. A Reliable Reinforcement Learning for Resource Allocation in Uplink NOMA-URLLC Networks
3. An Interference-Oriented 5G Radio Resource Allocation Framework for Ultradense Networks
4. Energy-Efficient Uplink Power Allocation in Ultra-Dense Network Through Multi-agent Reinforcement Learning
5. Network Slicing for URLLC and eMBB With Max-Matching Diversity Channel Allocation
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