Reinforcement Learning Based Adaptive Blocklength and MCS for Optimizing Age Violation Probability
Author:
Affiliation:
1. Aselsan Inc., Ankara, Turkey
2. Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey
Funder
Aselsan Inc
Middle East Technical University (METU) SRP-Scientific Research Projects
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10290881.pdf?arnumber=10290881
Reference35 articles.
1. Delay and Peak-Age Violation Probability in Short-Packet Transmissions
2. Robust Estimation of a Location Parameter
3. Data Freshness Optimization in Relaying Network Operating with Finite Blocklength Codes
4. Deep reinforcement learning: An overview;li;arXiv 1701 07274,2017
5. Status Update in IoT Networks: Age-of-Information Violation Probability and Optimal Update Rate
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Resource Allocation in the Finite Blocklength Regime Under PAoI and Delay Violation Constraints;2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt);2023-08-24
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