A Non-Stationary Bandit-Learning Approach to Energy-Efficient Femto-Caching With Rateless-Coded Transmission
Author:
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications
Link
http://xplorestaging.ieee.org/ielx7/7693/9137750/09080557.pdf?arnumber=9080557
Cited by 5 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. Age-Based Federated Learning Approach to In-Network Caching: An Online Scheduling Policy;ICC 2024 - IEEE International Conference on Communications;2024-06-09
2. Piecewise-Stationary Multi-Objective Multi-Armed Bandit With Application to Joint Communications and Sensing;IEEE Wireless Communications Letters;2023-05
3. Optimizing Caching in a C-RAN With a Hybrid Millimeter-Wave/Microwave Fronthaul Link via Dynamic Programming;IEEE Transactions on Communications;2023-02
4. Mobility-Aware Routing and Caching in Small Cell Networks using Federated Learning;IEEE Transactions on Communications;2023
5. Mobility-Aware Routing and Caching: A Federated Learning Assisted Approach;ICC 2021 - IEEE International Conference on Communications;2021-06
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