ML-Assisted Resource Allocation Outage Probability: Simple, Closed-Form Approximations-Reference-Cited by-同舟云学术

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ML-Assisted Resource Allocation Outage Probability: Simple, Closed-Form Approximations

Published:2023-12-17 Issue: Volume: Page:1-6
ISSN:
Container-title:2023 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)
language:
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Author:

Raina Rashika¹,Simmons Nidhi¹,Simmons David E.²,Yacoub Michel Daoud³

Affiliation:

1. Queen’s University,Centre for Wireless Innovation, School of Electronics, Electrical Engineering and Computer Science,Belfast,UK,BT3 9DT

2. Dhali Holdings Ltd.,Belfast,UK,BT5 7HW

3. University of Campinas,Wireless Technology Laboratory, School of Electrical and Computer Engineering,Campinas,Brazil,13083-970

Funder

Royal Academy of Engineering

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10468574/10468669/10469572.pdf?arnumber=10469572

Reference22 articles.

1. Artificial-Intelligence-Enabled Intelligent 6G Networks

2. Deep Learning for Moving Blockage Prediction using Real mmWave Measurements

3. Next Generation Terahertz Communications: A Rendezvous of Sensing, Imaging, and Localization

4. MACHINE LEARNING FOR RELIABLE MMWAVE SYSTEMS: BLOCKAGE PREDICTION AND PROACTIVE HANDOFF

5. Millimeter Wave Base Stations with Cameras: Vision-Aided Beam and Blockage Prediction

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