Learning to Predict and Optimize Imperfect MIMO System Performance: Framework and Application-Reference-Cited by-同舟云学术

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Learning to Predict and Optimize Imperfect MIMO System Performance: Framework and Application

Published:2022-12-04 Issue: Volume: Page:
ISSN:
Container-title:GLOBECOM 2022 - 2022 IEEE Global Communications Conference
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Author:

Su Jingyi¹,Meng Fan²,Liu Shengheng¹,Huang Yongming¹,Lu Zhaohua³

Affiliation:

1. School of Information Science and Engineering, Southeast University,Nanjing,China,210096

2. Purple Mountain Laboratories,Nanjing,China,211111

3. ZTE Corporation,State Key Laboratory of Mobile Network and Mobile Multimedia Technology,Shenzhen,China,518057

Funder

National Natural Science Foundation of China

National Key R&D Program of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10000063/10000593/10001369.pdf?arnumber=10001369

Reference15 articles.

1. GWO-BP Neural Network Based OP Performance Prediction for Mobile Multiuser Communication Networks

2. Machine Learning Based Quantitative Association Rule Mining Method for Evaluating Cellular Network Performance

3. Large System Analysis of Linear Precoding in Correlated MISO Broadcast Channels Under Limited Feedback

4. Traffic Prediction and Random Access Control Optimization: Learning and Non-Learning-Based Approaches

5. Handover Management for mmWave Networks With Proactive Performance Prediction Using Camera Images and Deep Reinforcement Learning

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. TDoA positioning with data-driven LoS inference in mmWave MIMO communications;Signal Processing;2024-07

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