Deep-Learning-Based Millimeter-Wave Massive MIMO for Hybrid Precoding-Reference-Cited by-同舟云学术

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Deep-Learning-Based Millimeter-Wave Massive MIMO for Hybrid Precoding

Published:2019-03 Issue:3 Volume:68 Page:3027-3032
ISSN:0018-9545
Container-title:IEEE Transactions on Vehicular Technology
language:
Short-container-title:IEEE Trans. Veh. Technol.

Author:

Huang Hongji^ORCID,Song Yiwei,Yang Jie,Gui Guan^ORCID,Adachi Fumiyuki^ORCID

Funder

Priority Academic Program Development of Jiangsu Higher Education Institutions

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/25/8667487/08618345.pdf?arnumber=8618345

Cited by 362 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. Sum-Rate Maximization for a Hybrid Precoding-Based Massive MIMO NOMA System with Simultaneous Wireless Information and Power Transmission;Telecom;2024-09-02

2. Sub-6G Aided Millimeter Wave Hybrid Beamforming: A Two-Stage Deep Learning Framework With Statistical Channel Information;IEEE Transactions on Green Communications and Networking;2024-09

3. Pilot Assignment for Cell Free Massive MIMO Systems: A Successive Interference Cancellation Approach;Düzce Üniversitesi Bilim ve Teknoloji Dergisi;2024-07-31

4. A Survey on Green Enablers: A Study on the Energy Efficiency of AI-Based 5G Networks;Sensors;2024-07-16

5. Deep Learning-Based Hybrid Precoding Approach in the Massive Multiple-Input Multiple-Output System;IETE Journal of Research;2024-07-07

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