A Model-Driven Deep Learning Network for Quantized GFDM Receiver-Reference-Cited by-同舟云学术

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A Model-Driven Deep Learning Network for Quantized GFDM Receiver

Published:2019-09 Issue:3 Volume:4 Page:53-59
ISSN:2096-1081
Container-title:Journal of Communications and Information Networks
language:
Short-container-title:J. Commun. Inf. Netw.

Author:

Zhang Mengjiao¹,Wen Chaokai²,Jin Shi¹,Zheng Fuchun³

Affiliation:

1. National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China

2. Institute of Communications Engineering, Sun Yat-sen University, Taiwan, China

3. School of Electronic and Information Engineering, Harbin Institute of Technology, Shenzhen, China; National Mobile Communications Research Laboratory, Southeast University, Nanjing, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Link

http://xplorestaging.ieee.org/ielx7/8892389/8917877/08917885.pdf?arnumber=8917885

Cited by 2 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. Deep learning-based receiver design for generalized frequency division multiplexing (GFDM);Physical Communication;2024-08

2. Noncoherent Massive Random Access for Inhomogeneous Networks: From Message Passing to Deep Learning;IEEE Journal on Selected Areas in Communications;2022-05

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