One-Bit mmWave MIMO Channel Estimation Using Deep Generative Networks-Reference-Cited by-同舟云学术

One-Bit mmWave MIMO Channel Estimation Using Deep Generative Networks

Published:2023-09 Issue:9 Volume:12 Page:1593-1597
ISSN:2162-2337
Container-title:IEEE Wireless Communications Letters
language:
Short-container-title:IEEE Wireless Commun. Lett.

Author:

Doshi Akash¹^ORCID,Andrews Jeffrey G.¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA

Funder

NVIDIA

Qualcomm Innovation Fellowship

NSF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

https://ieeexplore.ieee.org/ielam/5962382/10244213/10145921-aam.pdf

Reference20 articles.

1. Unsupervised representation learning with deep convolutional generative adversarial networks;radford;Proc ICLR,2015

2. Generative adversarial nets;goodfellow;Proc Adv NIPS,2014

3. Robust one-bit recovery via ReLU generative networks: Improved statistical rates and global landscape analysis;qiu;Proc NeurIPS Deep Inverse Workshop,2019

4. Compressed sensing using generative models;bora;Proc Int Conf Mach Learn (ICML),2017

5. AmbientGAN: Generative models from lossy measurements;bora;Proc ICLR,2018

Cited by 4 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. Dual-Driven Learning for Channel Estimation of Massive MIMO Systems With One-Bit ADCs;IEEE Wireless Communications Letters;2024-04

2. Variational Autoencoder for Channel Estimation: Real-World Measurement Insights;2024 27th International Workshop on Smart Antennas (WSA);2024-03-17

3. Deep Learning Based One Bit-ADCs Efficient Channel Estimation Using Fewer Pilots Overhead for Massive MIMO System;IEEE Access;2024

4. Enhancing mmWave Channel Estimation: A Practical Experimentation Approach With Modeled Physical Layer Impairments Incorporated in Deep Learning Training;IEEE Open Journal of the Communications Society;2024