ConvLSTM-Based Spectrum Sensing at Very Low SNR-Reference-Cited by-同舟云学术

ConvLSTM-Based Spectrum Sensing at Very Low SNR

Published:2023-06 Issue:6 Volume:12 Page:967-971
ISSN:2162-2337
Container-title:IEEE Wireless Communications Letters
language:
Short-container-title:IEEE Wireless Commun. Lett.

Author:

Wang Qian¹^ORCID,Su Bo¹,Wang Chenxi¹,Qian Li Ping¹^ORCID,Wu Yuan²^ORCID,Yang Xiaoniu³^ORCID

Affiliation:

1. College of Information Engineering, Zhejiang University of Technology, Hangzhou, China

2. State Key Laboratory of Internet of Things for Smart City and the Department of Computer and Information Science, University of Macau, Macau, China

3. Institute of Cyberspace Security, Zhejiang University of Technology, Hangzhou, China

Funder

Intergovernmental International Cooperation in Science and Technology Innovation Program

National Natural Science Foundation of China

Science and Technology Development Fund of Macau, SAR

FDCT-MOST Joint Project

Research Grant of University of Macau

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/5962382/10146529/10064055.pdf?arnumber=10064055

Reference20 articles.

1. A Cognitive Radio Spectrum Sensing Method for an OFDM Signal Based on Deep Learning and Cycle Spectrum

2. A survey of spectrum sensing algorithms for cognitive radio applications

3. Deep Learning for Spectrum Sensing

4. Unsupervised Deep Spectrum Sensing: A Variational Auto-Encoder Based Approach

5. An improvement of the convergence proof of the ADAM-optimizer;bock;arXiv 1804 10587,2018

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