Deep Cooperative Sensing: Cooperative Spectrum Sensing Based on Convolutional Neural Networks

Woongsup Lee; Minhoe Kim; Dong Ho Cho

doi:10.1109/TVT.2019.2891291

Deep Cooperative Sensing: Cooperative Spectrum Sensing Based on Convolutional Neural Networks

Woongsup Lee, Minhoe Kim, Dong Ho Cho

Graduate School of Information

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper, we investigate cooperative spectrum sensing (CSS) in a cognitive radio network (CRN) where multiple secondary users (SUs) cooperate in order to detect a primary user, which possibly occupies multiple bands simultaneously. Deep cooperative sensing (DCS), which constitutes the first CSS framework based on a convolutional neural network (CNN), is proposed. In DCS, instead of the explicit mathematical modeling of CSS, the strategy for combining the individual sensing results of the SUs is learned autonomously with a CNN using training sensing samples regardless of whether the individual sensing results are quantized or not. Moreover, both spectral and spatial correlation of individual sensing outcomes are taken into account such that an environment-specific CSS is enabled in DCS. Through simulations, we show that the performance of CSS can be greatly improved by the proposed DCS.

Original language	English
Article number	8604101
Pages (from-to)	3005-3009
Number of pages	5
Journal	IEEE Transactions on Vehicular Technology
Volume	68
Issue number	3
DOIs	https://doi.org/10.1109/TVT.2019.2891291
Publication status	Published - 2019 Mar

Bibliographical note

Funding Information:
This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2018R1D1A1B07040796).

Funding Information:
Manuscript received August 27, 2018; accepted December 30, 2018. Date of publication January 7, 2019; date of current version March 14, 2019. This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2018R1D1A1B07040796). The review of this paper was coordinated by Dr. O. Holland. (Corresponding author: Minhoe Kim.) W. Lee is with the Department of Information and Communication Engineering, Institute of Marine Industry, Gyeongsang National University, Tongyeong 53064, South Korea (e-mail:,seotaijiya@gmail.com).

Publisher Copyright:
© 1967-2012 IEEE.

All Science Journal Classification (ASJC) codes

Automotive Engineering
Aerospace Engineering
Electrical and Electronic Engineering
Applied Mathematics

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10.1109/TVT.2019.2891291

Cite this

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title = "Deep Cooperative Sensing: Cooperative Spectrum Sensing Based on Convolutional Neural Networks",

abstract = "In this paper, we investigate cooperative spectrum sensing (CSS) in a cognitive radio network (CRN) where multiple secondary users (SUs) cooperate in order to detect a primary user, which possibly occupies multiple bands simultaneously. Deep cooperative sensing (DCS), which constitutes the first CSS framework based on a convolutional neural network (CNN), is proposed. In DCS, instead of the explicit mathematical modeling of CSS, the strategy for combining the individual sensing results of the SUs is learned autonomously with a CNN using training sensing samples regardless of whether the individual sensing results are quantized or not. Moreover, both spectral and spatial correlation of individual sensing outcomes are taken into account such that an environment-specific CSS is enabled in DCS. Through simulations, we show that the performance of CSS can be greatly improved by the proposed DCS.",

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note = "Funding Information: This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2018R1D1A1B07040796). Funding Information: Manuscript received August 27, 2018; accepted December 30, 2018. Date of publication January 7, 2019; date of current version March 14, 2019. This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2018R1D1A1B07040796). The review of this paper was coordinated by Dr. O. Holland. (Corresponding author: Minhoe Kim.) W. Lee is with the Department of Information and Communication Engineering, Institute of Marine Industry, Gyeongsang National University, Tongyeong 53064, South Korea (e-mail:,seotaijiya@gmail.com). Publisher Copyright: {\textcopyright} 1967-2012 IEEE.",

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Deep Cooperative Sensing: Cooperative Spectrum Sensing Based on Convolutional Neural Networks

Abstract

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