Dataset Information

A Radio Frequency Region-of-Interest Convolutional Neural Network for Wideband Spectrum Sensing.

ABSTRACT: Wideband spectrum sensing plays a crucial role in various wireless communication applications. Traditional methods, such as energy detection with thresholding, have limitations like detecting signals with low signal-to-noise ratio (SNR). This article proposes a novel deep learning-based approach for RF signal detection in the wideband spectrum. The objective is to accurately estimate the noise distribution in a wideband radio spectrogram and improve the detection performance by substracting it. The proposed method utilizes convolutional neural networks to analyze radio spectrograms. Model evaluation demonstrates that the RFROI-CNN approach outperforms the traditional energy detection with thresholding method by achieving significantly better detection results, even up to 6 dB, and expanding the capabilities of wideband spectrum sensing systems. The proposed approach, with its precise estimation of noise distribution and consideration of neighboring signal power values, proves to be a promising solution for RF signal detection.

SUBMITTER: Olesinski A

PROVIDER: S-EPMC10383786 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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A Radio Frequency Region-of-Interest Convolutional Neural Network for Wideband Spectrum Sensing.

Olesiński Adam A Piotrowski Zbigniew Z

Sensors (Basel, Switzerland) 20230718 14

Wideband spectrum sensing plays a crucial role in various wireless communication applications. Traditional methods, such as energy detection with thresholding, have limitations like detecting signals with low signal-to-noise ratio (SNR). This article proposes a novel deep learning-based approach for RF signal detection in the wideband spectrum. The objective is to accurately estimate the noise distribution in a wideband radio spectrogram and improve the detection performance by substracting it. ...[more]

PMID: 37514776

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Dataset Information

A Radio Frequency Region-of-Interest Convolutional Neural Network for Wideband Spectrum Sensing.

Publications

A Radio Frequency Region-of-Interest Convolutional Neural Network for Wideband Spectrum Sensing.

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