M. M. Alammar, M. López-Benítez and J. Lehtomäki, "Automatic Extraction of Signal Areas from Radio Spectrograms Based on the Hough Transform," 2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2022, pp. 204-213, doi: 10.1109/WoWMoM54355.2022.00039.
Automatic extraction of signal areas from radio spectrograms based on the Hough transform
|Author:||Alammar, Mohammed M.1,2; López-Benítez, Miguel1,3; Lehtomäki, Janne4|
1Department of Electrical Engineering and Electronics, University of Liverpool, United Kingdom
2Department of Electrical Engineering, King Khalid University, Abha, Saudi Arabia
3ARIES Research Centre, Antonio de Nebrija University, Madrid, Spain
4Centre for Wireless Communications, Department of Communications Engineering, University of Oulu, Finland
|Online Access:||PDF Full Text (PDF, 1 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2022121471535
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2022-12-14
Radio communication signals are often represented in many practical application scenarios as a spectrogram, which indicates the power observed at several discrete time instants and frequency points within a certain time interval and frequency band, respectively. The concept of Signal Area (SA) was recently introduced in the context of spectrum occupancy measurements as the rectangular region in the time-frequency domain where a signal is believed to be present. An accurate estimation of the original SA for each radio transmission contained in a spectrogram can provide valuable information in many practical application scenarios, such as autonomous spectrum-aware wireless communication systems. In this context, this work proposes new methods for an accurate Signal Area Estimation (SAE) based on the application of the Hough Transform (HT) combined with other techniques from the field of image processing. The performance of the proposed methods is evaluated by means of simulations and experiments. The obtained results show that they can achieve a high level of SAE accuracy. Moreover, an interesting and distinguishing feature of the proposed methods is their ability to not only improve the accuracy of the SAE but also to extract automatically the coordinates and dimensions of each SA detected in a radio spectrogram. This feature can be useful in the automatic processing of radio spectrograms, for example in the context of autonomous spectrum-aware wireless systems.
|Pages:||204 - 213|
2022 IEEE 23rd international symposium on a world of wireless, mobile and multimedia networks (WoWMoM)
IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
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