A Collaborative Wideband Compressed Spectrum Sensing Scheme Based on Supervised Learning

doi:10.3969/j.issn.0372-2112.2020.12.008

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ACTA ELECTRONICA SINICA ›› 2020, Vol. 48 ›› Issue (12) : 2338-2344. DOI: 10.3969/j.issn.0372-2112.2020.12.008

A Collaborative Wideband Compressed Spectrum Sensing Scheme Based on Supervised Learning

MA Bin¹, WANG Hong-ming^1,2, XIE Xian-zhong¹

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Abstract

Wideband compressed spectrum sensing has the problems of unknown signal sparsity and high overhead of secondary users sensing. Therefore, this paper proposed an efficient cooperative scheme of wideband compressed spectrum sensing. Firstly, based on learning, a sparsity adaptive learning prediction model was derived. Secondly, a wideband spectrum filtering algorithm is designed. Finally, a cooperative wideband compressed spectrum sensing scheme was proposed. The simulation results show that the fitting effect of the adaptive prediction model are better than the existing prediction model, and the proposed sensing scheme effectively reduces the sampling rate and spectrum reconstruction delay of secondary users.

Key words

wideband spectrum sensing / collaborative sensing / compressed sensing / sparsity estimation / supervised learning

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MA Bin, WANG Hong-ming, XIE Xian-zhong. A Collaborative Wideband Compressed Spectrum Sensing Scheme Based on Supervised Learning[J]. Acta Electronica Sinica, 2020, 48(12): 2338-2344. https://doi.org/10.3969/j.issn.0372-2112.2020.12.008

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Funding

Science and Technology Research Major Program of Chongqing Municipal Education Commission (No.KJZD-M201900602); Basic Research and Frontier Exploration Project of Chongqing Municipality (No.CSTC2018jcyjAX0432); Chongqing Postgraduate Research and Innovation Project (No.CYS19252)