Cooperative Spectrum Sensing Algorithm Based on CS-SLIM Iterative Minimization Sparse Learning

Ning Cao, Xiaowen Hu, Hao Lu and Minghe Mao

International Journal of Distributed Sensor Networks, 2013, vol. 9, issue 5, 261953

Abstract: Dynamic spectrum management is a key technology in cognitive wireless sensor network (C-WSN), in which spectrum sensing plays an important role. In this paper, we propose an improved approach as sparse learning via iterative minimization based on compressive sampling (CS-SLIM) for wideband spectrum detection. CS-SLIM can provide wideband spectrum detection with almost the same accuracy but a lower computational burden than that of SLIM. The measurement matrix and the computational complexity for CS-SLIM are discussed. Mean squared errors (MSEs) at various measurement samples are provided to demonstrate the performance of the proposed approach in sparse scenes. It is also proved that the algorithm is suitable for sparse signal reconstruction and wideband spectrum sensing in C-WSN.

Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1155/2013/261953 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:9:y:2013:i:5:p:261953

DOI: 10.1155/2013/261953

Access Statistics for this article

More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().