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Online detection and SNR estimation in cooperative spectrum sensing

Abstract: Cooperative spectrum sensing has proved to be an effective method to improve the detection performance in cognitive radio systems. This work focuses on centralized cooperative schemes based on the soft fusion of the energy measurements at the cognitive radios (CRs). In these systems, the likelihood ratio test (LRT) is the optimal detection rule, but the sufficient statistic depends on the local signal-to-noise ratio (SNR) at the CRs, which are unknown in most practical cases. Therefore, the detection problem becomes a composite hypothesis test. The generalized LRT is the most popular approach in those cases. Unfortunately, in mobile environments, its performance is well below the LRT because the local energies are measured under varying SNRs. In this work, we present a new algorithm that jointly estimates the instantaneous SNRs and detects the presence of primary signals. Due to its adaptive nature, the algorithm is well suited for mobile scenarios where the local SNRs are time-varying. Simulation results show that its detection performance is close to the LRT in realistic conditions.

 Autoría: Perez J., Via J., Vielva L., Ramirez D.,

 Fuente: IEEE Transactions on Wireless Communications, 2022, 21(4), 2521-2533

 Editorial: Institute of Electrical and Electronics Engineers Inc.

 Fecha de publicación: 01/04/2022

 Nº de páginas: 13

 Tipo de publicación: Artículo de Revista

 DOI: 10.1109/TWC.2021.3113089

 ISSN: 1536-1276

 Proyecto español: TEC2017-86921-C2-1-R

 Url de la publicación: https://doi.org/10.1109/TWC.2021.3113089

Autoría

JAVIER VIA RODRIGUEZ

LUIS ANTONIO VIELVA MARTINEZ

DAVID RAMIREZ GARCIA