@conference{10902/15061,
year = {2018},
url = {http://hdl.handle.net/10902/15061},
abstract = {In this work we propose a new adaptive algorithm for cooperative spectrum sensing in dynamic environments where the channels are time varying. We assume a centralized spectrum sensing procedure based on the soft fusion of the signal energy levels measured at the sensors. The detection problem is posed as a composite hypothesis testing problem. The unknown parameters are estimated by means of an adaptive clustering algorithm that operates over the most recent energy estimates reported by the sensors to the fusion center. The algorithm does not require all sensors to report their energy estimates, which makes it suited to be used with any sensor selection strategy (active sensing). Simulation results show the feasibility and efficiency of the method in realistic slow-fading environments.},
organization = {This work has been funded by SODERCAN and Programa Operativo FEDER under grant CAIMAN - 12.JU01.64661, and by the Ministerio de Economía, Industria y Competitividad (MINECO) of Spain, and AEI/FEDER funds of the E.U., under grants TEC2017-86921-C2-1-R (CAIMAN), TEC2013-47141-C4-R (RACHEL) and TEC2016-75067- C4-4-R (CARMEN).},
publisher = {IEEE},
publisher = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, Canada, 2018, 2611-2615},
title = {Adaptive clustering algorithm for cooperative spectrum sensing in mobile environments},
author = {Pérez Arriaga, Jesús and Santamaría Caballero, Luis Ignacio},
}