A Locally Optimal Soft Linear-Quadratic Scheme for CR Systems in Shadowing Environments

JUAN AUGUSTO MAYA; LEONARDO REY VEGA; CECILIA G. GALARZA

IEEE Wireless Communications Letters

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Año: 2016 vol. 5 p. 296 - 299

In this letter, we analyze the problem of detecting spectrum holes in cognitive radio systems under the NeymanPearson scenario. We consider that a group of unlicensed users use non-coherent energy detectors to sense the radio signal and design a soft locally optimal linear-quadratic statistic based on the deflection coefficient. Each unlicensed user transmits the processed data to a central entity, where the decision about the presence or not of licensed users is made. Using the method of Monte Carlo, we show that the proposed statistic outperforms previous ones available in the literature in a wide range of shadow-fading scenarios and it is robust against parameters errors.