Spectrum Sensing Using Energy Detectors with Performance Computation Capabilities

Spectrum Sensing Using Energy Detectors with Performance Computation Capabilities

Rugini, L (University of Perugia)
Banelli, Paolo (University of Perugia)
Leus, G.J.T. (TU Delft Signal Processing Systems)

2016-12-01

We focus on the performance of the energy detector for cognitive radio applications. Our aim is to incorporate, into the energy detector, low-complexity algorithms that compute the performance of the detector itself. The main parameters of interest are the probability of detection and the required number of samples. Since the exact performance analysis involves complicated functions of two variables, such as the regularized lower incomplete Gamma function, we introduce new low-complexity approximations based on algebraic transformations of the one-dimensional Gaussian Q-function. The numerical comparison of the proposed approximations with the exact analysis highlights the good accuracy of the low-complexity computation approach.

Random variables
Gaussian approximation
Signal to noise ratio
Detectors
Performance evaluation
Europe

http://resolver.tudelft.nl/uuid:815a9111-1193-41a6-bbf4-bf410a355c22

https://doi.org/10.1109/eusipco.2016.7760520

IEEE, Piscataway, NJ

978-1-5090-1891-8

2016 24th European Signal Processing Conference, EUSIPCO 2016

EUSIPCO 2016, 2016-08-29 → 2016-09-02, Budapest, Hungary

Institutional Repository

conference paper

© 2016 L Rugini, Paolo Banelli, G.J.T. Leus