Spectrum Sensing Based on Energy Detection Algorithms Using GNU Radio and USRP for Cognitive Radio
Cosmina-Valentina Năstase, Alexandru Marţian, Călin Vlădeanu, Ion Marghescu
Abstract
Cosmina-Valentina Năstase, Alexandru Marţian, Călin Vlădeanu, Ion Marghescu
Abstract
Cognitive Radio technology focuses on the efficient use of the radio frequency spectrum. One of the challenging tasks for secondary users (SUs) is Spectrum Sensing., used to accurately detect primary users (PUs) and not to interfere with their signals. In this paper., we design a CR system in a real environment and test three spectrum sensing algorithms based on Energy Detection (ED). The capability of sensing the radio spectrum is implemented using two Universal Software Radio Peripheral (USRP) platforms combined with the GNU Radio software toolkit. The three ED algorithms are compared in terms of performance., taking into account the PU activity duty cycle in a low SNR scenario. We present the performance of these three algorithms for DPSK modulation as a primary signal to check the feasibility of these methods.
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Cognitive Radio technology focuses on the efficient use of the radio frequency spectrum. One of the challenging tasks for secondary users (SUs) is Spectrum Sensing., used to accurately detect primary users (PUs) and not to interfere with their signals. In this paper., we design a CR system in a real environment and test three spectrum sensing algorithms based on Energy Detection (ED). The capability of sensing the radio spectrum is implemented using two Universal Software Radio Peripheral (USRP) platforms combined with the GNU Radio software toolkit. The three ED algorithms are compared in terms of performance., taking into account the PU activity duty cycle in a low SNR scenario. We present the performance of these three algorithms for DPSK modulation as a primary signal to check the feasibility of these methods.
Key concepts: Universal Software Radio Peripheral, Cognitive radio, Software-defined radio, Computer science, Duty cycle, Energy (signal processing), Radio frequency, Real-time computing