Real-time implementation of fast sequency-ordered complex hadamard transform based parzen window entropy spectrum sensing algorithm for cognitive radio

Abstract

Spectrum sensing in real time is a challenging task in cognitive radio networks (CRN). Fast Sequency-Ordered Complex Hadamard Transform (FSCHT) based Parzen window entropy detection (PWED) algorithm gives superior SNR wall compared to other sensing algorithms. This paper presents a real-time performance evaluation of the FSCHT based PWED algorithm in Wireless Open-Access Research Platform (WARP). The pipeline architecture of the FSCHT-PWED algorithm is designed and implemented in the WARP boards. The performance is validated using bursts of QPSK signal. The implementation results are compared with the simulation results. The experimental results reveal that the algorithm can detect the primary user (PU) signal up to SNR of -54 dB and -46 dB in simulation and real time environment respectively with probability of detection (Pd) = 0.9 and probability of false alarm (Pfa) = 0.1 respectively. The detection time for single node spectrum sensing in WARP board is evaluated as 3.7μseconds.