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

2017 4th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2017-09-01 DOI:10.1109/ISPCC.2017.8269687

H. Yerranna, Varaprasad Revu, Swetha Namburu, Samrat LSabat

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引用次数: 1

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.

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基于parzen窗熵的认知无线电频谱感知算法的实时实现

在认知无线电网络中，实时频谱感知是一项具有挑战性的任务。基于快速序列有序复哈达玛变换(FSCHT)的Parzen窗熵检测(PWED)算法与其他传感算法相比具有更高的信噪比。本文对无线开放存取研究平台(WARP)中基于FSCHT的PWED算法进行了实时性能评估。在WARP板上设计并实现了FSCHT-PWED算法的流水线结构。利用QPSK信号的突发验证了该算法的性能。将实现结果与仿真结果进行了比较。实验结果表明，该算法在仿真和实时环境下分别可以检测到信噪比为- 54 dB和- 46 dB的主用户(PU)信号，检测概率(Pd) = 0.9，虚警概率(Pfa) = 0.1。WARP单板单节点频谱感知检测时间为3.7μs。

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2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)

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