Performance Analysis of Improved Energy Detector With Hardware Impairments for Accurate Spectrum Sensing

Abstract

The impact of transceiver hardware impairments on the accuracy of spectrum sensing cannot be ignored in low-cost and high data rate cognitive radio systems. Nevertheless, ideal hardware for spectrum sensing is widely assumed in the technical literature. This paper presents a novel method for evaluating the improved energy detector (IED) statistics using α-μ distribution over additive white Gaussian noise (AWGN) and Nakagami-m fading channel by considering transceiver hardware imperfections. Moreover, the performance of the IED over AWGN channel is highlighted by the area under the receiver operating curve. Furthermore, the average probability of detection is evaluated for both fading and non-fading environments. An asymptotic analysis studies detection probability over fading channels at a low average signal-to-noise-ratio region. Moreover, p-order law combining and p-order law selecting diversity techniques are proposed to increase the performance of the detector. Our simulation results demonstrate that the diversity techniques significantly improve the detector performance.

Keywords

• Area under the ROC curve (AUC)
• α-μ distribution
• false alarm probability
• improved energy detector
• m fading channel%22%2C%22default_operator%22%3A%22AND%22%7D%7D%7D"> Nakagami-<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">m</italic> fading channel
• probability of detection