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Mobile Information Systems
Volume 2017, Article ID 7321908, 9 pages
https://doi.org/10.1155/2017/7321908
Research Article

A Robust FLOM Based Spectrum Sensing Scheme under Middleton Class A Noise in IoT

1School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China
2Department of Electrical and Computer Engineering, McGill University, Montreal, QC, Canada H3A 0G4

Correspondence should be addressed to Xuemai Gu; nc.ude.tih@iameuxug

Received 14 December 2016; Accepted 16 March 2017; Published 6 April 2017

Academic Editor: Tao Han

Copyright © 2017 Enwei Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Accessibility to remote users in dynamic environment, high spectrum utilization, and no spectrum purchase make Cognitive Radio (CR) a feasible solution of wireless communications in the Internet of Things (IoT). Reliable spectrum sensing becomes the prerequisite for the establishment of communication between IoT-capable objects. Considering the application environment, spectrum sensing not only has to cope with man-made impulsive noises but also needs to overcome noise fluctuations. In this paper, we study the Fractional Lower Order Moments (FLOM) based spectrum sensing method under Middleton Class A noise and incorporate a Noise Power Estimation (NPE) module into the sensing system to deal with the issue of noise uncertainty. Moreover, the NPE process does not need noise-only samples. The analytical expressions of the probabilities of detection and the probability of false alarm are derived. The impact on sensing performance of the parameters of the NPE module is also analyzed. The theoretical analysis and simulation results show that our proposed sensing method achieves a satisfactory performance at low SNR.