Spectrum Sensing Based on Fractional Lower Order Power Spectral
Density in Alpha Stable Noise Environments
Xiaomei Zhu
1
& Yongjian Song
1
& Tianjing Wang
2
& Yaping Bao
1
1
College of Computer Science and Technology, Nanjing Tech University,
Nanjing, JiangSu Province, China.
2
Department of information and Computing Science, Nanjing Tech University,
Nanjing, JiangSu Province, China.
ABSTRACT: In view of the fact that the alpha distribution does not possess two order moment and power
spectrum, the detection performance of the traditional detectors, such as energy detector (ED) and power
spectral density (PSD) detector, will be degraded or even failed when the background noise be modeled as
alpha stable distribution in CR system. This paper presents a novel spectrum sensing scheme based on
fractional lower order statistics power spectral density (FPSD). The proposed algorithm, combining pseudo
PSD and Fourier transform (FT), calculates the FPSD of the received signal to determine whether primary
user (PU) is present or absent. Via the numerous simulations, the performance of the FPSD versus the
characteristic exponents
, the moment
and generalized signal-to-noise (GSNR) of the noise has been
studied. Simulations show that the proposed FPSD detector has greater performance than ED and PSD in
alpha stable noise environment. In addition, the new detector, as a blind detector, has high probability
detection without the priori-knowledge of PU signal and noise.
1. Introduction
Recently, with the increasing demand of
wireless devices, the limited spectrum resources
how to be effectively utilized has become a
significant problem. In view of this, the Cognitive
radio (CR) technology has been proposed to utilize
efficiently spectral holes and improve the spectrum
utilization [1-2]. In CR network, different from the
traditional fixed allocation principle [3], the
unlicensed users can access the licensed frequency
band to communicate when the primary user (PU)
is not occupying on the frequency band. In
addition, the unlicensed users must quit
immediately when the licensed users will use the
spectrum. The spectrum sensing [4-6] that is
proposed about that secondary users (SUs) detect
whether the presence of PU is one of the most
important techniques about a CR system.
The most spectrum sensing schemes, such as the
energy detector (ED) [7-9] and the eigenvalue
detector [10-12] are deemed that the background
noise is modeled as Gaussian distribution. While in
the practical communication environment, the
background noise is usually non-Gaussian [13-15],
and some spectrum sensing algorithms based on
the ED or the PSD will be declined or even failed
[16,17]. Therefore, some schemes have been
introduced to enhance the performance of the
detector in non-Gaussian background noise
modeled by a symmetric alpha stable distribution
[18-20]. The spectrum sensing scheme based on
the power spectrum density has attracted the
attention of researchers, because of its clear
physical meaning and easily analysis [21, 22]. [21]
has proposed the method based on the difference
between the maximum value and minimum value
of the power spectrum density (PMMD), which
uses the difference between the maximum and
minimum values of the received signal power
spectrum. PMMD reduces the influence of
randomness of the minimum value on the
algorithm. However, the alpha stable distribution
has not two order moments and power spectrum.
Aiming at this, some algorithms use the fractional
lower order statistics (FLOS) in spectrum
sensing[23,24], because the alpha stable
distribution has p-order momets (
).
Therefore, we combine the FLOS and PSD to
detect whether the presence of PU in a symmetric
alpha stable distribution noise.
In this paper, we propose new spectrum sensing
scheme based fractional lower order power
spectral density in frequency domain. Both the PU
signal and noise are modeled by alpha stable
distribution. The false alarm probability and
detection probability are studied in alpha stable
noise environment. A large number of simulations
illustrate that the probability detection of the
proposed detector is higher than the ED. In