Underutilization of many parts of radio frequency spectrum has increased the interest in dynamic spectrum allocation. Cognitive radios (CR) have been suggested as an enabling technology for dynamic allocation of spectrum resources. Spectrum sensing used for finding free spectrum is a key task in cognitive radio systems. It is an important requirement for the realization of cognitive radio networks. Spectrum sensing enables unlicensed users, referred to as cognitive radio users, to adapt to the environment by detecting unused spectrum bands without causing interference to the licensed network, referred to as the primary network. By detecting particular spectral holes, where the licensed (primary) radio systems are idle, and exploiting them rapidly, the cognitive radio can improve the spectrum utilization significantly. Therefore, in order to recognize a spectral hole one must study the channel variation and use the estimate of the received signal power in the next instant. Whereas most of the existing literature on spectrum sensing considers impairment by additive white Gaussian noise (AWGN) only, in practice, CRs also have to cope with various types of non–Gaussian noise such as man–made impulsive noise, co–channel interference, and ultra–wideband interference. Several measurement studies have shown that in many outdoor and indoor frequency bands the noise distribution has heavier tails than Normal distribution. This study presents a new method spectrum sensing based on particle filter theory in the presence of non_gaussian noise of environment. It has been shown that a broad and increasingly important left; LINE-HEIGHT: normal; MARGIN: 0in 0in 0pt; unicode-bidi: embed; DIRECTION: ltr" Keywords: Cognitive Radio, Spectrum Sensing, Impulsive Noise, Symmetric alpha-stable, Particle Filter, Kalman Filter, Lp-norm Detection.
