Research Of Blind Spectrum Sensing Algorithm Based On Distribution Statistical Testing

The rapid development of wireless communication technology and the fixed frequency spectrum management policy cause the shortage of spectrum resources. Cognitive Radio is a newly developing technology that can improve the spectrum utilization dramatically. The main purpose of Cognitive Radio is to detect the presence of primary user within the desired frequency band and then enable secondary users to access the vacant channel rapidly without causing interference to primary user. Therefore, a fast and accurate spectrum sensing is a prerequisite and fundamental task in Cognitive Radio.In this paper, the spectrum sensing technologies of Cognitive Radio are studied in detail, and the spectrum sensing is transformed as a distribution statistical testing problem. The main works done by the author are listed below:1. Goodness of fit test based spectrum sensing consists of semi-blind spectrum sensing and blind spectrum sensing. For examples, the Anderson-Darling (AD) sensing is a semi-blind spectrum sensing scheme and the spectrum sensing based on the characteristic function and AD criterion is a blind spectrum sensing scheme. AD sensing has excellent detection performance; however, the noise variance must be as prior information. To overcome the shortage of AD sensing, two schemes are proposed via estimating noise variance timely and constructing a new fitting object, including a blind AD sensing and a blind spectrum sensing based on F distribution. However, the proposed schemes and the existence of spectrum sensing schemes have larger computation complexity due to the fact that its computation complexity mainly includes the sorting operation of fitting objects and calculating the different criteria. To circumvent this difficulty, a blind spectrum sensing based on the ratio of mean square to variance and a blind spectrum sensing based on binomial distribution are proposed. Meanwhile, for the proposed schemes, we derive the probability density function (PDF) of statistic tests and give the detection threshold. Both analysis and simulation results show the validness of the proposed schemes.2. All above schemes in section 1 are only effective when the primary signal keeps unchangeable during sensing interval, which hinder its application in Cognitive Radio. To achieve sensing for dynamic primary signal, we employ the correlation coefficients between each antenna to achieve spectrum sensing due to the fact that multiple antennas can offer extra space dimension information. Subsequently, based on the conclusion of correlation coefficient in math, we draw an important conclusion that every correlation coefficient, after appropriate non-linear transformation, obeys Student’s distribution when the primary user is absent and deviates rightward from the Student’s distribution when the primary user is present. On the basis of this conclusion, we do some work about the following parts. On one hand, we reformulate the spectrum sensing as how to fuse all of the correlation coefficients. In this case, a new test is constructed via Equal Gain Combining (EGC) and a cooperative spectrum sensing scheme based on the correlation coefficient in mutil-antenna Cognitive Radio system is proposed. On the other hand, we formulate the spectrum sensing as a unilateral Student’s testing. In this simulation, the Right-tail AD criterion is employed to achieve spectrum sensing and then the joint correlation coefficient and RAD criterion assisted blind spectrum sensing is proposed, which is called RAD sensing. Furthermore, we derive a unilateral RAD (URAD) criterion, and apply the proposed criterion to sensing available spectrum. Finally, we propose a blind spectrum sensing scheme based on an URAD criterion for multi-antenna Cognitive Radio system, which is dulled URAD sensing. The theoretical analysis and enormous simulations verify the URAD sensing outperforms RAD sensing at the same condition.All in all, the proposed methods and proposals effectively overcome the existing problems of spectrum sensing in Cognitive Radio; and its effectiveness is proved by simulation. Our researching and proposed spectrum sensing methods have some theoretic and actual significance.