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Recognition of cognitive radio signal system

Author: LiuDan
Tutor: LongKePing
School: University of Electronic Science and Technology
Course: Communication and Information System
Keywords: Cognitive radio Blind Source Separation Support Vector Machine Signal recognition
CLC: TN925
Type: Master's thesis
Year: 2011
Downloads: 70
Quote: 0
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Abstract


Wireless communication is facing a growing shortage of spectrum resources, low utilization of spectrum that has its roots in the fixed allocation of spectrum. Effective method to solve this problem is one of the cognitive radio technology (CR: Cognitive Radio), cognitive radio is a new kind of intelligent wireless communication technology, cognitive users can be perceived the surrounding spectral changes in the environment, which change their transmission parameters spectrum holes (idle primary user of the band), so that it can use to improve the spectrum utilization. Signal recognition is one of the key technologies in cognitive radio, accurate signal recognition not only able to avoid the interference to the primary user, but also the cognitive users to share wireless spectrum from multidimensional frequency modulation, ubiquitous network access into the support, In addition, the format information of the identified primary user signal can also be fed back to the cognitive user to provide more information for the spectrum sensing, thereby further improving the performance of the spectrum sensing. In the cognitive networks can not communicate with the primary user and cognitive user, and thus our study is based on non-cooperative communication signal system identification. This paper studies the cognitive radio based on blind source separation and support vector machines SVM single signal of non-cooperation, and mixed-signal system identification problem, given less recognition of the signal system, especially the recognition of mixed-signal system has not yet seen The same receiver at the same time receive multiple signals in the presence of the actual communication, so we focused on single and mixed-signal system to identify separately proposed solutions. The specific content as well as main contributions include: 1. Research the background of cognitive radio, and understanding of the concept as well as the key technology of cognitive radio, and signal system to identify the importance of cognitive radio made. 2. Blind signal separation algorithm and SVM classifier, and provide technical support for the proposed algorithm. Input feature vectors. Single standard identification signal, time-frequency characteristics and analysis of a single signal system identification algorithm based on SVM, signal extraction, select the most likely to distinguish between several characteristics of the signal type as the SVM classifier , to optimize the parameters of SVM classifier constructed to improve the recognition rate of the signal. 4 focuses on the problem of non-cooperation in mixed-signal system identification, proposed mixed-signal system identification algorithm based on blind source separation and SVM. The blind source separation algorithm separated all signals, the re-extraction of each separated signal characterized using the SVM to recognize the separated signal, i.e. to draw a standard type of the respective signals in the mixed signal section Finally MATLAB simulation results of the algorithm, verify its feasibility.

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Wireless communications > Radio relay communications,microwave communications
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