Cooperative Cognitive Spectrum Sensing Based on Optimized Time-Frequency Signal Analysis

Rehman, Ubaid ur

kassel university press, ISBN: 978-3-86219-596-1, 2018, 113 Pages

Zugl.: Kassel, Univ., Diss. 2017

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Content: Spectrum sensing is used in cognitive radio to detect the free portions of spectrum in a licensed frequency band. We introduce a cooperative spectrum sensing scenario in which the decisions from the secondary users are combined for better sensing accuracy. Each secondary user sends its decision to a central node which combines all individual decisions. A discrete Fourier transform (DFT) filter bank based architecture is used by each secondary user for efficient detection of a primary user signal in a desired time-frequency slot. The prototype filters underlying the DFT filter banks are optimized to provide maximum time-frequency resolution. We formulate an objective function to represent the time-frequency distribution of signal energy and use numerical methods to obtain optimized prototype filter To address the problem of noise power uncertainty in cognitive radio systems, we introduce a method for denoising the received signal which is based on goodness-of-fit statistical test. We compare the performance of the proposed method with other spectrum sensing methods in terms of receiver operating characteristics (ROC). The spectrum sensing performance is also analyzed in the presence of noise power uncertainty. Finally, the hardware implementation aspects of the proposed architecture are also analyzed using a field programmable gate array (FPGA).

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