Spectrum sensing is the first and the most important part in the Cognitive radio cycle. In this thesis, a wide band sensing scheme based on subspace methods to detect the presence of the primary users under the dual effects of rayleigh fading and log-normal shadowing is considered. The use multiple antennas to combat multipath fading and cooperation amongst secondary users to negate the effects of shadowing is proposed. Specifically, based on the collected samples of the received signals over multiple antennas, each secondary user estimates the number of primary user signals and their carrier frequencies using the subspace method. Before fusing all local estimates, the fusion center needs to determine which estimates belong to which primary users. The k-means algorithm built on the minimum description length principle is proposed for the data association problem, which can further eliminate false alarms. A linear unbiased estimator is proposed for data fusion and it reduces to a weighted sum of local estimates that belong to the same primary user. Experiments are conducted to demonstrate the efficiency of the proposed algorithm in detecting the correct number of primary users and estimating their carrier frequencies.
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