Abstract
This correspondence proposes a novel multiple-antenna linearly weighted (MALW) spectrum sensing method with random arrivals of primary users (PUs) for cognitive users. The method first constructs a local test statistic for each antenna based on the assumption that the PU is randomly arriving, and then calculates the estimated optimum coefficient for every local test statistic and finally gets the total test statistic by linearly combing the local test statistics and the estimated optimum coefficients. Given false alarm probability, the proposed method calculates the corresponding threshold according to Neyman–Pearson criteria and makes the final decision by comparing the total test statistic with the threshold. Simulation results prove the validity and the superiority of the proposed MALW method when the PU is arriving randomly during the spectrum sensing period.
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