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Reliable detection of primary user activity by spectrum sensing is a crucial issue of cognitive radio systems. The objective of cooperative spectrum sensing is to combine the detection results of multiple cognitive radios in order to maximize the probability of detecting unused spectrum while meeting a required reliability of detecting primary user activity. In this paper, a Kullback-Leibler distance-based optimization approach for the local decision thresholds of cooperative spectrum sensing is proposed. It is both computationally efficient and scalable with the number of cognitive radios. To validate the concept, real spectrum sensing results are used. The employed practical setup is based on software defined radio and detects a WiMAX-like OFDM signal. The presented numerical results illustrate the feasibility and effectiveness of the approach.