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The autocorrelation-based detection of OFDM signals with cyclic prefix is an appealing method for cognitive radio because it has low complexity and it allows to separate between different OFDM-based legacy systems. Unfortunately, it is also sensitive to noise estimation errors provided that a single estimate of the autocorrelation function is calculated. In this paper we design an autocorrelation-based detector for OFDM signals with cyclic prefix that is also robust in the low SNR under noise uncertainty. The proposed decision statistic allows us to calculate the error probabilities in a closed-form.