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Experimental analysis of cyclostationary detectors under cyclic frequency offsets

Cyclostationary detection involves detecting cyclic features of modulated signals which are functions of various transmit parameters including the symbol rate, carrier frequency, and modulation format. However, imperfect knowledge of these transmit parameters at the sensing radio results in computing the detection test statistic under a cyclic frequency offset (CFO). The detection performance of the conventional cyclic autocorrelation function has been shown to degrade in the presence of the CFO impairment. In this paper, we propose a new multi-frame detection statistic that improves the robustness of the conventional cyclostationary detector to CFO impairments. The achievable gains in using this method over conventional detectors are quantified analytically and verified through hardware experiments using the Universal Software Radio Platform (USRP N200) transceivers.