A Cascaded Approach to Efficient Detection of OFDM Signals Based on Energy and Autocorrelation Detection

Abstract

Spectrum sensing is one of the most important parts of the cognitive radio system. In order to detect the primary user signal, the robust sensing method is required. In this paper, we propose a combination of the energy detection method and the autocorrelation-based detection method with a cascaded architecture to improve the probability of detection. Energy detection involves lower complexity and energy consumption, but it is unreliable at low signal-to-noise ratios (SNRs). Orthogonal frequency division multiplexing signal property is used by an autocorrelation-based detector, which involves more complexity and is more robust at low SNRs. We build the cascaded design of both energy detection and autocorrelation-based detection to take advantage of each technique. The performance of a cascaded detector is then presented. It is shown that the probability of detection of the cascaded design is always better than the probability of detection of a single detector. The design of the cascaded detector has been implemented which does not require additional sensing time. The complexity and utilization of each detector design is then presented to show the efficiency of the proposed design.