This paper proposes an optimized phase rotation sequence method for side lobe suppression by complementing and regulating the side lobe suppression sequence set. The sequence set is efficiently enhanced through the quadratically constrained least square model. The theoretical suppression performance of our method is discussed. Furthermore, our scheme is also suitable for cognitive radio, which is analyzed in the simulation part. The simulation results confirm the effectiveness of our schemes.

Cognitive Radio is an advanced enabling technology for efficient utilization of vacant spectrum due to its ability to sense the spectrum environment. Various detection methods have been proposed for spectrum sensing, which is the key function in implementing cognitive radio. However most of the existing methods put their interests in detecting TV signal and wireless microphone signals. In this paper, we explore the periodicity of the equally spaced pilot subcarriers in OFDM signal. Simulations in various fading environments show that the proposed cyclostationarity based detection method works well for OFDM signal.

The key issue in cognitive radio is to design a reliable spectrum sensing method that is able to detect the signal in the target channel as well as to recognize its type. In this paper, focusing on classifying different orthogonal frequency-division multiplexing (OFDM) signals, we propose a two-step detection and identification approach based on the analysis of the cyclic autocorrelation function. The key parameters to separate different OFDM signals are the subcarrier spacing and symbol duration. A symmetric peak detection method is adopted in the first step, while a pulse detection method is used to determine the symbol duration. Simulations validate the proposed method.