关键词: 认知无线电, 宽带频谱感知, 小波变换, 奇异值分解

Abstract: The signal detection issue is investigated for wideband spectrum sensing in cognitive radio. Considering that channel position and bandwidth are randomly distributed, an improved singularity detection algorithm based on second-order component of hankel matrix Singular Value Decomposition is proposed for real-time detection of multiple signals. Applied to frequency points singularity detection in the entire frequency range, the start-end frequencies and the bandwidths of each band can be obtained. On this basis, traditional multi-band detection in fixed channel is used to classify bands as occupied or vacant, so that it can efficiently accomplish wideband sensing, meanwhile. With the three new evaluated parameters, experimental results based on actual received microwave signal and emulational OFDM signal sustain that the proposed algorithm is better than multiresoluted wavelet in singularity detection.

Key words: cognitive radio, wideband spectrum sensing, wavelet transform, Singular Value Decomposition（SVD）