A Novel, Blind, Wideband Spectrum Detection under Non-Flat Spectrum and Fading Scenarios

Peng Shang, Decai Zou, Xue Wang, Ziyue Chu

科研成果: 期刊稿件文章同行评审

3 引用 (Scopus)

摘要

In the field of radio surveillance and cognitive radio, the reception of a signal is usually made in a non-cooperative manner, which means there exists little prior information to detect the signals reliably via a traditional method. At the same time, the prevalent wideband acquisition mode will receive multiple subband signals from homogeneous or heterogeneous systems, leading to deteriorated detection performance under a non-flat spectrum and fading channel. In view of the above concerns, a novel detection algorithm based on the Gaussian hidden Markov model (HMM) is proposed so as to separate the individual sub-band signal from the wideband spectrum accurately in a low signal-to-noise ratio (SNR). The simulated communication signals with spectral fluctuation and multipath fading indicate the superiority and applicability of the proposed algorithm as compared with other detection algorithms. Our algorithm can achieve a 94% detection probability at −10 dB SNR under an additive white Gaussian noise (AWGN) channel and has a nearly ideal receiver operating characteristic (ROC) curve. When faced with a Rayleigh fading channel, it still outperforms other algorithms. The acquired real data also very its practical application with moderate computation complexity and a more stable carrier-frequency estimation.

源语言英语
文章编号2415
期刊Electronics (Switzerland)
11
15
DOI
出版状态已出版 - 8月 2022
已对外发布

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