Wideband Spectrum Sensing based on Sparse Channel State Recovery in Cognitive Radio Networks
نویسندگان
چکیده
Motivated by the compressed sensing sparse channel estimation problem, the complete channel state is sparse under the conditions of low spectral efficiency. Other than traditional method of looking for the perception of spectrum holes, this paper focus on the sparse of occupied sub-channels. Based on compressed sensing technology, a novel cooperative wideband spectrum sensing method is proposed in the cognitive radio networks. The speed and the efficiency of the single CR node sensing process are improved through the sparse measurement matrix. The fusion center reconstructs the observed data by the turbo-decoding message-passing (TDMP) algorithm, dramatically reducing the computation complexity.
منابع مشابه
Application of Compressed Sampling for Spectrum Sensing and Channel Estimation in Wideband Cognitive Radio Networks
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