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Compressed Spectrum Sensing for Wavelet Based Cognitive Heterogeneous Network over Multipath Fading

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Abstract

Heterogeneous network can improve the reliability and data rate of communication services especially at cell edges and remote areas. Due to the spectrum scarcity, the large number of small cells may reuse the same frequency bands as the adjacent cells or primary systems. Cognitive features facilitate the secondary network to sense and utilize the spectrum holes. In this paper, compressed spectrum sensing is proposed for wideband signals to reduce the cost and implementation complexity of wideband analog to digital converter for heterogeneous network. This mechanism employs wavelet based energy detection with adaptive threshoding in decision making procedure. Linear and nonlinear recovery programs are addressed to be compared for compressed spectrum sensing. A paradigm of long term evolution advanced system is simulated to verify the robustness of the proposed method for heterogeneous network over multipath fading channel. The power spectrum density of reconstructed signals are compared and analyzed for various compressed sensing algorithms. The results of Log Barrier method are promising in terms of probability of detection and controlled probability of false alarm around the standard values with compression ratios higher than 20% of Nyquist rate.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada

    H. Hosseini, A. Anpalagan & K. Raahemifar

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  1. H. Hosseini
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  2. A. Anpalagan
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  3. K. Raahemifar
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Correspondence to A. Anpalagan.

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Hosseini, H., Anpalagan, A. & Raahemifar, K. Compressed Spectrum Sensing for Wavelet Based Cognitive Heterogeneous Network over Multipath Fading. Wireless Pers Commun 96, 3947–3964 (2017). https://doi.org/10.1007/s11277-017-4360-7

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  • DOI: https://doi.org/10.1007/s11277-017-4360-7

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