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Performance improvement of OFDM systems using compressive sensing with group LASSO signal reconstruction algorithm

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Abstract

Orthogonal frequency division multiplexing (OFDM) has been investigated for the high-speed transmission of data in radio frequency and optical wireless communications. The OFDM systems usually experience high amplitude variations called peak-to-average power ratio (PAPR). The high PAPR makes non-linear distortion and performance degradation because of clipping the signal. To alleviate the high PAPR, we introduce a new technique based on the compressive sensing approach. In the offered method, the OFDM signal is compressed in the time domain and then transmitted. At the receiver, a G-LASSO (group least absolute shrinkage and selection operator) recovery algorithm is applied to reconstruct the original signal. The reconstruction accuracy of the suggested G-LASSO algorithm is compared with the original LASSO algorithm. Numerical results indicate the effectiveness of the offered approach in terms of PAPR reduction and bit error rate performance.

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Authors and Affiliations

  1. Engineering Faculty of Khoy, Urmia University of Technology, Urmia, Iran

    Ghanbar Azarnia

  2. Department of Electrical Engineering, University of Bonab, Bonab, Iran

    Abbas Ali Sharifi

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  1. Ghanbar Azarnia
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  2. Abbas Ali Sharifi
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Correspondence to Abbas Ali Sharifi.

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Azarnia, G., Sharifi, A.A. Performance improvement of OFDM systems using compressive sensing with group LASSO signal reconstruction algorithm. Wireless Netw 28, 3771–3778 (2022). https://doi.org/10.1007/s11276-022-03080-z

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