Clipping noise estimation in uniform tone reservation scenario using OMP algorithm

In this paper, the clipping noise estimation problem based on compressed sensing (CS) is investigated when the subcarriers used for creating measurement vector are on the edge of the frequency band. Although selection of such subcarriers would not degrade data rate and is suitable for systems requiring high rates, it still weakens the performance of CS recovery algorithms especially in the presence of noise. To address this issue, a new approach based on the orthogonal matching pursuit (OMP) algorithm is proposed for improving the clipping noise estimation. Simulation results indicate that in the chosen scenario under unfavorable conditions, the proposed algorithm is still able to estimate clipping noise and according to its structure, only slightly increases the complexity of the original OMP algorithm.

[1]  Emmanuel J. Candès,et al.  Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information , 2004, IEEE Transactions on Information Theory.

[2]  K. Mohamed-Pour,et al.  Modified compressive sensing reconstruction algorithm for clipping noise estimation in OFDM systems , 2016, 2016 24th Iranian Conference on Electrical Engineering (ICEE).

[3]  Emmanuel J. Candès,et al.  Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies? , 2004, IEEE Transactions on Information Theory.

[4]  Lutz H.-J. Lampe,et al.  Compressive Sensing Recovery of Nonlinearly Distorted OFDM Signals , 2011, 2011 IEEE International Conference on Communications (ICC).

[5]  Tareq Y. Al-Naffouri,et al.  Peak Reduction and Clipping Mitigation in OFDM by Augmented Compressive Sensing , 2012, IEEE Transactions on Signal Processing.

[6]  Erik Dahlman,et al.  4G: LTE/LTE-Advanced for Mobile Broadband , 2011 .

[7]  Gordon L. Stüber,et al.  Clipping noise mitigation for OFDM by decision-aided reconstruction , 1999, IEEE Communications Letters.

[8]  Tareq Y. Al-Naffouri,et al.  On Reducing the Complexity of Tone-Reservation Based PAPR Reduction Schemes by Compressive Sensing , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[9]  Joel A. Tropp,et al.  Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit , 2007, IEEE Transactions on Information Theory.

[10]  Farrokh Marvasti,et al.  Clipping noise cancellation in OFDM systems using oversampled signal reconstruction , 2002, IEEE Communications Letters.

[11]  Hideki Ochiai,et al.  Performance analysis of deliberately clipped OFDM signals , 2002, IEEE Trans. Commun..

[12]  David L Donoho,et al.  Compressed sensing , 2006, IEEE Transactions on Information Theory.

[13]  Yasir Rahmatallah,et al.  Peak-To-Average Power Ratio Reduction in OFDM Systems: A Survey And Taxonomy , 2013, IEEE Communications Surveys & Tutorials.

[14]  Alexander M. Haimovich,et al.  Iterative estimation and cancellation of clipping noise for OFDM signals , 2003, IEEE Communications Letters.