Sparsity-aware joint narrowband interference and impulse noise mitigation for hybrid powerline-wireless transmission

Exploiting multiple physical layers for communications has gained increasing interest recently to improve reliability and/or coverage range. Powerline and unlicensed wireless communication networks are attractive candidates to realize this objective because of their ubiquity. However, their performance can be severely degraded by impulsive noise (IN) and narrowband interference (NBI), respectively. In this paper, we exploit the inherent sparse structures of NBI and IN in the frequency and time domains, respectively, to propose an efficient joint estimation and mitigation scheme based on compressive sensing (CS) principles. Moreover, we investigate the metric of maximum expected coherence of our scheme for realistic powerline communication (PLC) and wireless channels, which provides some insight into its performance. Finally, our numerical experiments demonstrate the superiority of jointly processing the wireless and PLC channel outputs for CS-based NBI and IN mitigation over separate processing of individual channel outputs.

[1]  Naofal Al-Dhahir,et al.  A Sparsity-Aware Approach for NBI Estimation in MIMO-OFDM , 2011, IEEE Transactions on Wireless Communications.

[2]  Joel A. Tropp,et al.  Greed is good: algorithmic results for sparse approximation , 2004, IEEE Transactions on Information Theory.

[3]  John G. Proakis,et al.  Digital Communications , 1983 .

[4]  Eldad Perahia,et al.  Next Generation Wireless LANs: Contents , 2013 .

[5]  Waheed U. Bajwa,et al.  Finite Frames for Sparse Signal Processing , 2013 .

[6]  G. G. Messier,et al.  Using the Wireless and PLC Channels for Diversity , 2012, IEEE Transactions on Communications.

[7]  Tareq Y. Al-Naffouri,et al.  Impulse noise cancellation in OFDM: an application of compressed sensing , 2008, 2008 IEEE International Symposium on Information Theory.

[8]  Stefano Galli,et al.  A Novel Approach to the Statistical Modeling of Wireline Channels , 2011, IEEE Transactions on Communications.

[9]  Poras T. Balsara,et al.  Alien crosstalk mitigation in vectored DSL systems for backhaul applications , 2012, 2012 IEEE International Conference on Communications (ICC).

[10]  Christoph Meinel,et al.  Digital Communication , 2014, X.media.publishing.

[11]  Jin Zhang,et al.  G.HNEM: the new ITU-T standard on narrowband PLC technology , 2011, IEEE Communications Magazine.

[12]  John Newbury,et al.  Power line communications : theory and applications for narrowband and broadband communications over power lines , 2010 .

[13]  Yonina C. Eldar,et al.  Block-Sparse Signals: Uncertainty Relations and Efficient Recovery , 2009, IEEE Transactions on Signal Processing.

[14]  Eldad Perahia,et al.  Next Generation Wireless LANs: Preface , 2008 .

[15]  Gerhard Fettweis,et al.  Capacity Analysis for OFDM Systems with Transceiver I/Q Imbalance , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[16]  Y. C. Pati,et al.  Orthogonal matching pursuit: recursive function approximation with applications to wavelet decomposition , 1993, Proceedings of 27th Asilomar Conference on Signals, Systems and Computers.

[17]  Hüseyin Arslan,et al.  Analysis of a multi-channel receiver: Wireless and PLC reception , 2010, 2010 18th European Signal Processing Conference.

[18]  E. Candès,et al.  Stable signal recovery from incomplete and inaccurate measurements , 2005, math/0503066.