Browsing by Author "Elgenedy, Mahmoud"
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Item Cyclostationary Noise Mitigation for SIMO Powerline Communications(IEEE-Inst Electrical Electronics Engineers Inc) Elgenedy, Mahmoud; Sayed, Mostafa; Al-Dhahir, Naofal; Chabaan, Rakan C.; 0000 0003 5178 379X (Al-Dhahir, N); 0000-0002-1866-0272 (Sayed, M); 113149196515374792028 (Al-Dhahir, N); Elgenedy, Mahmoud; Sayed, Mostafa; Al-Dhahir, NaofalThe cyclostationary noise in low-voltage narrowband powerline communications (NB-PLC) severely degrades the communication reliability. In this paper, we adopt single-input multi-output (SIMO) transmission to enhance the reliability of NB-PLC. Considering the SIMO receiver structure, we exploit the NB-PLC noise cyclostationarity and the high spatial correlations across multiple receive phases to design practical and efficient noise mitigation techniques. In particular, we propose two time-domain frequency shift (FRESH) filtering-based cyclostationary signal recovery techniques with different performance and complexity levels. The proposed time-domain-based FRESH filtering techniques minimize the mean squared error in estimating the orthogonal frequency division multiplexing (OFDM) information signal in the time-domain The FRESH filtering exploits the cyclic auto-correlation of both the NB-PLC noise and the OFDM information signal in addition to their cyclic cross-correlation across the receive phases. Moreover, we propose a frequency-domain-based cyclostationary noise mitigation technique that minimizes the mean squared error in estimating the OFDM information signal in the frequency-domain The proposed frequency domain-based technique exploits the cyclostationarity of the noise to estimate its power spectral density as well as the cross-correlation, per frequency subchannel, over multiple stationary noise temporal regions. Our proposed SIMO NB-PLC noise mitigation techniques are shown via simulation results conducted using noise field measurements to achieve considerable performance gains over single-input single-output techniques. In addition, we show that our proposed techniques achieve considerable performance gains over the conventional SIMO maximal-ratio-combiner designed assuming stationary noise.Item Sparsity-Based Joint NBI and Impulse Noise Mitigation in Hybrid PLC-Wireless Transmissions(Institute of Electrical and Electronics Engineers Inc.) Elgenedy, Mahmoud; Mokhtar, M.; Hamila, R.; Bajwa, W. U.; Ibrahim, A. S.; Al-Dhahir, Naofal; 0000-0003-3402-5188 (Elgenedy, M); 113149196515374792028 (Al-Dhahir, N); Elgenedy, Mahmoud; Al-Dhahir, NaofalWe propose a new sparsity-aware framework to model and mitigate the joint effects of narrow-band interference (NBI) and impulsive noise (IN) in hybrid powerline and unlicensed wireless communication systems. The proposed mitigation techniques, based on the principles of compressive sensing (CS), exploit the inherent (non-contiguous or contiguous) sparse structures of NBI and IN in the frequency and time domains, respectively. For the non-contiguous NBI and IN, we develop a multi-level orthogonal matching pursuit recovery algorithm that exploits prior knowledge about the sparsity level at each receive antenna and powerline to further reduce computational complexity without performance loss. In addition, for the non-contiguous asynchronous NBI scenario, we investigate the application of time-domain windowing to enhance the NBI’s sparsity and, hence, improve the NBI mitigation performance. For the contiguous NBI and IN scenario, we estimate the NBI and IN signals by modeling their burstiness as block-sparse vectors with and without prior knowledge of the bursts’ boundaries. Moreover, we show how to exploit the spatial correlations of the NBI and IN across the receive antennas and powerlines to convert a non-contiguous NBI and IN problem to a block-sparse estimation problem with much lower complexity. Furthermore, we investigate a Bayesian linear minimum mean square error based approach for estimating both non-contiguous and contiguous NBI and IN based on their second-order statistics to further improve the estimation performance. Finally, our numerical results illustrate the superiority of the joint processing of our proposed NBI and IN sparsity-based mitigation techniques compared to separate processing of the wireless and powerline received signals.