31 research outputs found

    Sparsity-Based Joint NBI and impulse noise mitigation in hybrid PLC-Wireless transmissions

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    We 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, 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. 2013 IEEE.This work was supported by NPRP through the Qatar National Research Fund (a member of Qatar Foundation) under Grant NPRP 8-627-2-260.Scopu

    Advanced DSP Algorithms For Modern Wireless Communication Transceivers

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    A higher network throughput, a minimized delay and reliable communications are some of many goals that wireless communication standards, such as the fifthgeneration (5G) standard and beyond, intend to guarantee for its customers. Hence, many key innovations are currently being proposed and investigated by researchers in the academic and industry circles to fulfill these goals. This dissertation investigates some of the proposed techniques that aim at increasing the spectral efficiency, enhancing the energy efficiency, and enabling low latency wireless communications systems. The contributions lay in the evaluation of the performance of several proposed receiver architectures as well as proposing novel digital signal processing (DSP) algorithms to enhance the performance of radio transceivers. Particularly, the effects of several radio frequency (RF) impairments on the functionality of a new class of wireless transceivers, the full-duplex transceivers, are thoroughly investigated. These transceivers are then designed to operate in a relaying scenario, where relay selection and beamforming are applied in a relaying network to increase its spectral efficiency. The dissertation then investigates the use of greedy algorithms in recovering orthogonal frequency division multiplexing (OFDM) signals by using sparse equalizers, which carry out the equalization in a more efficient manner when the low-complexity single tap OFDM equalizer can no longer recover the received signal due to severe interferences. The proposed sparse equalizers are shown to perform close to conventional optimal and dense equalizers when the OFDM signals are impaired by interferences caused by the insertion of an insufficient cyclic prefix and RF impairments

    EVALUATION OF COMPRESSED SENSING IN SYSTEMS UWB WITH NBI

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    EVALUATION OF COMPRESSED SENSING IN SYSTEMS UWB WITH NBI

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