Interference management in large-scale MIMO systems for 5G

Zahran Hajji 1, 2
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : The thesis is part of the prospect of the explosion of data traffic generated by the increase of the number of users as well as the growth of the bit rate which must be taken into account in the definition of future generations of radio-cellular communications. A solution is the large-scale MIMO technology (MIMO systems oflarge size) which poses several challenges. The design of the new low complexity detection algorithms is indispensable since the conventional algorithms are no longer adapted to this configuration because of their poor detection performance or their too high complexity depending on the number of antennas. A first contribution of the thesis is an algorithm based on the technique of compressed sensing by exploiting the propertiesof the signals with finite alphabet. Applied to large-scale, determined and under-determined MIMO systems, this algorithm achieves promising and superior performance (quality ofdetection, complexity) compared to state-ofthe-art algorithms. A thorough theoretical study was conducted to determine the optimal operating conditions and the statistical distribution of outputs. A second contribution is the integration of the original algorithm into an iterative receiver by differentiating the coded and uncoded cases. Another challenge to keeping the promise of large- scale MIMO systems (high spectral efficiency) is channel estimation. A third contribution of the thesis is the proposal of semi-blind channel estimation algorithms that work with a minimum size of pilot sequences (equal to the number of users) and reach performances very close to the theoretical bound.
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Submitted on : Tuesday, September 17, 2019 - 3:33:06 PM
Last modification on : Thursday, September 19, 2019 - 1:19:16 AM


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  • HAL Id : tel-02290325, version 1


Zahran Hajji. Interference management in large-scale MIMO systems for 5G. Signal and Image processing. Ecole nationale supérieure Mines-Télécom Atlantique, 2018. English. ⟨NNT : 2018IMTA0109⟩. ⟨tel-02290325⟩



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