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A ray-based approach for massive MIMO systems: Statistical analysis and digital processing

Abstract : Moving from small-scale MIMO to large scale massive MIMO systems leads to a paradigm shift in digital processing techniques. Indeed, the complexity of classical signal processing algorithms scales with the antenna array sizes, so does the system angular resolution. It is then interesting to take advantage of the angular dimension properties of the propagation in the processing to constraint the algorithmic complexity while controlling the performance. In this thesis, we first studied and characterized multi-path propagation channels, with due consideration to the Saleh-Valenzuela model. This preliminary study provided us with a simplified cluster model. From this model, we studied theoretically the cluster separation problem and proposed a novel algorithm for this purpose. We also applied this model to assess the limits of cluster extrapolation for FDD precoding. We finally proposed enhancements to OMP-based Massive MIMO channel estimation that leverages the sparsity of millimeter wave channels.
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Contributor : Matthieu ROY Connect in order to contact the contributor
Submitted on : Thursday, August 4, 2022 - 4:08:20 PM
Last modification on : Thursday, August 4, 2022 - 6:02:04 PM


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  • HAL Id : tel-03745871, version 1


Matthieu Roy. A ray-based approach for massive MIMO systems: Statistical analysis and digital processing. Signal and Image processing. Institut National des Sciences Appliquées de Rennes, 2020. English. ⟨tel-03745871⟩



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