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The uplink reception and downlink transmission in MU-MIMO for 5G

Abstract : Multiple-input multiple-output (MIMO) technologies were developed to increase system capacity and offer better link reliability. They allow a dense network architecture that will allow many users to connect in the same area without experiencing slowdowns. 5G networks and beyond will use these MIMO technologies with many small antennas allowing the beam to be focused on a given area. Coupled with high-frequency bands, the use of these antennas will significantly increase throughput.In such systems, multi-user (MU)-MIMO detection in the uplink reception and MU-MIMO precoding in the downlink transmission enable separating user data streams and pre-cancelling interference. However, some challenges have to be met under realistic conditions such as the reasonable complexity of the decoding and precoding processes, the erroneous channel knowledge, and the adjacent cell interference. This thesis addresses all these limitations above for the uplink reception and the downlink transmission in MU-MIMO systems.In the uplink reception, we study the well-known sphere decoding (SD) algorithm for MIMO detection. We seek to reduce its complexity which increases exponentially with the number of antennas and the constellation size. Thus, we profit from recent advances in neural networks (NNs) to develop the low-complexity NN assisted SD. We also propose the block recursive MIMO decoding, which achieves almost the maximum likelihood (ML) performance. Using deep neural networks (DNNs), we suggest a new and low complex scheme for signal processing and cloud-RAN (C-RAN) detection. This DNN scheme aims to mimic the whole transmission in uplink C-RAN, which considers the quantization constraints at the radio remote units (RRUs) and the corrupted observations at the central processor (CP).In the downlink transmission, we study the non-linear vector perturbation (VP) precoding. We design the combined VP to serve multiple users with different modulation coding schemes (MCSs). We also introduce the block VP algorithm, which merges both linear and non-linear precoding to offer a tunable tradeoff between complexity and performance. To deal with the erroneous channel state information (CSI) in the downlink precoding, we develop the new CSI accuracy indicator reporting to design a novel precoder that is less sensitive to CSI errors.
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Submitted on : Saturday, July 3, 2021 - 1:01:42 AM
Last modification on : Tuesday, October 19, 2021 - 11:14:15 AM
Long-term archiving on: : Monday, October 4, 2021 - 6:01:26 PM


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  • HAL Id : tel-03277330, version 1


Aymen Askri. The uplink reception and downlink transmission in MU-MIMO for 5G. Networking and Internet Architecture [cs.NI]. Institut Polytechnique de Paris, 2021. English. ⟨NNT : 2021IPPAT006⟩. ⟨tel-03277330⟩



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