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Cell-Free massive MIMO receiver design and channel estimation

Abstract : Next generation wireless systems shall satisfy the increasing demand of higher and higher data rates at very competitive prices as well as be able to efficiently accommodate for and adapt to a huge dynamic range of services, applications, and types of devices expected in the near. Appealing architectural solutions have been leveraged on ultra-densification of antennas. Ultra-dense wireless systems envision ultra-dense distributed antenna systems (UD-DAS) based on remote distributed antennas empowered by the e-cloud. However, neither DAS nor massive MIMO technology will meet the increasing data rate demands of the next generation wireless communications due to the inter-cell interference and large quality of service (QoS) variations. To address these limitations, beyond-5G networks need to enter the cell-free (CF) paradigm, where the absence of cell boundaries mitigates the inter-cell interference and handover issues but also causes new challenges. One of the major issues in the large-scale networks such as CF massive MIMO systems is complexity at the receivers. In this regard, first part of this thesis is devoted to analyzing the favorable propagation properties of CF massive MIMO systems in asymptotic conditions. Channel state information (CSI) in massive MIMO systems, both cellular and CF, plays a major role in improving the system performance. Therefore, in the second part of this thesis, we address the pilot contamination problem in CF massive MIMO systems. Finally, in the last part of this thesis, we propose an MP algorithm based on the EP principle to iteratively conduct the Bayesian semi-blind method for channel estimation and data detection in CF massive systems.
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Submitted on : Wednesday, February 9, 2022 - 1:48:08 PM
Last modification on : Friday, February 11, 2022 - 9:43:37 AM
Long-term archiving on: : Tuesday, May 10, 2022 - 6:46:36 PM


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  • HAL Id : tel-03563050, version 1


Roya Gholamipourfard. Cell-Free massive MIMO receiver design and channel estimation. Networking and Internet Architecture [cs.NI]. Sorbonne Université, 2021. English. ⟨NNT : 2021SORUS285⟩. ⟨tel-03563050⟩



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