Alsabah, Muntadher ORCID: https://orcid.org/0000-0001-7937-3093 (2020) Downlink Training Sequence Design Based on Achievable Sum Rate Maximisation in FDD Massive MIMO Systems. PhD thesis, University of Sheffield.
Abstract
This thesis addresses the key technical challenges related to the design of the downlink (DL) training sequence for the channel state information (CSI) estimation in frequency division duplex (FDD) massive multiple-input multiple-output (massive MIMO) systems with single- stage precoding and limited coherence time. To this end, a computationally feasible solutions for designing the DL training sequences are proposed and novel closed-form solutions for the optimum pilot length that maximises the sum rate with single-stage precoding and limited coherence time are derived. The results in this thesis show that for practical base station (BS) array sizes of N < 250 antennas and limited coherence time, the sum rate of an FDD system using DL channel estimation is comparable to the performance of a time division duplex (TDD) system. The results demonstrate that for array sizes of N > 50 the diversity of spatial correlations between multiple users achieved more than 40 bits/s/Hz improvement in the sum rate of the regularised zero forcing (RZF) precoder in comparison to uncorrelated channels with identical channel covariance matrices. Finally, the analyses of the complexity results in this thesis show that more than four orders-of-magnitude reduction in the computational complexity is achieved using the superposition design, which signifies the feasibility of this approach for practical implementations compared with state-of-the-art training designs. An asymptotic random matrix theory along with the P-degrees of freedom (P-DoF) channel model are adopted in this thesis to develop an analytical closed-form solution for the sum rate of the beamforming (BF) and RZF precoders, with perfect and imperfect CSI estimation. Excellent agreement between the numerical, analytical and simulated results are obtained, which underpins the contributions of this research. Overall, the proposed approaches open up the possibility for FDD massive MIMO systems operating in a general scenario of single-stage precoding and more realistic channel conditions, particularly channel correlation and limited coherence time.
Metadata
Supervisors: | O'Farrell, Timothy |
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Keywords: | Channel estimation, spatial correlation, achievable sum rate, mean square error, training sequence design, channel state information, random matrix theory. |
Awarding institution: | University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Electronic and Electrical Engineering (Sheffield) |
Identification Number/EthosID: | uk.bl.ethos.816926 |
Depositing User: | Mr Muntadher Alsabah |
Date Deposited: | 25 Oct 2020 23:27 |
Last Modified: | 01 Dec 2021 10:53 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:27916 |
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