Modelling and simulation of the complex received signal in wireless communication systems

Abstract

More than ever, emerging wireless communication systems will be expected to offer high-quality service whilst continuing to push the boundaries on reliability and efficiency. This is made even more challenging due to an increasing diversity of use cases, meaning that the propagation conditions encountered are often non-trivial and may not always conform to the classical assumption of independent and identically distributed, Gaussian quadrature components. As will be shown in this thesis, extrapolations made from the received signal envelope to the complex domain may also lead to incorrect assumptions on the properties of the fading that is encountered, impacting any ensuing system performance analysis. Additionally, for a more complex characterisation of the complex received signal and assessment of system performance, often overlooked spatiotemporal effects are required. To address these challenges, the work in this thesis has focused on the modelling of complex received signals, accounting for intricate fading conditions likely to be encountered in emergent applications. This thesis first investigates the influence that line-of-sight (LoS) shadowing has on a complex received signal, which undergoes Rician fading. Therein, the results are used to analyse the performance of systems using phase-based modulation schemes. This is followed by a study that aims to unify LoS, non-line-of-sight (NLoS), and quasi-line-of-sight (QLoS) propagation states within a single fading model. The fundamental statistics of this novel fading model are explored, including the complex autocorrelation function (ACF). The versatility and validity of the model have been empirically studied using two example use cases. Aiming to improve the performance of cooperative reconfigurable intelligent surface (RIS) based systems, a new simulation framework is proposed. It combines knowledge of the fading experienced in the wireless channel and a system model for cooperative RIS operation. The utility of the proposed simulation framework is demonstrated through some examples, which are used to provide insights into the influence of spatiotemporal effects on system performance.

Date of Award	Jul 2022
Original language	English
Awarding Institution	Queen's University Belfast
Sponsors	Northern Ireland Department for the Economy
Supervisor	Simon Cotton (Supervisor) & David Morales (Supervisor)