THESIS
2022
1 online resource (xxiii, 212 pages) : illustrations (some color)
Abstract
This thesis presents novel signal processing techniques and performance analysis of future
communication technologies for the upcoming beyond 5G (B5G) and sixth-generation
(6G) wireless communication systems. Broadly speaking, the thesis is divided into two
parts: the first on classical communications, the second on quantum communications. In
the first part, we focus on reconfigurable intelligent surface (RIS), which is a new energy
efficient physical layer technology proposed for B5G/6G systems. We propose a deep
learning based channel estimation scheme for RIS-assisted communication systems. In
order to reduce the high pilot overhead due to the passive RIS elements, ‘On-Off’ based
and ‘Grouping’ based adaptive transmission schemes are investigated. We derive an upper
bound on the achi...[
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This thesis presents novel signal processing techniques and performance analysis of future
communication technologies for the upcoming beyond 5G (B5G) and sixth-generation
(6G) wireless communication systems. Broadly speaking, the thesis is divided into two
parts: the first on classical communications, the second on quantum communications. In
the first part, we focus on reconfigurable intelligent surface (RIS), which is a new energy
efficient physical layer technology proposed for B5G/6G systems. We propose a deep
learning based channel estimation scheme for RIS-assisted communication systems. In
order to reduce the high pilot overhead due to the passive RIS elements, ‘On-Off’ based
and ‘Grouping’ based adaptive transmission schemes are investigated. We derive an upper
bound on the achievable rate, and present closed form approximations for the optimum
number of RIS elements to be switched on, and the optimum group size that maximizes
the achievable rate. We also analyze the performance of a RIS-assisted communication
system, where we characterize the statistical properties of the received signal-to-noise ratio
and derive analytical approximations for the outage probability, average achievable
rate and average symbol error probability.
The second part of the thesis focuses on quantum key distribution (QKD) protocols,
that can be used for ultra-secure data transmission in B5G/6G networks. We propose
a multiple-input multiple-output (MIMO) transmission scheme for a continuous variable
QKD (CV-QKD) system operating at terahertz (THz) frequencies and solve related channel
estimation and secret key rate (SKR) analysis problems. The MIMO CV-QKD scheme
helps to overcome the high path loss at THz frequencies and improves the SKR of the
system. In the last part of the thesis, we propose data-driven algorithms for efficient
parameter estimation of single-mode Gaussian quantum states, which are an essential
component of the CV-QKD protocol for encoding the key information.
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