Estimation and detection theory in visible light communication systems: a perspective on realistic receivers

Abstract

Visible light communications (VLC) has been proposed as a promising way for nextgeneration wireless communication networks to mitigate the scarcity of the radio frequency (RF) spectrum, and has consequently attracted much attention. Accordingly, this thesis investigates single-input single-output (SISO) VLC when subject to signaldependent shot noise (SDSN). Firstly, we consider the case of fixed-location user located in an indoor environment. For instance, in a classroom setting, a teacher may utilize VLC to transmit lecture notes and supplementary materials to students’ tablets or laptops, ensuring a seamless exchange of information without the need for traditional wireless networks. The topics of discussion include channel estimation and data transmission, where in the former, we introduce both least square (LS) and maximum likelihood (ML) estimators. The Cramér–Rao lower bound (CRLB) of the channel estimation error is also derived. In terms of data transmission, we propose optimal and sub-optimal receiver designs and present their bit error rate (BER) performances. In specific, we derive a closed-form expression of the BER for the sub-optimal receiver and an approximated version for the optimal one. Our analysis indicates that the performance of the CRLB demonstrates no linear relationship with the SDSN, thermal noise, or fading channel gain. On the other hand, SDSN has quite a severe effect on the channel estimation error bound, and as such, it can dramatically degrade the BER performance. Heightened performance degradation can also be explained by the joint effects of the channel estimation error and SDSN. Secondly, we consider the case of random location of the user located in an indoor environment, such as a conference room within a corporate office where the user may move around freely during a meeting or presentation. In particular, the second part of this research estimates the channel of the considered system using ML, LS, linear minimum mean square error (LMMSE), maximum posteriori probability (MAP) and minimum mean square error (MMSE) estimators. Furthermore, a Bayesian Cramér-Rao lower bound (BCRLB) is derived for the proposed system and it is compared to the mean square error (MSE) of the proposed estimators. The problem of the unknown SDSN factor at the receiver side is discussed and two solutions are investigated. The receiver of a VLC system under SDSN and random channel gain is designed and its BER is studied. Monte Carlo simulation results of the proposed estimators, which show the dramatic effect of the SDSN on the considered system, are provided. In particular, the presence of noise variance, as well as the SDSN factor, causes an increase in the MSE of the system, while increasing the power reinforces the system performance. Moreover, the third part of this research explores the interplay between SDSN and another inherent noise in the light source called relative intensity noise (RIN), revealing their combined adverse effect on channel estimation accuracy in a VLC system. Towards this direction, we first derive CRLB in the presence of the SDSN and the RIN, which gives a lower estimate for the variance of an unbiased estimator. Then, we present the derivation of LS and ML channel estimators. Furthermore, we present the optimal receiver in ML sense and compare it with a simple threshold detector as a sub-optimal solution, quantifying the impact of channel estimation accuracy on both receivers. The findings presented in this part reveal that the RIN and the SDSN jointly have a significant adverse effect on the VLC channel estimation, consequently leading to a pronounced degradation in BER performance of the VLC system. In addition, we proposed optimal and sub-optimal receiver designs and present their BER. The Monte Carlo simulation results of the BER for the two presented receivers show that the optimal receiver performance excels beyond the performance of the sub-optimal receiver. In other words, our study focuses on investigating the effects of signal-dependent noise in VLC systems. Initially, we explored how SDSN impacts VLC systems serving fixed-location users. Subsequently, we delved into the influence of SDSN in scenarios where channel gain variability arises from the randomness of user locations. Following, we analyzed the combined impact of SDSN and RIN on the performance of VLC systems catering to fixed-location users in indoor environments. Our investigation involved the use of various channel estimation techniques, which were compared against a derived lower bound to evaluate their performance. Additionally, we designed different receivers to demonstrate how such noise affects the BER of the considered VLC systems.