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Yayın Comparative performance evaluation of VLC, LTE and WLAN technologies in indoor environments(IEEE, 2021-05-24) Zeshan, Arooba; Karbalayghareh, Mehdi; Miramirkhani, Farshad; Uysal, Murat; Baykaş, TunçerRecent years have seen an exponential rise in the demand for indoor wireless connections that have driven future generation networks to aim for higher data rates with extended coverage and affordable rates. The two most prominent technologies for providing indoor wireless connections, WLAN and LTE, have their limitations and they can not coexist in a single band to form heterogeneous networks (HetNets). Visible light communication (VLC) has seen rapid growth in recent years as it has the capability to seamlessly merge with the existing technologies and provide wireless connections with high data rates. VLC based hybrid indoor network effectively combines the preferences of an end-user with the practicality of implementation. In this work, we investigate specific VLC/WLAN and VLC/LTE hybrid scenarios to perform a detailed analysis on the effect of user mobility on the performance of the system and how the performance of the network (in terms of throughput) can be maximized. The study aims to show how different technologies complement each other in the best and even the worst-case scenarios.Yayın Path loss and RMS delay spread model for VLC-based patient health monitoring system(Institute of Electrical and Electronics Engineers Inc., 2022-05-13) Dönmez, Barış; Miramirkhani, FarshadVisible Light Communication (VLC) emerges as a supplementary technology to ubiquitous Radio Frequency (RF) since VLC meets the very high data rate, very high reliability, and ultra-low latency requirements driven by the trends in beyond-5G communication systems. Since VLC offers a solution to Electromagnetic Interference (EMI) and security problems in hospital environments, it becomes a better alternative for Medical Body Sensor Networks (MBSNs). Nonetheless, user mobility in a 3D environment causes a degradation in channel DC gain that leads to an optical path loss and also affects the time dispersive properties of multipath channels. In our paper, we adopt a ray tracing-based site-specific channel modeling method to characterize VLC-based MBSNs channel parameters. Based on the channel characteristics, we propose statistical models for path loss and Root Mean Square (RMS) delay spread in realistic Intensive Care Unit (ICU) ward and Family-Type Patient Room (FTPR) where user upon which three MBSNs nodes placed walks over extensive realistic random trajectories. The simulation results indicate that both path loss and RMS delay spread follow a log-normal distribution.Yayın Optimizing indoor localization accuracy with neural network performance metrics and software-defined IEEE 802.11az Wi-Fi set-up(IEEE, 2023-10-28) Kouhalvandi, Lida; Aygün, Sercan; Matekovits, Ladislau; Miramirkhani, FarshadAccurately classifying regions based on Wi-Fi signals can be a difficult task, especially when considering different frequency values. In this study, we aimed to improve the accuracy of indoor localization by developing a novel approach that does not rely on pre-trained models. To achieve this, fingerprints from the IEEE 802.11az standard were randomly selected, and the data samples were trained using parameterized station characteristics and neural network hyperparameters. The impact of each parameter on the localization accuracy was measured, and performance monitoring metrics such as F1-Measure and confusion matrix-based metrics were evaluated. Furthermore, the Thompson sampling (TS) algorithm was employed to determine the optimal parameters, which helped to achieve the best possible accuracy. The proposed approach demonstrated improved accuracy in region localization compared to conventional heuristic approaches which typically yield an accuracy range of 65% to 77%. The proposed approach achieved up to 80% accuracy in region localization and could be a promising solution for indoor localization in various settings.Yayın Channel modeling and characterization for VLC-based MBSNs impaired by 3D user mobility(IEEE, 2021-11-27) Dönmez, Barış; Miramirkhani, FarshadThis paper focuses on channel modeling and characterization of indoor visible light communication (VLC)-based medical body sensor networks (MBSNs) which establish links between light-emitting diodes (LEDs) and MBSNs nodes couple with photodetectors (PDs) placed on the shoulder (D1), wrist (D2), and ankle (D3) of the mobile user who walks over random trajectories in 3D scenarios of ICU ward and family type patient room. We adopt non-sequential ray-tracing to obtain channel impulse responses (CIRs) and channel characteristics over random trajectories. Based on simulation results, it is observed that channel DC gains exhibit sinusoidal behaviour for D1 and D2 except for D3 (i.e., due to the number of diffuse rays received at D3), as the user approaches and moves away from the luminaries. It is also revealed that a flat fading channel can be modeled if a data rate lower than 7.03 Mbit/s, i.e., sufficient for MBSNs applications, is chosen.Yayın A path loss model for vehicle-to-vehicle visible light communications(Institute of Electrical and Electronics Engineers Inc., 2019-07) Eldeeb, Hossien Badr; Miramirkhani, Farshad; Uysal, MuratThe increasing adoption of LEDs in exterior automotive lighting makes visible light communication (VLC) a natural solution for vehicular networking. In this paper, we consider a vehicle-to-vehicle link and propose a path loss expression as a function of distance and different weather conditions. We conduct ray tracing simulations and verify the accuracy of proposed expression. We further use this expression to derive the achievable transmission distance for a targeted data rate while satisfying a given value of bit error rate. Numerical results are presented to demonstrate the achievable distances for single and dual photodetector deployment cases.Yayın Machine learning for adaptive modulation in medical body sensor networks using visible light communication(Institute of Electrical and Electronics Engineers Inc., 2024) Rizi, Reza Bayat; Forouzan, Amir Reza; Miramirkhani, Farshad; Sabahi, Mohamad FarzanIn the context of medical body sensor networks that rely on visible light communication (VLC), adaptive modulation plays a crucial role. Despite VLC's advantages, challenges arise due to fluctuating signal strength caused by patient movement. To address this, we propose an adaptive modulation system that adjusts based on link conditions, specifically the signal-to-noise ratio (SNR). Our approach involves an uplink channel for feedback, allowing the receiver to select the appropriate modulation scheme based on measured SNR after noise mitigation. The analysis focuses on various medical situations and investigates machine learning algorithms. The study compares adaptive modulation based on supervised learning with that based on reinforcement learning. By implementing a bi-directional system with real-time modulation tracking, we demonstrate the effectiveness of adaptive VLC in handling environmental changes (interference and noise). Notably, the use of the Q-learning algorithm enables real-time adaptation without prior knowledge of the environment. Our simulation results show that photodetectors placed on the shoulder and wrist benefit significantly from this approach, experiencing improved performance.
