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Article Citation - WoS: 9Citation - Scopus: 12On the Performance of Energy Criterion Method in Wi-Fi Transient Signal Detection(Mdpi, 2022) Mohamed, Ismail; Dalveren, Yaser; Catak, Ferhat Ozgur; Kara, AliIn the development of radiofrequency fingerprinting (RFF), one of the major challenges is to extract subtle and robust features from transmitted signals of wireless devices to be used in accurate identification of possible threats to the wireless network. To overcome this challenge, the use of the transient region of the transmitted signals could be one of the best options. For an efficient transient-based RFF, it is also necessary to accurately and precisely estimate the transient region of the signal. Here, the most important difficulty can be attributed to the detection of the transient starting point. Thus, several methods have been developed to detect transient start in the literature. Among them, the energy criterion method based on the instantaneous amplitude characteristics (EC-a) was shown to be superior in a recent study. The study reported the performance of the EC- a method for a set of Wi-Fi signals captured from a particular Wi-Fi device brand. However, since the transient pattern varies according to the type of wireless device, the device diversity needs to be increased to achieve more reliable results. Therefore, this study is aimed at assessing the efficiency of the EC-a method across a large set ofWi-Fi signals captured from variousWi-Fi devices for the first time. To this end, Wi-Fi signals are first captured from smartphones of five brands, for a wide range of signalto-noise ratio (SNR) values defined as low (3 to 5 dB), medium (5 to 15 dB), and high (15 to 30 dB). Then, the performance of the EC-a method and well-known methods was comparatively assessed, and the efficiency of the EC-a method was verified in terms of detection accuracy.Article Citation - WoS: 14Citation - Scopus: 26Deep Learning-Based Vehicle Classification for Low Quality Images(Mdpi, 2022) Tas, Sumeyra; Sari, Ozgen; Dalveren, Yaser; Pazar, Senol; Kara, Ali; Derawi, MohammadThis study proposes a simple convolutional neural network (CNN)-based model for vehicle classification in low resolution surveillance images collected by a standard security camera installed distant from a traffic scene. In order to evaluate its effectiveness, the proposed model is tested on a new dataset containing tiny (100 x 100 pixels) and low resolution (96 dpi) vehicle images. The proposed model is then compared with well-known VGG16-based CNN models in terms of accuracy and complexity. Results indicate that although the well-known models provide higher accuracy, the proposed method offers an acceptable accuracy (92.9%) as well as a simple and lightweight solution for vehicle classification in low quality images. Thus, it is believed that this study might provide useful perception and understanding for further research on the use of standard low-cost cameras to enhance the ability of the intelligent systems such as intelligent transportation system applications.Article Citation - WoS: 8Citation - Scopus: 9Propagation Measurements for Iqrf Network in an Urban Environment(Mdpi, 2022) Bouzidi, Mohammed; Dalveren, Yaser; Mohamed, Marshed; Dalveren, Yaser; Moldsvor, Arild; Cheikh, Faouzi Alaya; Derawi, Mohammad; Dalveren, Yaser; Department of Electrical & Electronics Engineering; Department of Electrical & Electronics EngineeringRecently, IQRF has emerged as a promising technology for the Internet of Things (IoT), owing to its ability to support short- and medium-range low-power communications. However, real world deployment of IQRF-based wireless sensor networks (WSNs) requires accurate path loss modelling to estimate network coverage and other performances. In the existing literature, extensive research on propagation modelling for IQRF network deployment in urban environments has not been provided yet. Therefore, this study proposes an empirical path loss model for the deployment of IQRF networks in a peer-to-peer configured system where the IQRF sensor nodes operate in the 868 MHz band. For this purpose, extensive measurement campaigns are conducted outdoor in an urban environment for Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) links. Furthermore, in order to evaluate the prediction accuracy of well-known empirical path loss models for urban environments, the measurements are compared with the predicted path loss values. The results show that the COST-231 Walfisch-Ikegami model has higher prediction accuracy and can be used for IQRF network planning in LoS links, while the COST-231 Hata model has better accuracy in NLoS links. On the other hand, the effects of antennas on the performance of IQRF transceivers (TRs) for LoS and NLoS links are also scrutinized. The use of IQRF TRs with a Straight-Line Dipole Antenna (SLDA) antenna is found to offer more stable results when compared to IQRF (TRs) with Meander Line Antenna (MLA) antenna. Therefore, it is believed that the findings presented in this article could offer useful insights for researchers interested in the development of IoT-based smart city applications.Article Citation - WoS: 6Citation - Scopus: 10Lpwan Cyber Security Risk Analysis: Building a Secure Iqrf Solution(Mdpi, 2023) Bouzidi, Mohammed; Amro, Ahmed; Dalveren, Yaser; Cheikh, Faouzi Alaya; Derawi, MohammadLow-power wide area network (LPWAN) technologies such as IQRF are becoming increasingly popular for a variety of Internet of Things (IoT) applications, including smart cities, industrial control, and home automation. However, LPWANs are vulnerable to cyber attacks that can disrupt the normal operation of the network or compromise sensitive information. Therefore, analyzing cybersecurity risks before deploying an LPWAN is essential, as it helps identify potential vulnerabilities and threats as well as allowing for proactive measures to be taken to secure the network and protect against potential attacks. In this paper, a security risk analysis of IQRF technology is conducted utilizing the failure mode effects analysis (FMEA) method. The results of this study indicate that the highest risk corresponds to four failure modes, namely compromised end nodes, a compromised coordinator, a compromised gateway and a compromised communication between nodes. Moreover, through this methodology, a qualitative risk evaluation is performed to identify potential security threats in the IQRF network and propose countermeasures to mitigate the risk of cyber attacks on IQRF networks.Article Citation - WoS: 2Citation - Scopus: 3Modelling and Design of Pre-Equalizers for a Fully Operational Visible Light Communication System(Mdpi, 2023) Bostanoglu, Murat; Dalveren, Yaser; Catak, Ferhat Ozgur; Kara, AliNowadays, Visible Light Communication (VLC) has gained much attention due to the significant advancements in Light Emitting Diode (LED) technology. However, the bandwidth of LEDs is one of the important concerns that limits the transmission rates in a VLC system. In order to eliminate this limitation, various types of equalization methods are employed. Among these, using digital pre-equalizers can be a good choice because of their simple and reusable structure. Therefore, several digital pre-equalizer methods have been proposed for VLC systems in the literature. Yet, there is no study in the literature that examines the implementation of digital pre-equalizers in a realistic VLC system based on the IEEE 802.15.13 standard. Hence, the purpose of this study is to propose digital pre-equalizers for VLC systems based on the IEEE 802.15.13 standard. For this purpose, firstly, a realistic channel model is built by collecting the signal recordings from a real 802.15.13-compliant VLC system. Then, the channel model is integrated into a VLC system modeled in MATLAB. This is followed by the design of two different digital pre-equalizers. Next, simulations are conducted to evaluate their feasibility in terms of the system's BER performance under bandwidth-efficient modulation schemes, such as 64-QAM and 256-QAM. Results show that, although the second pre-equalizer provides lower BERs, its design and implementation might be costly. Nevertheless, the first design can be selected as a low-cost alternative to be used in the VLC system.Article Citation - WoS: 29Citation - Scopus: 33On the Performance of Variational Mode Decomposition-Based Radio Frequency Fingerprinting of Bluetooth Devices(Mdpi, 2020) Aghnaiya, Alghannai; Dalveren, Yaser; Kara, AliRadio frequency fingerprinting (RFF) is one of the communication network's security techniques based on the identification of the unique features of RF transient signals. However, extracting these features could be burdensome, due to the nonstationary nature of transient signals. This may then adversely affect the accuracy of the identification of devices. Recently, it has been shown that the use of variational mode decomposition (VMD) in extracting features from Bluetooth (BT) transient signals offers an efficient way to improve the classification accuracy. To do this, VMD has been used to decompose transient signals into a series of band-limited modes, and higher order statistical (HOS) features are extracted from reconstructed transient signals. In this study, the performance bounds of VMD in RFF implementation are scrutinized. Firstly, HOS features are extracted from the band-limited modes, and then from the reconstructed transient signals directly. Performance comparison due to both HOS feature sets is presented. Moreover, the lower SNR bound within which the VMD can achieve acceptable accuracy in the classification of BT devices is determined. The approach has been tested experimentally with BT devices by employing a Linear Support Vector Machine (LSVM) classifier. According to the classification results, a higher classification performance is achieved (similar to 4% higher) at lower SNR levels (-5-5 dB) when HOS features are extracted from band-limited modes in the implementation of VMD in RFF of BT devices.Data Paper Citation - WoS: 42Citation - Scopus: 62A Database for the Radio Frequency Fingerprinting of Bluetooth Devices(Mdpi, 2020) Uzundurukan, Emre; Dalveren, Yaser; Kara, AliRadio frequency fingerprinting (RFF) is a promising physical layer protection technique which can be used to defend wireless networks from malicious attacks. It is based on the use of the distinctive features of the physical waveforms (signals) transmitted from wireless devices in order to classify authorized users. The most important requirement to develop an RFF method is the existence of a precise, robust, and extensive database of the emitted signals. In this context, this paper introduces a database consisting of Bluetooth (BT) signals collected at different sampling rates from 27 different smartphones (six manufacturers with several models for each). Firstly, the data acquisition system to create the database is described in detail. Then, the two well-known methods based on transient BT signals are experimentally tested by using the provided data to check their solidity. The results show that the created database may be useful for many researchers working on the development of the RFF of BT devices.Article Citation - WoS: 6Citation - Scopus: 9Design and Optimization of Piezoelectric-Powered Portable Uv-Led Water Disinfection System(Mdpi, 2021) Sala, Derda E.; Dalveren, Yaser; Kara, Ali; Derawi, MohammadDue to the environmental pollution threatening human life, clean water accessibility is one of the major global issues. In this context, in literature, there are many portable water disinfection systems utilizing ultraviolet (UV) radiation. UV water disinfection systems employ piezoelectric-based electric power along with UV light-emitting diode (LED) sources. This paper elaborates on the detailed design and parametric optimization of a portable UV disinfection system. The proposed system aims to generate piezoelectric harvesting-based electrical power simply by shaking, and the generated power is then used to supply UV-LEDs for water disinfection. To this end, overall system parameters along with a physical-mathematical model of mechanical, electrical and biochemical aspects of the system are fully developed. Moreover, the main design parameters of the developed model are derived for optimal operation of the system by employing Genetic Algorithm (GA). Finally, optimal design parameters were identified for three different cost scenarios. The model can further be improved for practical implementation and mass production of the system.Article Citation - WoS: 2Citation - Scopus: 2Advancing Mmwave Altimetry for Unmanned Aerial Systems: a Signal Processing Framework for Optimized Waveform Design(Mdpi, 2024) Awan, Maaz Ali; Dalveren, Yaser; Kara, Ali; Derawi, MohammadThis research advances millimeter-wave (mmWave) altimetry for unmanned aerial systems (UASs) by optimizing performance metrics within the constraints of inexpensive automotive radars. Leveraging the software-defined architecture, this study encompasses the intricacies of frequency modulated continuous waveform (FMCW) design for three distinct stages of UAS flight: cruise, landing approach, and touchdown within a signal processing framework. Angle of arrival (AoA) estimation, traditionally employed in terrain mapping applications, is largely unexplored for UAS radar altimeters (RAs). Time-division multiplexing multiple input-multiple output (TDM-MIMO) is an efficient method for enhancing angular resolution without compromising the size, weight, and power (SWaP) characteristics. Accordingly, this work argues the potential of AoA estimation using TDM-MIMO to augment situational awareness in challenging landing scenarios. To this end, two corner cases comprising landing a small-sized drone on a platform in the middle of a water body are included. Likewise, for the touchdown stage, an improvised rendition of zoom fast Fourier transform (ZFFT) is investigated to achieve millimeter (mm)-level range accuracy. Aptly, it is proposed that a mm-level accurate RA may be exploited as a software redundancy for the critical weight-on-wheels (WoW) system in fixed-wing commercial UASs. Each stage is simulated as a radar scenario using the specifications of automotive radar operating in the 77-81 GHz band to optimize waveform design, setting the stage for field verification. This article addresses challenges arising from radial velocity due to UAS descent rates and terrain variation through theoretical and mathematical approaches for characterization and mandatory compensation. While constant false alarm rate (CFAR) algorithms have been reported for ground detection, a comparison of their variants within the scope UAS altimetry is limited. This study appraises popular CFAR variants to achieve optimized ground detection performance. The authors advocate for dedicated minimum operational performance standards (MOPS) for UAS RAs. Lastly, this body of work identifies potential challenges, proposes solutions, and outlines future research directions.Article Citation - WoS: 6Citation - Scopus: 6Indoor Propagation Analysis of Iqrf Technology for Smart Building Applications(Mdpi, 2022) Bouzidi, Mohammed; Gupta, Nishu; Dalveren, Yaser; Mohamed, Marshed; Alaya Cheikh, Faouzi; Derawi, MohammadOwing to its efficiency in the Internet of Things (IoT) applications in terms of low-power connectivity, IQRF (Intelligent Connectivity using Radio Frequency) technology appears to be one of the most reasonable IoT technologies in the commercial market. To realize emerging smart building applications using IQRF, it is necessary to study the propagation characteristics of IQRF technology in indoor environments. In this study, preliminary propagation measurements are conducted using IQRF transceivers that operate on the 868 MHz band in a peer-to-peer (P2P) configured system. The measurements are conducted both in a single corridor of a building in a Line-of-Sight (LoS) link and two perpendicular corridors in a Non-Line-of-Sight (NLoS) with one single knife-edge link. Moreover, the measured path loss values are compared with the predicted path loss values in order to comparatively assess the prediction accuracy of the well-known empirical models, such as log-distance, ITU, and WINNER II. According to the results, it is concluded that the ITU-1 path loss model agrees well with the measurements and could be used in the planning of an IQRF network deployment in a typical LoS corridor environment. For NLoS corridors, both ITU-3 and WINNERII-2 models could be used due to their higher prediction accuracy. We expect that the initial results achieved in this study could open new perspectives for future research on the development of smart building applications.

