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Article Performance Evaluation of Empirical Path Loss Models for a Linear Wireless Sensor Network Deployment in Suburban and Rural Environments(2020) Dalveren, Yaser; Kara, AliThis article presents a preliminary propagation study on the accuracy of empirical path loss models for efficient planning and deployment of a linear wireless sensor network (LWSN) based on long range (LoRa) enabled sensor nodes in suburban and rural environments. Real-world deployment of such network requires accurate path loss modelling to estimate the network coverage and performance. Although several models have been studied in the literature to predict the path loss for LoRa links, the assessment of empirical path loss models within the context of low-height peer to peer configured system has not been provided yet. Therefore, this study aims at providing a performance evaluation of well-known empirical path loss models including the Log-distance, Okumura, Hata, and COST-231 Hata model in a peer to peer configured system where the sensor nodes are deployed at the same low heights. To this end, firstly, measurement campaigns are carried out in suburban and rural environments by utilizing LoRa enabled sensor nodes operating at 868 MHz band. The measured received signal strength values are then compared with the predicted values to assess the prediction accuracy of the models. The results achieved from this study show that the Okumura model has higher accuracyArticle 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: 9Multipath Exploitation in Emitter Localization for Irregular Terrains(Spolecnost Pro Radioelektronicke inzenyrstvi, 2019) Dalveren, Yaser; Kara, AliElectronic Support Measures (ESM) systems have many operational challenges while locating radar emitter's position around irregular terrains such as islands due to multipath scattering. To overcome these challenges, this paper addresses exploiting multipath scattering in passive localization of radar emitters around irregular terrains. The idea is based on the use of multipath scattered signals as virtual sensor through Geographical Information System (GIS). In this way, it is presented that single receiver (ESM receiver) passive localization can be achieved for radar emitters. The study is initiated with estimating candidate multipath scattering centers over irregular terrain. To do this, ESM receivers' Angle of Arrival (AOA) and Time of Arrival (TOA) information are required for directly received radar pulses along with multipath scattered pulses. The problem then turns out to be multiple-sensor localization problem for which Time Difference of Arrival (TDOA)-based techniques can easily be applied. However, there is high degree of uncertainty in location of candidate multipath scattering centers as the multipath scattering involves diffuse components over irregular terrain. Apparently, this causes large localization errors in TDOA. To reduce this error, a reliability based weighting method is proposed. Simulation results regarding with a simplified 3D model are also presented.Article A Case Study on the Assessment of Rf Switch and Splitter Options for Coupling of Transceiver Modules To Bidirectional Antennas Employed in Linear Wireless Sensor Networks(Wiley, 2021) Dalveren, Yaser; Durukan, Ahmet Mert; Kara, AliRecently, a concept of linear wireless sensor networks (LWSNs) has attracted much attention. For such networks, one of the key challenges in sensor node design is to couple transceiver modules with bidirectional antennas placed back-to-back for opposite radiation. As is known, simply, this can be achieved by using well-known coupling options like radio frequency (RF) switch or splitter. However, it is important to decide between two seemingly equally good options according to the system requirements such as RF performance, power consumption, and cost. Therefore, this study aims to comparatively assess these options from the system level point of view to find out what advantages or disadvantages either provides as per the other from widespread use of them in a LWSN-based cathodic protection monitoring of oil and natural gas pipelines in extreme environments. Preliminary field tests are also conducted to validate the efficiency of coupling options for LWSN links. Results show that RF splitter offers low power consumption and cost whereas RF switch has advantages of low loss. Thus, it is believed that this study may provide useful insights to design bidirectional sensor links for LWSNs.Article Citation - WoS: 7Citation - Scopus: 8Flexible and Lightweight Mitigation Framework for Distributed Denial-Of Attacks in Container-Based Edge Networks Using Kubernetes(Ieee-inst Electrical Electronics Engineers inc, 2024) Koksal, Sarp; Catak, Ferhat Ozgur; Dalveren, YaserMobile Edge Computing (MEC) has a significant potential to become more prevalent in Fifth Generation (5G) networks, requiring resource management that is lightweight, agile, and dynamic. Container-based virtualization platforms, such as Kubernetes, have emerged as key enablers for MEC environments. However, network security and data privacy remain significant concerns, particularly due to Distributed Denial-of-Service (DDoS) attacks that threaten the massive connectivity of end-devices. This study proposes a defense mechanism to mitigate DDoS attacks in container-based MEC networks using Kubernetes. The mechanism dynamically scales Containerized Network Functions (CNFs) with auto-scaling through an Intrusion Detection and Prevention System (IDPS). The architecture of the proposed mechanism leverages distributed edge clusters and Kubernetes to manage resources and balance the load of IDPS CNFs. Experiments conducted in a real MEC environment using OpenShift and Telco-grade MEC profiles demonstrate the effectiveness of the proposed mechanism against Domain Name System (DNS) flood and Yo-Yo attacks. Results also verify that Kubernetes efficiently meets the lightweight, agile, and dynamic resource management requirements of MEC networks.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.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: 7A Simplified Method Based on Rssi Fingerprinting for Iot Device Localization in Smart Cities(Ieee-inst Electrical Electronics Engineers inc, 2024) Dogan, Deren; Dalveren, Yaser; Kara, Ali; Derawi, MohammadThe Internet of Things (IoT) has significantly improved location-based services in smart cities, such as automated public transportation and traffic management. Estimating the location of connected devices is a critical problem. Low Power Wide Area Network (LPWAN) technologies are used for localization due to their low power consumption and long communication range. Recent advances in Machine Learning have made Received Signal Strength Indicator (RSSI) fingerprinting with LPWAN technologies effective. However, this requires a connection between devices and gateways or base stations, which can increase network deployment, maintenance, and installation costs. This study proposes a cost-effective RSSI fingerprinting solution using IQRF technology for IoT device localization. The region of interest is divided into grids to provide training locations, and measurements are conducted to create a training dataset containing RSSI fingerprints. Pattern matching is performed to localize the device by comparing the fingerprint of the end device with the fingerprints in the created database. To evaluate the efficiency of the proposed solution, measurements were conducted in a short-range local area ( $80\times 30$ m) at 868 MHz. In the measurements, four IQRF nodes were utilized to receive the RSSIs from a transmitting IQRF node. The performances of well-known ML classifiers on the created dataset are then comparatively assessed in terms of test accuracy, prediction speed, and training time. According to the results, the Bagged Trees classifier demonstrated the highest accuracy with 96.87%. However, with an accuracy of 95.69%, the Weighted k-NN could also be a reasonable option for real-world implementations due to its faster prediction speed (37615 obs/s) and lower training time (28.1 s). To the best of the authors' knowledge, this is the first attempt to explore the feasibility of the IQRF networks to develop a RSSI fingerprinting-based IoT device localization in the literature. The promising results suggest that the proposed method could be used as a low-cost alternative for IoT device localization in short-range location-based smart city applications.Conference Object Citation - WoS: 3Comparative Analysis of Tdoa-Based Localization Methods in the Presence of Sensor Position Errors(Ieee, 2017) Dalveren, Yaser; Kara, AliIt is widely known that localization of emitters can be efficiently achieved by time difference of arrival (TDOA) techniques in a multiple sensor system. Several studies have been proposed in the literature to improve the localization accuracy of TDOA techniques. Among these, very few of them have considered the error in the sensor positions although the accuracy of localization is very sensitive to sensor position errors. In this study, existing TDOA-based localization methods in the presence of sensor position errors are briefly discussed, and then they are comparatively analyzed for specific scenarios. To this end, simulations are performed to compare the localization accuracy of the methods, specifically, with high level of sensor positional errors. It is intended to decide an efficient and robust estimator to be used for an ongoing research on passive localization of radar emitters in dense scattering environments.Article Citation - WoS: 6Citation - Scopus: 7An Enhanced Course in Digital Communications(Tempus Publications, 2014) Kara, Ali; Cagiltay, Nergiz Ercil; Dalveren, Yaser; Department of Electrical & Electronics Engineering; Software EngineeringToday technological improvements provide several alternatives and opportunities for improving traditional educational systems. However, integrating these technologies in an appropriate and successful way into the curriculum of traditional systems is a challenge. This work presents the enhancements added to an undergraduate course on Digital Communications which is an introductory course offered to senior undergraduates or first year graduate students. The Digital Communications course covers some essential stages in a typical digital communication system, namely, signal formatting such as analog to digital conversion, baseband modulation and bandpass modulation by concentrating on demodulation and detection at the receiver end. The enhancements include computer simulations, web-based simulation tools and remote laboratory experiments along with several out of class activities. The enhancements have improved the course significantly by supporting constructivist and blended learning methods. The improvement to the course was demonstrated over two years, from the student progress assessed from the collated results of the student evaluation forms and a questionnaire on the course learning outcomes, and a comparison of their performance in the written exams. The results show that there is a significant improvement both in the progress and satisfaction of the students on the enhanced course curriculum. This study shows how different technologies have been successfully integrated to the curriculum of Digital Communications course in a higher education organization and concludes its success factors.
