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Article Distance Laboratory Applications ERRL: A Study on Radio Communication in Electronic Field(IEEE, 2008) Aydın, Cansu Çiğdem; Özyurt, E.; Aydın, Elif; Çağıltay, Nergiz; Özbek, Mehmet Efe; Alparslan, Ceren; Kara, AliIn the last decade, the effect of internet usage in education is gradually increased. When we look from academic perspective, the new technologies provided alternatives for students learning. As distance education becomes important everyday, the indispensable elements of teaching and education, laboratories must be reachable via remote connection. Consequently, the education that is going to be given to the students will be more flexible with respect to place and time constraints and students can reach laboratory facilities at any time and anywhere not only in lectures and practical hours. In this study, European Remote Radio Laboratory (ERRL) which is a distance remote Radio Frequency (RF) laboratory designed for electrical-electronics students, is described generally. The software architecture, infrastructure and experiment that can be done with a remote connection have been described.Conference Object An Overview of Challenges To Long-Term Sustainability and Scalability of Radio Frequency Fingerprinting(IEEE, 2024) Demiroglu, Harun Senol; Awan, Maaz Ali; Kara, AliInternet of Things (IoT) technology has become ubiquitous with a broad spectrum of applications. This vast penetration entails formidable cyber-security for the stable operation of the associated systems. Most inexpensive IoT devices employ rudimentary cryptographic security mechanisms due to their resource-limited architecture. Radio frequency fingerprinting (RFF) is a physical layer security mechanism that leverages hardware impairments for authentication and device classification. To this end, its scope has been limited to academia owing to daunting challenges. In this work, an abridged overview of the state-of-the-art is provided, along with a summary of the challenges that hinder progress toward practical applications. The article culminates with a discussion on the intricacies of performance metrics in RFF and the direction for future research.Article A Remote Laboratory for Training in Radio Communications: Errl(IEEE, 2007) Kara, Ali; Aydın, Elif; Öktem, Ruşen; Çağıltay, NergizThis paper presents, first, a short survey of remote laboratory initiatives in electrical and computer engineering, and then discusses design and development phases of remote laboratory environment on radio communications, the ERRL (European Remote Radio Laboratory). As being the first attempt in establishing of such a large scale remote laboratory on radio communications, ERRL enables access to high technology RF equipments and setups through the Internet. The software structure, target groups and experimental set ups of ERRL are shortly discussed. First attempts on implementation of pilot experiments are discussed.Article Principles for the Design of a Remote Laboratory: A Case Study on ERRL(IEEE, 2010) Çağıltay, Nergiz; Aydın, Elif; Kara, AliRemote laboratories are getting very popular in engineering education programs. However, there are not many studies addressing the requirements and design issues of such laboratories. This paper discusses the results of a study of the requirements for developing a remote Radio Frequency (RF) laboratory for university students. This study draws on the perspectives of the students at the university, department of electrical engineering. The results are based on a research study established by 111 engineering students from France, Germany, Romania and Turkey. It investigates how students would like to use the technical content of a state of the art RF laboratory. The result of this study is also compared with the previous outcomes showing perspectives of the other learner groups of such laboratories; engineers and technicians in the technical colleges on the Radio Frequency (RF) domain. Considering the outcomes developed so far, some principles that need to be considered while designing and developing such a laboratory have been proposed. As a case study the proposed principles are implemented in a remote laboratory project. In this paper, the details of user requirements of such laboratories, the proposed principles and the implementation examples are all provided and discussed. Primarily, the general aim of this study is to guide remote laboratory platform developers towards the most effective design of their platforms.Conference Object Citation - WoS: 1Citation - Scopus: 1Optimizing Radio Frequency Fingerprinting for Device Classification: a Study Towards Lightweight Dl Models(IEEE, 2024) Iyiparlakoglu, Raif; Awan, Maaz Ali; Dalveren, Yaser; Kara, AliAs the Internet of Things (IoT) permeates diverse application domains, ensuring the security of wireless networks has become increasingly critical. However, the constraints of resource-limited IoT devices render complex encryption impractical. Consequently, Radio Frequency Fingerprinting (RFF) has emerged as a promising avenue, leveraging unique device characteristics resulting from manufacturing nonlinearities. RFF enhances physical layer security by enabling device classification and authentication at IoT gateways. While deep learning (DL) aided RFF systems offer exceptional classification accuracy, their deployment on edge devices remains challenging to this end. Accordingly, there is a gap in the literature for efficient model exploration and implementation. This study proposes a lightweight Convolutional Neural Network (CNN) model using 1D convolutional filters to reduce inference latency. The model was applied to an open-source dataset comprising 30 LoRa devices. An evaluation was conducted to compare classification accuracy and inference latency using Short Time Fourier Transform (STFT) and Fast Fourier Transform (FFT) for preprocessing. Additionally, the performance of the proposed model was compared against a CNN model utilizing 2D convolutional filters. The model exhibited a significant reduction in inference latency with miniscule degradation in classification accuracy, addressing the identified gap, and propelling the academic discourse towards RFF for edge devices.
