All Outputs (62)

The Role of Digital Twin in 6G-Based URLLCs: Current Contributions, Research Challenges, and Next Directions (2025)
Journal Article
Masaracchia, A., van Huynh, D., Duong, T. Q., Dobre, O. A., Nallanathan, A., & Canberk, B. (2025). The Role of Digital Twin in 6G-Based URLLCs: Current Contributions, Research Challenges, and Next Directions. IEEE Open Journal of the Communications Society, 6, 1202-1215. https://doi.org/10.1109/ojcoms.2025.3540287

Substantial improvements in the area of ultra reliable and low-latency communication (URLLC) capabilities, as well as possibilities of meeting the rising demand for high-capacity and high-speed connectivity are expected to be achieved with the deploy... Read More about The Role of Digital Twin in 6G-Based URLLCs: Current Contributions, Research Challenges, and Next Directions.

GenTwin: Generative AI-Powered Digital Twinning for Adaptive Management in IoT Networks (2025)
Journal Article
Duran, K., Shin, H., Duong, T. Q., & Canberk, B. (online). GenTwin: Generative AI-Powered Digital Twinning for Adaptive Management in IoT Networks. IEEE Transactions on Cognitive Communications and Networking, https://doi.org/10.1109/tccn.2025.3527719

The dramatic increase in smart services makes adaptive management of communication networks more critical. Especially for Internet of Things (IoT) networks, adaptive management faces several challenges, like fluctuating network conditions, heterogene... Read More about GenTwin: Generative AI-Powered Digital Twinning for Adaptive Management in IoT Networks.

Beam Alignment for IEEE 802.11be Powered by Task Oriented Indoor UWB Localization (2025)
Presentation / Conference Contribution
Karakaya, S. S., Sarı, T., Ak, E., Canberk, B., & Seçinti, G. (2024, September). Beam Alignment for IEEE 802.11be Powered by Task Oriented Indoor UWB Localization. Presented at 2024 IEEE 35th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Valencia, Spain

Coordinated beamforming is one of the crucial improvements for WiFi7. However, to provide sufficient Quality of Service, the corresponding beams have to be aligned accurately. Conventional approaches search for optimal beams in the available codebook... Read More about Beam Alignment for IEEE 802.11be Powered by Task Oriented Indoor UWB Localization.

Q-CSM: Q-Learning-based Cognitive Service Management in Heterogeneous IoT Networks (2024)
Presentation / Conference Contribution
Duran, K., Ozdem, M., Gursu, K., & Canberk, B. (2024, November). Q-CSM: Q-Learning-based Cognitive Service Management in Heterogeneous IoT Networks. Presented at 2024 IEEE 10th World Forum on Internet of Things (WFIoT2024), Ottawa, Canada

The dramatic increase in the number of smart services and their diversity poses a significant challenge in Internet of Things (IoT) networks: heterogeneity. This causes significant quality of service (QoS) degradation in IoT networks. In addition, th... Read More about Q-CSM: Q-Learning-based Cognitive Service Management in Heterogeneous IoT Networks.

Autonomous Queue Management System in Software-defined Routers for Sensor Networks (2024)
Presentation / Conference Contribution
Yigit, Y., Maglaras, L., Karantzalos, K., Gursu, K., Ozdem, M., Buchanan, W. J., & Canberk, B. (2024, November). Autonomous Queue Management System in Software-defined Routers for Sensor Networks. Presented at 2024 IEEE 10th World Forum on Internet of Things (WF-IoT), Ottawa, Canada

Recent advancements in sensor networks, the In-ternet of Things (IoT), and machine communication technologies have led to a significant increase in network traffic across various domains. However, this growth has brought forth the critical challenge... Read More about Autonomous Queue Management System in Software-defined Routers for Sensor Networks.

A Data Serialization-based Framework for Efficient IoT Management (2024)
Presentation / Conference Contribution
Huseynov, K., Cakir, L. V., Al-Shareeda, S., Özdem, M., & Canberk, B. (2024, November). A Data Serialization-based Framework for Efficient IoT Management. Presented at 2024 IEEE 10th World Forum on Internet of Things (WF-IoT), Ottawa, Canada

The Internet of Things (IoT) management relies on the efficient and timely transfer of data from sensors to applications. Processing required data transformations at the edge gateway introduces spatial complexity issues, particularly concerning resou... Read More about A Data Serialization-based Framework for Efficient IoT Management.

Efficient Roof Selection in Rainwater Harvesting: Hybrid Multi-criteria and Experimental Approach (2024)
Journal Article
Hamidi, M. N., Shitreh, S., Cengiz, A. I., Ozcelik, K., Eryildiz-Yesir, B., Ekmekcioğlu, Ö., Halat, O. M., Demirel, M. C., Canberk, B., Koyuncu, I., Isik, O., Guven, H., Ozgun, H., & Ersahin, M. E. (online). Efficient Roof Selection in Rainwater Harvesting: Hybrid Multi-criteria and Experimental Approach. Water Resources Management, https://doi.org/10.1007/s11269-024-04023-3

This study aimed to investigate the effects of different roof configurations on the quality of harvested rainwater (HRW) for sustainable irrigation in agriculture. Three roofing materials (i.e. shingle, galvanized metal, and clay tile) and three roof... Read More about Efficient Roof Selection in Rainwater Harvesting: Hybrid Multi-criteria and Experimental Approach.

Generative AI-enabled Digital Twins for 6G-enhanced Smart Cities (2024)
Presentation / Conference Contribution
Duran, K., Cakir, L. V., Ozdem, M., Gursu, K., & Canberk, B. (2024, December). Generative AI-enabled Digital Twins for 6G-enhanced Smart Cities. Paper presented at IEEE Global Communications Conference (GLOBECOM) 2024, Cape Town, South Africa

6G networks are envisioned to enable a wide range of applications, such as autonomous vehicles and smart cities. However, this rapid expansion of network topologies makes the management of 6G wireless networks more complex and leads to performance de... Read More about Generative AI-enabled Digital Twins for 6G-enhanced Smart Cities.

Group-Signature Authentication to Secure Task Offloading in Vehicular Edge Twin Networks (2024)
Presentation / Conference Contribution
Al-Shareeda, S., Ozguner, F., & Canberk, B. (2024, December). Group-Signature Authentication to Secure Task Offloading in Vehicular Edge Twin Networks. Paper presented at 2024 IEEE Global Communications Conference (GLOBECOM), Cape Town, South Africa

This study delves into the integration of Group Signature (GS)-based authentication within Vehicular Edge Twin Networks (VETNs), a critical component in ensuring secure and efficient vehicular communication. By leveraging Proximal Policy Optimization... Read More about Group-Signature Authentication to Secure Task Offloading in Vehicular Edge Twin Networks.

Digital Twin-empowered Green Mobility Management in Next-Gen Transportation Networks (2024)
Journal Article
Duran, K., Cakir, L. V., Fonzone, A., Duong, T. Q., & Canberk, B. (2024). Digital Twin-empowered Green Mobility Management in Next-Gen Transportation Networks. IEEE Open Journal of Vehicular Technology, 5, 1650-1662. https://doi.org/10.1109/ojvt.2024.3484956

Evolving transportation networks need seamless integration and effective infrastructure utilisation to form the next-generation transportation networks. Also, they should be capable of capturing the traffic flow data at the right time and promptly ap... Read More about Digital Twin-empowered Green Mobility Management in Next-Gen Transportation Networks.

DTRAN: A Special Use Case of RAN Optimization using Digital Twin (2024)
Presentation / Conference Contribution
Tunc, C., Duran, K., Bilgin, B., Kalem, G., & Canberk, B. (2024, June). DTRAN: A Special Use Case of RAN Optimization using Digital Twin. Paper presented at 2024 European Conference on Networks and Communications EuCNC & 6G Summit, Antwerp, Belgium

The emergence of beyond 5G (B5G) and 6G networks underscores the critical role of advanced computer-aided tools, such as network digital twins (DTs), in fostering autonomous networks and ubiquitous intelligence. Existing solutions in the DT domain pr... Read More about DTRAN: A Special Use Case of RAN Optimization using Digital Twin.

Real-Time Digital Twin Platform: A Case Study on Core Network Selection in Aeronautical Ad-hoc Networks (2024)
Journal Article
Cakir, L. V., Kocak, M., Özdem, M., & Canberk, B. (2024). Real-Time Digital Twin Platform: A Case Study on Core Network Selection in Aeronautical Ad-hoc Networks. ITU Journal of Wireless Communications and Cybersecurity, 1(1), 41-46

The development of Digital Twins (DTs) is hindered by a lack of specialized, open-source solutions that can meet the demands of dynamic applications. This has caused state-of-the-art DT applications to be validated using offline data. However, this a... Read More about Real-Time Digital Twin Platform: A Case Study on Core Network Selection in Aeronautical Ad-hoc Networks.

Intelligent Digital Twin Communication Framework for Addressing Accuracy and Timeliness Tradeoff in Resource-Constrained Networks (2024)
Journal Article
Cakir, L. V., Thomson, C. J., Özdem, M., Canberk, B., Nguyen, V.-L., & Duong, T. Q. (online). Intelligent Digital Twin Communication Framework for Addressing Accuracy and Timeliness Tradeoff in Resource-Constrained Networks. IEEE Transactions on Cognitive Communications and Networking, https://doi.org/10.1109/tccn.2024.3469234

The accuracy and timeliness tradeoff prevents Digital Twins (DTs) from realizing their full potential. High accuracy is crucial for decision-making, and timeliness is equally essential for responsiveness. Therefore, this tradeoff in DT communication... Read More about Intelligent Digital Twin Communication Framework for Addressing Accuracy and Timeliness Tradeoff in Resource-Constrained Networks.

AI-Enhanced Digital Twin Framework for Cyber-Resilient 6G Internet of Vehicles Networks (2024)
Journal Article
Yigit, Y., Maglaras, L., Buchanan, W. J., Canberk, B., Shin, H., & Duong, T. Q. (2024). AI-Enhanced Digital Twin Framework for Cyber-Resilient 6G Internet of Vehicles Networks. IEEE Internet of Things, 11(22), 36168-36181. https://doi.org/10.1109/jiot.2024.3455089

Digital twin technology is crucial to the development of the sixth-generation (6G) Internet of Vehicles (IoV) as it allows the monitoring and assessment of the dynamic and complicated vehicular environment. However, 6G IoV networks have critical chal... Read More about AI-Enhanced Digital Twin Framework for Cyber-Resilient 6G Internet of Vehicles Networks.

Continuous Transfer Learning for UAV Communication-aware Trajectory Design (2024)
Presentation / Conference Contribution
Sun, C., Fontanesi, G., Chetty, S. B., Liang, X., Canberk, B., & Ahmadi, H. (2024, July). Continuous Transfer Learning for UAV Communication-aware Trajectory Design. Presented at The 11th International Conference on Wireless Networks and Mobile Communications (WINCOM 2024), Leeds, England

Deep Reinforcement Learning (DRL) emerges as a prime solution for Unmanned Aerial Vehicle (UAV) trajectory planning, offering proficiency in navigating high-dimensional spaces, adaptability to dynamic environments, and making sequential decisions bas... Read More about Continuous Transfer Learning for UAV Communication-aware Trajectory Design.

Digi-Infrastructure: Digital Twin-Enabled Traffic Shaping with Low-Latency for 6G Smart Cities (2024)
Journal Article
Yigit, Y., Ahmadi, H., Yurdakul, G., Canberk, B., Hoang, T., & Duong, T. Q. (2024). Digi-Infrastructure: Digital Twin-Enabled Traffic Shaping with Low-Latency for 6G Smart Cities. IEEE Communications Standards Magazine, 8(3), 28-34. https://doi.org/10.1109/mcomstd.0002.2300027

Digital twin (DT)-based smart cities are anticipated to achieve seamless integration between physical and digital objects to satisfy an enormous number of users across all domains. Therefore, the infrastructure of 6G smart cities has become an import... Read More about Digi-Infrastructure: Digital Twin-Enabled Traffic Shaping with Low-Latency for 6G Smart Cities.

Throughput Maximization in RIS-Assisted NOMA-THz Communication Network (2024)
Journal Article
Do-Duy, T., Masaracchia, A., Canberk, B., Nguyen, L. D., & Duong, T. Q. (2024). Throughput Maximization in RIS-Assisted NOMA-THz Communication Network. IEEE Open Journal of the Communications Society, 5, 5706-5717. https://doi.org/10.1109/ojcoms.2024.3454255

In order to overcome spectrum scarcity and provide higher data rates, the sixth-generation (6G) wireless communication network is expected to perform data transmission using terahertz (THz) frequencies. However, the effective implementation of these... Read More about Throughput Maximization in RIS-Assisted NOMA-THz Communication Network.

Digital Twin-enabled Low-Carbon Sustainable Edge Computing for Wireless Networks (2024)
Presentation / Conference Contribution
Huynh, D. V., Khosravirad, S. R., Sharma, V., Canberk, B., Dobre, O. A., & Duong, T. Q. (2024, December). Digital Twin-enabled Low-Carbon Sustainable Edge Computing for Wireless Networks. Paper presented at 2024 IEEE Global Communications Conference: Wireless Communications (GLOBECOM), Cape Town, South Africa

The advancement of sophisticated communication technologies and robust computing systems has unlocked opportunities for new applications across various domains. While these applications promise enhanced convenience and improved living standards, they... Read More about Digital Twin-enabled Low-Carbon Sustainable Edge Computing for Wireless Networks.

Machine Learning for Smart Healthcare Management Using IoT (2024)
Book Chapter
Yigit, Y., Duran, K., Moradpoor, N., Maglaras, L., Van Huynh, N., & Canberk, B. (2024). Machine Learning for Smart Healthcare Management Using IoT. In IoT and ML for Information Management: A Smart Healthcare Perspective (135-166). Springer. https://doi.org/10.1007/978-981-97-5624-7_4

This chapter explores the significant impact of Machine Learning (ML) and the Internet of Things (IoT) on smart healthcare management, marking a new era of innovation with enhanced patient care and health outcomes. The fusion of IoT devices for real-... Read More about Machine Learning for Smart Healthcare Management Using IoT.

Geometrical Features Based-mmWave UAV Path Loss Prediction Using Machine Learning for 5G and Beyond (2024)
Journal Article
Hussain, B., Bacha, S. F. N., Cheema, A. A., Canberk, B., & Duong, T. Q. (2024). Geometrical Features Based-mmWave UAV Path Loss Prediction Using Machine Learning for 5G and Beyond. IEEE Open Journal of the Communications Society, 5, 5667-5679. https://doi.org/10.1109/ojcoms.2024.3450089

Unmanned aerial vehicles (UAVs) are envisioned to play a pivotal role in modern telecommunication and wireless sensor networks, offering unparalleled flexibility and mobility for communication and data collection in diverse environments. This paper p... Read More about Geometrical Features Based-mmWave UAV Path Loss Prediction Using Machine Learning for 5G and Beyond.