Thursday, 13 June
Time: 8:30 - 17:30
Location: Director's Row H/Lobby Level
Session 01 (Thursday, 13th June, 2024, 0830 am to 1015 am)
Session Chair: Dr Ejaz Waleed, Lakehead University, Canada
Welcome (0830 am-0835 am)
Invited keynote Talk (0835 am-0905 am)
Title: Deep Unsupervised Learning for Constrained Radio Resource Management Problems in 6G
Abstract: The next generation wireless networks are anticipated to be more complex and heterogeneous. Subsequently, the application of traditional optimization-based radio resource management (RRM) solutions is becoming difficult as they are typically non-scalable and computationally exhaustive. In this context, deep unsupervised learning is emerging as a potential solution to enable online implementation of RRM solutions without high-quality training labels and much reduced time complexity. Nevertheless, incorporating and satisfying various constraints with zero violation in a deep unsupervised learning architecture is a fundamental challenge. Therefore, this talk will discuss two novel differentiable projection-based approaches and their application to solve radio resource management problems in the presence of convex and non-convex constraints. The first approach utilizes a differentiable convex optimization layer to implicitly define a projection function, whereas the other approach uses an iterative differentiable correction process. This talk will conclude with the future search directions in this area.
Biography: Hina Tabbassum is currently an Associate Professor at the Lassonde School of Engineering, York University, Canada, where she joined as an Assistant Professor in 2018. She is also appointed as York Research Chair on 5G/6G-enabled mobility and sensing applications in 2023 for five years. She received her PhD degree from King Abdullah University of Science and Technology (KAUST) in 2013, and completed postdoctoral research at University of Manitoba, Canada, in 2018. Dr. Tabassum has made significant contributions in the development of a diverse spectrum of statistical models and numerical optimization algorithms. These innovations are tailored to enhance the performance of 5G and 6G wireless networks, catering to a wide array of applications encompassing vehicular, aerial, space, and IoT sensing networks. She received Lassonde Innovation Early-Career Researcher Award in 2023, N2Women: Rising Stars in Computer Networking and Communications in 2022 and listed in the Stanford's list of the World’s Top Two-Percent Researchers in 2021, 2022, and 2023. She has published over 90 refereed articles in well-reputed IEEE journals, magazines, and conferences. Her publications thus far have garnered 5900+ citations with an h-index of 35 (according to Google Scholar). She delivered several tutorials and invited talks, including recently IEEE PIMRC’22, IEEE WCNC’23, IEEE ICC'24, IEEE IoT World Forum’23.
Technical Paper Presentation (0905 am-1015 am)
1570989638: Age-of-Information Dependent Random Access for Periodic Updating (via Recorded Video Presentation)
| Yuqing Zhu; Yiwen Zhu; Aoyu Gong; Yan Lin; Yijin Zhang |
1570989868: Explainable Edge Computing in a Distributed AI-Powered Autonomous Vehicular Networks
|
Palvi Mahajan; Gagangeet Singh Aujla; Rama Krishna Challa |
1570989603: Irregular STAR-RIS-Aided Wireless Systems with a Limited Number of Passive Elements (via Recorded Video Presentation)
|
Ahmed Saeed Ben Fadel; Taissir Y. Elganimi; Khaled M. Rabie; Galymzhan Nauryzbayev; Xingwang Li |
Session 02 (Thursday, 13th June, 2024, 1045 am to 1230 pm)
Session Chair: Dr Metin Ozturk, Ankara Yildirim Beyazit University, Turkey
1570989418: SURAKSHA: Secure Message Exchange Framework Using Spiking Neural Network and Blockchain for IIoT Application
Aditya Patel; Ayushi Shah; Nilesh Kumar Jadav; Sudeep Tanwar; Anish Jindal
1570989586: On the Benefits of Coding for Network Slicing
Homa Esfahanizadeh; Vipindev Adat Vasudevan; Benjamin Kim; Shruti Siva; Jennifer Kim; Alejandro Cohen; Muriel Médard
1570996007: Secrecy Analysis of RIS-assisted Uplink NOMA Systems under Nakagami-m Fading (via Recorded Video Presentation)
Khawaja Muhammad Hamza; Sarah Basharat; Haejoon Jung; Mikael Gidlund; Syed Ali Hassan
1570996028: A Lightweight Machine Learning Approach for Delay-Aware Cell-Switching in 6G HAPS Networks
Görkem Berkay Koç; Berk Çiloğlu; Metin Ozturk; Halim Yanikomeroglu
1570996130: DRL-based Joint Resource Scheduling of eMBB and URLLC in O-RAN (via Recorded Video Presentation)
Rana Muhammad Sohaib; Syed Tariq Tariq Shah; Oluwakayode Onireti; Yusuf A. Sambo; Qammer H Abbasi; Muhammad Ali Imran
Session 03 (Thursday, 13th June, 2024, 1330 pm to 1515 pm)
Session Chair: Prof Martin Reed, University of Essex, UK
Panel Discussion (1330 pm -1430 pm)
"Technologies that will Revolutionise 6G"
Moderated by: Prof Martin Reed, University of Essex, UK
Panelists:
Dr Gagangeet Aujla, University of Durham, UK (Empowering Distributed Cloud Computing Applications and Research (CHEDDAR) for 6G)
Dr Ejaz Waleed, Lakehead University, Canada (Digital Divide and 6G Technologies)
Dr Metin Ozturk, Carleton University, Canada (Non-Terrestrial Networks for Sustainable and Intelligent 6G Networks)
Technical Paper Presentation (1430 pm-1455 pm)
1570989402: A Simplified Soft-demapping Scheme for Probabilistic Constellation Shaping
Yinhua Jia; Liangming Wu; Changlong Xu; Wei Liu; Hao Xu; Thomas Richardson
Session 04 (Thursday, 13th June, 2024, 1545 pm to 1730 pm)
Session Chair: Prof Dushantha Nalin K. Jayakody, Lusófona University, Portugal
1570996144: Throughput Optimization in Ambient Backscatter-Based Energy Constraint Cognitive Radio Networks (via Recorded Video Presentation)
Syed Tariq Tariq Shah; Maheen Fazal; Mahmoud Ahmed Shawky; Rana Muhammad Sohaib; Syed Faraz Hasan; Muhammad Ali Imran; Qammer H Abbasi
1570991833: URLLC-Aided System Protection in Smart Electric Power Distribution Systems (via Recorded Video Presentation)
Priya Raghuraman; Mesut E. Baran; Ismail Güvenç
1570985152: Performance Analysis of Intelligent Reflecting Surfaces for 5G/6G-Enabled Future Smart Industries with a Focus on Millimeter-Wave Band Communications (via Recorded Video Presentation)
Muhammad Farhan Khan; Ali Raza; Adeel Iqbal; Adnan Rashid; Muhammad Ali Jamshed; Dirk Pesch
1570989334: Interference Prediction in Unconnected In-X Mobile 6G Subnetworks Using a Data-Driven Approach
Pramesh Gautam; Carsten Bockelmann; Armin Dekorsy
1570989305: Pipelined Multi-User IR-HARQ for Improved Latency Performance and Energy Efficiency in URLLC
Rafael Santos; Daniel Castanheira; Adão Silva; Atílio Gameiro
