Invited Speakers of 2024
Prof. Pascal Lorenz, University of Haute-Alsace, France
Biography: Pascal Lorenz (lorenz@ieee.org) received his M.Sc. (1990) and Ph.D. (1994) from the University of Nancy, France. Between 1990 and 1995 he was a research engineer at WorldFIP Europe and at Alcatel-Alsthom. He is a professor at the University of Haute-Alsace, France, since 1995. His research interests include QoS, wireless networks and high-speed networks. He is the author/co-author of 3 books, 3 patents and 200 international publications in refereed journals and conferences. He was Technical Editor of the IEEE Communications Magazine Editorial Board (2000-2006), IEEE Networks Magazine since 2015, IEEE Transactions on Vehicular Technology since 2017, Chair of IEEE ComSoc France (2014-2020), Financial chair of IEEE France (2017-2022), Chair of Vertical Issues in Communication Systems Technical Committee Cluster (2008-2009), Chair of the Communications Systems Integration and Modeling Technical Committee (2003-2009), Chair of the Communications Software Technical Committee (2008-2010) and Chair of the Technical Committee on Information Infrastructure and Networking (2016-2017), Chair of IEEE/ComSoc Satellite and Space Communications Technical (2022-2023), IEEE R8 Finance Committee (2022-2023), IEEE R8 Conference Coordination Committee (2023). He has served as Co-Program Chair of IEEE WCNC'2012 and ICC'2004, Executive Vice-Chair of ICC'2017, TPC Vice Chair of Globecom'2018, Panel sessions co-chair for Globecom'16, tutorial chair of VTC'2013 Spring and WCNC'2010, track chair of PIMRC'2012 and WCNC'2014, symposium Co-Chair at Globecom 2007-2011, Globecom'2019, ICC 2008-2010, ICC'2014 and '2016. He has served as Co-Guest Editor for special issues of IEEE Communications Magazine, Networks Magazine, Wireless Communications Magazine, Telecommunications Systems and LNCS. He is associate Editor for International Journal of Communication Systems (IJCS-Wiley), Journal on Security and Communication Networks (SCN-Wiley) and International Journal of Business Data Communications and Networking, Journal of Network and Computer Applications (JNCA-Elsevier). He is senior member of the IEEE, IARIA fellow and member of many international program committees. He has organized many conferences, chaired several technical sessions and gave tutorials at major international conferences. He was IEEE ComSoc Distinguished Lecturer Tour during 2013-2014.
Speech Title: Advanced architectures of Next Generation Wireless Networks
Abstract: Internet Quality of Service (QoS) mechanisms are expected to enable wide spread use of real time services. New standards and new communication architectures allowing guaranteed QoS services are now developed. We will cover the issues of QoS provisioning in heterogeneous networks, Internet access over 5G networks and discusses most emerging technologies in the area of networks and telecommunications such as IoT, SDN, Edge Computing and MEC networking. We will also present routing, security, baseline architectures of the inter-networking protocols and end-to-end traffic management issues.
Prof. Abdellatif KOBBANE, Mohammed V University in Rabat, Morocco
Biography: Dr. Abdellatif KOBBANE is currently serving as a Full Professor at the Ecole Nationale Supérieure d'Informatique et d'Analyse des Systèmes (ENSIAS), Mohammed V University in Rabat, Morocco, since 2009. , jointly awarded by Mohammed V-Agdal University (Morocco) and the University of Avignon (France). He previously received a Master of Science in Computer Science, Telecommunication, and Multimedia from Mohammed V-Agdal University in 2003. Additionally, Dr. Kobbane holds the position of Adjunct Professor at the L2TI laboratory, Paris 13 University, France.
His research interests primarily revolve around wireless mobile networking, performance evaluation, flexible resource management, and distributed AI in 5G/6G networks utilizing AI and advanced techniques in distributed mean-field game theory. He is the author of numerous scientific publications in prestigious IEEE conferences and journals such as IEEE ICC, IEEE Globecom, IWCMC, ICNC, IEEE WCNC…
Dr. Kobbane's research also delves into the application of artificial intelligence , Generative AI mean-field game theory in modeling and evaluating the performance of various systems, including Digital Twins and Internet of Things, SDN and NFV, Use cases of 5G networks, flexible resource management in wireless mobile networks, emerging technologies, Blockchain, Trust and cybersecurity issues, Mobile cloud computing, Mobile Social networks, Caching and backhaul problems, Heterogeneous networks, 6G, and Future networks. He is the author of numerous scientific publications in prestigious IEEE conferences and journals such as IEEE ICC, IEEE Globecom, IWCMC, ICNC, IEEE WCNC…
Dr. Kobbane's research extends beyond technical domains, aiming to apply AI and Generative AI to address real-world challenges in various fields, including: Agriculture, Healthcare, Natural resource management (water, energy, climate change), Societal well-being,…
Furthermore, Dr. Kobbane He actively participates in the research community and holds the distinction of being a Senior Member of ComSoc IEEE, an Ex-Chair of the IEEE Communication Software Technical Committee, and the Ex-President and Founder of the Association of Research in Mobile Wireless Networks and Embedded Systems (MobiTic) in Morocco. He is also the founder of the WINCOM conference and has previously served as the responsible for the Master (MS) of Internet of Things and Mobile Services (IOSM).
Speech Title: AI-enabled Resource Management for Next-Generation Networks
Abstract: 5G and beyond 5G/6G are poised to shape the future economic growth across multiple vertical industries by providing the necessary network infrastructure to fuel innovation and create new economic models. They enable a wide spectrum of services, including higher data rates, ultra-low latency, and high reliability. To fulfill their promises, 5G and beyond 5G/6G rely on advanced artificial intelligence techniques and game theory to ensure optimal resource management. In this presentation, we will discuss resource management challenges in an SDN network and highlight the use of federated learning algorithms to ensure efficient resource management.
Prof. Gang Wang, Ningbo University, China (IEEE Senior Member)
Biography: Gang Wang received the B.Eng. degree from Shandong University, Jinan, China, and the Ph.D. degree from Xidian University, Xi’an, China, both in electronic engineering, in 2006 and 2011, respectively. He joined Ningbo University, Ningbo, China, in January 2012, where he is currently a full Professor. His research interests are in the areas of target localization and tracking in wireless networks, array singal processing, and robust ellipse fitting in image processing.
Dr. Wang is an elected member of the Sensor Array and Multichannel Technical Committee of the IEEE Signal Processing Society. He serves as the Associate Editor for IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS and the Handling Editor for Signal Processing (Elsevier). He was a Handling Editor for Digital Signal Processing (Elsevier) from Sept. 2019 to Oct. 2022. He is a Senior Member of the IEEE.
Speech Title：Multistatic localization in the Absence of Transmitter Positions
Abstract: Multistatic localization, involving one or several transmitters actively sending out signals to locate an object from its echo, is widely used in practical systems. This talk presents some results for the multistatic localization problem in absence of transmitter positions. For the problem of locating a stationary object in the absence of transmitter positions, we propose a semidefinite relaxation (SDR) method for joint estimation of the object and transmitter positions using time delay (TD) measurements from both indirect and direct paths. Moreover, we present some key theoretical results for the performance of the proposed method. Furthermore, we introduce a calibration object to address the multistatic localization problem in the absence of synchronizations between the transmitter and receivers and among the receivers. For this challenging problem, we propose a three-step estimation method to jointly estimate the transmitter position, synchronization errors, and object position. Theoretical analysis is conducted to validate the performance of the proposed method.
Prof. Yuanguo Bi, Northeastern University, China
Biography: Yuanguo Bi received the Ph.D. degree in computer science and technology from Northeastern University, Shenyang, China, in 2010. He was a visiting Ph.D. student with the BroadBand Communications Research (BBCR) lab, Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada from 2007 to 2009. He is currently a Professor with the School of Computer Science and Engineering, Northeastern University, China. He has authored/coauthored more than 80 journal/ conference papers, including high quality journal papers, such as IEEE JSAC, IEEE TMC, IEEE TWC, IEEE TITS, IEEE TVT, IEEE IoT Journal, IEEE Communications Magazine, IEEE Wireless Communications, IEEE Network, and mainstream conferences, such as AAAI, IEEE INFOCOM, IEEE GLOBECOM, IEEE ICC, etc. His research interests include vehicular networks, mobile edge computing, federated and distributed machine learning, unmanned aerial vehicle networks, space-air-ground integrated networks, etc. He has served as an Editor/Guest Editor for IEEE Communications Magazine, IEEE Wireless Communications, IEEE Network. He has also served as a TPC Co-chair for IEEE/CIC ICCC 2023, a General Co-chair for ICCSN 2023, and a Publication Co-chair for IEEE MSN 2018, etc.
Speech Title: Federated Learning for Connected and Automated Vehicles
Abstract: As a distributed machine learning paradigm, federated learning can protect local data privacy while achieving joint training between devices. Applying federated learning to in vehicle edge computing provides a prospect for supporting intelligent transportation applications. In this speech, we will introduce an adaptive collaborative federated learning scheme. This scheme adopts a dynamic local training round adjustment method and a collaborative edge server training scheme to improve model reliability and reduce communication rounds. In addition, in scenarios involving multiple federated learning systems, we will also introduce an edge server reallocation scheme to improve training efficiency and network resource utilization, while mitigating the impact of heterogeneous data.
Assoc. Prof. Hongyan Fu, Tsinghua University, China
Biography: Dr. Fu is currently a tenured-associate professor, deputy director of Research Office, and director of Nano-fabrication Platform, Tsinghua Shenzhen International Graduate School (SIGS), Tsinghua University, Shenzhen, China. From 2010 to April 2017, Dr. Fu was a founding member and leading the advanced optic communications research at Central Research Institute, Huawei. His research interest focuses on integrated photonics and its related applications for communications and sensing, including optical wireless communication, LiDAR and silicon photonics, etc. He is a senior member of IEEE, Optica and life member of SPIE. He is the founding advisors of Optica/IEEE Photonics Society/SPIE Student Chapters at Tsinghua SIGS, Tsinghua University. He has authored/coauthored over 360 journal or conference papers, 3 book chapters, over 80 granted/pending China / US patents.
Speech Title: Integrated sensing and communication systems with OWC and LiDAR
Abstract: We will review our recent research progresses on the integrated sensing and communication systems based on optical wireless communication and high-speed LiDAR, with the focus on exploring and breaking through the key enabling technologies.
Assoc. Prof. Liwei Yang, China Agricultural University, China (Personal Page)
Biography: She received the B.E. degree in Telecommunication Engineering from Chongqing University of Posts and Telecommunications, China, and the Ph.D. degree in Information and Communications Engineering from Beijing University of Posts and Telecommunications, China. From 2009 to 2011, she was a Postdoctoral Research Fellow with the Department of Electronic Engineering, Tsinghua University, China. In 2015, she joined the faculty of the College of Information and Electrical Engineering, China Agricultural University. Her research interests include optical networks, optical wireless communications and visible light communication. She participated in a number of national projects and published more than 100 papers. She served as a TPC member of several international academic conferences and a reviewer for several international journals.
Speech Title: Dynamic Resource Allocation for Indoor VLC/WiFi
Heterogeneous Network Based on Q-learning
Abstract: The rapid increase in user data traffic has led
to conventional single radio frequency (RF) wireless communication no
longer meeting user demand. Light-emitting diode (LED) visible light
communication (VLC) can also not meet the communication demand due to its
over-reliance on line-of-sight transmission. The heterogeneity of visible
light networks and traditional RF networks can meet user demand well.
However, because the communication link limits LED optical communication,
the traditional resource allocation algorithm can no longer meet user
demand and system utilisation. This paper addresses the issue by proposing
a joint method for channel detection and access based on Q-learning
multi-agent and a dynamic strategy for bandwidth adjustment for fixed
channels. This approach resolves the issue of multiple users frequently
switching links. It optimises the VLC communication constrained by the
communication link using the benchmark the user transmits in the optimal
channel link. Simulation results show that the proposed strategy
dramatically improves the system's throughput, utilisation and user
fairness compared with the traditional link-switching method with fixed
bandwidth.
Assoc. Prof. Tian Pan, Beijing University of Posts and Telecommunications, China
Biography: Tian Pan is an associate professor and PhD supervisor at the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications. His research focuses on public cloud networks, data center networks, high-performance programmable network devices, and satellite Internet. In the field of computer networks, he has published over 100 papers in prestigious conferences and journals such as SIGCOMM, NSDI, CoNEXT, INFOCOM, ICNP, ICDCS, ToN, TPDS, and JSAC, including 32 CCF-A papers, 20 CCF-B papers, and holds more than 60 invention patents. His related achievements have been recognized with the 2021 Innovation Team Award from the China Electronics Society, the first prize of the 2017 Science and Technology Award from the China Institute of Communications, and the second prize of the 2023 Science and Technology Award from the China Institute of Communications. He also serves as a member of the CCF Internet Committee and as a TPC member for various international conferences.
Speech Title: Research on Networking Protocols and Emulation Testbed for Large-Scale LEO Satellite Constellations
Abstract: LEO satellites offer several advantages over GEO/MEO satellites in terms of communication latency, construction costs, network robustness, and capacity scalability. However, due to dynamic topology changes, large network scales, and resource constraints on satellites, the design of LEO satellite network protocols faces numerous challenges. Specifically, these include route calculation under dynamic inter-satellite topologies, routing convergence in ultra-large constellations, network addressing for satellite constellations and ground nodes, and mobility handover in dynamic space-ground topologies. To address these issues, the report will share methods for designing LEO satellite networking protocols, including: 1) A hybrid orbit prediction shortest path priority routing protocol. 2) A stable routing generation algorithm for the dynamic topologies of LEO satellite networks. 3) A lightweight flooding mechanism for LEO satellite networks. 4) A mobility management protocol for LEO satellite networks based on identity and location separation. Additionally, considering that ground emulation testbeds can help verify networking protocols on the ground before satellites are launched, effectively reducing trial-and-error costs, the report will also share experiences in building large-scale satellite network emulation systems.
Assoc. Prof. Xiaoxuan Wang, Beijing Jiaotong University, China
Biography: Dr. Xiaoxuan Wang received his Ph.D. degree in traffic control and information engineering from Beijing Jiaotong University, Beijing, China, in 2020. From 2017 to 2018, he was a Visiting Scholar with Dr. Lingjia Liu in Wireless@VT, Virginia Tech, VA, USA. He is currently an Associate Professor at the School of Electronic and Information Engineering, Beijing Jiaotong University, and the Associate Director at the Cyber-Physical Systems & Industrial Software Lab. His main research interests are in dependability and security for wireless communications and communication networks in smart city, intelligent transportation and railway transportation. He has published more than 30 research papers in top international conferences and journals, such as IEEE T-ITS, T-VT, IoT-J, IET-ITS, ICC, WCNC, Globecom, VTC, etc. He has been the recipients of the 2018 International Conference on Intelligent Rail Transportation Best Paper Award.
Speech Title: Research on Trustworthy Communication and Information Security Networking for Multi-Traffic Entity Interoperability
Abstract: Current traffic communication systems prioritize optimizing communication quality over the utility of multi-entity interoperability, and there is a dearth of research on trustworthy communication for such interoperability. This presentation tackles the multi-need analysis and the construction of a trustworthy communication network oriented towards the interoperability of multiple traffic entities. It deeply analyzes the disordered interconnectivity issues stemming from cross-entity application demands in complex traffic scenarios and establishes a hierarchical communication architecture that supports large-scale distributed collaboration among groups, facilitating dynamic information interaction aligned with the interoperability needs of heterogeneous entities. Drawing on the interoperability business scenarios of multiple traffic entities, a collaborative network architecture involving humans, vehicles, roads, networks, edges, and clouds is established. The research delves into the resilient modeling of trustworthy communication with high entity collaboration, achieving the mapping and resolution of communication networking demands oriented towards interoperability intentions in complex traffic scenarios. The study also explores trustworthy communication technologies such as high-credibility multi-attribute physical layer authentication and vehicle-road-cloud collaborative intrusion detection and security defense, culminating in the construction of an information security architecture tailored to interoperability demands.
Assoc. Prof. Hoshang Kolivand, Liverpool John Moores University, UK (IEEE Senior Member)
Biography: Hoshang Kolivand is an Assoc. Prof in AI and Mixed Reality at Liverpool John Moores University (LJMU). With an MSc degree in Applied Mathematics and Computer Science, a PhD and a Postdoc in Augmented Reality, he is a leading expert in these fields. As the Head of the Applied Computing Research Group at LJMU, Dr. Kolivand leads a team of over 35 researchers, focusing on AI and Augmented Reality. He has published extensively with over 190 papers in international journals and has presented at numerous conferences. Dr. Kolivand is a Senior Member of the IEEE and has served as a keynote speaker at more than 55 international conferences. He has organized over 30 conferences in AR, VR, AI, and HCI. In addition to his academic contributions, Dr. Kolivand has authored book chapters and several products which received over 14 awards for his work in Virtual Reality and Augmented Reality. As a dedicated researcher and educator, Dr. Hoshang Kolivand plays a significant role in advancing AI and Mixed Reality technologies, making valuable contributions to the field through his expertise and leadership.
Speech Title: Breaking Boundaries with AI: Current and Future of Mixed Reality
Abstract: In this talk, we delve into the profound impact of AI on Mixed Reality, uncovering the latest advancements and groundbreaking innovations that are breaking the boundaries of digital experiences. From sophisticated real-time simulations to personalized virtual environments, explore how AI's integration with Mixed Reality is driving unprecedented immersion and transforming the way we perceive and interact with the virtual world. Join us as we unravel the limitless possibilities and implications of this transformative fusion.
Assoc. Prof. Chao Fang, Beijing University of Technology, China (IEEE Senior Member)
Biography: Chao Fang received his B.S
degree in Information Engineering from Wuhan University of Technology,
Wuhan, China, in 2009, and the Ph.D. degree with the State Key Laboratory
of Networking and Switching Technology in Information and Communication
Engineering from Beijing University of Posts and Te4lecommunications,
Beijing, China, in 2015. He joined the Beijing University of Technology in
2016 and now is an associate professor. From August 2013 to August 2014,
he had been funded by China Scholarship Council to visit Carleton
University, Ottawa, ON, Canada, as a joint doctorate. Moreover, he is the
visiting scholar of University of Technology Sydney, Commonwealth
Scientific and Industrial Research Organization, Hong Kong Polytechnic
University, Kyoto University, Muroran Institute of Technology, and Queen
Mary University of London.
Dr. Fang is the senior member of IEEE, and the vice chair of technical
affairs committee in IEEE ComSoc Asia/Pacific Region (2022-2023).
Moreover, he is the leading editors of Electronics and Symmetry special
issues. He also served as the Session Chairs of ICC NGN'2015 and ICCC
NMNRM'2021, and Poster Co-Chair of HotICN'2018. He won the Best Paper
Award of IEEE ICFEICT'2022. His current research interests include future
networks, information-centric networking (ICN), cloud-edge-terminal
cooperation networks, intelligent network control, resource management and
content delivery.
Speech Title: Gated Recurrent Unit-Based
Network Traffic Prediction for Load Balance
Abstract: To improve the reasonable allocation of network
resources, and reduce service interruption or overwhelming delay for
software-defined networking (SDN) due to excessive network load, this
paper proposes a network load balancing scheme based on gated recurrent
units (GRU) aiming at optimizing load balancing strategies. First, a link
prediction and priority adjustment model is constructed to describe the
network load balance optimization problem. Second, a GRU-based network
traffic prediction algorithm is proposed to capture network traffic
features. Specifically, a graph convolution network (GCN) is utilized to
learn the spatial features in the network topology, and GRU is used to
capture the long-term dependencies in the traffic data sequences. Finally,
a logical ordering and threshold filtering strategy is designed to achieve
priority ordering of links and determine the preferred links for services
to improve network load balancing. The experimental results show that the
GRU-based network traffic prediction algorithm exhibits 3% higher
prediction accuracy compared to the existing baseline methods, and the
network load balancing scheme based on GRU performs 4x network load
balancing.
Assoc. Prof. Dawei Wang, Sun Yat-sen University, China (Personal Page)
Biography: Dr. Dawei Wang received his bachelor's and doctorate degrees in 2008 and 2013 from Zhejiang University, Hangzhou. In 2013, he joined Huawei Technologies, Shenzhen, as a research scientist and in 2016 a senior researcher at the Optical & Quantum Lab of Huawei Technologies German Research Center, Munich. He is currently an associate professor at Sun Yat-sen University, Guangzhou. His research interest focuses on advanced optical and quantum communication technologies.
Speech Title: Polarization Kinetic Manipulation
Abstract: Polarization manipulation based on the cascaded
waveplates model shared similar underlying mathematical structures with
the robot arm kinematics. We successfully developed the polarization
kinetic control theory based on linearization and designed improved
control algorithms based on the Jacobian matrix of the control model. The
theory enabled endless polarization tracking of an arbitrary polarization
state without any control signal resetting with low computational
complexity. We achieved a record 100 krad/s tracking speed when applying
the algorithm to a thin-film LiNbO3-based device. The theory applied to
all waveplate types, and we pinpointed the exact cases in which the
control singularities would occur. Moreover, we developed polarization
scrambling models within the same theoretical framework, demonstrating
improved controllability regarding scrambling speed and probability
distribution of the polarization state.
Assoc. Prof. Mengwei Xu, Beijing University of Posts and Telecommunications, China
Biography: Mengwei Xu is an associate professor, doctoral advisor with Computer Science Department, Beijing University of Posts and Telecommunications (BUPT). He obtained his PhD and Bachelor degrees both from Peking University. He was a visiting scholar in Purdue University during Nov.2018-Nov.2019. He joined the “Star-track” visiting professor program of Microsoft Research Asia (MSRA) from Dec. 2020 to Mar. 2021. He won the distinguished PhD thesis of ACM SIGMobile China, 2021. Dr. Mengwei Xu’s research interests lie in the intersection of edge systems and machine learning, with a recent focus on enabling state-of-the-art deep learning techniques on the resource-constrained edge devices. His work has been published on premier CS conferences like ACM MobiCom, MobiSys, ASPLOS, USENIX ATC, and WWW.
Speech Title: On-device LLM Service: Opportunity, Challenges, and Efforts
Abstract: Large Language Models (LLMs) and related multimodal variants are fundamentally changing the capabilities of electronic devices, supporting new applications such as personal agents. Deploying large language models on edge devices, such as smartphones, is an important development trend. It not only ensures user data privacy but also improves the availability and cost-effectiveness of services. However, the high demand for memory, computation, and power consumption by large language models poses challenges to algorithm and system design. This report will focus on a solution for efficient deployment of large models on the edge, termed LLM-as-a-Service. This service is provided by the operating system to offer a unified LLM service for applications. It interacts with applications through methods like Prompt/LoRa, ensuring service scalability and hardware compatibility. The report will showcase our team's preliminary exploration in this direction.
Senior Engineer Dr. Dongdong Wang, Network Communication Research Institute of China Electronics Technology Group Corporation, China
Biography: Dongdong Wang received the Ph.D. degree in Information and Communication Engineering from the Beijing University of Posts and Telecommunications (BUPT), in 2018. He is currently a Senior Engineer and Young Expert in the field of LEO satellite transmission technology with the Science and Technology on Communication Networks Laboratory, Network Communication Research Institute of China Electronics Technology Group Corporation. He is a member of the Young Scientist Club of the Chinese Society of Electronics. He has authored or coauthored over 30 technical articles in international journals and conferences. His research interests include information theory and channel coding, 5G based LEO satellite transmission technology.
Speech Title: The Key Technology of MAC Sub-layer of 5G NR based LEO Satellite
Abstract: Up to now, the development of the LEO satellite Internet has gone through three stages, from the first stage of satellite and terrestrial networks competing with each other, to the second stage of satellite and terrestrial networks complementing each other, then to the current third stage of satellite and terrestrial networks merging with each other to provide seamless global coverage. 3GPP has been developing the non-terrestrial network (NTN) standard for seven and a half years, and last year released the release 17 NR-NTN and IoT-NTN standards for transparent forwarding satellites. In this report, we first briefly return to the development history of the LEO satellite Internet and the research process of NTN standard. Then, we explore some of the problems faced by 5G NR when applied to a very interesting beam-hopping scenario in the LEO satellite Internet, and suggest potential solutions.
Dr. Yanan Liang, Beijing Jiaotong University, China
Biography: Dr. Yanan Liang received her Ph.D. degree in communication and information systems from Beijing Jiaotong University, Beijing, China, in 2020. From 2017 to 2018, she was a Visiting Scholar at the University of Notre Dame, IN, USA. She is currently a Lecturer at the School of Electronic and Information Engineering, Beijing Jiaotong University. Her research interests include random access schemes for 5G networks, multiple access schemes for wireless self-organizing networks, and coupling mechanisms for networking and collaborative control. She has published more than 20 research papers in top international conferences and journals, such as IEEE T-WC, T-COM, CL, ICC, WCNC, VTC, etc.
Speech Title: Swarm Collaborative Network Applications and Key Technologies
Abstract: Swarm collaborative network provides the transmission channel for the information exchange between swarm individuals, forming the neural network of the swarm, which can multiply the efficiency of swarm collaboration. This report first elaborates on the concept and connotation of swarm collaborative network, and then summarizes typical application scenarios of swarm collaboration in the military field. The special requirements that typical application scenarios have for swarm collaborative network are analyzed, such as dense networking, intermittent links, anti-access area denial, cross domain collaboration, etc. Based on these requirements, the key technologies applicable to different application scenarios are introduced, including large-scale network architecture, distributed non-orthogonal multiple access, relative spatiotemporal basis reconstruction, cross domain network slicing and resource management, etc.
Dr. Amjad Ali Amjad, Zhejiang University, China
Biography: Amjad Ali Amjad received his B.S. degree (Hons.) in Computer Systems Engineering from the University of Engineering and Technology (UET), Peshawar, Pakistan, in 2014, his M.S. degree in Electrical Engineering from the University of Lahore, Islamabad, Pakistan, in 2017, and his Ph.D. from Zhejiang University in 2021. He recently completed his first postdoctoral research at the School of Electronic and Computer Engineering at Peking University. He is currently engaged in his second postdoctoral research at the Donghai Laboratory in collaboration with Zhejiang University. His research interests include wireless optical communications, underwater wireless optical communication, solid state lighting, and visible light communication. He has co-authored one book chapter and several papers on these subjects, published in refereed journals and conference proceedings.
Speech Title: Laser Diode-Based high speed optical wireless communication and high CRI Solid State Lighting
Abstract: Gallium nitride (GaN) phosphor-converted white light-emitting diodes (Pc-WLEDs) are emerging as an indispensable solid-state lighting (SSL) source for next-generation display systems and the lighting industry. Together with the function of lighting, visible light communication (VLC) using Pc-WLEDs has gained increasing attention to fulfill the growing demand for wireless data communication. Over the past few years, white-light-emitting diodes have been used for both high-speed visible light communication and solid-state lighting simultaneously. Practically, the low modulation response and low emitting intensity of light-emitting diodes (LED) are the drawbacks to the development of ultrahigh-speed VLC and a high-quality SSL system. Blue GaN laser diode (LD) and color convertor quantum dots-based white light can simultaneously be used for both high-speed VLC and SSL.
Invited Speakers of ICCSN2023
Prof. Bin Lin, Dalian Maritime
University, China
SMIEEE, Dean of Communication Engineering with the
College of Information Science and Technology
Dr. Dongdong Wang, The 54th Research Institute of China Electronics Technology Group Corporation, China
Assoc. Prof. Xuebo Zhang, Northwest Normal University, China
Assoc. Prof. Jie Gong, Sun Yat-sen University, China
Assoc. Prof. Shu Fu, Chongqing University, China
Invited Speaker in Sepcial Session 2: Key Technologies
for Mobile Phones directly connect to Satellites
Assoc. Prof. Ke Wang, Beijing
University of Posts and Telecommunications, China
Invited Speaker in Sepcial Session 2: Key Technologies
for Mobile Phones directly connect to Satellites
Assoc. Prof. Danshi Wang, Beijing
University of Posts and Telecommunications, China
Invited Speaker in Sepcial Session 2: Key Technologies
for Mobile Phones directly connect to Satellites
Assoc. Prof. Mingwu Yao, Xidian University, China
Assoc. Prof. Chen Zhang, Nanjing
University of Posts and Telecommunications, China
Invited Speaker in Sepcial Session 2: Key Technologies
for Mobile Phones directly connect to Satellites