在ylzz总站线路检测成功举办两期国际产学研用合作会议的框架下，我司积极承办本次分论坛。邀请俄罗斯、澳大利亚与新加坡等国家专家学者，与学院师生共同研讨科技创新与务实合作，开启学院国际合作特别是与“一带一路”沿线国家高校和科研机构合作的新篇章。现将相关事宜通知如下：

1. 会议安排：

2. 会议主题：Beyond 6G通信技术的机遇与挑战

3. 会议时间：

   2021年9月13日 14:00-16:00

4. 会议地点：

   线上Zoom平台会议链接：https://zoom.com.cn/j/82168053552?pwd=WUdKY0oraTROdmlrUlRUNmd6Z0ZFZz09

   会议号：821 6805 3552

   密码：790370

   线下会场：南湖校区一教304

5. 特邀嘉宾及主讲内容：

6. Title: Intelligent Reflecting Surface (IRS) for 6G: Opportunities and Challenges.

   Abstract: In this talk, we introduce a new promising paradigm for future wireless networks by leveraging a massive number of low-cost passive elements with independently controllable reflection amplitude and/or phase, named Intelligent Reflecting Surface (IRS), which is able to smartly reconfigure wireless channels for enhancing the communication performance. We present the signal and channel models of IRS by taking into account its hardware constraints in practice. We then illustrate the main functions and applications of IRS in achieving spectral and energy efficient wireless networks, and highlight its cost and performance advantages as compared to existing wireless technologies. Next, we focus on the main design challenges in efficiently integrating IRSs to  future wireless networks such as 6G, including passive reflection optimization, IRS channel acquisition and IRS deployment, and overview their state-of-the-art solutions. In particular, we will emphasize on the latest results on double-/multi-IRS aided wireless networks, beyond the conventional single IRS for point-to-point passive relaying. We will also discuss other extensions and point out directions worthy of investigation in the future.

   Zhang Rui：新加坡国立大学电子与计算机工程系教授，IEEE Fellow

    

7. Title:  Artificial Intelligence of Underwater Things and Marine Data Analytics.

   Abstract: Artificial Intelligence and the Internet of Things are touted as two of the most innovative technologies which are transforming our daily life. There is great synergy that can be exploited between AI and IoT, thanks to the rationale that most AI algorithms would not function without sensors collect data in the first place. In this talk, we will apply AIoT technology to the field of the Internet of underwater things and marine data analytics. We will use Australia’s Great Barrier Reef as a case study to demonstrate how AIoT technology can be leveraged to overcome great challenges as well as reaping substantial opportunities in monitoring and sensing harsh marine environments.

   Wei Xiang：拉筹伯大学教授，SMIEEE, FIEAust, FIET

    

8. Title: Self-Energized UAV-Assisted Scheme for Cooperative Wireless Relay Networks.

   Abstract: Unmanned aerial vehicles (UAVs) have recently been envisaged as an enabling technology of 5G and Beyond. UAVs act as an intermediate relay node to facilitate uninterrupted, high quality communication between information sources and their destination. However, UAV energy management has been a major issue of consideration due to limited power supply, affecting flight duration. Thus, we introduce in this paper a unified energy management framework by resorting to wireless power transfer (WPT), simultaneous wireless information and power transfer (SWIPT) and self-interference (SI) energy harvesting (EH) schemes, in cooperative relay communications. In our new technique, UAVs are deployed as relays equipped with a decode and forward protocol and EH capability operating in a full-duplex (FD) mode. The UAV assists information transmission between a terrestrial base station and a user. The UAV’s transmission capability is powered exclusively by the energy harvested from WPT, radio frequency signal transmitted from the source via time-switching SWIPT protocol and SI exploitation. We improve the overall system throughput by the use of FD based UAV-assisted cooperative system. In this proposed system, we formulate two optimization problems to minimize end-to-end outage probability, subject to UAV’s power profile and trajectory for a DF relay scheme, respectively.

   Dushantha Nalin K. Jayakody：托木斯克理工大学计算机科学与机器人学院教授，资讯通讯实验室主任

9. Title: Materials for 6G technology - problems, challenges, tasks.

   Abstract: The transition to 6th generation (6G) wireless data transmission technologies, expected by 2030, requires a careful consideration not only of issues related to the development of data transmission methods and big data processing, but also of issues related to the technological support of this transition with appropriate scientific solutions. To ensure this transition, scientists will have to face the need to develop and obtain new materials, optimize existing data transmission systems and search for fundamentally new scientific ideas. As an example of such scientific problems, within the framework of this report, there will be considered the issues of the need to obtain materials for the equipment protection from electromagnetic radiation in the planned data transmission ranges (100-200 GHz and higher) and potential candidates for the role of such protective materials, as well as ways to increase the heat dissipation of large heat flows from the main elements of electronic systems caused by the intensification of data transmission and an increase in the volume of transmitted information.

   Ivan Shanenkov：俄罗斯托木斯克理工大学强电流电子学院副教授、博士（强电流和电工材料领域）

    

    

   四位主讲人分享后，欢迎与会师生分享自己的研究提案，也可以针对自己在本次报告中或科研工作上遇到的问题进行交流。

   欢迎广大师生参加本次Beyond 6G通信技术的机遇与挑战分论坛！