报告时间：10月17日下午15：30-17：30

报告地点：D419会议室

赵楠学术报告

题目：无人机通信网络悬停位置与飞行轨迹优化

摘要：无人机具有移动性、悬停性、灵活性等优势，可以突破传统地面无线通信网络空间的限制，从空中为地面终端提供高效可靠的无线接入服务，尤其适用于灾区应急通信和人流密集的致密小蜂窝网络。本报告着眼于无人机静态位置优化以及动态轨迹优化两个方向，针对NOMA无人机基站位置优化、无人机多中继位置优化、小区边缘无人机飞行轨迹优化、NOMA基站与无人机协作的飞行轨迹优化等四个问题，进行深入探讨，提出解决方案。在此基础上，对未来的一些研究挑战进行讨论。

报告人介绍：赵楠，大连理工大学副教授、博士生导师，IEEE通信学会亚太地区杰出青年学者奖，大连市青年科技之星，IEEE和中国电子学会高级会员，从事无线干扰管理、物理层安全、无人机通信等领域的研究，发表录用150余篇学术论文，IEEE系列期刊论文60余篇，谷歌学术引用1900余次，ESI高引论文10篇。任IEEE Transactions on Green Communications and Networking等多个国际期刊编委，曾获VTC、ICNC、CSPS和MLICOM等多个国际会议最佳论文奖。

唐建华学术报告

题目：Service Multiplexing and Revenue Maximization in Sliced C-RAN Incorporated with URLLC and Multicast eMBB

摘要：The fifth generation (5G) wireless systems aims to differentiate its services based on different application scenarios. Instead of constructing different physical networks to support each application, radio access network (RAN) slicing is deemed as a prospective solution to help operate multiple logical separated wireless networks in a single physical network. In this talk, we incorporate two typical 5G services, i.e., enhanced Mobile BroadBand (eMBB) and Ultra-Reliable Low-Latency Communications (URLLC), in a cloud RAN (C-RAN), which is suitable for RAN slicing due to its high flexibility. In particular, for eMBB, we make use of multicasting to improve the throughput, and for URLLC, we leverage finite blocklength capacity to capture the delay accurately. We envision that there will be many slice requests for each of these two services. Accepting a slice request means a certain amount of revenue (consists of long-term revenue and shot-term revenue) is earned by the C-RAN operator. Our objective is to maximize the C-RAN operator's revenue by properly admitting the slice requests, subject to the limited physical resource constraints. We formulate the problem as a mixed-integer nonlinear programming (MINLP) and exploit efficient approaches to solve it, such as successive convex approximation and semidefinite relaxation. Simulation results show that our proposed algorithm significantly saves system power consumption and receives the near-optimal revenue with an acceptable time complexity.

报告人介绍：Jianhua Tang received the B.E. degree in communication engineering from Northeastern University, China, in 2010, and the Ph.D. degree in electrical and electronic engineering from Nanyang Technological University, Singapore, in 2015. He was a Post-Doctoral Research Fellow with the Singapore University of Technology and Design from 2015 to 2016. He is currently a Research Assistant Professor with the Department of Electrical and Computer Engineering, Seoul National University. His research interests include cloud computing, content-centric network, and cloud radio access network.