Intelligent Next Generation Communication Networks
|Event Date:||April 13, 2015|
|Speaker:||Dr. Ying Li|
|Speaker Affiliation:||Futurewei Technologies|
|Open To:||ACCEPTABLE FOR ECE 694
Mobile traffic demand grows exponentially. It is critical for the future networks to support the spectacular growth in traffic volume, where flexibly and efficiently using spectrum is one of the most important technologies. Optimization and built-in intelligence can be effective tools to provide the improvement. In this talk, a vision of intelligent next generation communication networks is provided, together with some examples to show how optimization can be used, and how the intelligence can be built in the network for more efficient spectrum usage.
To support increasing mobile data, intelligent ultra-dense network is one of the most important aspects. The network topology is changing from one tier of macro base stations to multi-tier ultra-dense networks with more types of base stations with various sizes, such as micro, pico, femto, relay, etc. For multi-tier ultra-dense networks, one of the challenging problems is how to associate a mobile station to cell(s), such that the radio resources can be used more efficiently. The talk includes an example of how to associate heterogeneous traffic of a mobile station, to cells with heterogeneous characteristics, such that efficient resource allocation can be achieved.
Another aspect is to explore millimeter wave band (6-300GHz). Key advantages for these frequencies are spectrum availability, and larger band for much higher throughput comparing to the 4G. However, challenging problems have to be solved, such as the network topology revolution, beam forming, beam management, etc. The talk includes some examples of beamformed media access control, where intelligence can be built in beam management, to improve the efficiency of the radio resources.
Yet another aspect is a new architecture for the intelligent networks as the revolution for wireless. Intelligent mobile software defined networking (Mobi-SDN) is emerging, which incorporates big data analytics and machine learning. Mobi-SDN technology provides a new network architecture, where the intelligence can be embedded in the network controller (the brain). The intelligence can come from the learning, such as learning to be content-aware, context-aware, network path or link conditions-aware. The brain can also coordinate the resource allocation for cells on different tiers, as well as the resources for radio access, or for wireless backhaul which may be in-band. The intelligence can also be distributed to the cells, and mobile stations. The new architecture can be envisioned as a network of robots of various sizes at various locations, intelligently managing the radio resources, for high spectral efficiency.
Dr. Ying Li received the M.A. and Ph.D. degrees in Electrical Engineering at Princeton University, Princeton, NJ, in 2005 and 2008, respectively. She received the B.E. degree (with highest honors) and the M.E. degree (with highest honors) in Information and Communication Engineering from Xi'an Jiaotong University, Xi'an, China. She is currently with Futurewei Technologies, Bridgewater, NJ, since Mar. 2015, where she works on big data analytics assisted radio resource management and self-organized networks. She was with Samsung Research America, Dallas, TX, from Nov. 2013 to Mar. 2015, and was with Samsung Telecommunications America, Dallas, TX, from Oct. 2008 to Oct. 2013, where she has been involved in research on communication networks and smart energy networks. She was a visiting Ph.D. student in Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in summer 2007 and in Motorola Multimedia Research Labs, Schaumburg, IL, in fall 2007, respectively. She worked as a faculty member in the Department of Information and Communication Engineering at Xi'an Jiaotong University from 2000 to 2003 and as a visiting scholar in Fuji Xerox Co. Ltd., Japan, from 2000 to 2001. Dr. Li’s research areas include optimization, communication networks, next generation wireless communications, big data, heterogeneous networks, cross-layer design, content distribution, multimedia communication, smart energy networks, energy monitoring and management, information theory, and signal processing. Dr. Li is a recipient of Distinguished Inventor Award 2013 from Samsung Research America at Dallas, and the Inventor of the Year 2012 and Distinguished Inventor Award 2010 from Samsung Telecommunications America. She is a recipient of Gordon Wu Fellowship from the School of Engineering and Applied Science at Princeton University in 2003-2007.