Speaker: Mu Xu, Ph.D. Candidate, Georgia Institute of Technology
Statistical Signal Processing Enhanced Digital Mobile Fronthaul
The emerging demands on virtual reality (VR) and 5G-New Radio, will quickly deplete the bandwidth resource of current transport and access networks, which forces researchers to think about revolutionary technologies empowering future digital radio over fiber (D-RoF) based mobile front haul (MFH). Although, D-RoF features lower transmission efficiency, it inherits part of the advantages from both analog-RoF (A-RoF) and functional split. D-RoF is format agnostic with simple hardware implementation at radio access units (RAU). Meanwhile it benefits from digitization with high robustness against nonlinear degradations. In my PhD work, to improve the bandwidth efficiency and capacity of D-RoF systems, research topics in the following directions have been studied: (a) fast statistical estimation, relaxed Lloyd algorithm, and differential coding are proposed and jointly applied for data compression to reduce the quantization noise and improve the compression gain in a digital MFH; (b) advanced modulation formats and statistical digital signal processing (DSP) techniques in coherent optical systems acting as 5G high-capacity MFH networks; (c) advanced multiband modulation techniques for spectral efficient bidirectional data transmission and multiplexing in digital fronthaul systems.
Mu Xu grew up in Anhui, China. He’s currently is a Ph.D. student at Georgia Institute of Technology. Before that, he received his B.S. and M.S. at Tianjin University and Shanghai Jiao Tong University in 2010 and 2013 respectively. His research mainly focuses on system design and networking in optical mobile fronthaul as well as digital signal processing in radio-over-fiber systems.