Key digital-RoF mobile-fronthaul technologies with statistical data compression and multiband multiplexing

Abstract

The continuously-growing demands on high-speed internet, high-definition TV, and real-time entertainment services have created a great challenge for future broadband access. The emerging new services, such as virtual reality and 5G-New Radio, will quickly deplete the bandwidth resource of current transport and access networks. Those trends force researchers to think about revolutionary technologies empowering future mobile fronthaul (MFH) with higher capacity and lower latency. Among them, fiber wireless integration and networking are promising solutions which integrate the fiber and wireless resources and optimize the both in an MFH system as a whole. Recently, as a candidate to support MFH, the advantage of digital radio over fiber (D-RoF) scheme may be under-estimated. Although, D-RoF features lower transmission efficiency, it is format agnostic with simple hardware implementation at radio access units (RAU). Meanwhile it benefits from digitization with high robustness against nonlinear degradations. In this thesis 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.