Title:  Key Digital-RoF Mobile-fronthaul Technologies with Statistical Data Compression and Multiband Multiplexing

Committee: 

Dr. Chang, Advisor      

Dr. Ma, Chair

Dr. Weitnauer

Abstract:

The objective of the proposed research is to design and implement new methods that improve the efficiency and signal quality in data conversion, transmission, and multiplexing processes in next-generation mobile fronthaul networks. The main technical areas involve statistical data compression of digitized wireless signal, spectral-efficient signal multiplexing, and impairment mitigation in heterodyne or homodyne detection in optical UL transmission. As a counterpart of analog radio-over-fiber (A-RoF) technology, digital radio-over-fiber (D-RoF) system, such as common public radio interface (CPRI), is a matured and robust solution to support RF signal delivery in traditional mobile fronthaul (MFH) networks. In view of recent progresses in delta-sigma modulation, data compression, and advanced error correcting coding, the efficiency of D-RoF is significantly improved, which motivates researchers to re-evaluate the role of D-RoF in future mobile fronthaul networks to support 5G and beyond wireless communications. In this proposal, we demonstrate two critical technologies to improve the transmission efficiency and flexibility of D-RoF systems. A fast-statistical estimation based data compression algorithm is proposed to reduce the number of quantization digits in a D-RoF based MFH with low complexity and high quality. Combined with re-sampling and advanced formats, data-transmission efficiency of a 25-Gbit/s D-RoF testbed is improved by around five times. We also studied an offset-QAM carrier-less amplitude and phase modulation (OQAM-CAP) technique for spectral efficient multi-band RoF systems. In comparison with traditional QAM based CAP modulation schemes, the digital filter for each channel in OQAM-CAP can be adaptively redesigned to obtain either higher spectral efficiency or lower computational complexity.