Optical: Robust, Spectrally Efficient Optical Fiber Transmission Techniques: Nonlinear Analysis, Coded Modulation Techniques and System Experiments

Stanford University, Stanford CA

Investigators

Abstract

0335013 Kahn As optical fiber systems rapidly approach the limits of binary modulation and direct detection, alternative modulation, coding and detection techniques will play increasing roles. This project will address this evolution with several thrusts: Analysis of nonlinear DPSK, PSK and QAM systems. Differential phase-shift keying (DPSK), phase-shift keying (PSK) and quadrature-amplitude multiplexing (QAM) offer increased spectral efficiency and robustness. Fiber Kerr nonlinearity fundamentally limits system performance, but is typically studied using Monte Carlo simulation. Analytical techniques to compute error probability in nonlinear systems using these modulation techniques will be developed. These analyses will provide insight into system optimization and will yield practical engineering design criteria. Nonlinear phase noise: analysis and compensation. Nonlinear phase noise (NLPN) arises when signal and amplifier noise together modulate the fiber refractive index via the Kerr effect. NLPN potentially limits systems using DPSK, PSK or QAM. NLPN will be characterized analytically, and electrical techniques to compensate NLPN will be demonstrated. Coded nonbinary modulation techniques. Current optical systems use binary modulation and coding schemes matched to binary modulation. In order to realize the full benefits of nonbinary modulation, appropriate coding techniques will be investigated, including trellis-coded modulation (TCM) and turbo TCM. System experiments. Coherent detection of PSK will be performed using MEMS-based external-cavity lasers. These experiments will verify the nonlinear system analysis, test electrical compensation of NLPN, and demonstrate that coherent detection can yield substantial improvements in spectral efficiency and robustness. This project will make several broader contributions, by educating students from diverse backgrounds and genders, involving undergraduate students in research, and training future educators. Results will be incorporated into graduate-level lecture and laboratory courses.