H_∞ filter-based dynamic joint carrier frequency offset and linear phase noise tracking for CO-OFDM systems

Area of Science:

• Electrical Engineering
• Signal Processing
• Telecommunications

Background:

• Coherent Optical Orthogonal Frequency Division Multiplexing (CO-OFDM) systems are crucial for high-speed data transmission.
• Carrier Frequency Offset (CFO) and Linear Phase Noise (LPN) are significant impairments affecting CO-OFDM system performance.
• Existing tracking algorithms may lack robustness against system uncertainties and disturbances.

Purpose of the Study:

• To propose a robust, dynamic, and joint tracking algorithm for CFO and LPN in CO-OFDM systems.
• To enhance the accuracy and reliability of signal detection in the presence of noise and disturbances.
• To improve the overall performance and tolerance of CO-OFDM systems.

Main Methods:

• Utilizing the H∞ filter for robust dynamic tracking of CFO and LPN.
• Implementing Bayesian filtering for time-recursive posterior state estimation.
• Designing a min-max optimization problem with a performance bound-defined constraint for robustness.
• Proposing a decision-feedback algorithm for accurate signal detection post-estimation.

Main Results:

• The proposed H∞ filter algorithm achieves joint estimation of CFO and LPN.
• Mean Squared Errors (MSEs) for CFO and LPN reach Cramér-Rao Lower Bounds (CRLB) and Bayesian CRLB (BCRLB).
• Demonstrated excellent tolerance to noise and chromatic dispersion (CD) in an 88.9 Gb/s 16-QAM CO-OFDM system.

Conclusions:

• The H∞ filter-based algorithm provides a robust and accurate solution for CFO and LPN tracking in CO-OFDM systems.
• The proposed method outperforms conventional Extended Kalman Filter (EKF) and Gaussian Particle Filter (GPF) in terms of accuracy and robustness.
• This algorithm significantly enhances the performance and reliability of high-speed optical communication systems.