A joint compensation scheme for IQ imbalance and phase noise based on the extended Kalman filter is proposed. Our proposed scheme can compensate IQ imbalance and the phase noise jointly with quick convergence speed and excellent BER performance.
KEYWORDS: Polarization, Filtering (signal processing), Signal to noise ratio, Tolerancing, Digital signal processing, Adaptive optics, Interference (communication), Signal detection, Optical engineering, Detection and tracking algorithms
An adaptive Kalman filter (AKF) scheme for joint polarization and phase recovery is proposed and experimentally demonstrated. In this scheme, the noise covariance is estimated adaptively along with the recursive of KF. The simulation results show that the tuning parameter Q can adaptively converge to an optimal value in wide ranges of optical signal-to-noise ratio (OSNR), polarization rotation frequency, and laser linewidth. As a result, the proposed AKF has less OSNR sensitivity penalty, better polarization tracking capability, and laser linewidth tolerance compared with extended Kalman filter (EKF) with fixed Q value. Finally, in the experiment of 16 quadrature amplitude modulation system, AKF also shows a better polarization tracking capability than the EKF.
A joint compensation scheme based on cascaded Kalman filter is proposed, which can implement polarization tracking, channel equalization, frequency offset, and phase noise compensation simultaneously. The experimental results show that the proposed algorithm can not only compensate multiple channel impairments simultaneously but also improve the polarization tracking capacity and accelerate the convergence speed. The scheme has up to eight times faster convergence speed compared with radius-directed equalizer (RDE) + Max-FFT (maximum fast Fourier transform) + BPS (blind phase search) and can track up polarization rotation 60 times and 15 times faster than that of RDE + Max-FFT + BPS and CMMA (cascaded multimodulus algorithm) + Max-FFT + BPS, respectively.
We propose a joint estimation scheme for fast, accurate, and robust frequency offset (FO) estimation along with phase estimation based on modified adaptive Kalman filter (MAKF). The scheme consists of three key modules: extend Kalman filter (EKF), lock detector, and FO cycle slip recovery. The EKF module estimates time-varying phase induced by both FO and laser phase noise. The lock detector module makes decision between acquisition mode and tracking mode and consequently sets the EKF tuning parameter in an adaptive manner. The third module can detect possible cycle slip in the case of large FO and make proper correction. Based on the simulation and experimental results, the proposed MAKF has shown excellent estimation performance featuring high accuracy, fast convergence, as well as the capability of cycle slip recovery.
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