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Transmitter IQ Mismatch Estimation by Number-Theoretic Net-Based Gaussian Particle Filter for Coherent Optical Communications | IEEE Conference Publication | IEEE Xplore
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Transmitter IQ Mismatch Estimation by Number-Theoretic Net-Based Gaussian Particle Filter for Coherent Optical Communications


Abstract:

In this paper, we propose a novel approach for estimating in-phase/quadrature-phase (IQ) mismatch at the transmitter using a number-theoretic net (NT-net)-based Gaussian ...Show More

Abstract:

In this paper, we propose a novel approach for estimating in-phase/quadrature-phase (IQ) mismatch at the transmitter using a number-theoretic net (NT-net)-based Gaussian particle filter (NT-GPF). The proposed method generates particles on an ellipse of the given bivariate Gaussian distribution, which helps locate the correct region of the actual state parameters more efficiently. Simulation results demonstrate that the NT-GPF-based approach offers higher estimation accuracy, with the mean squared error (MSE) consistently lower than that of traditional GPF across different particle numbers. Moreover, the proposed NT-GPF-based algorithm significantly improves estimation efficiency and noise tolerance, requiring only 21 particles under low signal-to-noise ratio (SNR).
Date of Conference: 04-07 November 2023
Date Added to IEEE Xplore: 01 January 2024
ISBN Information:
Conference Location: Wuhan, China

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