Fast chromatic dispersion estimation
US-9225431-B1 · Dec 29, 2015 · US
US9729232B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9729232-B2 |
| Application number | US-201415030834-A |
| Country | US |
| Kind code | B2 |
| Filing date | May 23, 2014 |
| Priority date | Oct 22, 2013 |
| Publication date | Aug 8, 2017 |
| Grant date | Aug 8, 2017 |
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Disclosed are a chromatic dispersion estimation method and device in optical coherent communication, wherein, the method includes: performing a fast Fourier transform on IQ-imbalance compensated data to obtain frequency-domain data in two polarization directions; calculating autocorrelation sequences of the frequency-domain data and performing an inverse fast Fourier transform on the values of the autocorrelation sequences; calculating modulus squares of the results of the inverse fast Fourier transform, and adding the results in the two polarization directions to obtain; determining a mean value of s of a plurality of data sets; calculating an index of the maximum value of, and estimating a dispersion value of the optical fiber link according to the index of the maximum value of. The abovementioned technical solution allows a significantly accurate and rapid estimation of dispersion values.
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What is claimed is: 1. A dispersion estimation and compensation method in optical coherent communication, comprising the following steps that are executed by a digital signal processor of a digital coherent receiver: performing an imbalance compensation on an IQ; performing dispersion estimation; and performing dispersion compensation by using a dispersion value provided by the dispersion estimation; wherein performing the dispersion estimation comprises: performing a fast Fourier transform on IQ-imbalance compensated data to obtain frequency domain data in two polarization directions; respectively calculating autocorrelation sequences of the frequency domain data in the two polarization directions to obtain values of the two autocorrelation sequences corresponding to the frequency domain data in the two polarization directions; respectively performing the fast inverse Fourier transform on the values of the two autocorrelation sequences to obtain two inverse Fourier transform results; respectively calculating modulus squares of the two fast inverse Fourier transform results to obtain two modulus square results; adding the two modulus square results to obtain a sum of the modulus square results P[n]; for a plurality of IQ-imbalance compensated data, calculating a plurality of sums of the modulus square results, averaging all sums of the modulus square results to obtain a dispersion objective function P[n]; calculating an index n 0 of a maximum value of the dispersion objective function P[n], and estimating an optical fiber link dispersion value based on the index n 0 . 2. The method of claim 1 , wherein, the step of performing a fast Fourier transform on IQ-imbalance compensated data to obtain frequency domain data in two polarization directions comprises: respectively performing the fast Fourier transform on the two IQ-imbalance compensated polarization data to obtain frequency domain data X[k] and Y[k] in two polarization directions in the following manner, where k=0, . . . , N fft −1, k is a frequency index, N fft is a number of Fourier transform points: calculating a spectrum of non-orthogonal signals in the two polarization directions according to the following equation to obtain the frequency domain data in the two polarization directions: X t [ k ] =X [ k ] cos θ t +Y [ k ] sin θ t , t=1, 2, wherein, θ 1 = 0 , θ 2 = π 4 . 3. The method of claim 2 , wherein, the step of performing a fast Fourier transform on IQ-imbalance compensated data to obtain frequency domain data in two polarization directions comprises: using a frequency domain convolution transform or a fast Fourier transform to obtain the frequency domain data in the two polarization directions. 4. The method of claim 3 , wherein, an autocorrelation sequence interval of the frequency domain data in the two polarization directions is a baud rate; the step of calculating autocorrelation sequences of the frequency-domain data in the two polarization directions to obtain values of the two autocorrelation sequences corresponding to the frequency domain data in the two polarization directions comprises: according to the following equation, calculating the autocorrelation sequence C 1 [k] of the spectrum X 1 [k] and the autocorrelation sequence C 2 [k] of the spectrum X 2 [k] in the frequency domain data in the two polarization directions: C t [ k ]=X t [ k ]X t tk [ k+k baud ], k=0, . . . , K, t=1, 2, wherein, K is an integer not greater than N fft −1−k baud , k baud is a frequency index interval corresponding to the baud rate. 5. The method of claim 4 , wherein, the step of respectively performing the fast inverse Fourier transform on the values of the two autocorrelation sequences to obtain two inverse Fourier transform results comprises: according to the following equation, respectively performing the fast inverse Fourier transform on the values of the two autocorrelation sequences: P t [ n ]=Σ k=1 K C t [ k ]θ |2πnk/N 1fft , n=−N 1fft , . . . , N 1fft −1, t=1, 2, wherein N 1fft is a number of Fourier transform points. 6. The method of claim 5 , wherein, the step of adding the two modulus square results to obtain a sum of the modulus square results P[n] comprises: calculating the sum of the modulus square results according to the following equation: P[n]=|P 1 [ n ]| 2 +|P 2 [ n ]| 2 , n=−N 1fft , . . . , N 1fft −1, where N 1fft is the number of Fourier transform points. 7. The method of claim 6 , wherein, after calculating the index n 0 of the maximum value of the dispersion objective function P[n], the method further comprises: using an interpolation equation to correct the index n 0 . 8. The method of claim 7 , wherein, the step of using the interpolation equation to correct the index n 0 comprises: correcting the index n 0 according to the following Parabolic interpolation equation to obtain a corrected result: n 0 ′ = n 0 + P ~ [ n 0 - 1 ] - P ~ [ n 0 + 1 ] 2 ( P ~ [ n 0 - 1 ]
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