CN114785650B - Novel blind phase search algorithm structure and implementation method - Google Patents
Novel blind phase search algorithm structure and implementation method Download PDFInfo
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- CN114785650B CN114785650B CN202210505811.1A CN202210505811A CN114785650B CN 114785650 B CN114785650 B CN 114785650B CN 202210505811 A CN202210505811 A CN 202210505811A CN 114785650 B CN114785650 B CN 114785650B
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- 238000010845 search algorithm Methods 0.000 title claims abstract description 29
- 238000000034 method Methods 0.000 title claims abstract description 15
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 16
- 238000012360 testing method Methods 0.000 claims abstract description 16
- 238000004364 calculation method Methods 0.000 claims description 5
- 238000004891 communication Methods 0.000 abstract description 6
- 239000013307 optical fiber Substances 0.000 abstract description 4
- 238000007493 shaping process Methods 0.000 description 8
- 230000015556 catabolic process Effects 0.000 description 5
- 238000006731 degradation reaction Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000011084 recovery Methods 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
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Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/0014—Carrier regulation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
- H04B10/60—Receivers
- H04B10/61—Coherent receivers
- H04B10/612—Coherent receivers for optical signals modulated with a format different from binary or higher-order PSK [X-PSK], e.g. QAM, DPSK, FSK, MSK, ASK
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
- H04B10/60—Receivers
- H04B10/61—Coherent receivers
- H04B10/616—Details of the electronic signal processing in coherent optical receivers
- H04B10/6163—Compensation of non-linear effects in the fiber optic link, e.g. self-phase modulation [SPM], cross-phase modulation [XPM], four wave mixing [FWM]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
- H04B10/60—Receivers
- H04B10/61—Coherent receivers
- H04B10/616—Details of the electronic signal processing in coherent optical receivers
- H04B10/6165—Estimation of the phase of the received optical signal, phase error estimation or phase error correction
Abstract
The invention discloses a novel blind phase search algorithm structure and an implementation method, which can effectively improve the performance damage of the existing blind phase search algorithm in a low signal-to-noise ratio optical fiber communication system, obviously reduce the length of a required filter and improve the accuracy of phase estimation. The invention is realized by the following steps: firstly, rotating an input signal according to a test angle; sending the rotated signal to a decision circuit, and outputting a standard constellation point with the nearest Euclidean distance to the rotated signal; calculating the difference between the rotated signal and the standard constellation point and squaring the difference to obtain the square distance between the rotated signal and the standard constellation point; initializing a Gaussian blur filter; convolving the gaussian filter with squared distances having the same test angle; summing the updated square distances; sending the summed square distance sum to a minimum comparator, and outputting a minimum sum corresponding to the test angle as phase noise estimated by an algorithm; when all the signals are output, the whole algorithm is finished.
Description
Technical Field
The invention relates to the technical field of communication, in particular to a novel blind phase search algorithm structure and an implementation method
Background
With the advent of big data, cloud computing, and various emerging smart applications, global communication data traffic has increased, and demand for data transmission rates has shown an explosive trend. Probability shaping techniques have received extensive attention in academia and industry due to their flexibility in rate adjustment and the property of more approaching shannon's limit. On the other hand, the probability shaping technology makes each constellation point of the signal no longer have equal probability distribution, and especially the probability of occurrence of high-amplitude signal points is lower, which is equivalent to reducing the modulation order of the signal, thus reducing the requirement of the signal-to-noise ratio required by the system. However, the conventional digital signal processing algorithm is designed based on the premise of equal probability distribution of signal constellation points, so that the direct application of the algorithm in a probability shaping system may have incompatibility problem. It has been reported that carrier phase recovery algorithms, especially blind phase search algorithms (Blind phase search, BPS), suffer serious degradation in performance in probability shaping systems, mainly due to degradation of system mutual information. This degradation is more pronounced, especially at lower signal-to-noise ratios.
How to cope with the degradation of the performance of the blind phase search algorithm in a low signal-to-noise ratio optical fiber communication system has raised a great deal of attention in research. In general, to cope with such performance degradation, the existing blind phase search algorithm alleviates performance loss by increasing the filter length, but too long filter length reduces its ability to track the phase while increasing the complexity of algorithm processing and processing delay.
Recently, there have been attempts to improve the performance of blind phase search algorithms by adding forgetting factors. However, the selection of the forgetting factor is achieved through a complex optimization process, and the forgetting factor is also related to the signal-to-noise ratio of the system. Different signal-to-noise ratios require different forgetting factors to be changed, which all increase system costs.
The invention provides a novel blind phase search algorithm structure and an implementation method by comprehensively considering the characteristics of a blind phase search algorithm of a low signal-to-noise ratio optical fiber communication system.
Disclosure of Invention
The invention aims to improve the performance damage of the existing blind phase search algorithm in the low signal-to-noise ratio optical fiber communication system, greatly reduce the length of a filter and introduce a filter with unequal weight, thereby providing a blind phase search algorithm (Gaussian blur aided blind phase search, GBA-BPS) based on Gaussian blur.
The GBA-BPS algorithm of the invention comprises the following specific implementation steps:
step 1: to-be-processed signal r containing phase noise k Multiplied by B test phases, i.e. the signal is rotated at the constellation plane,
wherein the test phase expression is characterized by (1)
Wherein,the number of test phases is represented by B, and the index of the test phase is represented by B.
It can be found that the parameter B directly affects the accuracy of the algorithm, and that a larger B results in a more accurate phase noise estimation but at the same time results in a larger calculation amount and algorithm complexity.
Step 2: the signal obtained in the step 1 enters a decision circuit and outputs the standard constellation point which is closest to the signal obtained in the step 1,
step 3: subtracting the constellation points obtained in the step 1 from the signal obtained in the step 2, squaring, and obtaining square distances between the rotated signal and ideal constellation points;
step 4: initializing a Gaussian blur filter; the gaussian blur filter formula is characterized by (2):
the length of the Gaussian filter is N, the length setting of the Gaussian blur filter is consistent with the length of the filter of the existing blind phase search algorithm, and specific parameters are adjusted according to actual conditions;
the variance of the Gaussian blur filter is the expectation of the square of a signal at a transmitting end, and the calculation formula is represented by (3):
σ 2 ＝E(|A k | 2 ) (3)
wherein sigma 2 Representing the variance of the gaussian blur filter, E representing taking the desired result, || representingThe result of taking the mould, A k Signal representing transmitting end
Step 5: updating the square distance obtained in the step 3 by using a Gaussian blur filter, wherein a convolution formula is characterized by (4):
the square distances with the same test angle obtained in the step 3 are respectively convolved with the Gaussian blur filter obtained in the step 4, so that updated square distances are obtained;
wherein N is s Representing the number of symbols to be processed G λ Representing a gaussian blur filter, b representing an index of the test angle;
step 6: summing the sum of square distances obtained in the step 4 under the same test angle, wherein a calculation formula is characterized by (5):
wherein, |d m-n,B | 2 Representing the squared distance after updating by a gaussian filter, N representing the length of the filter;
step 7: sending the square distance sum obtained in the step 6 to a minimum value comparator to obtain the minimum square distance sum, wherein the corresponding test angle is the phase noise estimated by the final algorithm;
so far, from step 1 to step 7, the whole algorithm operation ends.
Advantageous effects
The novel blind phase search algorithm structure and the implementation method provided by the invention have the effect of effectively reducing the length of the filter and the complexity of the algorithm due to the consideration of the correlation of the front and rear symbols. Meanwhile, different weights are given to taps of the filter through Gaussian blur, so that the method has a better effect of eliminating white noise compared with the existing blind phase search algorithm, and all the method has the effect of assisting the blind phase search algorithm in accurately estimating the phase. Therefore, the novel blind phase search algorithm provided by the invention can simultaneously reduce the length of the filter and improve the accuracy of phase estimation.
Drawings
FIG. 1 is a schematic illustration of a novel blind phase search algorithm proposed by the present invention;
FIG. 2 is a diagram of a simulation system in embodiment 1 of the present invention;
FIG. 3 is a graph of shaping factor versus mutual information for the present invention in example 1 employing a novel blind phase search algorithm and an existing blind phase search algorithm;
Detailed Description
Example 1
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention are clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
Fig. 1 is a diagram of a simulation system of the present embodiment 2, and it can be seen from the diagram that the modulation formats are two (PS-16 QAM and PS-64 QAM). At the transmitting end, firstly, a pseudo-random sequence is mapped into an amplitude sequence with probability distribution through a distribution matcher, and then, symbol mapping of 16QAM and 64QAM is carried out. And then transmitted in a channel with additive white gaussian noise. The laser linewidth in this example was set to 100kHz, the shaping factor was set to 0 to 0.15, and the step size was adjusted to 0.01. In the offline processing process of the receiving end, the signals enter a carrier phase recovery algorithm module through data, and then mutual information calculation is carried out after the skip cycle is eliminated.
Fig. 3 shows the relationship between the mutual information of the receiving end and the shaping factor of the transmitting end under the condition of adopting the Conventional blind phase search algorithm, namely the Conventional BPS, and the algorithm GBA-BPS proposed by the present invention, wherein the abscissa is the shaping factor of the transmitting end, and the ordinate is the mutual information of the receiving end. It can be found that under the same filter length, the mutual information which can be achieved by the blind phase search algorithm based on Gaussian blur is obviously higher than that of the existing blind phase search algorithm.
The foregoing is a preferred embodiment of the present invention, and the present invention should not be limited to the embodiment and the disclosure of the drawings. All equivalents and modifications that come within the spirit of the disclosure are desired to be protected.
Claims (4)
1. The implementation method of the novel blind phase search algorithm structure is characterized by comprising the following steps:
step 1: rotating the input signal according to the test angle;
step 2: the signal obtained in the step 1 enters a judging circuit and outputs a standard constellation point with the nearest Euclidean distance to the signal obtained in the step 1;
step 3: subtracting the standard constellation points obtained in the step 1 from the signals obtained in the step 2, squaring the subtracted signals, and obtaining square distances between the rotated signals and the standard constellation points;
step 4: initializing a Gaussian blur filter;
wherein the length of the Gaussian filter is N;
the variance of the Gaussian blur filter is the expectation of the square of a signal at a transmitting end, and the calculation formula is represented by (1):
σ 2 ＝E(|A k | 2 ) (1)
wherein sigma 2 Representing the variance of the gaussian blur filter, E representing taking the desired result, ||representing taking the modulo result, a k A signal representing the transmitting end;
step 5: updating the square distance obtained in the step 3 by using the Gaussian blur filter obtained in the step 4;
the square distances with the same test angle obtained in the step 3 are respectively convolved with the Gaussian blur filter obtained in the step 4, so that updated square distances are obtained;
step 6: summing the sum of square distances obtained in the step 5 under the same test angle;
step 7: sending the square distance sum obtained in the step 6 to a minimum value comparator to obtain the minimum square distance sum, wherein the corresponding test angle is the phase noise estimated by the final algorithm;
so far, from step 1 to step 7, the whole algorithm operation ends.
2. The method for implementing a novel blind phase search algorithm structure according to claim 1, wherein in step 4, the gaussian blur filter is initialized: the variance of the gaussian blur filter is set to the desired square of the signal at the transmitting end.
3. The method for implementing a novel blind phase search algorithm structure according to claim 1, wherein in step 4, the gaussian blur filter is initialized: the length setting of the Gaussian blur filter is consistent with the filter length of the existing blind phase search algorithm.
4. The method for implementing a novel blind phase search algorithm structure according to claim 1, wherein in step 5, the gaussian blur filter updates the square distance: the square distances with the same test angles are respectively convolved with Gaussian blur filters, and new square distances are updated and established.
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