CN113536725B - Pre-amplification parameter optimization method applied to ultra-wideband wavelength division multiplexing system - Google Patents

Abstract

The invention discloses a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system. The method includes: obtaining a randomly initialized optical pre-amplification parameter vector, wherein the optical pre-amplification parameter vector is used to represent The gain slope vector and gain offset vector of several band optical amplifiers in the ultra-wideband wavelength division multiplexing system; according to the optical pre-amplification parameter vector and the preset stimulated Raman scattering corrected Gaussian noise closed solution model, the loss function is obtained value; determine the optimized optical pre-amplification parameter vector according to the optical pre-amplification parameter vector, the loss function value and the simulated annealing algorithm. The present invention optimizes the pre-amplification power spectrum of each channel through the above method, so that the signal-to-noise ratio of the channel in the overall bandwidth during transmission is maximized, thereby obtaining the maximum communication transmission capacity.

Description

A Pre-amplification Parameter Optimization Method Applied to UWB WDM System

technical field

The invention relates to the technical field of digital signal processing, in particular to a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system.

Background technique

The rapid development of the mobile Internet not only gave birth to the fifth-generation communication Internet, but also made various mobile communication applications spring up like mushrooms in the past five years. Such as 4k video streaming, ultra-high-definition video telephony, cloud computing and so on. As the backbone network of the communication network, the optical fiber communication system is facing huge challenges and opportunities in the improvement of communication capacity.

However, with the widening of the communication bandwidth, the spectrum is correspondingly broadened. Since each band contains many channels, multiple bands lead to a very large number of channels (hundreds of channels). After the optical power of different bands is pre-amplified, the optical fiber The overall optical power inside will be very large, generally up to more than 20 dBm. Such a large optical power combined with an ultra-wide bandwidth will cause stimulated Raman scattering effects in addition to nonlinear effects such as self-phase modulation, four-wave mixing, and cross-phase modulation, and generate gains for low-frequency channels. These gains will A nonlinear effect is generated, resulting in higher nonlinear noise power, which reduces the signal-to-noise ratio of the signal, thereby reducing the communication capacity limit of the channel.

Therefore, the prior art still needs to be improved and developed.

Contents of the invention

The technical problem to be solved by the present invention is to provide a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system in view of the above-mentioned defects of the prior art, aiming at solving the problems caused by optical signals in the prior art after preventing large Stimulated Raman scattering effects in addition to nonlinear effects such as self-phase modulation, four-wave mixing, cross-phase modulation, etc., and generate gains for low-frequency channels, these gains will generate nonlinear effects, resulting in higher nonlinear noise power , so that the signal-to-noise ratio of the signal is reduced, thereby reducing the limit of the communication capacity of the channel.

The technical solution adopted by the present invention to solve the problem is as follows:

In a first aspect, an embodiment of the present invention provides a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system, wherein the method includes:

Obtain the optical pre-amplification parameter vector after random initialization, wherein the optical pre-amplification parameter vector is used to characterize the gain slope vector and the gain bias vector of several band optical amplifiers in the ultra-wideband wavelength division multiplexing system;

According to the light pre-amplification parameter vector and the preset stimulated Raman scattering corrected Gaussian noise closed solution model, the loss function value is obtained;

An optimized optical pre-amplification parameter vector is determined according to the optical pre-amplification parameter vector, the loss function value, and a simulated annealing algorithm.

In an implementation manner, wherein said obtaining the optical pre-amplification parameter vector after random initialization includes:

generate some random values;

A vector composed of several random values is used as an optical pre-amplification parameter vector.

In an implementation manner, wherein the loss function value obtained according to the light pre-amplification parameter vector and the preset stimulated Raman scattering corrected Gaussian noise closed solution model includes:

Obtain channel bandwidth, channel power vector and amplified spontaneous emission noise power;

According to the optical pre-amplification parameter vector, the channel input fiber power vector is obtained;

Based on the Gaussian noise closed solution model after the correction of the stimulated Raman scattering, perform power calculation on the channel power vector to obtain a nonlinear noise power vector;

summing the nonlinear noise power vector and the amplified spontaneous emission noise power to obtain a total noise power vector;

Dividing the channel input power vector by the total noise power vector to obtain a power quotient vector;

performing a logarithmic operation on the power quotient vector to obtain a signal-to-noise ratio vector;

According to the signal-to-noise ratio vector, a loss function value is obtained.

In an implementation manner, wherein, according to the optical pre-amplification parameter vector, obtaining the channel fiber-in power vector includes:

Obtain the center frequency of the optical signal of each band and the center frequency vector of each channel;

subtracting the center frequency of each band optical signal from the center frequency vector to obtain a frequency difference vector;

multiplying the gain slope vector in the optical pre-amplification parameter vector by the frequency difference vector to obtain a product vector;

The product vector is added to the gain offset vector in the optical pre-amplification parameter vector to obtain a channel fiber input power vector.

In an implementation manner, wherein the obtaining the loss function value according to the signal-to-noise ratio vector includes:

Performing a logarithmic operation on the SNR vector to obtain a capacity vector;

Acquiring the mean value of the capacity, the maximum value of the capacity and the minimum value of the capacity of the capacity vector;

calculating the reciprocal of the mean value of capacity to obtain the reciprocal value of the mean value of capacity;

The loss function value is obtained by adding the reciprocal value of the mean value of the capacity to the maximum value of the capacity and subtracting the minimum value of the capacity.

In an implementation manner, wherein, according to the optical pre-amplification parameter vector, the loss function value and the simulated annealing algorithm, determining the optimized optical pre-amplification parameter vector includes:

Get random probability value;

Obtain an initial temperature parameter and an initial iteration parameter, wherein the initial temperature parameter is used to characterize the variable parameters of the simulated annealing algorithm;

updating the initial temperature parameter according to the simulated annealing algorithm and the initial iteration parameter to obtain an updated temperature parameter;

Iteratively calculating the optical pre-amplification parameter vector and the updated temperature parameter to obtain an updated optical pre-amplification parameter vector;

According to the updated optical pre-amplification parameter vector and the preset stimulated Raman scattering corrected Gaussian noise closed solution model, the updated loss function value is obtained;

According to the loss function value and the updated loss function value, an optimized optical pre-amplification parameter vector is obtained.

In an implementation manner, wherein the updating of the initial temperature parameter according to the simulated annealing algorithm and the initial iteration parameter, and obtaining the updated temperature parameter includes:

When the number of iterative operations performed on the optical pre-amplification parameter vector and the updated temperature parameter reaches a preset threshold number of iterations, performing a self-accumulation operation on the initial iterative parameters to obtain an iterative parameter;

Divide the initial temperature parameter by the iteration parameter to obtain an updated temperature parameter.

In an implementation manner, wherein the obtaining the optimized optical pre-amplification parameter vector according to the loss function value and the updated loss function value includes:

When the updated loss function value is less than or equal to the loss function value, continue to execute the Gaussian noise closed solution model corrected according to the updated optical pre-amplification parameter vector and the preset stimulated Raman scattering to obtain the updated loss function value step;

When the updated loss function value is greater than the loss function value, an exponential operation is performed on the updated loss function value, the loss function value and the temperature parameter to obtain the probability value of the optical pre-amplification parameter vector; when the When the probability value of the optical pre-amplification parameter vector is greater than or equal to the random probability value, continue to execute the Gaussian noise closed solution model corrected according to the updated optical pre-amplification parameter vector and the preset stimulated Raman scattering, and the updated The step of the loss function value of ;

When the updated temperature parameter reaches a preset temperature parameter threshold, or when the number of updates to the initial temperature parameter according to the simulated annealing algorithm and the initial iteration parameter reaches a preset update times threshold and the update When the final optical pre-amplification parameter vector is constant, the simulated annealing algorithm is stopped to obtain the optimized loss function value;

The updated optical pre-amplification parameter vector corresponding to the optimized loss function value is used as the optimized optical pre-amplification parameter vector.

In the second aspect, the embodiment of the present invention also provides a pre-amplification parameter optimization device applied to an ultra-wideband wavelength division multiplexing system, wherein the device includes:

The optical pre-amplification parameter vector module is used to obtain the optical pre-amplification parameter vector after random initialization, wherein the optical pre-amplification parameter vector is used to characterize the gain slope vector and gain of several band optical amplifiers in the ultra-wideband wavelength division multiplexing system bias vector;

The loss function value acquisition module is used to obtain the loss function value according to the optical pre-amplification parameter vector and the preset stimulated Raman scattering corrected Gaussian noise closed solution model;

The optimized optical pre-amplification parameter vector determination module is used to determine the optimized optical pre-amplification parameter vector according to the optical pre-amplification parameter vector, the loss function value and the simulated annealing algorithm.

In the third aspect, the embodiment of the present invention also provides an intelligent terminal, including a memory, and one or more programs, wherein one or more programs are stored in the memory, and configured to be executed by one or more processors The one or more programs are used to execute the pre-amplification parameter optimization method applied to the ultra-wideband wavelength division multiplexing system as described in any one of the above.

In the fourth aspect, the embodiment of the present invention also provides a non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by the processor of the electronic device, the electronic device can execute the The optimization method of pre-amplification parameters applied to ultra-wideband wavelength division multiplexing system described above.

Beneficial effects of the present invention: the embodiment of the present invention first obtains the optical pre-amplification parameter vector after random initialization, wherein the optical pre-amplification parameter vector is used to represent the gain slope vector of several band optical amplifiers in the ultra-wideband wavelength division multiplexing system and gain offset vector; to prepare for subsequent optimization, and then correct the Gaussian noise closed solution model according to the optical pre-amplification parameter vector and the preset stimulated Raman scattering, and obtain the loss function value to prepare for subsequent further optimization ; Finally, according to the optical pre-amplification parameter vector, the loss function value and the simulated annealing algorithm, the optimized optical pre-amplification parameter vector is determined, and the optimized optical pre-amplification parameter vector can be used for the pre-amplification of each channel optimized The power spectrum maximizes the channel signal-to-noise ratio within the overall bandwidth during transmission, thereby obtaining the maximum communication transmission capacity. Compared with the traditional power control optimization algorithm, this program does not require violent scanning, and the time complexity is low, and the closed solution model of Gaussian noise after the correction of stimulated Raman scattering takes into account the stimulated Raman scattering caused by ultra-broadband, and the result is more accurate , which can increase the limit communication capacity to a greater extent.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments described in the present invention. Those skilled in the art can also obtain other drawings based on these drawings without creative work.

Fig. 1 is a schematic flowchart of a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system provided by an embodiment of the present invention.

Fig. 2 is a schematic diagram of power spectrum slope and central polarization after amplification by three band amplifiers provided by an embodiment of the present invention.

FIG. 3 is a flowchart of an annealing algorithm provided by an embodiment of the present invention.

FIG. 4 is a block diagram of a power control parameter optimization process based on a simulated annealing algorithm provided by an embodiment of the present invention.

Fig. 5 is a limit capacity spectrum diagram of all channels provided by the embodiment of the present invention.

FIG. 6 is a functional block diagram of a pre-amplification parameter optimization device applied to an ultra-wideband wavelength division multiplexing system provided by an embodiment of the present invention.

FIG. 7 is a functional block diagram of an internal structure of a smart terminal provided by an embodiment of the present invention.

Detailed ways

The present invention discloses a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system. In order to make the purpose, technical solution and effect of the present invention clearer and clearer, the present invention will be further described in detail below with reference to the accompanying drawings and examples . It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

Those skilled in the art will understand that unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the word "comprising" used in the description of the present invention refers to the presence of said features, integers, steps, operations, elements and/or components, but does not exclude the presence or addition of one or more other features, Integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Additionally, "connected" or "coupled" as used herein may include wireless connection or wireless coupling. The expression "and/or" used herein includes all or any elements and all combinations of one or more associated listed items.

Those skilled in the art can understand that, unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art to which this invention belongs. It should also be understood that terms, such as those defined in commonly used dictionaries, should be understood to have meanings consistent with their meaning in the context of the prior art, and unless specifically defined as herein, are not intended to be idealized or overly Formal meaning to explain.

In the existing technology, the improvement of optical communication capacity can start with the use of light dimensions, which include: polarization, time, wavelength, and mode. The wavelength, as a physical property of light, is very suitable for multiplexing light due to its wide range. At present, ultra-wideband wavelength division multiplexing has attracted extensive attention because of the capacity increase brought by ultra-high bandwidth.

The wavelength range of the ultra-high bandwidth WDM system consists of C-band, L-band and S-band. The C-band is currently in commercial use, and the L-band is expected to be applied after the amplifiers of the corresponding band are mature. Currently, the S-band has not yet been added to the wavelength division multiplexing band because the corresponding amplifier has not yet been commercialized. However, the range of the S-band is almost twice that of the C-band. Therefore, after the development of the instrument in the future, it is bound to introduce a wavelength division multiplexing system to form an ultra-high bandwidth wavelength division multiplexing coherent communication system to greatly increase the communication capacity.

But with the widening of the communication bandwidth, the frequency spectrum is widened accordingly. Therefore, when the number of channels is very large (hundreds of channels), the overall optical power in the optical fiber will be very large, generally up to more than 20 dBm. Such a large optical power combined with an ultra-wide bandwidth will cause stimulated Raman scattering effects in addition to nonlinear effects such as self-phase modulation, four-wave mixing, and cross-phase modulation, and generate gains for low-frequency channels. The frequency shift of the gain is about 13THz. This leads to a decrease in the power of the high-frequency signal and a further increase in the power of the low-frequency signal, resulting in a higher nonlinear effect in the low-frequency region. These nonlinear effects will lead to higher nonlinear noise power and reduce the signal-to-noise ratio of the signal, thereby reducing the communication capacity limit of the channel.

In order to deal with the problem that the limit of communication capacity will drop due to the introduction of more bands, we propose a closed solution and simulated annealing algorithm based on the Gaussian noise model modified by stimulated Raman scattering, which is used to optimize the Pre-amplify the power spectrum to maximize the channel signal-to-noise ratio within the overall bandwidth during transmission, thereby obtaining the maximum communication transmission capacity.

In order to solve the problems of the prior art, this embodiment provides a pre-amplification parameter optimization method applied to ultra-wideband wavelength division multiplexing systems. The above method is used to optimize the pre-amplification power spectrum of each channel, so that the overall The signal-to-noise ratio of the channel within the bandwidth is the largest, thereby obtaining the largest communication transmission capacity. During specific implementation, obtain the optical pre-amplification parameter vector after random initialization, wherein, the optical pre-amplification parameter vector is used to characterize the gain slope vector and the gain bias vector of several band optical amplifiers in the ultra-wideband wavelength division multiplexing system; then According to the optical pre-amplification parameter vector and the preset stimulated Raman scattering corrected Gaussian noise closed solution model, the loss function value is obtained; finally, according to the optical pre-amplification parameter vector, the loss function value and the simulated annealing algorithm, Determine the optimized optical pre-amplification parameter vector.

exemplary method

This embodiment provides a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system, and the method can be applied to an intelligent terminal for digital signal processing. Specifically as shown in Figure 1, the method includes:

Step S100, obtaining a randomly initialized optical pre-amplification parameter vector, wherein the optical pre-amplification parameter vector is used to characterize the gain slope vector and gain offset vector of several band optical amplifiers in an ultra-wideband wavelength division multiplexing system;

Specifically, the randomly initialized optical pre-amplification parameter vector may be generated on the server, and then the randomly initialized optical pre-amplification parameter vector on the server may be obtained, or may be directly generated on the terminal device, without limitation. Wherein, the optical pre-amplification parameter vector is used to characterize the gain slope vector and gain offset vector of several band optical amplifiers in the ultra-wideband wavelength division multiplexing system, as shown in FIG. 2 .

In order to obtain the optical pre-amplification parameter vector, the optical pre-amplification parameter vector after the random initialization includes the following steps:

S101. Generate several random values;

S102. Make a vector composed of several random values as an optical pre-amplification parameter vector.

In the present embodiment, the optical pre-amplification parameter vector includes amplifiers of three bands (L band, C band and S band), and the amplifier of each band includes two parameters: gain slope vector slope and gain offset vector offset, like this , a total of six parameters. First, 6 numbers are randomly generated, and these 6 numbers are formed into a vector, and the vector is used as a light pre-amplification parameter vector.

After the optical pre-amplification parameter vector is obtained, the following steps as shown in Figure 1 can be performed: S200, according to the optical pre-amplification parameter vector and the preset stimulated Raman scattering corrected Gaussian noise closed solution model, to obtain the loss function value;

Specifically, the light pre-amplification parameter vector can be input into the preset Gaussian noise closed solution model after Stimulated Raman Scattering correction, or the light pre-amplification parameter vector and the preset Stimulated Raman Scattering correction The post-Gaussian noise closed solution model performs mixed operations to obtain the loss function value, which is not specifically limited.

In order to obtain the loss function value, the Gaussian noise closed solution model modified according to the optical pre-amplification parameter vector and the preset stimulated Raman scattering, and obtaining the loss function value includes the following steps:

S201. Obtain channel bandwidth, channel power vector and amplified spontaneous emission noise power;

S202. Obtain a channel input fiber power vector according to the optical pre-amplification parameter vector;

S203. Based on the Gaussian noise closed solution model after the Stimulated Raman scattering correction, perform power calculation on the channel power vector to obtain a nonlinear noise power vector;

S204. Summing the nonlinear noise power vector and the amplified spontaneous emission noise power to obtain a total noise power vector;

S205. Divide the channel input power vector by the total noise power vector to obtain a power quotient vector;

S206. Perform a logarithmic operation on the power quotient vector to obtain a signal-to-noise ratio vector;

S207. Obtain a loss function value according to the signal-to-noise ratio vector.

Specifically, first obtain the channel bandwidth B (can be set to 28 GHz), channel power vectors Pi, P _i,j and the amplified spontaneous emission noise power P _ASE ; in this embodiment, the amplified spontaneous emission noise power P _ASE is obtained by the following formula :

P _ASE =B*hv*Nf*(G-1)

Among them, B represents the channel width, h is Planck's constant (6.62607004×10-34m2 kg/s), v represents the optical frequency of the channel, NF represents the noise figure of the optical amplifier, and G is the gain coefficient of the amplifier in the channel. According to the optical pre-amplification parameter vector x, the channel input fiber power vector P _ch is obtained; correspondingly, the channel input fiber power vector is obtained according to the optical pre-amplification parameter vector. center frequency and the center frequency vector of each channel; the center frequency of each band optical signal is subtracted from the center frequency vector to obtain a frequency difference vector; the gain slope vector in the optical pre-amplification parameter vector is multiplied by the The frequency difference vector is used to obtain a product vector; the product vector is added to the gain offset vector in the optical pre-amplification parameter vector to obtain a channel input fiber power vector. For example: x is a vector with six elements x1-x6, x1 represents the gain slope of the L-band, x2 represents the gain bias of the L-band, x3 represents the gain slope of the C-band, x4 represents the gain bias of the C-band, x5 represents the gain slope of the S-band, and x6 represents the gain bias of the S-band. When x is input into the Gaussian noise model, the six elements of x are actually input to the amplifiers of the three bands respectively, so that the channel power after the amplification of the three bands (that is, the optical power distribution of each channel into the fiber) is as follows Formula distribution:

power _L ＝x1(ff _L )+x2

power _C ＝x3(ff _C )+x4

power _S ＝x5(ff _S )+x6

Where f represents the center frequency of each channel (it is a vector), f _L , f _C , and f _S represent the overall center frequencies of the L-band, C-band and S-band respectively. After obtaining the optical power distribution of the entire bandwidth into the fiber, the nonlinear power of each channel can be further calculated. The channel input power vector P _ch is composed of power _L , power _C and power _S. After obtaining the channel fiber-in power vector, based on the Gaussian noise closed solution model after the correction of the stimulated Raman scattering, perform power calculation on the channel power vector Pi, Pi _,j to obtain the nonlinear noise power vector P _NLI ; for example , the nonlinear noise power vector P _NLI is obtained by the following formula:

Among them, Pi represents the power of the i-th channel, P _i,j represents the power of the j-th channel, η _SPM,j (fi) and η _XPM,j (fi) represent the modified self-phase modulation nonlinear coefficient and Cross-phase modulation nonlinear coefficient, n ^∈ represents nonlinear noise. Then the nonlinear noise power vector P _NLI and the amplified spontaneous emission noise power _PASE are summed to obtain the total noise power vector; the channel input fiber power vector P _ch is divided by the total noise power vector to obtain the power Quotient value vector; Logarithmic operation is carried out to described power quotient value vector, obtains signal-to-noise ratio vector SNR; For example, signal-to-noise ratio vector Finally, a loss function value is obtained according to the SNR vector. Correspondingly, the obtaining the loss function value according to the SNR vector includes the following steps: performing a logarithmic operation on the SNR vector to obtain a capacity vector; obtaining the capacity mean value, capacity maximum value and The minimum value of capacity; calculating the reciprocal of the mean value of capacity to obtain the reciprocal value of the mean value of capacity; adding the reciprocal value of the mean value of capacity to the maximum value of capacity and subtracting the minimum value of capacity to obtain a loss function value. For example, the capacity vector capacity is obtained by the following formula:

capacity=B×log2(1+SNR)

Among them, B is the channel bandwidth, and SNR is the signal-to-noise ratio vector, which represents the signal-to-noise ratio of each channel.

The loss function value Loss is obtained by the following formula:

Among them, capacity is a vector representing the capacity of all channels.

After the loss function value is obtained, the following steps as shown in FIG. 1 can be performed: S300, determine the optimized optical pre-amplification parameter vector according to the optical pre-amplification parameter vector, the loss function value and the simulated annealing algorithm.

Specifically, as shown in FIGS. 2-3 , according to the simulated annealing algorithm, the minimum loss function value is obtained by updating and iterating the light pre-amplification parameter vector and the loss function value. Correspondingly, the determining the optimized optical pre-amplification parameter vector according to the optical pre-amplification parameter vector, the loss function value and the simulated annealing algorithm includes:

S301. Obtain a random probability value;

S302. Obtain an initial temperature parameter and an initial iteration parameter, wherein the initial temperature parameter is used to represent a variable parameter of the simulated annealing algorithm;

S303. According to the simulated annealing algorithm and the initial iteration parameters, update the initial temperature parameters to obtain updated temperature parameters;

S304. Perform an iterative operation on the optical pre-amplification parameter vector and the updated temperature parameter to obtain an updated optical pre-amplification parameter vector;

S305. Obtain an updated loss function value according to the updated optical pre-amplification parameter vector and the preset Stimulated Raman scattering corrected Gaussian noise closed solution model;

S306. Obtain an optimized optical pre-amplification parameter vector according to the loss function value and the updated loss function value.

Specifically, first obtain the random probability value p0, p0 is a random probability value randomly generated between 0 and 1 according to the uniform distribution, and obtain the initial temperature parameter Tmax and the initial iteration parameter iter_num, wherein the initial temperature parameter is used to characterize the The variable parameters of the simulated annealing algorithm; according to the simulated annealing algorithm and the initial iteration parameters, update the initial temperature parameters to obtain updated temperature parameters; correspondingly, according to the simulated annealing algorithm and the The initial iterative parameter, the initial temperature parameter is updated, and the temperature parameter obtained after the update includes the following steps: when the number of iterative operations performed on the optical pre-amplification parameter vector and the updated temperature parameter reaches the preset number of iterations When the threshold is equal, the initial iteration parameter is self-accumulated to obtain an iteration parameter; the initial temperature parameter is divided by the iteration parameter to obtain an updated temperature parameter. For example, the temperature parameter will decrease with the increase of the above iterative process. For example, the temperature will be reduced every 100 rounds of operation. The cooling formula is as follows:

T=Tmax/iter_num

The temperature parameter after T is updated, Tmax represents the initial temperature parameter, the value is 300, iter_num represents the number of iterations (initial value is 1), and the iter_num value is increased by 1 every 100 iterations. The condition for the simulated annealing algorithm to stop is two One, when the temperature parameter is reduced to the initial minimum temperature parameter (such as 100), stop the optimization, and the second is to reduce the temperature of the loss 20 times, and stop when the updated optical pre-amplification parameter vector x _new still does not decrease search for excellence. Then iteratively calculate the optical pre-amplification parameter vector and the updated temperature parameter to obtain the updated optical pre-amplification parameter vector; for example, after obtaining the loss value loss of the current optical pre-amplification parameter vector x, simulated annealing The algorithm will update and generate an updated optical pre-amplification parameter vector x_new on the basis of the optical pre-amplification parameter vector x. The generation method is shown in the following formula:

Among them, upper represents the maximum value of the optical pre-amplification parameter vector x, lower represents the minimum value of the optical pre-amplification parameter vector x, r is a random number in [-1,1], and T represents the temperature parameter. According to the updated optical pre-amplification parameter vector x _new and the preset stimulated Raman scattering corrected Gaussian noise closed solution model, the updated loss function value loss _new is obtained; the specific process is to update the optical pre-amplification parameter vector x _new is used as the previous optical pre-amplification parameter vector, and the step S200 is continued to obtain the updated loss function value loss _new . Then according to the loss function value and the updated loss function value, the optimized optical pre-amplification parameter vector is obtained, and correspondingly, the optimized optical pre-amplification parameter vector is obtained according to the loss function value and the updated loss function value. Amplifying the parameter vector includes the following steps: when the updated loss function value is less than or equal to the loss function value, continue to execute the Gaussian noise closed solution model based on the updated optical pre-amplification parameter vector and the preset stimulated Raman scattering correction , the step of obtaining the updated loss function value; when the updated loss function value is greater than the said loss function value, perform an exponential operation on the updated loss function value, said loss function value and said temperature parameter to obtain said The probability value of the optical pre-amplification parameter vector; when the probability value of the optical pre-amplification parameter vector is greater than or equal to the random probability value, continue to perform the Stimulated Raman scattering according to the updated optical pre-amplification parameter vector and preset Stimulated Raman scattering The step of obtaining the updated loss function value after the Gaussian noise closed solution model is corrected; when the updated temperature parameter reaches the preset temperature parameter threshold, or when according to the simulated annealing algorithm and the initial iteration parameter, the When the number of times the initial temperature parameter is updated reaches the preset update times threshold and the updated light pre-amplification parameter vector remains unchanged, the simulated annealing algorithm is stopped to obtain an optimized loss function value; the optimized The updated optical pre-amplification parameter vector corresponding to the loss function value is used as the optimized optical pre-amplification parameter vector. For example, if loss_new<=loss, then treat x_new as a new x, continue to use the above update formula to iteratively find x_new with lower loss_new; if loss_new>loss, then accept the x_new with a certain probability, the light pre-amplification parameter vector The probability value of is generated by the following formula:

In the above formula, the distribution range of the probability value p of the light pre-amplification parameter vector is (0, 1). If the temperature parameter T is smaller, then p is closer to 0, and the random probability value p0 is between 0 and 1 according to the uniform distribution A random probability generated randomly, if p>=p0, accept the updated optical pre-amplification parameter vector x_new as the new optical pre-amplification parameter vector x and enter the next iteration. Otherwise it is not accepted. Therefore, when the temperature parameter is higher, the probability of accepting the updated optical pre-amplification parameter vector x_new with relatively low quality is greater, so the temperature is lowered through the simulated annealing algorithm, and high-quality updated optical pre-amplification is obtained with a higher probability parameter vector. Through the iterative operation of the above-mentioned simulated annealing algorithm, when the iteration ends, the optimized loss function value will finally be obtained. At this time, the optimized loss function value is the smallest, then the optimized loss function value corresponds to the updated The optical pre-amplification parameter vector is optimal, and can be used as the optimized optical pre-amplification parameter vector, thereby maximizing the limit capacity of the overall channel and maintaining capacity balance between channels.

As shown in Figure 4, it shows an embodiment of the pre-amplification parameter optimization method applied to the ultra-wideband wavelength division multiplexing system of the present invention, as shown in Figure 5, it shows the results of the preliminary simulation, and the abscissa represents the ultra-wideband Channel, the vertical axis represents the capacity of the channel. Here we have chosen three different optimization strategies. The circles represent the optimization results for maximizing the overall capacity. It can be seen that choosing this optimization strategy has a disadvantage, that is, it will lead to unbalanced capacity among channels. The asterisk represents the pursuit of the most balanced capacity between channels within the band, but it can be seen that the overall capacity is not high. The plus sign combines the advantages of the first two strategies, not only has a relatively high overall capacity, but also has a relatively stable capacity distribution.

exemplary device

As shown in Figure 6, an embodiment of the present invention provides a pre-amplification parameter optimization device applied to an ultra-wideband wavelength division multiplexing system, the device includes: an optical pre-amplification parameter vector module 401, a loss function value acquisition module 402 and an optimization After optical pre-amplification parameter vector determination module 403, wherein:

The optical pre-amplification parameter vector module 401 is used to obtain the optical pre-amplification parameter vector after random initialization, wherein the optical pre-amplification parameter vector is used to characterize the gain slope vector and the gain bias vector;

The loss function value acquisition module 402 is used to obtain the loss function value according to the light pre-amplification parameter vector and the preset Gaussian noise closed solution model after Stimulated Raman scattering correction;

The optimized optical pre-amplification parameter vector determination module 403 is configured to determine the optimized optical pre-amplification parameter vector according to the optical pre-amplification parameter vector, the loss function value and the simulated annealing algorithm.

Based on the above embodiments, the present invention also provides an intelligent terminal, the functional block diagram of which may be shown in FIG. 7 . The intelligent terminal includes a processor, a memory, a network interface, a display screen and a temperature sensor connected through a system bus. Wherein, the processor of the smart terminal is used to provide calculation and control capabilities. The memory of the smart terminal includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface of the smart terminal is used to communicate with external terminals through a network connection. When the computer program is executed by a processor, a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system is realized. The display screen of the smart terminal may be a liquid crystal display screen or an electronic ink display screen, and the temperature sensor of the smart terminal is pre-set inside the smart terminal for detecting the operating temperature of the internal equipment.

Those skilled in the art can understand that the schematic diagram in Figure 7 is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the intelligent terminal to which the solution of the present invention is applied. The specific intelligent terminal may include There may be more or fewer components than shown in the figures, or certain components may be combined, or have different component arrangements.

In one embodiment, an intelligent terminal is provided, including a memory, and one or more programs, wherein one or more programs are stored in the memory, and are configured to be executed by one or more processors. One or more programs include instructions for performing the following operations: obtain a randomly initialized optical pre-amplification parameter vector, wherein the optical pre-amplification parameter vector is used to characterize the performance of several band optical amplifiers in an ultra-wideband wavelength division multiplexing system Gain slope vector and gain bias vector;

According to the light pre-amplification parameter vector and the preset stimulated Raman scattering corrected Gaussian noise closed solution model, the loss function value is obtained;

An optimized optical pre-amplification parameter vector is determined according to the optical pre-amplification parameter vector, the loss function value, and a simulated annealing algorithm.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above-mentioned embodiments can be completed by instructing related hardware through computer programs, and the computer programs can be stored in a non-volatile computer-readable memory In the medium, when the computer program is executed, it may include the processes of the embodiments of the above-mentioned methods. Wherein, any reference to memory, storage, database or other media used in the various embodiments provided by the present invention may include non-volatile and/or volatile memory. Nonvolatile memory can include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Chain Synchlink DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

In summary, the present invention discloses a pre-amplification parameter optimization method, an intelligent terminal, and a storage medium applied to an ultra-wideband wavelength division multiplexing system. The method includes: obtaining a randomly initialized optical pre-amplification parameter vector, wherein the The optical pre-amplification parameter vector is used to characterize the gain slope vector and the gain offset vector of several band optical amplifiers in the ultra-wideband wavelength division multiplexing system; according to the optical pre-amplification parameter vector and preset stimulated Raman scattering correction Gaussian noise closed solution model to obtain the loss function value; according to the optical pre-amplification parameter vector, the loss function value and simulated annealing algorithm, determine the optimized optical pre-amplification parameter vector. The present invention optimizes the pre-amplification power spectrum of each channel through the above method, so that the signal-to-noise ratio of the channel in the overall bandwidth during transmission is maximized, thereby obtaining the maximum communication transmission capacity.

Based on the above-mentioned embodiments, the present invention discloses a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system. It should be understood that the application of the present invention is not limited to the above-mentioned examples. For those of ordinary skill in the art, Improvements or changes can be made according to the above description, and all these improvements and changes should belong to the protection scope of the appended claims of the present invention.

Claims (7)

1. A method for optimizing pre-amplification parameters applied to an ultra wideband wavelength division multiplexing system, the method comprising:

acquiring a randomly initialized optical pre-amplification parameter vector, wherein the optical pre-amplification parameter vector is used for representing gain slope vectors and gain offset vectors of a plurality of wave band optical amplifiers in an ultra-wideband wavelength division multiplexing system;

obtaining a loss function value according to the light pre-amplification parameter vector and a Gaussian noise closed solution model after the correction of the preset stimulated Raman scattering;

determining an optimized optical pre-amplification parameter vector according to the optical pre-amplification parameter vector, the loss function value and a simulated annealing algorithm;

the Gaussian noise closed solution model corrected according to the light pre-amplification parameter vector and the preset stimulated Raman scattering, and the loss function value obtaining comprises the following steps:

acquiring a channel bandwidth, a channel power vector and amplified spontaneous emission noise power;

obtaining a channel fiber-entering power vector according to the optical pre-amplification parameter vector;

based on the Gaussian noise closed solution model after stimulated Raman scattering correction, carrying out power calculation on the channel power vector to obtain a nonlinear noise power vector;

summing the nonlinear noise power vector and the amplified spontaneous emission noise power to obtain a noise total power vector;

dividing the channel fiber-entering power vector by a noise total power vector to obtain a power quotient vector;

carrying out logarithmic operation on the power quotient vector to obtain a signal-to-noise ratio vector; obtaining a loss function value according to the signal-to-noise ratio vector;

the obtaining a loss function value according to the signal-to-noise ratio vector comprises:

carrying out logarithmic operation on the signal-to-noise ratio vector to obtain a capacity vector;

acquiring a capacity average value, a capacity maximum value and a capacity minimum value of the capacity vector;

calculating the reciprocal of the capacity mean value to obtain a capacity mean reciprocal value;

adding the capacity maximum value to the capacity average value and subtracting the capacity minimum value to obtain a loss function value;

the loss function value is expressed as:

wherein capability represents a capacity vector;

the determining the optimized optical pre-amplification parameter vector according to the optical pre-amplification parameter vector, the loss function value and the simulated annealing algorithm comprises the following steps:

acquiring a random probability value;

acquiring an initial temperature parameter and an initial iteration parameter, wherein the initial temperature parameter is used for representing variable parameters of the simulated annealing algorithm;

updating the initial temperature parameter according to the simulated annealing algorithm and the initial iteration parameter to obtain an updated temperature parameter;

performing iterative operation on the optical pre-amplification parameter vector and the updated temperature parameter to obtain an updated optical pre-amplification parameter vector;

acquiring an updated loss function value according to the updated light pre-amplification parameter vector and a preset stimulated Raman scattering corrected Gaussian noise closed solution model;

and obtaining an optimized optical pre-amplification parameter vector according to the loss function value and the updated loss function value.

2. The method for optimizing a pre-amplification parameter for an ultra wideband wavelength division multiplexing system according to claim 1, wherein the obtaining the randomly initialized optical pre-amplification parameter vector comprises:

generating a plurality of random values;

and forming a vector by using a plurality of random values as a light pre-amplification parameter vector.

3. The method for optimizing the preamplification parameter applied to the ultra wideband wavelength division multiplexing system according to claim 1, wherein the obtaining the channel fiber-in power vector according to the optical preamplification parameter vector comprises:

acquiring the central frequency of each band optical signal and the central frequency vector of each channel;

subtracting the center frequency of each band optical signal from the center frequency vector to obtain a frequency difference vector;

multiplying the gain slope vector in the optical pre-amplification parameter vector by the frequency difference vector to obtain a product vector;

and adding the product vector to a gain offset vector in the optical pre-amplification parameter vector to obtain a channel fiber-entering power vector.

4. The method for optimizing preamplification parameter applied to ultra wideband wavelength division multiplexing system according to claim 1, wherein updating the initial temperature parameter according to the simulated annealing algorithm and the initial iteration parameter, the obtaining the updated temperature parameter comprises:

when the number of iterative operation on the optical pre-amplification parameter vector and the updated temperature parameter reaches a preset iteration number threshold, performing self-accumulation operation on the initial iteration parameter to obtain an iteration parameter;

dividing the initial temperature parameter by the iteration parameter to obtain an updated temperature parameter.

5. The method for optimizing a preamplification parameter for an ultra wideband wavelength division multiplexing system according to claim 1, wherein the obtaining an optimized optical preamplification parameter vector according to the loss function value and the updated loss function value comprises:

when the updated loss function value is smaller than or equal to the loss function value, continuing to execute the Gaussian noise closed solution model corrected according to the updated optical pre-amplification parameter vector and the preset stimulated Raman scattering to obtain the updated loss function value;

when the updated loss function value is larger than the loss function value, performing exponential operation on the updated loss function value, the loss function value and the temperature parameter to obtain a probability value of the optical pre-amplification parameter vector; when the probability value of the optical pre-amplification parameter vector is larger than or equal to the random probability value, continuing to execute a Gaussian noise closed solution model corrected according to the updated optical pre-amplification parameter vector and preset stimulated Raman scattering, and obtaining an updated loss function value;

stopping the simulated annealing algorithm when the updated temperature parameter reaches a preset temperature parameter threshold or when the number of times of updating the initial temperature parameter reaches a preset updating number threshold according to the simulated annealing algorithm and the initial iteration parameter and the updated optical pre-amplification parameter vector is unchanged, so as to obtain an optimized loss function value;

and taking the updated optical pre-amplification parameter vector corresponding to the optimized loss function value as the optimized optical pre-amplification parameter vector.

6. An intelligent terminal comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors, the one or more programs comprising instructions for performing the method of any of claims 1-5.

7. A non-transitory computer readable storage medium, wherein instructions in the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the method of any one of claims 1-5.