阅读说明：本技术 一种应用于超宽带波分复用系统的预放大参数优化方法 (Pre-amplification parameter optimization method applied to ultra-wideband wavelength division multiplexing system ) 是由 罗怀健 陆佳宁 余长源 于 2021-06-23 设计创作，主要内容包括：本发明公开了一种应用于超宽带波分复用系统的预放大参数优化方法,所述方法包括：获取随机初始化后的光预放大参数向量,其中,所述光预放大参数向量用于表征超宽带波分复用系统中若干波段光放大器的增益斜率向量和增益偏置向量；根据所述光预放大参数向量和预设的受激拉曼散射修正后高斯噪声闭合解模型,得到损失函数值；根据所述光预放大参数向量、所述损失函数值和模拟退火算法,确定优化后的光预放大参数向量。本发明通过上述方法来优化每个信道的预放大功率谱,使得传输时的整体带宽内的信道信噪比最大,进而得到最大的通信传输容量。(The invention discloses a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system, which comprises the following steps: obtaining an optical pre-amplification parameter vector after random initialization, wherein the optical pre-amplification parameter vector is used for representing a gain slope vector and a gain offset vector of a plurality of 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 preset Gaussian noise closed solution model after stimulated Raman scattering correction; and determining the optimized light pre-amplification parameter vector according to the light pre-amplification parameter vector, the loss function value and a simulated annealing algorithm. The invention optimizes the pre-amplification power spectrum of each channel by the method, so that the signal-to-noise ratio of the channel in the whole bandwidth is maximum during transmission, and the maximum communication transmission capacity is further obtained.)

1. A pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system is characterized by comprising the following steps:

obtaining an optical pre-amplification parameter vector after random initialization, wherein the optical pre-amplification parameter vector is used for representing a gain slope vector and a gain offset vector of a plurality of 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 preset Gaussian noise closed solution model after stimulated Raman scattering correction;

and determining the optimized light pre-amplification parameter vector according to the light pre-amplification parameter vector, the loss function value and a simulated annealing algorithm.

2. The pre-amplification parameter optimization method applied to the UWB WDM 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 an optical pre-amplification parameter vector.

3. The pre-amplification parameter optimization method applied to the ultra-wideband wavelength division multiplexing system according to claim 1, wherein the obtaining of the loss function value according to the optical pre-amplification parameter vector and a preset excited raman scattering modified gaussian noise closed solution model comprises:

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

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

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

summing the nonlinear noise power vector and the amplified spontaneous radiation 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 logarithm operation on the power quotient vector to obtain a signal-to-noise ratio vector;

and obtaining a loss function value according to the signal-to-noise ratio vector.

4. The pre-amplification parameter optimization method for ultra-wideband wavelength division multiplexing systems as claimed in claim 3, wherein the obtaining the channel incoming power vector according to the pre-amplification parameter vector comprises:

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

subtracting the central frequency of each wave band optical signal from the central frequency vector to obtain a frequency difference value 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.

5. The pre-amplification parameter optimization method for use in an ultra-wideband wavelength division multiplexing system according to claim 3, wherein the deriving the loss function value from the snr vector comprises:

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

acquiring a capacity mean 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 value reciprocal value;

and adding the capacity maximum value to the capacity mean value and then subtracting the capacity minimum value to obtain a loss function value.

6. The pre-amplification parameter optimization method applied to the uwb wdm system according to claim 1, wherein 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:

acquiring a random probability value;

acquiring an initial temperature parameter and an initial iteration parameter, wherein the initial temperature parameter is used for representing a variable parameter 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 light pre-amplification parameter vector and the updated temperature parameter to obtain an updated light pre-amplification parameter vector;

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

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

7. The pre-amplification parameter optimization method applied to the UWB WDM system according to claim 6, wherein the updating the initial temperature parameter according to the simulated annealing algorithm and the initial iteration parameter, and the obtaining the updated temperature parameter comprises:

when the iterative operation times of the optical pre-amplification parameter vector and the updated temperature parameter reach a preset iterative time threshold value, performing self-accumulation operation on the initial iterative parameter to obtain an iterative parameter;

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

8. The pre-amplification parameter optimization method applied to the uwb wdm system according to claim 6, wherein the obtaining the optimized light pre-amplification 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 a Gaussian noise closed solution model corrected according to the updated light pre-amplification parameter vector and preset stimulated Raman scattering to obtain an 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 light pre-amplification parameter vector is larger than or equal to the random probability value, continuing to execute a Gaussian noise closed solution model after correction according to the updated light pre-amplification parameter vector and preset stimulated Raman scattering to obtain an updated loss function value;

stopping the simulated annealing algorithm when the updated temperature parameter reaches a preset temperature parameter threshold value, or when the number of times of updating the initial temperature parameter reaches a preset updating number threshold value and the updated light pre-amplification parameter vector is unchanged according to the simulated annealing algorithm and the initial iteration parameter, 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.

9. An intelligent terminal comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory, and wherein the one or more programs being configured to be executed by the one or more processors comprises instructions for performing the method of any of claims 1-8.

10. 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 of claims 1-8.

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

The rapid development of the mobile internet not only prompts the fifth generation of communication internet, but also enables various mobile communication applications to appear in the time of nearly five years like spring bamboo shoots. Such as 4k video streaming, ultra high definition video telephony, cloud computing, and the like. As a backbone network of a communication network, an optical fiber communication system faces a great challenge and opportunity in increasing communication capacity.

However, as the communication bandwidth is widened, the frequency spectrum is correspondingly widened, since each band contains many channels, the number of channels is very large (hundreds of channels) due to multiple bands, and after the optical power of different bands is pre-amplified, the total optical power in the optical fiber is very large, and can reach 20 dBm generally. Such a large optical power, combined with an ultra-wide bandwidth, may cause a stimulated raman scattering effect in addition to nonlinear effects such as self-phase modulation, four-wave mixing, and cross-phase modulation, and generate gains for low-frequency channels, which may generate nonlinear effects, resulting in higher nonlinear noise power, so that the signal-to-noise ratio of signals is reduced, thereby reducing the communication capacity limit of the channels.

Thus, there is still a need for improvement and development of the prior art.

Disclosure of 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, aiming at solving the problems that in the prior art, optical signals are prevented from causing stimulated raman scattering effects other than nonlinear effects such as self-phase modulation, four-wave mixing, cross-phase modulation, etc., and gains are generated for low-frequency channels, and the gains generate nonlinear effects, thereby causing higher nonlinear noise power, reducing the signal-to-noise ratio of the signals, and further reducing the communication capacity limit of the channels.

The technical scheme adopted by the invention for solving the problems 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, where the method includes:

obtaining an optical pre-amplification parameter vector after random initialization, wherein the optical pre-amplification parameter vector is used for representing a gain slope vector and a gain offset vector of a plurality of 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 preset Gaussian noise closed solution model after stimulated Raman scattering correction;

and determining the optimized light pre-amplification parameter vector according to the light pre-amplification parameter vector, the loss function value and a simulated annealing algorithm.

In one implementation, the obtaining the randomly initialized light pre-amplification parameter vector includes:

generating a plurality of random values;

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

In an implementation manner, the obtaining a loss function value according to the light pre-amplification parameter vector and a preset excited raman scattering modified gaussian noise closed solution model includes:

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

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

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

summing the nonlinear noise power vector and the amplified spontaneous radiation 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 logarithm operation on the power quotient vector to obtain a signal-to-noise ratio vector;

and obtaining a loss function value according to the signal-to-noise ratio vector.

In one implementation, the obtaining a channel fiber-entering power vector according to the optical pre-amplification parameter vector includes:

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

subtracting the central frequency of each wave band optical signal from the central frequency vector to obtain a frequency difference value 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.

In one implementation, the obtaining a loss function value according to the snr vector includes:

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

acquiring a capacity mean 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 value reciprocal value;

and adding the capacity maximum value to the capacity mean value and then subtracting the capacity minimum value to obtain a loss function value.

In one implementation, the determining the optimized light pre-amplification parameter vector according to the light pre-amplification parameter vector, the loss function value, and a simulated annealing algorithm includes:

acquiring a random probability value;

acquiring an initial temperature parameter and an initial iteration parameter, wherein the initial temperature parameter is used for representing a variable parameter 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 light pre-amplification parameter vector and the updated temperature parameter to obtain an updated light pre-amplification parameter vector;

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

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

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

when the iterative operation times of the optical pre-amplification parameter vector and the updated temperature parameter reach a preset iterative time threshold value, performing self-accumulation operation on the initial iterative parameter to obtain an iterative parameter;

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

In one implementation, the obtaining the optimized light pre-amplification parameter vector according to the loss function value and the updated loss function value includes:

when the updated loss function value is smaller than or equal to the loss function value, continuing to execute a Gaussian noise closed solution model corrected according to the updated light pre-amplification parameter vector and preset stimulated Raman scattering to obtain an 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 light pre-amplification parameter vector is larger than or equal to the random probability value, continuing to execute a Gaussian noise closed solution model after correction according to the updated light pre-amplification parameter vector and preset stimulated Raman scattering to obtain an updated loss function value;

stopping the simulated annealing algorithm when the updated temperature parameter reaches a preset temperature parameter threshold value, or when the number of times of updating the initial temperature parameter reaches a preset updating number threshold value and the updated light pre-amplification parameter vector is unchanged according to the simulated annealing algorithm and the initial iteration parameter, 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.

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

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

the loss function value acquisition module is used for obtaining a loss function value according to the optical pre-amplification parameter vector and a preset Gaussian noise closed solution model after stimulated Raman scattering correction;

and the optimized light pre-amplification parameter vector determining module is used for determining the optimized light pre-amplification parameter vector according to the light pre-amplification parameter vector, the loss function value and the simulated annealing algorithm.

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

In a fourth aspect, embodiments of the present invention further provide a non-transitory computer-readable storage medium, where instructions of the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system as described in any one of the above.

The invention has the beneficial effects that: the method comprises the steps of firstly, obtaining an optical pre-amplification parameter vector after random initialization, wherein the optical pre-amplification parameter vector is used for representing a gain slope vector and a gain offset vector of a plurality of band optical amplifiers in an ultra-wideband wavelength division multiplexing system; preparing for subsequent optimization, and then obtaining a loss function value according to the light pre-amplification parameter vector and a preset Gaussian noise closed solution model after stimulated Raman scattering correction, so as to prepare for subsequent further optimization; and finally, 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, wherein the optimized optical pre-amplification parameter vector can be used for optimizing the pre-amplification power spectrum of each channel, so that the signal-to-noise ratio of the channel in the whole bandwidth during transmission is maximized, and the maximum communication transmission capacity is obtained. Compared with the traditional power control tuning algorithm, the program does not need violent scanning, the time complexity is low, the stimulated Raman scattering caused by the ultra-wideband is considered by the Gaussian noise closed solution model after the stimulated Raman scattering correction, the result is more accurate, and the limit communication capacity can be improved to be larger.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

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

Fig. 2 is a schematic diagram of the power spectrum slope and the central polarization after amplification of the amplifier with three bands according to the embodiment of the present invention.

Fig. 3 is a flowchart of an annealing algorithm according to an embodiment of the present invention.

Fig. 4 is a block diagram of a power control parameter optimization flow based on a simulated annealing algorithm according to an embodiment of the present invention.

Fig. 5 is a spectrum diagram of the limit capacity of all channels according to an embodiment of the present invention.

Fig. 6 is a schematic block diagram of a pre-amplification parameter optimization apparatus applied to an ultra-wideband wavelength division multiplexing system according to an embodiment of the present invention.

Fig. 7 is a schematic block diagram of an internal structure of an intelligent terminal according to an embodiment of the present invention.

Detailed Description

The invention discloses a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system, and in order to make the purpose, technical scheme and effect of the invention clearer and clearer, the invention is further described in detail below by referring to the attached drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude 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. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.

It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

Because in the prior art, increasing optical communication capacity can be started from the dimension of utilizing light, the dimensions are as follows: polarization, time, wavelength, mode. The wavelength is a physical property of light, and is very suitable for multiplexing light due to its wide range. At present, the capacity increase of ultra-wideband wavelength division multiplexing due to its ultra-high bandwidth is receiving wide attention.

The wavelength range of the ultra-high bandwidth wavelength division multiplexing system consists of a C wave band, an L wave band and an S wave band. Currently, the C band is in commercial use, the L band is expected to be applied after the amplifiers of the corresponding bands are mature, and the S band is not added with the wavelength division multiplexing band because the corresponding amplifiers of the S band are not in commercial use at present. However, the range of the S band is almost twice of the C band, so that a wavelength division multiplexing system is inevitably introduced to form a wavelength division multiplexing coherent communication system with an ultra-high bandwidth after the future instrument development is mature, so as to greatly improve the communication capacity.

But as the communication bandwidth is widened, the frequency spectrum is correspondingly widened. Thus, when the number of channels is very large (hundreds of channels), the total optical power within the fiber can be very large, typically up to 20 dBm. Such a large optical power, combined with an ultra-wide bandwidth, may cause a stimulated raman scattering effect in addition to nonlinear effects such as self-phase modulation, four-wave mixing, cross-phase modulation, and the like, and may generate a gain for a low-frequency channel. The frequency shift of the gain is approximately around 13 THz. This results in a decrease in the power of the high frequency signal and a further increase in the power of the low frequency signal, thereby creating a higher non-linear effect in the low frequency region. These non-linear effects result in higher non-linear noise power, which reduces the signal-to-noise ratio of the signal, and thus the communication capacity limit of the channel is reduced.

In order to solve the problem of limit reduction of communication capacity caused by introducing more wave bands, a closed solution based on a Gaussian noise model after stimulated Raman scattering correction and a program of a simulated annealing algorithm are provided for optimizing a pre-amplification power spectrum of each channel, so that the signal-to-noise ratio of the channel in the whole bandwidth during transmission is maximized, and the maximum communication transmission capacity is obtained.

In order to solve the problems in the prior art, the embodiment provides a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system, and the pre-amplification power spectrum of each channel is optimized by the method, so that the signal-to-noise ratio of the channel in the whole bandwidth during transmission is maximized, and further, the maximum communication transmission capacity is obtained. In specific implementation, obtaining an optical pre-amplification parameter vector after random initialization, wherein the optical pre-amplification parameter vector is used for representing a gain slope vector and a gain offset vector of a plurality of band optical amplifiers in an ultra-wideband wavelength division multiplexing system; then, obtaining a loss function value according to the light pre-amplification parameter vector and a preset Gaussian noise closed solution model after stimulated Raman scattering correction; and finally, determining the optimized optical pre-amplification parameter vector according to the optical pre-amplification parameter vector, the loss function value and a simulated annealing algorithm.

Exemplary method

The 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. As shown in fig. 1 in detail, the method includes:

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

specifically, the randomly initialized optical pre-amplification parameter vector may be generated in a server, and then the randomly initialized optical pre-amplification parameter vector on the server is obtained, or may be directly generated on a terminal device, which is not limited specifically. The optical pre-amplification parameter vector is used to characterize a gain slope vector and a gain offset vector of a plurality of band optical amplifiers in an ultra-wideband wavelength division multiplexing system, as shown in fig. 2.

In order to obtain the optical pre-amplification parameter vector, the obtaining of the randomly initialized optical pre-amplification parameter vector includes the following steps:

s101, generating a plurality of random values;

and S102, forming a vector by using a plurality of random values as a light pre-amplification parameter vector.

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

After obtaining the optical pre-amplification parameter vector, the following steps can be performed as shown in fig. 1: s200, obtaining a loss function value according to the light pre-amplification parameter vector and a preset Gaussian noise closed solution model after stimulated Raman scattering correction;

specifically, the optical pre-amplification parameter vector may be input to a preset stimulated raman scattering corrected gaussian noise closed solution model, or the optical pre-amplification parameter vector and the preset stimulated raman scattering corrected gaussian noise closed solution model may be subjected to a hybrid operation to obtain a loss function value, which is not particularly limited.

In order to obtain a loss function value, the obtaining of the loss function value according to the optical pre-amplification parameter vector and a preset gaussian noise closed solution model after stimulated raman scattering correction comprises the following steps:

s201, acquiring channel bandwidth, channel power vector and amplified spontaneous emission noise power;

s202, obtaining a channel fiber-entering power vector according to the optical pre-amplification parameter vector;

s203, performing power calculation on the channel power vector based on the Gaussian noise closed solution model after the stimulated Raman scattering correction to obtain a nonlinear noise power vector;

s204, summing the nonlinear noise power vector and the amplified spontaneous emission noise power to obtain a noise total power vector;

s205, dividing the channel fiber-entering power vector by a noise total power vector to obtain a power quotient vector;

s206, carrying out logarithmic operation on the power quotient vector to obtain a signal-to-noise ratio vector;

and S207, obtaining a loss function value according to the signal-to-noise ratio vector.

Specifically, channel bandwidth B (which may be set to 28GHz), channel power vectors Pi, P are obtained first_i,jAnd amplifying the spontaneous emission noise power P_ASE(ii) a In the present embodiment, the spontaneous radiation noise power P is amplified_ASEObtained by the following formula:

P_ASE＝B*hv*Nf*(G-1)

where B represents the channel width, h is the Planckian constant (6.62607004X 10-34m2 kg/s), v represents the channel optical frequency, NF represents the noise figure of the optical amplifier, and G is the gain figure of the amplifier at the channel. Then according to the optical pre-amplification parameter vector x, obtaining a channel fiber-entering power vector P_ch(ii) a Correspondingly, the step of obtaining the channel fiber-entering power vector according to the optical pre-amplification parameter vector comprises the following steps: acquiring the central frequency of each band optical signal and the central frequency vector of each channel; subtracting the central frequency of each wave band optical signal from the central frequency vector to obtain a frequency difference value 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. For example: x is a vector in which 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, in practice, 6 elements of x are respectively input into amplifiers of three bands, and the channel power after amplification of the three bands (i.e. the fiber-in power distribution of each channel) is distributed according to the following formula:

power_L＝x1(f-f_L)+x2

power_C＝x3(f-f_C)+x4

power_S＝x5(f-f_S)+x6

wherein f represents eachThe center frequency (being a vector) of each channel, f_L，f_CAnd f and_Srepresenting the overall center frequencies of the L-band, C-band and S-band, respectively. After the fiber-in optical power distribution of the whole bandwidth is obtained, the nonlinear power of each channel can be further calculated. Channel fiber-entering power vector P_chBy power_L、power_CAnd power_SAnd (4) forming. After the channel fiber-entering power vector is obtained, the channel power vectors Pi and P are subjected to the Gaussian noise closed solution model based on the stimulated Raman scattering correction_i,jPerforming power calculation to obtain a nonlinear noise power vector P_NLI(ii) a For example, the non-linear noise power vector P_NLIObtained by the following formula:

where Pi represents the power of the ith channel, P_i,jRepresenting the power of the jth channel, η_SPM,j(fi) and η_XPM,j(fi) respectively representing the modified self-phase modulation nonlinear coefficient and cross-phase modulation nonlinear coefficient, n^∈Representing nonlinear noise. Then the nonlinear noise power vector P_NLIAnd the amplified spontaneous emission noise power P_ASESumming to obtain a noise total power vector; putting the channel into a fiber power vector P_chDividing the total power vector of the noise to obtain a power quotient vector; carrying out logarithm operation on the power quotient vector to obtain a signal-to-noise ratio vector SNR; for example, a signal-to-noise ratio vector And finally, obtaining a loss function value according to the signal-to-noise ratio vector. Correspondingly, the step of obtaining the loss function value according to the signal-to-noise ratio vector comprises the following steps: carrying out logarithmic operation on the signal-to-noise ratio vector to obtain a capacity vector; obtaining the capacity mean value and the capacity of the capacity vectorMaximum and capacity minimum; calculating the reciprocal of the capacity mean value to obtain a capacity mean value reciprocal value; and adding the capacity maximum value to the capacity mean value and then subtracting the capacity minimum value to obtain a loss function value. For example, the capacity vector capacity is obtained by the following formula:

capacity＝B×log2(1+SNR)

where B is the channel bandwidth and SNR is the signal-to-noise ratio vector representing the signal-to-noise ratio of each channel.

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

wherein, capacity is a vector representing the capacity of all channels.

After obtaining the loss function value, the following steps can be performed as shown in fig. 1: s300, determining the optimized light pre-amplification parameter vector according to the light pre-amplification parameter vector, the loss function value and the simulated annealing algorithm.

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

s301, acquiring a random probability value;

s302, obtaining an initial temperature parameter and an initial iteration parameter, wherein the initial temperature parameter is used for representing a variable parameter of the simulated annealing algorithm;

s303, updating the initial temperature parameter according to the simulated annealing algorithm and the initial iteration parameter to obtain an updated temperature parameter;

s304, carrying out iterative operation on the light pre-amplification parameter vector and the updated temperature parameter to obtain an updated light pre-amplification parameter vector;

s305, obtaining an updated loss function value according to the updated light pre-amplification parameter vector and a preset Gaussian noise closed solution model after stimulated Raman scattering correction;

and S306, obtaining an optimized light pre-amplification parameter vector according to the loss function value and the updated loss function value.

Specifically, a random probability value p0 is obtained, wherein p0 is a random probability value randomly generated according to uniform distribution between 0 and 1, and an initial temperature parameter Tmax and an initial iteration parameter iter _ num are obtained, wherein the initial temperature parameter is used for representing a variable parameter 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; correspondingly, the step of updating the initial temperature parameter according to the simulated annealing algorithm and the initial iteration parameter to obtain an updated temperature parameter comprises the following steps: when the iterative operation times of the optical pre-amplification parameter vector and the updated temperature parameter reach a preset iterative time threshold value, performing self-accumulation operation on the initial iterative parameter to obtain an iterative parameter; and dividing the initial temperature parameter by the iteration parameter to obtain an updated temperature parameter. For example, the temperature parameter may decrease as the above iterative process increases, for example, the temperature decreases once per 100 runs, and the temperature decrease formula is as follows:

T＝Tmax/iter_num

t, the updated temperature parameter is Tmax representing the initial temperature parameter, the value is 300, iter _ num represents the iteration hundred rounds (the initial value is 1), 1 is added to the iter _ num value in each iteration of 100 rounds, the simulated annealing algorithm stops under two conditions, one is to stop optimizing when the temperature parameter is reduced to the initially set minimum temperature parameter (such as 100), the second is to reduce the loss for 20 times, and the updated light pre-amplification parameter vector x is updated_newIf the degradation does not occur, the optimization is stopped. Then, carrying out iterative operation on the light pre-amplification parameter vector and the updated temperature parameter to obtain an updated light pre-amplification parameter vector; for example, after obtaining the loss value loss of the current optical pre-amplification parameter vector x, simulation is performedThe annealing algorithm updates and generates an updated optical pre-amplification parameter vector x _ new on the basis of the optical pre-amplification parameter vector x, and the generation method is shown as the following formula:

wherein, upper represents the maximum value of the light pre-amplification parameter vector x, lower represents the minimum value of the light pre-amplification parameter vector x, and r is [ -1,1 [ ]]T represents a temperature parameter. Pre-amplifying the parameter vector x according to the updated light_newAnd a preset Gaussian noise closed solution model after stimulated Raman scattering correction to obtain an updated loss function value loss_new(ii) a The specific process is to pre-amplify the updated light parameter vector x_newWhen the previous optical pre-amplification parameter vector is used, the step S200 is continuously executed to obtain the updated loss function value loss_new. Then, obtaining an optimized light pre-amplification parameter vector according to the loss function value and the updated loss function value, wherein correspondingly, obtaining the optimized light pre-amplification parameter vector according to the loss function value and the updated loss function value comprises the following steps: when the updated loss function value is smaller than or equal to the loss function value, continuing to execute a Gaussian noise closed solution model corrected according to the updated light pre-amplification parameter vector and preset stimulated Raman scattering to obtain an 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 light pre-amplification parameter vector is larger than or equal to the random probability value, continuing to execute a Gaussian noise closed solution model after correction according to the updated light pre-amplification parameter vector and preset stimulated Raman scattering to obtain an updated loss function value; when the updated temperature parameter reaches a preset temperature parameter threshold value, or when the initial temperature parameter is subjected to the simulated annealing algorithm and the initial iteration parameterStopping the simulated annealing algorithm when the updated times reach a preset update time threshold and the updated light pre-amplification parameter vector is unchanged, and obtaining 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. For example, if loss _ new<If x _ new is taken as new x, continuing to use the above updating formula to iteratively find x _ new with lower loss _ new; if loss _ new>loss, then accept the x _ new with a certain probability, the probability value of the light pre-amplification parameter vector is generated as follows:

in the above equation, 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, p is closer to 0, the random probability value p0 is a random probability randomly generated according to uniform distribution between 0 and 1, and if p > is p0, the updated light pre-amplification parameter vector x _ new is received as a new light pre-amplification parameter vector x, and the next iteration is performed. Otherwise, it is not accepted. Therefore, the higher the temperature parameter is, the higher the probability of receiving the updated optical pre-amplification parameter vector x _ new having a relatively low quality is, so that the temperature is lowered by the simulated annealing algorithm, and the high-quality updated optical pre-amplification parameter vector is obtained with a higher probability. Through the iterative operation of the simulated annealing algorithm, when the iteration is finished, an optimized loss function value is finally obtained, the optimized loss function value is the minimum, and then the updated optical pre-amplification parameter vector corresponding to the optimized loss function value is the optimum and can be used as the optimized optical pre-amplification parameter vector, so that the limit capacity of the whole channel is maximized, and the capacity balance among the channels is kept.

Referring to fig. 4, illustrating an embodiment of the pre-amplification parameter optimization method applied to the ultra-wideband wavelength division multiplexing system of the present invention, referring to fig. 5, the result of the preliminary simulation is shown, wherein the abscissa represents the ultra-wideband channel and the ordinate represents the capacity of the channel. Here we have chosen three different optimization strategies, and the circles represent the optimization results for the maximization of the overall capacity, so it can be seen that there is a disadvantage in choosing such an optimization strategy, which results in the imbalance of the capacity among channels. The asterisk indicates that the best equalization of inter-channel capacity within the band is sought, but it can be seen that the overall capacity is not high. The plus sign has the advantages of the first two strategies, namely relatively high overall capacity and relatively stable capacity distribution.

Exemplary device

As shown in fig. 6, an embodiment of the present invention provides a pre-amplification parameter optimization apparatus applied to an ultra-wideband wavelength division multiplexing system, including: an optical pre-amplification parameter vector module 401, a loss function value obtaining module 402, and an optimized optical pre-amplification parameter vector determining module 403, where:

an optical pre-amplification parameter vector module 401, configured to obtain an optical pre-amplification parameter vector after random initialization, where the optical pre-amplification parameter vector is used to represent a gain slope vector and a gain offset vector of a plurality of band optical amplifiers in an ultra-wideband wavelength division multiplexing system;

a loss function value obtaining module 402, configured to obtain a loss function value according to the optical pre-amplification parameter vector and a preset gaussian noise closed solution model after stimulated raman scattering correction;

and an optimized optical pre-amplification parameter vector determining module 403, configured to determine an optimized optical pre-amplification parameter vector according to the optical pre-amplification parameter vector, the loss function value, and a simulated annealing algorithm.

Based on the above embodiment, the present invention further provides an intelligent terminal, and a schematic block diagram thereof may be as shown in fig. 7. The intelligent terminal comprises a processor, a memory, a network interface, a display screen and a temperature sensor which are connected through a system bus. Wherein, the processor of the intelligent terminal is used for providing calculation and control capability. The memory of the intelligent terminal comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the intelligent terminal is used for being connected and communicated with an external terminal through a network. The computer program is executed by a processor to implement a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system. The display screen of the intelligent terminal can be a liquid crystal display screen or an electronic ink display screen, and the temperature sensor of the intelligent terminal is arranged inside the intelligent terminal in advance and used for detecting the operating temperature of internal equipment.

It will be understood by those skilled in the art that the schematic diagram of fig. 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 to the intelligent terminal to which the solution of the present invention is applied, and a specific intelligent terminal may include more or less components than those shown in the figure, or combine some components, or have different arrangements of components.

In one embodiment, an intelligent terminal is provided that includes a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: obtaining an optical pre-amplification parameter vector after random initialization, wherein the optical pre-amplification parameter vector is used for representing a gain slope vector and a gain offset vector of a plurality of 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 preset Gaussian noise closed solution model after stimulated Raman scattering correction;

and determining the optimized light pre-amplification parameter vector according to the light pre-amplification parameter vector, the loss function value and a simulated annealing algorithm.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile 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 a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

In summary, the present invention discloses a pre-amplification parameter optimization method, an intelligent terminal, and a storage medium for use in an ultra-wideband wavelength division multiplexing system, wherein the method comprises: obtaining an optical pre-amplification parameter vector after random initialization, wherein the optical pre-amplification parameter vector is used for representing a gain slope vector and a gain offset vector of a plurality of 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 preset Gaussian noise closed solution model after stimulated Raman scattering correction; and determining the optimized light pre-amplification parameter vector according to the light pre-amplification parameter vector, the loss function value and a simulated annealing algorithm. The invention optimizes the pre-amplification power spectrum of each channel by the method, so that the signal-to-noise ratio of the channel in the whole bandwidth is maximum during transmission, and the maximum communication transmission capacity is further obtained.

Based on the above 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 examples, and it will be obvious to those skilled in the art that modifications and changes can be made according to the above description, and all such modifications and changes are intended to fall within the scope of the appended claims.