CN113536725B - Pre-amplification parameter optimization method applied to ultra-wideband wavelength division multiplexing system - Google Patents
Pre-amplification parameter optimization method applied to ultra-wideband wavelength division multiplexing system Download PDFInfo
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Abstract
The invention discloses a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system, which comprises the following steps: 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; and 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. 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 obtained.
Description
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 has not only induced the generation of the fifth generation of communication internet, but also caused various mobile communication applications to appear in nearly five years as the 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 improving communication capacity.
However, as the communication bandwidth is widened, the frequency spectrum is correspondingly widened, and since each band contains many channels, the number of channels is very large (hundreds of channels) due to the multiple bands, and after the optical power of different bands is pre-amplified, the total optical power in the optical fiber can be very large, which can reach 20 dBm generally. Such large optical power combined with ultra wide bandwidth causes stimulated raman scattering effects in addition to nonlinear effects such as self-phase modulation, four-wave mixing, cross-phase modulation, etc., and produces gains for low frequency channels that produce nonlinear effects that result in higher nonlinear noise power, resulting in a reduced signal-to-noise ratio of the signal, and thus a reduced communication capacity limit for the channel.
Accordingly, there is a need for improvement and development in the art.
Disclosure of Invention
The invention aims to solve the technical problems that aiming at the defects in the prior art, a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system is provided, and aims to solve the problems that in the prior art, the optical signal is prevented from stimulated Raman scattering effects beyond nonlinear effects such as self-phase modulation, four-wave mixing, cross-phase modulation and the like caused by large amplitude, gains are generated on a low-frequency channel, the gains generate nonlinear effects, thus higher nonlinear noise power is caused, the signal-to-noise ratio of the signal is reduced, and the communication capacity limit of the channel is reduced.
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 method for optimizing a pre-amplification parameter applied to an ultra wideband wavelength division multiplexing system, where the method includes:
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;
and 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.
In one implementation, the acquiring the randomly initialized optical pre-amplification parameter vector includes:
generating a plurality of random values;
and forming a vector by using a plurality of random values as a light pre-amplification parameter vector.
In one implementation manner, the obtaining 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 includes:
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;
and obtaining a loss function value according to the signal-to-noise ratio vector.
In one implementation manner, the obtaining the channel fiber-in 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 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.
In one implementation, the obtaining the loss function value according to the signal-to-noise ratio vector includes:
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;
and adding the capacity maximum value to the capacity average value and subtracting the capacity minimum value to obtain a loss function value.
In one implementation, 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:
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.
In one implementation manner, the updating the initial temperature parameter according to the simulated annealing algorithm and the initial iteration parameter, to obtain an updated temperature parameter includes:
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.
In one implementation, 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 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.
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 gain slope vectors and gain offset vectors of a plurality of wave band optical amplifiers in the ultra-wideband wavelength division multiplexing system;
the loss function value acquisition module is used for acquiring 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 optical pre-amplification parameter vector determining module is used for 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.
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 the one or more processors, where the one or more programs include a method for performing the pre-amplification parameter optimization method according to any one of the above, where the method is applied to an ultra wideband wavelength division multiplexing system.
In a fourth aspect, an embodiment of the present invention further provides a non-transitory computer readable storage medium, where instructions in 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 set forth in any one of the above.
The invention has the beneficial effects that: firstly, 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; preparing for subsequent optimization, and then correcting the Gaussian noise closed solution model according to the optical pre-amplification parameter vector and preset stimulated Raman scattering to obtain a loss function value, so as to prepare for subsequent further optimization; and finally, determining an 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 is maximum during transmission, and the maximum communication transmission capacity is further obtained. Compared with the traditional power control optimization algorithm, the method has the advantages that violent scanning is not needed, the time complexity is low, the stimulated Raman scattering caused by ultra-wideband is considered by the Gaussian noise closed solution model after 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 that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings may be obtained according to the drawings without inventive effort to those skilled in the art.
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 power spectrum slope and center polarization after amplification by three band amplifiers according to an 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 optimizing flow based on a simulated annealing algorithm according to an embodiment of the present invention.
Fig. 5 is a diagram of the limit capacity spectrum of all channels provided in the embodiment of the present invention.
Fig. 6 is a schematic block diagram of a pre-amplification parameter optimization device 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, which is used for making the purposes, technical schemes and effects of the invention clearer and more definite, and is further described in detail below by referring to the accompanying drawings and the embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless expressly stated otherwise, as understood by those skilled in the art. 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. The term "and/or" as used herein includes all or any element and all combination of one or more of the associated listed items.
It will be understood by those skilled in the art that 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 unless defined otherwise. 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.
Since in the prior art, the increase of optical communication capacity can be started from the dimension of utilizing light, these dimensions are: polarization, time, wavelength, mode. Where wavelength is a physical property of light, it is well suited for use in multiplexing of light due to its broad range. Currently, ultra wideband wavelength division multiplexing is receiving a great deal of attention due to the capacity increase caused by its ultra-high bandwidth.
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. The C-band is currently being commercially used, the L-band is expected to be applied after the corresponding band amplifier is mature, and the S-band is currently not commercially used because its corresponding amplifier has not yet been added to the wavelength division multiplexing band. However, the range of the S wave band is almost twice that of the C wave band, so that after the future instrument development matures, a wavelength division multiplexing system is likely to be introduced to form a wavelength division multiplexing coherent communication system with ultra-high bandwidth, so that the communication capacity is greatly improved.
However, as the communication bandwidth is widened, the spectrum is correspondingly widened. Thus when the number of channels is very large (hundreds of channels), the overall optical power within the fiber can be very large, typically up to 20 dBm. Such large optical powers, combined with ultra-wide bandwidths, can cause stimulated raman scattering effects in addition to nonlinear effects such as self-phase modulation, four-wave mixing, cross-phase modulation, etc., and produce gain for low frequency channels. The frequency shift of the gain is around 13 THz. This results in a decrease in the high frequency signal power and a further increase in the low frequency signal power, thereby producing a higher nonlinear effect in the low frequency region. These nonlinear effects can lead to higher nonlinear noise power, reducing the signal-to-noise ratio of the signal, and thus reducing the communication capacity limit of the channel.
In order to solve the problem of the reduction of the communication capacity limit 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 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 maximum, and the maximum communication transmission capacity is obtained.
In order to solve the problems in the prior art, the present embodiment provides a method for optimizing a pre-amplification parameter applied to an ultra wideband wavelength division multiplexing system, and optimizes a pre-amplification power spectrum of each channel by the method, so that a signal-to-noise ratio of the channel in an overall bandwidth during transmission is maximum, and the maximum communication transmission capacity is obtained. In specific implementation, 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; then, according to the light pre-amplification parameter vector and a preset stimulated Raman scattering corrected Gaussian noise closed solution model, obtaining a loss function value; and finally, 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.
Exemplary method
The embodiment provides a pre-amplification parameter optimization method applied to an ultra-wideband wavelength division multiplexing system, which can be applied to an intelligent terminal for digital signal processing. As shown in fig. 1, the method includes:
step S100, 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;
specifically, the randomly initialized optical pre-amplification parameter vector may be generated at 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, which is not specifically limited. 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 the ultra-wideband wavelength division multiplexing system, as shown in fig. 2.
In order to obtain the optical pre-amplification parameter vector, the method for obtaining the optical pre-amplification parameter vector after random initialization comprises the following steps:
s101, generating a plurality of random values;
s102, forming a plurality of random value composition vectors as light pre-amplification parameter vectors.
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: the gain slope vector slope and the gain offset vector offset, so that there are six parameters in total. Firstly, 6 numbers are randomly generated, the 6 numbers are combined into a vector, and the vector is used as a light pre-amplification parameter vector.
After obtaining the optical pre-amplification parameter vector, the following steps may be performed as shown in fig. 1: s200, 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;
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 mixed operation to obtain a loss function value, which is not particularly limited.
In order to obtain a loss function value, the step of obtaining 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, obtaining a channel bandwidth, a 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, carrying out power calculation on the channel power vector based on the Gaussian noise closed solution model after 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;
s207, obtaining a loss function value according to the signal-to-noise ratio vector.
Specifically, channel bandwidth B (which may be set to 28 GHz), channel power vectors Pi, P are acquired first i,j And amplifying the spontaneous emission noise power P ASE The method comprises the steps of carrying out a first treatment on the surface of the In the present embodiment, the spontaneous emission noise power P is amplified ASE Is obtained by the following formula:
P ASE ＝B*hv*Nf*(G-1)
where B represents the channel width, h is the Planckian constant (6.62607004 ×10-34m2 kg/s), v represents the channel optical frequency, NF represents the noise figure of the optical amplifier, and G is the gain coefficient of the amplifier in the channel. According to the light pretreatmentAmplifying the parameter vector x to obtain a channel fiber-entering power vector P ch The method comprises the steps of carrying out a first treatment on the surface of the Correspondingly, the 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 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. For example: x is a vector in which there are six elements x1-x6, x1 representing the gain slope of the L-band, x2 representing the gain offset of the L-band, x3 representing the gain slope of the C-band, x4 representing the gain offset of the C-band, x5 representing the gain slope of the S-band, and x6 representing the gain offset of the S-band. When x is input into the gaussian noise model, actually, 6 elements of x are respectively input into amplifiers of three wavebands, so that channel powers (i.e. fiber-in optical power distribution of each channel) amplified by the three wavebands are 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
where f represents the center frequency of each channel (is a vector), f L ，f C And f S Representing the overall center frequencies of the L, C and S bands, respectively. After the optical power distribution of the incoming fiber with the whole bandwidth is obtained, the nonlinear power of each channel can be further calculated. Channel fibre-entry power vector P ch From power L 、power C And Power S Composition is prepared. After obtaining the channel fiber-entering power vector, correcting the Gaussian noise closed solution model based on the stimulated Raman scattering, and performing calculation on the channel power vectors Pi and P i,j Performing power calculation to obtain a nonlinear noise power vector P NLI The method comprises the steps of carrying out a first treatment on the surface of the For example, a nonlinear noise power vector P NLI Is obtained by the following formula:
where Pi represents the power of the ith channel, P i,j Represents the power, eta of the jth channel SPM,j (fi) and eta XPM,j (fi) represents the corrected self-phase modulation nonlinear coefficient and the cross-phase modulation nonlinear coefficient, n ∈ Representing nonlinear noise. The nonlinear noise power vector P is then applied NLI And the amplified spontaneous emission noise power P ASE Summing to obtain a noise total power vector; the channel is entered into a fiber power vector P ch Dividing the 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 SNR; for example, signal-to-noise ratio vector And finally, obtaining a loss function value according to the signal-to-noise ratio vector. Correspondingly, the 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; 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; and adding the capacity maximum value to the capacity average value and 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, 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:
where capability is a vector representing the capacity of all channels.
After obtaining the loss function value, the following steps may be performed as shown in fig. 1: s300, 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.
Specifically, as shown in fig. 2-3, the minimum loss function value is obtained by updating and iterating the optical pre-amplification parameter vector and the loss function value according to a simulated annealing algorithm. 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 comprises the following steps:
s301, acquiring a random probability value;
s302, 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;
s303, updating the initial temperature parameter according to the simulated annealing algorithm and the initial iteration parameter to obtain an updated temperature parameter;
s304, performing iterative operation on the optical pre-amplification parameter vector and the updated temperature parameter to obtain an updated optical 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;
s306, obtaining an optimized optical pre-amplification parameter vector according to the loss function value and the updated loss function value.
Specifically, firstly, a random probability value p0 is obtained, wherein the 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 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. For example, the temperature parameter may decrease with increasing iteration process, for example, the temperature is decreased once every 100 rounds of operation, and the temperature decrease formula is as follows:
T＝Tmax/iter_num
t is updated to be Tmax and represents initial temperature parameter, the value is 300, iter_num represents iteration hundred rounds (initial value is 1), 1 is added to the value of iter_num of each iteration 100 rounds, the condition for stopping the simulated annealing algorithm is two, one is that when the temperature parameter is reduced to the minimum temperature parameter (such as 100) which is originally set, the optimization is stopped, the second is that loss is reduced for 20 times, and the updated optical pre-amplification parameter vector x is obtained new And stopping optimizing when the temperature is not reduced. Performing iterative operation on the optical pre-amplification parameter vector and the updated temperature parameter to obtain an updated optical pre-amplification parameter vector; for example, after the loss value loss of the current optical pre-amplification parameter vector x is obtained, the simulated annealing algorithm updates and generates an updated optical pre-amplification parameter vector x_new based on the optical pre-amplification parameter vector x, and the generation method is as follows:
wherein 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, and r is [ -1, 1)]T represents a temperature parameter. According to the updated optical pre-amplification parameter vector x new And a Gaussian noise closed solution model after the correction of the preset stimulated Raman scattering is adopted to obtain an updated loss function value loss new The method comprises the steps of carrying out a first treatment on the surface of the The specific process is to pre-amplify the updated light to the parameter vector x new When the previous optical pre-amplification parameter vector is used, the step S200 is continuously executed to obtain an updated loss function value loss new . And then obtaining an optimized optical pre-amplification parameter vector according to the loss function value and the updated loss function value, and correspondingly, obtaining the optimized optical 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 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. For example, if loss_new<Taking x_new as new x, continuing to iteratively find x_new lower than loss_new by using the above update formula; if loss_new>And if loss is low, receiving the x_new with a certain probability, wherein the probability value of the optical pre-amplification parameter vector is generated by the following formula:
in the above formula, the distribution range of the probability value p of the optical pre-amplification parameter vector is (0, 1), if the temperature parameter T is smaller, the 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 > =p0, the updated optical pre-amplification parameter vector x_new is accepted as a new optical pre-amplification parameter vector x, and then 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 reduced by the simulated annealing algorithm, and the updated optical pre-amplification parameter vector having a high quality is obtained with a higher probability. Through the iterative operation of the simulated annealing algorithm, when iteration is finished, an optimized loss function value is finally obtained, and the optimized loss function value at the moment is minimum, so that the updated optical pre-amplification parameter vector corresponding to the optimized loss function value is optimal and can be used as the optimized optical pre-amplification parameter vector, the limit capacity of the whole channel is further maximized, and capacity balance among channels is kept.
Referring to fig. 4, an embodiment of the pre-amplification parameter optimization method of the present invention applied to an ultra wideband wavelength division multiplexing system is shown, and as shown in fig. 5, the result of preliminary simulation is shown, where the abscissa represents an ultra wideband channel and the ordinate represents the capacity of the channel. Here we have chosen three different optimization strategies, the circles representing the optimization results pursuing the maximization of the overall capacity, it can be seen that there is a disadvantage in choosing such an optimization strategy that it can lead to an imbalance in the capacity between the channels. Asterisks indicate that the most balanced capacity between channels within the band is pursued, but it can be seen that the overall capacity is not high. The plus sign has the advantages of the first two strategies, and has quite high overall capacity and relatively stable capacity distribution.
Exemplary apparatus
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, the apparatus comprising: a light pre-amplification parameter vector module 401, a loss function value acquisition module 402, and an optimized light pre-amplification parameter vector determination module 403, wherein:
the optical pre-amplification parameter vector module 401 is configured to obtain a randomly initialized optical pre-amplification parameter vector, where the optical pre-amplification parameter vector is used to characterize gain slope vectors and gain offset vectors of a plurality of band optical amplifiers in the ultra wideband wavelength division multiplexing system;
the loss function value obtaining module 402 is 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;
the optimized optical pre-amplification parameter vector determining module 403 is 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 functional block diagram thereof may be 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. The processor of the intelligent terminal is used for providing computing and control capabilities. 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 the operating system and computer programs in the non-volatile storage media. The network interface of the intelligent terminal is used for communicating with an external terminal through network connection. The computer program, when executed by a processor, implements a pre-amplification parameter optimization method for 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 a temperature sensor of the intelligent terminal is arranged in the intelligent terminal in advance and used for detecting the running temperature of internal equipment.
It will be appreciated by those skilled in the art that the schematic diagram of fig. 7 is merely a block diagram of a portion of the structure related to the present invention, and does not constitute a limitation of the smart terminal to which the present invention is applied, and a specific smart terminal may include more or less components than those shown in the drawings, or may combine some components, or have different arrangements of components.
In one embodiment, a smart 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 one or more processors, the one or more programs comprising instructions for: 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;
and 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.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The 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 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), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
In summary, the invention discloses a pre-amplification parameter optimization method, an intelligent terminal and a storage medium applied to an ultra-wideband wavelength division multiplexing system, wherein the method comprises the following steps: 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; and 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. 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 obtained.
Based on the above embodiments, the present invention discloses a method for optimizing pre-amplification parameters 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 those skilled in the art can make modifications or changes according to the above description, and all such modifications and changes should fall within the scope of the appended claims.
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.
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