CN116805889B - Optical fiber transceiver module based on CPO technology - Google Patents
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Abstract
The invention belongs to the technical field, and particularly relates to an optical fiber transceiver module based on CPO technology. The system comprises: the special integrated circuit is configured to receive data to be transmitted and convert the data to be transmitted into signals to be transmitted in the form of analog electric signals; a co-packaged fiber optic transceiver module comprising: an emission unit, an optical shape molding unit, an optical transmission unit, a photoelectric conversion unit, and a phase recovery unit; the transmitting unit is used for converting a signal to be transmitted in the form of an analog electric signal into an optical signal; the optical shape molding unit is used for optimizing the shape of the optical signal by using an optical shape molding algorithm to obtain an optimized optical signal; the optical signal optimized by the photoelectric conversion unit is converted into an electric signal; and the phase recovery module obtains final signal output. The invention effectively improves the transmission performance and the receiving quality of the optical signal, and greatly enhances the stability, the efficiency and the robustness of the optical communication system.
Description
Technical Field
The invention belongs to the technical field of optical transmission, and particularly relates to an optical fiber transceiver module based on a CPO technology.
Background
In the information age, optical communications have a significant role in rapidly delivering large amounts of information. Optical communication mainly relies on optical fiber network to transmit information, and the speed and efficiency of information transmission are effectively improved by utilizing the excellent transmission characteristic and large-capacity bandwidth. However, since the optical signal is affected by various factors during the transmission process, the transmission performance of the optical signal is affected, such as attenuation and dispersion of the signal, which is also an important technical problem to be solved in the optical communication field.
In the prior art that has been disclosed, a number of effective solutions have been proposed in order to solve the problems of attenuation and dispersion during optical signal transmission. Such as the introduction of a variety of complex signal modulation techniques and signal processing methods, e.g., using multi-level modulation techniques and special signal coding techniques, to encode information onto different parameters of the optical signal, such as amplitude, frequency, phase, etc. In addition, various efficient signal recovery techniques, such as equalizer and phase recovery techniques, are employed to process the received optical signal to recover the original information signal as much as possible.
However, some problems still remain in the prior art. On the one hand, existing signal modulation and coding techniques often require more complex hardware devices and higher computational complexity when processing complex signals and high-speed signals, which makes them limited in practical applications. On the other hand, when the original signal is recovered, the existing signal recovery techniques are often limited by the quality of the received optical signal, and if the quality of the received optical signal is poor, for example, the amplitude of the signal is small, or the phase of the signal has a large deviation, the effect of these signal recovery techniques will be greatly reduced.
In addition, the prior art often only focuses on a single problem, such as how to increase the transmission speed of the signal, or how to reduce the error rate of the signal, and ignores the correlation between these problems. For example, increasing the transmission speed of a signal tends to cause an increase in the bit error rate of the signal, while decreasing the bit error rate of the signal tends to cause a decrease in the transmission speed of the signal. Therefore, how to reduce the error rate of the signal while ensuring the signal transmission speed becomes a problem to be solved urgently.
Disclosure of Invention
The invention mainly aims to provide the optical fiber transceiver module based on the CPO technology, which effectively improves the transmission performance and the receiving quality of optical signals and greatly enhances the stability, the efficiency and the robustness of an optical communication system.
In order to solve the technical problems, the invention provides an optical fiber transceiver module based on CPO technology,
a fiber optic transceiver module based on CPO technology, the module comprising: the special integrated circuit is configured to receive data to be transmitted and convert the data to be transmitted into signals to be transmitted in the form of analog electric signals; a co-packaged fiber optic transceiver module comprising: an emission unit, an optical shape molding unit, an optical transmission unit, a photoelectric conversion unit, and a phase recovery unit; the transmitting unit is used for converting a signal to be transmitted in the form of an analog electric signal into an optical signal; the optical shape molding unit is used for optimizing the shape of the optical signal by using an optical shape molding algorithm to obtain an optimized optical signal; the optical transmission unit is used for transmitting the optimized signal to the photoelectric conversion unit; the optical signal optimized by the photoelectric conversion unit is converted into an electric signal; the phase recovery unit is used for carrying out phase recovery processing on the electric signal by using a phase recovery algorithm based on a Bayesian method, so as to obtain final signal output.
Further, the application specific integrated circuit comprises a plurality of symbol encoding circuits for converting the data to be transmitted into symbol data in the form of digital signals; the asic further includes digital signal processing circuitry to optimize the symbol data; the asic further includes a plurality of digital-to-analog converters to convert symbol data in the form of digital signals to be transmitted in the form of analog electrical signals.
Further, the emitting unit is a laser diode; when the laser diode converts a signal to be transmitted in the form of an analog electric signal into an optical signal, the optical signal is subjected to 16-bit multi-level modulation; the optical transmission unit is an optical fiber.
Further, the light shape shaping algorithm is an arc shape shaping algorithm based on tail attenuation; the arc shape modeling algorithm based on tail attenuation optimizes the shape of the optical signal, and the time domain representation of the arc waveform of the optimized optical signal is represented by using the following formula:wherein (1)>Is the amplitude of soliton, +.>Is the position of the soliton centre, +.>Is a hyperbolic cosine function, ">Is a time domain representation of an arc sub-waveform, +.>Is the attenuation of the soliton tail.
Further, the arc sub-speed of the optimized optical signal is expressed using the following formula:wherein (1)>Is first-order dispersion, & lt & gt>Is second order dispersion>Is third order dispersion +.>Is fourth order dispersion +.>Is at->Arc speed at time.
Further, the dispersion parameter of the optical fiber is subjected to fourth-order expansion in the frequency domain,、/>、/>and->The following constraint relationship is satisfied: />The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Is the refractive index of the optical fiber, < >>Is the dispersion parameter of the fiber,/>For the frequency of the optical fiber->Is the center frequency of the fiber.
Further, when the optical signal after optimization of the photoelectric conversion unit is converted into an electrical signal, the obtained electrical signal is expressed by using the following formula:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Amplitude->Is phase, & lt + & gt>Is a frequency domain representation of the optimized optical signal, < >>Is an imaginary unit; wherein (1)>。
Further, the phase recovery module performs phase recovery processing on the electric signal by using a phase recovery algorithm based on a bayesian method, so as to obtain a final signal output, and the method comprises the following steps: performing initial phase estimation on each signal point in the electric signal; calculating a phase error based on the initial phase estimate; based on the phase error, the phase correction is performed using a bayesian method, the posterior probability distribution of the phase is calculated, the phase maximizing the posterior probability is found based on the posterior probability distribution, and the received electric signal is corrected using the predicted phase as the predicted phase, thereby completing the phase recovery.
Further, the initial phase estimate obtained after performing the initial phase estimation on each signal point in the electrical signal is represented by using the following formula:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>For one signal point in the electrical signal, +.>A phase of a signal point in the electrical signal; />Representing the angle, i.e. the phase, of the complex number; />Is an imaginary unit; />Estimating for an initial phase; the phase error is calculated using the following formula: />；/>Is true phase, +.>Is an initial phase estimate.
Further, the method for correcting the phase by using a bayesian method based on the phase error, calculating a posterior probability distribution of the phase, finding a phase maximizing the posterior probability based on the posterior probability distribution, and correcting the received electric signal by using the predicted phase as a predicted phase, thereby completing the phase recovery includes:
the posterior probability distribution of the true phase is calculated using the following formula:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Is the true phase; />Posterior probability distribution for true phase, +.>Is the variance of the phase noise;
the phase that maximizes the posterior probability is found as the predicted phase using the following formula:the method comprises the steps of carrying out a first treatment on the surface of the Finally, use of predicted phase +.>To correct the received electrical signal to complete the phase recovery.
The optical fiber transceiver module based on the CPO technology has the following beneficial effects:
first, the design of the optical shape modeling algorithm fully considers the dispersion and attenuation problems that may occur in the optical signal during transmission. By shaping the shape of the arc, the optical signal can be effectively controlled and managed in the transmission process, so that the transmission performance of the optical signal in a complex environment is obviously improved. The implementation of the algorithm not only reduces the dependence on complex hardware equipment and reduces the implementation difficulty, but also improves the transmission stability and efficiency of the optical signals.
Secondly, a phase recovery algorithm based on a Bayesian method is adopted, so that the signal can be more accurately recovered in an electric signal receiving link. Based on the Bayesian principle, the algorithm can better estimate and correct the phase error, thereby obtaining higher-quality signal recovery. Compared with the traditional phase recovery technology, the method has lower requirements on the quality of the received optical signal, and can recover the original signal with high quality under the condition of poor optical signal quality, thereby greatly improving the robustness of the system.
In addition, the invention improves the optical signal transmission performance and simultaneously fully considers the implementation cost and complexity of the system. The implementation process of the whole algorithm does not introduce complex hardware equipment or use complex calculation process, and the implementation difficulty and cost of the whole system are effectively controlled. Therefore, the method can ensure the transmission performance of the optical signal and meet the requirements of cost and complexity in practical application.
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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 embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of a co-packaged optical fiber transceiver module based on a CPO technology according to an embodiment of the present invention.
Detailed Description
The method of the present invention will be described in further detail with reference to the accompanying drawings.
Example 1: a fiber optic transceiver module based on CPO technology, the system comprising: the special integrated circuit is configured to receive data to be transmitted and convert the data to be transmitted into signals to be transmitted in the form of analog electric signals; a co-packaged fiber optic transceiver module comprising: an emission unit, an optical shape molding unit, an optical transmission unit, a photoelectric conversion unit, and a phase recovery unit; the transmitting unit is used for converting a signal to be transmitted in the form of an analog electric signal into an optical signal; the optical shape molding unit is used for optimizing the shape of the optical signal by using an optical shape molding algorithm to obtain an optimized optical signal; the optical transmission unit is used for transmitting the optimized signal to the photoelectric conversion unit; the optical signal optimized by the photoelectric conversion unit is converted into an electric signal; the phase recovery module is used for carrying out phase recovery processing on the electric signal by using a phase recovery algorithm based on a Bayesian method, so as to obtain final signal output.
Specifically, the shaping of the light refers to changing the amplitude, phase or polarization of the light wave by using a certain device or technology, so that the light wave has a desired distribution characteristic in space, time or frequency. The technology is widely applied to the fields of optical communication, laser processing, optical imaging and the like.
In optical communications, light shaping is typically achieved by optical systems (e.g., lenses, mirrors, gratings, etc.) or devices using spatial light modulators (SpatialLightModulator, SLM). The optical shaping can optimize the optical signal, such as reducing beam divergence, reducing mode dispersion, improving spot quality, etc., thereby improving transmission quality and efficiency of optical communications.
Phase recovery refers to estimating and recovering signal phase information that may be lost due to various reasons (such as noise, interference, channel imperfections, etc.) in the transmission process by some algorithm at the receiving end. In optical communication, during the transmission of signals in optical fibers, due to the nonlinear and dispersive effects of the optical fibers, the phase shift of the signals is caused, so that the signal phase of a receiving end is inconsistent with the signal phase of a transmitting end. If the phase recovery is not performed, the receiving end cannot correctly demodulate the signal, so that the error rate is increased. There are many methods of phase recovery, such as maximum likelihood estimation, viterbi decoding, kalman filtering, etc. The phase recovery algorithm based on the Bayesian method is an effective phase recovery method, and can accurately recover the phase information of the signal by fully utilizing the statistical characteristics of the signal.
In an optical communication system, a transmitting end optimizes an optical signal through an optical shape molding technology, and then transmits the optimized optical signal to a receiving end through an optical fiber. At the receiving end, due to nonlinear and dispersive effects of the optical fiber, phase drift of the signal may be caused during transmission. Therefore, the receiving end needs to recover the phase information of the signal by the phase recovery technique, thereby ensuring correct demodulation of the signal.
In this process, optical shape shaping and phase recovery are coordinated to improve the transmission quality and efficiency of optical communications. The optical shape molding technology can improve the transmission characteristic of the optical signal, thereby reducing the loss and distortion of the signal in the transmission process; the phase recovery technology can recover the phase information lost in the transmission process of the signal, thereby reducing the error rate and improving the accuracy of data transmission.
Example 2: on the basis of the above embodiment, the asic includes a plurality of symbol encoding circuits to convert the data to be transmitted into symbol data in the form of digital signals; the asic further includes digital signal processing circuitry to optimize the symbol data; the asic further includes a plurality of digital-to-analog converters to convert symbol data in the form of digital signals to be transmitted in the form of analog electrical signals.
Specific: symbol encoding: in this step, the data is converted into symbol data. Symbol encoding is a common technique in communications that functions to convert raw data (e.g., binary data) to be transmitted into a format more suitable for transmission in a particular communication channel. The symbol encoding circuitry may use digital modulation schemes such as QAM (four-quadrant amplitude modulation), PSK (phase shift keying), or others to convert the data to be transmitted into symbol data. These modulation schemes may have different optimization effects for different data streams and communication channels. Digital signal processing: in this step, the symbol data is further optimized to be ready to become an analog electrical signal. The digital signal processing circuit may perform some optimization processing on the signal, such as filtering, equalization, gain control, etc., to reduce noise, eliminate interference, and optimize the quality of the signal. This helps to more efficiently convert the digital signal to an analog electrical signal in a subsequent step and ultimately improves the quality of the optical signal. Digital-to-analog conversion: in this step, the optimized symbol data is converted into an analog electrical signal. Digital-to-analog converters (DACs) are key components in application specific integrated circuits that convert digital signals to analog signals. In optical communications, digital-to-analog converters function to convert digital signals into analog electrical signals that can be converted to optical signals by a laser.
Example 3: on the basis of the above embodiment, the emission unit is a laser diode; when the laser diode converts a signal to be transmitted in the form of an analog electric signal into an optical signal, the optical signal is subjected to 16-bit multi-level modulation; the optical transmission unit is an optical fiber.
Specifically, the emission unit (laser diode): a Laser Diode (LD) is a key element in a fiber-optic transceiver module, and is used for converting a signal to be transmitted in the form of an analog electrical signal into an optical signal. The laser diode has the advantages of small volume, low power consumption, long service life, high efficiency and the like, and is suitable for being used as a light source for optical fiber communication. In this system, the laser diode employs a 16-bit multi-level modulation technique. The multi-level modulation is an advanced modulation technique, which can modulate signals in amplitude and phase simultaneously, so as to transmit more information bits in each symbol, thereby greatly improving the data transmission rate of optical fiber communication. For example, a multi-level modulation of 16 bits means that each symbol can represent the 16 th power state of 2, which is equivalent to each symbol carrying 16 bits of information, which is far higher than conventional binary modulation (each symbol can only carry 1 bit of information).
Optical transmission unit (optical fiber): the optical fiber is another key element of the optical fiber transceiver module, and is used for transmitting the optimized optical signal to the photoelectric conversion unit. The optical fiber has the advantages of large transmission bandwidth, long transmission distance, strong electromagnetic interference resistance and the like, and is an ideal transmission medium for optical fiber communication. In an optical fiber, a signal is transmitted in the form of light, which not only can avoid electromagnetic interference, but also optical fiber communication has a very high data transmission rate because the transmission speed of light is very fast. In addition, the bandwidth of the optical fiber is very wide, and a large amount of data can be transmitted simultaneously, so that the high bandwidth requirement of modern communication is met.
In particular, soliton shaping is the process of optimizing a signal prior to its emission. Through the optimization, the shape of the signal can be kept in the transmission process, and distortion and attenuation are reduced, so that the quality of the signal is improved. This is important for later phase recovery because if the quality of the signal is too poor, the original signal may not be recovered even if the best phase recovery algorithm is used. In the soliton shape shaping process, the phase of the soliton needs to be calculated, and the phase information is reserved in the signal transmission process. In the phase recovery process, this phase information is used to recover the signal.
Example 4: based on the previous embodiment, the light shape shaping algorithm is an arc shape shaping algorithm based on tail attenuation; the arc shape modeling algorithm based on tail attenuation optimizes the shape of the optical signal, and the time domain representation of the arc waveform of the optimized optical signal is represented by using the following formula:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Is the amplitude of soliton, +.>Is the position of the soliton centre, +.>Is a hyperbolic cosine function, ">Is a time domain representation of an arc sub-waveform, +.>Is the attenuation of the soliton tail.
In particular, the method comprises the steps of,is a representation of the arc sub-waveform in the time domain. An arc is a special pulse shape that is designed to propagate in an optical fiber at a constant velocity without distortion. This is because an optical signal of an arc shape adjusts its shape by itself during propagation to maintain stability of its shape and speed, and thus an arc is widely used in long-distance high-speed optical communication. />The amplitude of the arc determines the signal strength. />Is the position of the arc sub-center, which is the time reference point of the signal. />Is the tail attenuation coefficient, which is a parameter that controls the attenuation rate of an arc sub-waveform as it moves away from its center position.Will influence the optimizing effect of the optical signal. />Is a hyperbolic cosine function, which is a kind of a binary phaseEven functions in the real number domain. The main function of the arc shape shaping algorithm is to optimize the transmission performance of the optical signal. Because the arc can propagate in the optical fiber without distortion under specific conditions, the optical signal with the optimized shape has better stability and anti-interference capability in the transmission process.
Example 5: on the basis of the above embodiment, the arc sub-speed of the optimized optical signal is expressed using the following formula:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Is first-order dispersion, & lt & gt>Is second order dispersion>Is third order dispersion +.>Is fourth order dispersion +.>Is at->Arc speed at time.
In particular, the formula describes how the propagation velocity of an optical pulse (arc) in an optical fiber follows its shape (amplitudeAnd waveform->) And the dispersion parameters of the fiber (>) And (3) a change. The principle is based on a nonlinear Schrodinger equation in optical fiber communication, wherein the equation comprises dispersion and nonlinear effect to lightImpact of pulse propagation. For fiber optic communication systems, it is important to understand and control the propagation speed of the optical pulses in the optical fiber. Because light of different frequencies propagates at different speeds due to the dispersion characteristics of the optical fiber, the light pulses are spread and distorted in the optical fiber, which affects whether the receiving end can accurately receive information. By the formula, the propagation speed of the optical pulse is not only dependent on the dispersion parameter of the optical fiber, but also dependent on the shape of the optical pulse, so that the propagation speed of the optical pulse in the optical fiber can be controlled by adjusting the shape of the optical pulse, signal distortion caused by dispersion is reduced, and the efficiency of optical fiber communication is improved.
Example 6: on the basis of the above embodiment, the dispersion parameters of the optical fiber are subjected to fourth-order expansion in the frequency domain,、、/>and->The following constraint relationship is satisfied:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Is the refractive index of the optical fiber, < >>Is the dispersion parameter of the fiber,/>For the frequency of the optical fiber->Is the center frequency of the fiber.
In particular, the dispersion parameter formula describes the dispersion characteristics of the fiberSex, i.e. how the propagation speed of light of different frequencies in the fiber varies. The formula is obtained by carrying out Taylor series expansion on the dispersion parameter of the optical fiber in the frequency domain, and comprises the derivative of each order of the dispersion parameter along with the change of frequency）。
In fiber optic communication systems, the frequency of the optical pulses is variable, as multiple frequencies of light are typically used to transmit information. Due to the dispersive properties of the optical fiber, the propagation speeds of these different frequencies of light in the optical fiber are different, which may lead to spreading and distortion of the light pulses in the optical fiber. The dispersion parameter formula can help understand and predict the extent of such expansion and distortion so that the effect of dispersion on fiber optic communications can be reduced by designing the appropriate optical pulse shape and selecting the appropriate transmission frequency.
Example 7: on the basis of the above embodiment, when the optical signal after optimization of the photoelectric conversion unit is converted into an electrical signal, the obtained electrical signal is expressed by using the following formula:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Amplitude->Is the phase of the light and the phase of the light,is a frequency domain representation of the optimized optical signal, < >>Is an imaginary unit; wherein (1)>。
Specifically, in fiber optic communications, the transmitted information is encoded by manipulating the intensity (amplitude) and color (frequency) of the light. The task of the photoelectric conversion unit at the receiving end is to convert these optical signals back into electrical signals so that they can be processed and decoded by electronic equipment.
In the course of this formula (ii) the formula,representing the resulting electrical signal. />Representing a representation of the optimized optical signal in the frequency domain. This formula tells that the electrical signal +.>Consists of three parts: amplitude->Phase->And a frequency domain representation +.>。
Is based on an analytical solution of the nonlinear schrodinger equation. This formula depicts the shape of a tail attenuated soliton pulse in the frequency domain. Solitons are a special optical pulse in nonlinear optics, which can propagate in an optical fiber without divergence, and the solitons can cross each other without distortion. This makes solitons very suitable for use in fiber optic communications.
In the course of this formula (ii) the formula,is the amplitude of soliton, +.>Is the phase of soliton, +.>Is a hyperbolic cosine function，/>Is the attenuation parameter. Wherein (1)>Part describes the attenuation of soliton pulses in the frequency domain, which is based on +.>Is indicative of the rapid decay in the intensity of the soliton pulse at the high frequency.
The effect of this formula is that the amplitude of the soliton can be controlledAnd phase->And selecting the appropriate attenuation parameters +.>The shape of the optical signal is optimized, so that the optimal electric signal can be obtained during photoelectric conversion, and the efficiency and accuracy of optical fiber communication are improved.
Example 8: based on the above embodiment, the method for performing phase recovery processing on the electrical signal by the phase recovery module using a phase recovery algorithm based on a bayesian method, thereby obtaining a final signal output includes: performing initial phase estimation on each signal point in the electric signal; calculating a phase error based on the initial phase estimate; based on the phase error, the phase correction is performed using a bayesian method, the posterior probability distribution of the phase is calculated, the phase maximizing the posterior probability is found based on the posterior probability distribution, and the received electric signal is corrected using the predicted phase as the predicted phase, thereby completing the phase recovery.
Specifically, the phase recovery based on the bayesian method is an important algorithm widely applied to a communication system, and aims to recover phase offset caused by various non-ideal factors (such as noise, interference, equipment nonlinearity and the like) in the transmission process at a receiving end, so that an original information signal can be accurately decoded.
First, this algorithm performs an initial phase estimation for each received signal point. This initial phase estimation may be performed using various methods, such as using a maximum likelihood method, or using some pre-set phase estimation algorithm.
Then, based on this initial phase estimate, the algorithm calculates the phase error. This phase error represents the deviation of the initial phase estimate from the true phase.
This algorithm then uses a bayesian approach for phase correction. The bayesian method is a statistical method whose basic idea is to update the probability distribution for a certain parameter with a priori information and new observed data. Here, a bayesian method is used to update the estimate of the phase.
Specifically, the algorithm first calculates a posterior probability distribution of the phase. This posterior probability distribution represents the degree of confidence in each possible phase value after accounting for phase errors. The algorithm then finds the phase value that maximizes this posterior probability distribution as the predicted phase. This predicted phase is the best estimate after taking into account the new observed data (i.e. phase error).
Finally, the algorithm uses this predicted phase to modify the received electrical signal to complete the phase recovery. This correction process typically involves a complex multiplication in which the corrected phase is expressed as a complex angle.
In general, a bayesian-based phase recovery algorithm functions to recover the phase shifted during transmission, thereby improving the performance of the communication system. The advantage of this recovery method is that it can effectively cope with various complex non-ideal factors such as noise and interference, and its performance improves as the amount of received data increases, as more data provides more information to perform phase estimation.
Example 9: on the basis of the above embodiment, the initial phase estimation obtained by performing the initial phase estimation on each signal point in the electric signal is as followsThe following formula is expressed:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>For one signal point in the electrical signal, +.>A phase of a signal point in the electrical signal; />Representing the angle, i.e. the phase, of the complex number; />Is an imaginary unit; />Estimating for an initial phase; the phase error is calculated using the following formula: />；/>Is the true phase of the phase-change signal,is an initial phase estimate.
Specifically, the initial phase estimation in the formula uses the angle or phase of the complex number. The basic principle of this formula is to use the rotation properties of complex numbers: complex number multiplied byCorresponding to rotating the plural numbers->Radian. This formula is first for each signal point +.>Make a corresponding rotation, then make all the rotationsThe complex numbers are summed. The result of this summation is a complex number, and then the angle of this complex number is taken as the initial phase estimate +.>。
The purpose of this formula is to base all signal points receivedAnd its corresponding phase->To calculate a unified phase estimate +.>. This phase estimate may be considered as a "mean" or "central trend" of all signal point phases. In practical use, the->Is typically measured directly by the hardware device (e.g., phase demodulator) at the receiving end.
Phase errorIs true phase +.>Estimate +.>Is a difference between (a) and (b). This error measures how far the initial phase estimate is from the true phase. In a bayesian phase recovery algorithm, this phase error will be used to calculate a posterior probability distribution of the phase, and then a phase estimate corrected based on this posterior probability distribution.
Example 10: based on the above embodiment, the phase correction is performed using the bayesian method based on the phase error, the posterior probability distribution of the phase is calculated, the phase maximizing the posterior probability is found based on the posterior probability distribution, and the predicted phase is used as the predicted phaseThe method for correcting the received electrical signal by bits to complete the phase recovery includes: the posterior probability distribution of the true phase is calculated using the following formula:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Is the true phase; />Posterior probability distribution for true phase, +.>Is the variance of the phase noise;
the phase that maximizes the posterior probability is found as the predicted phase using the following formula:the method comprises the steps of carrying out a first treatment on the surface of the Finally, use of predicted phase +.>To correct the received electrical signal to complete the phase recovery.
Specifically, the formulaAnd calculating posterior probability distribution of the true phase. This formula is the basis of the Bayesian method, which is determined by known conditions (here phase error +.>) To infer a certain unknown quantity (here true phase +.>) Is a probability of (2). This formula is a gaussian distribution (alternatively called normal distribution) in which +.>Is the variance of the phase noise, affecting the width of the distribution. The meaning of this formula is given phaseError->Real phase +.>Is a probability of (2).
Formula (VI)Finding the phase where the posterior probability is maximized, this value being the true phase +.>Is the best prediction of (1), here->The operation represents a seek function +.>Corresponding to the maximum value>Values. In short, it is exactly which phase value is found so that the posterior probability is maximized.
Finally, the predicted phaseIs used to modify the received electrical signal. This process is called phase recovery. In practice, due to noise and interference during propagation, the phase of the received electrical signal may deviate from the original phase of the transmitting end, and the phase recovery is to reduce the deviation as much as possible, so that the signal phase of the receiving end is as close as possible to the original signal phase of the transmitting end. This process is very important to ensure the correctness of the data transmission.
While specific embodiments of the present invention have been described above, it will be understood by those skilled in the art that these specific embodiments are by way of example only, and that various omissions, substitutions, and changes in the form and details of the methods and systems described above may be made by those skilled in the art without departing from the spirit and scope of the invention. For example, it is within the scope of the present invention to combine the above-described method steps to perform substantially the same function in substantially the same way to achieve substantially the same result. Accordingly, the scope of the invention is limited only by the following claims.
Claims (9)
1. A fiber optic transceiver module based on CPO technology, the module comprising: the special integrated circuit is configured to receive data to be transmitted and convert the data to be transmitted into signals to be transmitted in the form of analog electric signals; a co-packaged fiber optic transceiver module comprising: an emission unit, an optical shape molding unit, an optical transmission unit, a photoelectric conversion unit, and a phase recovery unit; the transmitting unit is used for converting a signal to be transmitted in the form of an analog electric signal into an optical signal; the optical shape molding unit is used for optimizing the shape of the optical signal by using an optical shape molding algorithm to obtain an optimized optical signal; the optical transmission unit is used for transmitting the optimized signal to the photoelectric conversion unit; the optical signal optimized by the photoelectric conversion unit is converted into an electric signal; the phase recovery unit is used for carrying out phase recovery processing on the electric signal by using a phase recovery algorithm based on a Bayesian method so as to obtain final signal output; the light shape modeling algorithm is an arc shape modeling algorithm based on tail attenuation; the arc shape modeling algorithm based on tail attenuation optimizes the shape of the optical signal, and the time domain representation of the arc waveform of the optimized optical signal is represented by using the following formula:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Is the amplitude of the arc, +.>Is the position of the arc center, < >>Is a hyperbolic cosine function, ">Is a time domain representation of an arc sub-waveform, +.>Is the attenuation of the tail of the arc.
2. The CPO technology based optical fiber transceiver module as claimed in claim 1, wherein said asic includes a plurality of symbol encoding circuits to convert said data to be transmitted into symbol data in the form of digital signals; the asic further includes digital signal processing circuitry to optimize the symbol data; the asic further includes a plurality of digital-to-analog converters to convert symbol data in the form of digital signals to be transmitted in the form of analog electrical signals.
3. The CPO technology based optical fiber transceiver module as claimed in claim 1, wherein said transmitting unit is a laser diode; when the laser diode converts a signal to be transmitted in the form of an analog electric signal into an optical signal, the optical signal is subjected to 16-bit multi-level modulation; the optical transmission unit is an optical fiber.
4. The CPO technology based fiber optic transceiver module according to claim 3, wherein the arc sub-speed of the optimized optical signal is expressed using the formula:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Is first-order dispersion, & lt & gt>Is second order dispersion>Is third order dispersion +.>Is fourth order dispersion +.>Is at->Arc speed at time.
5. The CPO technology-based optical fiber transceiver module as claimed in claim 4, wherein the dispersion parameters of the optical fiber are subjected to fourth-order expansion in the frequency domain,、/>、/>and->The following constraint relationship is satisfied:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Is the refractive index of the optical fiber, < >>Is the dispersion parameter of the fiber,/>For the frequency of the optical fiber->Is the middle of the optical fiberHeart frequency.
6. The CPO technology-based optical fiber transceiver module as claimed in claim 5, wherein when the optical signal optimized by the optical-to-electrical conversion unit is converted into an electrical signal, the resulting electrical signal is expressed using the following formula:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Amplitude->Is phase, & lt + & gt>Is a frequency domain representation of the optimized optical signal, < >>Is an imaginary unit;
wherein,。
7. the CPO technology-based optical fiber transceiver module as claimed in claim 6, wherein said phase recovery unit performs phase recovery processing on the electrical signal using a bayesian-based phase recovery algorithm, thereby obtaining a final signal output, comprising: performing initial phase estimation on each signal point in the electric signal; calculating a phase error based on the initial phase estimate; based on the phase error, the phase correction is performed using a bayesian method, the posterior probability distribution of the phase is calculated, the phase maximizing the posterior probability is found based on the posterior probability distribution, and the received electric signal is corrected using the predicted phase as the predicted phase, thereby completing the phase recovery.
8. As claimed inThe CPO technology-based optical fiber transceiver module as set forth in claim 7, wherein the initial phase estimate obtained after performing the initial phase estimation on each signal point in the electrical signal is represented by using the following formula:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>For one signal point in the electrical signal, +.>A phase of a signal point in the electrical signal; />Representing the angle, i.e. the phase, of the complex number; />Is an imaginary unit; />Estimating for an initial phase; the phase error is calculated using the following formula:；/>is true phase, +.>Is an initial phase estimate.
9. The CPO-based optical fiber transceiver module as claimed in claim 8, wherein the phase correction is performed using a bayesian method based on the phase error, a posterior probability distribution of the phase is calculated, the phase maximizing the posterior probability is found based on the posterior probability distribution, and the received electrical signal is corrected using the predicted phase as the predicted phase, thereby completing the phase recovery method comprising:
the posterior probability distribution of the true phase is calculated using the following formula:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Is the true phase; />Posterior probability distribution for true phase, +.>Is the variance of the phase noise; the phase that maximizes the posterior probability is found as the predicted phase using the following formula: />The method comprises the steps of carrying out a first treatment on the surface of the Finally, use of predicted phase +.>To correct the received electrical signal to complete the phase recovery.
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