A spatial optical communication FEC decoding method and system based on stochastic resonance

Abstract

The present invention belongs to a spatial optical communication FEC decoding method. In order to solve the technical problem that the method for performing service data error correction by FEC encoding and decoding in the current spatial laser communication cannot perform normal error correction when the signal-to-noise ratio of the original signal is too low, a spatial optical communication FEC decoding method and system based on random resonance are provided. Aiming at the problem that the signal-to-noise ratio of the optical signal is poor after the spatial optical signal is transmitted over a long distance, the normalized scale transformation bistable random resonance is adopted to process the baseband electrical signal waveform after digital-to-analog conversion sampling, which can effectively improve the signal-to-noise ratio before entering the decoding. The decoding method is not limited by the channel coding type, is applicable to different types of decoding processing, and is performed in the digital domain, is easy to integrate, and is particularly suitable for small platform applications with limited volume and weight.

Description

Technical Field

[0001] The present invention belongs to a spatial optical communication FEC decoding method, and in particular relates to a spatial optical communication FEC decoding method and system based on stochastic resonance. Background Art

[0002] Space laser communication technology has broad application prospects in many fields due to its characteristics of resistance to electromagnetic interference, easy miniaturization, high confidentiality and security, and large communication capacity.

[0003] When facing long-distance communication needs in deep space and deep sea, the signal-to-noise ratio of laser signals reaching the receiving end after long-distance transmission is poor, which easily leads to high bit errors. If the laser transmission power is increased, it will inevitably bring greater system complexity. The size, weight, and power consumption of deep space spacecraft, as well as the laser transmission scattering environment in the deep sea, have all limited its application scope.

[0004] At present, in order to overcome the above limitations, the channel forward error correction (FEC) coding is often combined to perform error correction of service data. Common channel FEC coding methods include RS (Reed-Solomon), LDPC (Low Density Parity Check Code), Viterbi, etc., which are widely used in communication equipment. However, decoding error correction also has requirements for the signal-to-noise ratio (SNR) of the original signal. When the SNR is too low, error correction cannot be performed normally. Summary of the invention

[0005] The present invention aims to solve the technical problem that the FEC encoding and decoding method for service data error correction in current space laser communication cannot perform normal error correction when the signal-to-noise ratio of the original signal is too low. The present invention provides a space optical communication FEC decoding method and system based on random resonance.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A spatial optical communication FEC decoding method based on stochastic resonance is characterized in that it comprises the following steps:

[0008] S1, converts the received spatial optical signal into a baseband digital signal S1(n);

[0009] S2, resample the baseband digital signal S1(n) and then multiply it by the gain coefficient G cur Perform amplitude conversion to obtain signal S3(n);

[0010] S3, the absolute value of the amplitude of the signal S3(n) is statistically averaged to obtain Compare and target amplitude threshold A th ,like Then reduce the gain factor G cur ,like Then increase the gain factor G cur , until

[0011] S4, through the Runge-Kutta numerical calculation method, the signal S3(n) is substituted into the system equation to solve the system equation and obtain the signal S4(n);

[0012] S5, performs bit synchronization processing on signal S4(n) to obtain a synchronous sampling value of signal S4(n), which is recorded as signal S5(n);

[0013] S6, according to the preset decision threshold, obtain the binary data stream S6(n) corresponding to the signal S5(n);

[0014] S7, extracting valid data from the binary data stream S6(n);

[0015] S8, performing decoding and error correction processing on the valid data according to the preset coding type to obtain the original service data, and completing the spatial optical communication FEC decoding.

[0016] Further, in step S2, the resampling of the baseband digital signal S1(n) is specifically performed as follows:

[0017] According to the communication data rate and the sampling rate during the conversion in step S1, according to the preset communication symbol rate R s The optimal sampling rate F S_opt , resample the baseband digital signal S1(n).

[0018] Further, in step S2, the resampling of the baseband digital signal S1(n) is specifically performed as follows:

[0019] The baseband digital signal S1(n) is interpolated according to the following formula to obtain the interpolated value S2(n):

[0020]

[0021] Among them, C i (u) represents the interpolation parameter, according to the communication symbol rate R s The optimal sampling rate F S_opt Determine, i = -1, 0, 1, 2, i is the parameter serial number of the fourth-order interpolation, n is an integer greater than or equal to zero, indicating the sampling time, and u indicates the decimal part of the interpolation offset of the interpolation filter used when interpolating.

[0022] Furthermore, step S6-7 is included between step S6 and step S7, extracting a preset data frame header identifier from the binary data stream S6(n), and then extracting valid data from the binary data stream S6(n) according to the data frame header format.

[0023] The present invention also provides a spatial optical communication FEC decoding system based on stochastic resonance, which is used to implement the above-mentioned spatial optical communication FEC decoding method based on stochastic resonance, and its special feature is that it includes an analog processing unit, an SR preprocessing unit and an FEC decoding unit connected in sequence;

[0024] The analog processing unit input end is connected to an external spatial optical signal receiving component, and is used to convert the received spatial optical signal into a baseband digital signal S1(n);

[0025] The SR preprocessing unit is used to resample the baseband digital signal S1(n) and then multiply it by the gain coefficient G cur The amplitude is transformed to obtain the signal S3(n); the absolute value of the amplitude of the signal S3(n) is statistically averaged to obtain according to and target amplitude threshold A th Adjust the gain factor G cur ,make Finally, the Runge-Kutta numerical calculation method is used to substitute the signal S3(n) into the system equation to obtain the signal S4(n);

[0026] The FEC decoding unit is used to perform bit synchronization processing on the signal S4(n) to obtain a synchronous sampling value recorded as the signal S5(n), obtain a binary data stream S6(n) corresponding to the signal S5(n) according to a preset decision threshold, and extract valid data from the binary data stream S6(n).

[0027] Furthermore, the analog processing unit includes a photoelectric conversion module and an ADC analog-to-digital conversion module, and the output end of the photoelectric conversion module is connected to the input end of the ADC analog-to-digital conversion module;

[0028] The input end of the photoelectric conversion module is connected to an external spatial optical signal receiving component, and is used to convert the received spatial optical signal into a baseband electrical signal and send it to the ADC analog-to-digital conversion module;

[0029] The output end of the ADC analog-to-digital conversion module is connected to the SR preprocessing unit, and is used to convert the baseband electrical signal into a baseband digital signal S1 (n), and send it to the SR preprocessing unit.

[0030] Further, the SR preprocessing unit includes a scale transformation module and a Runge-Kutta numerical calculation module, and the output end of the scale transformation module is connected to the input end of the Runge-Kutta numerical calculation module;

[0031] The input end of the scale conversion module is connected to the output end of the ADC analog-to-digital conversion module, which is used to resample the baseband digital signal S1(n) and then multiply it by the gain coefficient G. cur The amplitude is transformed to obtain the signal S3(n); the absolute value of the amplitude of the signal S3(n) is statistically averaged to obtain according to and target amplitude threshold A th Adjust the gain factor G cur ,make

[0032] The output end of the Runge-Kutta numerical calculation module is connected to the input end of the FEC decoding unit, and is used to use the Runge-Kutta numerical calculation method to bring in the signal S3(n) to solve the system equation and obtain the signal S4(n).

[0033] Further, the scale conversion module includes a resampling submodule and a digital AGC submodule, and the output end of the resampling submodule is connected to the input end of the digital AGC submodule;

[0034] The resampling submodule adopts an interpolation filter, and the input end of the resampling submodule is connected to the output end of the ADC analog-to-digital conversion module, and is used to resample the baseband digital signal S1(n) according to the optimal sampling rate corresponding to the communication symbol rate of S1(n) in the stored frequency parameter lookup table;

[0035] The output end of the AGC submodule is connected to the input end of the Runge-Kutta numerical calculation module, and is used to multiply the gain coefficient G cur The amplitude is transformed to obtain the signal S3(n); the absolute value of the amplitude of the signal S3(n) is statistically averaged to obtain according to and target amplitude threshold A th Adjust the gain factor G cur ,make

[0036]

[0037] Further, the FEC decoding unit includes a bit synchronization module, a symbol hard decision module, a frame synchronization and data extraction module and an error correction decoding module connected in sequence;

[0038] The input end of the bit synchronization module is connected to the output end of the Runge-Kutta numerical calculation module, and is used to perform bit synchronization processing on the signal S4(n) to obtain a synchronous sampling value recorded as the signal S5(n);

[0039] The symbol hard decision module is used to obtain a binary data stream S6(n) corresponding to the signal S5(n) according to a preset decision threshold;

[0040] The frame synchronization and data extraction module is used to extract valid data from the binary data stream S6 (n);

[0041] The error correction decoding module is used to perform decoding and error correction processing on the valid data according to a preset coding type to obtain original business data.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] 1. The present invention proposes a spatial optical communication FEC decoding method based on random resonance. Aiming at the problem of poor signal-to-noise ratio of optical signals after long-distance transmission of spatial optical signals, the normalized scale transformation bistable random resonance is used to process the baseband electrical signal waveform after digital-to-analog conversion sampling, which can effectively improve the signal-to-noise ratio before decoding.

[0044] 2. The space optical communication FEC decoding method of the present invention is not limited by the channel coding type, is applicable to different types of decoding processing, and is performed in the digital domain, which is easy to integrate. It is especially suitable for small platform applications with limited volume and weight. Therefore, in the field of space laser communication technology, it has broad application prospects for this special application scenario.

[0045] 3. The present invention also provides a spatial optical communication FEC decoding system based on random resonance, which can implement the aforementioned decoding method. By setting an analog processing unit, an SR preprocessing unit and an FEC decoding unit, the aforementioned decoding method is implemented in a modular form, and has the advantages of the aforementioned decoding method.

[0046] 4. In the spatial optical communication FEC decoding system of the present invention, the scale transformation module adopts an implementation method that is more suitable for engineering applications. It uses a feedforward method of adjusting resampling and digital AGC according to a frequency parameter lookup table to perform scale transformation, which can meet the requirements of random resonance processing for input signals. Compared with existing parameter feedback methods such as particle swarm optimization, the implementation structure is simple and the response speed is faster. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a principle diagram of an embodiment of a spatial optical communication FEC decoding method and system based on stochastic resonance of the present invention;

[0048] Figure 2 is a schematic diagram of an SR preprocessing unit in an embodiment of the present invention;

[0049] Figure 3is a schematic diagram of a resampling submodule in an embodiment of the present invention;

[0050] Figure 4 1 is a time domain waveform diagram before and after being processed by the SR preprocessing module in an embodiment of the present invention; wherein (a) is a time domain waveform diagram before being processed by the SR preprocessing module, and (b) is a time domain waveform diagram after being processed by the SR preprocessing module;

[0051] Figure 5 It is a comparison diagram of the power spectrum density before and after being processed by the SR preprocessing module in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0053] The present invention provides a spatial optical communication FEC decoding method based on random resonance, which mainly performs normalized random resonance processing on the baseband digital signal converted into the electrical domain by the receiving end, which can improve the signal-to-noise ratio of the signal entering the post-decoding module and improve the decoding error correction performance. The received spatial optical signal is converted into a baseband digital signal S1(n). The baseband digital signal S1(n) is resampled and then multiplied by the gain coefficient G cur Perform amplitude transformation to obtain signal S3(n). Perform statistical averaging on the absolute value of the amplitude of signal S3(n) to obtain Compare and target amplitude threshold A th ,like Then reduce the gain factor G cur ,like Then increase the gain factor G cur , until By using the Runge-Kutta numerical calculation method, the signal S3(n) is brought into the system equation to solve the system equation and obtain the signal S4(n). The signal S4(n) is subjected to bit synchronization processing to obtain the signal S5(n). According to the preset decision threshold, the binary data stream S6(n) corresponding to the signal S5(n) is obtained. The preset data frame header identifier and valid data are extracted from the binary data stream S6(n). Decoding and error correction processing is performed according to the preset coding type to obtain the original service data and complete the spatial optical communication FEC decoding.

[0054] like Figure 1In order to realize the above-mentioned spatial optical communication FEC decoding method, the present invention also provides a spatial optical communication FEC decoding system based on stochastic resonance, including an analog processing unit, an SR preprocessing unit and an FEC decoding unit connected in sequence. Among them, the SR preprocessing unit includes a scale transformation module and a Runge-Kutta numerical calculation module, and the scale transformation module includes a resampling submodule and a digital AGC submodule. The following is a specific embodiment of a spatial optical communication FEC decoding method based on stochastic resonance of the present invention, which is implemented by the spatial optical communication FEC decoding system of the present invention, and specifically includes the following steps:

[0055] 1) The receiving end optical antenna receives the spatial optical signal transmitted by the transmitting communication terminal, converts it into a baseband electrical signal through the photoelectric conversion module, and then passes through the ADC analog-to-digital conversion module to obtain a baseband digital signal S1 (n). This step 1) is completed in the analog processing unit.

[0056] Among them, the photoelectric conversion module adopts corresponding coherent or incoherent detection according to the modulation method agreed upon by the communicating parties, including but not limited to OOK, PPM, and MPSK modulation. In coherent detection, the photoelectric conversion module includes but is not limited to a low-noise amplifier, an automatic power control unit (Automatics Power Control, APC), an optical phase-locked loop, a balanced detector, and a control circuit; in incoherent detection, the photoelectric conversion module includes but is not limited to a low-noise amplifier, an intensity detector, and a control circuit. In this embodiment, the spatial optical signal uses OOK intensity modulation, corresponding to the incoherent detection method.

[0057] In this embodiment, the communication data rate can be switched to R in real time. s =5Mbps / 10Mbps / 20Mbps. In engineering, stochastic resonance (SR) processing generally requires a sampling rate of at least the data rate to be enhanced R s More than 10 times of SR state, in order to meet the requirements of SR state generation and the above three levels of R s Communication data rate, ADC analog-to-digital conversion module sampling rate is F s =1GHz. The quantization bit width of the ADC analog-to-digital conversion module takes the empirical value N Q =12bit.

[0058] 2) Since the SR state generation condition is a small parameter condition of adiabatic approximation, that is, in engineering applications, the amplitudes of the input signal and noise are required to be much smaller than 1, and the frequency of the input signal is much smaller than the sampling rate. For the communication system of the present invention, the frequency of the input signal is the communication symbol rate. Therefore, it is necessary to perform a scale transformation on the input signal so that the amplitude parameter reflecting the signal amplitude of the input SR preprocessing unit and the time parameter reflecting the sampling frequency meet the SR state generation condition.

[0059] The SR preprocessing unit uses high-frequency noise to improve the signal-to-noise ratio of low-frequency weak signals, which involves multi-parameter joint adjustment. Commonly used methods are particle swarm, simulated annealing, ant colony and other parameter optimization methods, but these methods have problems such as non-convergence of iteration or slow search speed.

[0060] like Figure 2 As shown, the present invention uses a method of identifying and judging the baseband digital signal according to a preset parameter set stored in a lookup table to complete the scale transformation of the corresponding parameters, so that the SR preprocessing unit is in the SR state, and the transformed signal is sent to a fourth-order Runge-Kutta numerical calculation module to solve the bistable Langevin system equation, and then the solved signal is sent to the FEC decoding unit.

[0061] The normalized bistable Langevin system equation is: In the equation, t is the time variable, g is the time parameter, h is the amplitude parameter, y is the output signal, which represents the function that changes with time, x is the input signal, and a and b are the parameters of the bistable Langevin system equation under the standard small parameter condition, which can be optimized according to prior knowledge. However, in practical applications, it is difficult for the system equation to directly meet the small parameter condition. By adjusting the g and h parameters, the system equation can meet the small parameter condition and produce the SR state, thereby improving the signal-to-noise ratio of the output signal. At the same time, by adjusting g and h, the parameters a and b can be adjusted. The calculation process of discrete time is as follows:

[0062] k1=f(y n ,x n )

[0063]

[0064]

[0065]

[0066]

[0067] Where w(t) is white noise with a mean of 0, D is the noise intensity, and x n is the input signal of the SR preprocessing unit, y n is the output signal of the SR preprocessing unit, n=0,1,2,..., n represents the sampling time, k1,k2,k3,k4 are all intermediate variables of the calculation.

[0068] In the present invention, the SR preprocessing unit specifically includes a scale change module and a Runge-Kutta numerical calculation module. In the scale change module, the time parameter g and the amplitude parameter h are adjusted respectively by scale transformation processing to meet the generation conditions of the SR state, and then the output signal of the SR is solved by the Runge-Kutta numerical calculation module. The specific steps are as follows:

[0069] 2.1) Resampling: According to the currently set communication data rate and the sampling rate of the ADC analog-to-digital conversion module, the resampling submodule searches the communication symbol rate R in the stored frequency parameter table. s The optimal sampling rate F S_opt , resample the baseband digital signal S1(n), complete the sampling rate conversion reflected by the time parameter g, and obtain the signal S2(n);

[0070] like Figure 2 The resampling submodule can be implemented by, but not limited to, an interpolation filter. Specifically, this embodiment uses a fourth-order Lagrange interpolation filter to complete the resampling. The Lagrange interpolation filter structure block diagram is shown in FIG. Figure 3 As shown, it includes an interpolator and an NCO controller, u is the decimal part of the interpolation offset of the NCO controller input interpolation filter, and m is the integer part of the interpolation offset of the NCO controller input interpolation filter.

[0071] Among them, the NCO controller is based on F S_opt To generate an interpolation trigger signal, the interpolation trigger signal triggers the interpolation filter to fit S1(n) according to the fourth-order Lagrange interpolation formula to obtain the interpolated value S2(n). The fourth-order Lagrange interpolation formula is as follows:

[0072]

[0073] Where x2() represents S1(n) to be interpolated, y2(n) is S2(n) after interpolation, i is the parameter number of the fourth-order interpolation, i = -2, 1, 0, 1, and the interpolation parameter C i (u) are calculated as follows:

[0074]

[0075]

[0076]

[0077]

[0078] In this embodiment, at the communication symbol rate R s =5Mbps, take the resampling rate F S_opt=250MHz=F S / 4. Take the best time parameter g=250000000>0, and scale it proportionally, then the equivalent sampling frequency Equivalent communication symbol rate The adiabatic approximation condition is satisfied, and the communication symbol rate is much smaller than the sampling rate.

[0079] Similarly, R s =10Mbps, g=500000000, F S_opt =500MHz=F S / 2; R s =20Mbps, g=1000000000, F S_opt =1GHz=F S .

[0080] 2.2) The resampled S2(n) is sent to the digital AGC submodule and the current gain coefficient G cur Multiply them to obtain the amplitude-converted signal S3(n)=G output by the digital AGC submodule cur *S2(n), the absolute value of the amplitude of S3(n) is statistically averaged to obtain Where n = 0, 1, 2, ..., represents the sampling time.

[0081] Will and target amplitude threshold A th For comparison: If Then reduce G cur ;like Then increase G cur Finally, the amplitude of S3(k) is kept at state.

[0082] The statistical average formula of the absolute value is: N w For the statistical average length, an empirical value of 5000 is taken in this embodiment. According to the ADC analog-to-digital conversion module quantization bit width N Q =12 bits, the decimal part occupies 11 bits.

[0083] In this embodiment, the amplitude parameter h must make S3(n) meet the requirement that the signal and noise amplitudes are far less than 1 in the adiabatic approximation condition, and the target amplitude threshold A is set according to the optimal amplitude parameter set corresponding to different signal-to-noise ratio conditions stored in advance. th From the normalized bistable Langevin system equation, it can be seen that the scale transformation amplitude parameter h is the gain coefficient G of the digital AGC submodule in the present invention. cur In this embodiment, A th=0.4, the effective value of the digital AGC submodule output S3(k) also remains near the value 0.4.

[0084] For the optimal amplitude parameter set that meets the conditions for generating the SR state, the specific analysis is as follows:

[0085] First, the total power P1 of the ADC collected waveform S1(n) is the effective signal power P S1 and noise power P N1 The sum of P1 = P S1 +P N1 In practical applications, the noise is mainly the base noise inside the receiver, so in practice, the communication receiver uses P N1 The value is considered as a fixed value and can be obtained by actual measurement. S1 As P1 decreases, it decreases, that is, the signal-to-noise ratio of S1(n) Proportional to P S1 .

[0086] The average amplitude of S1(n) is A S1 , P S1 Proportional to (A S1 ) 2 , so we can measure A in advance S1 The mapping relationship curve e(A corresponding to SNR1 S1 ,SNR1), and store the curve in advance in the receiving end. When in the communication working state, first measure A in real time S1 , and then from the stored e(A S1 , SNR1) to obtain the optimal target amplitude threshold A under the current SNR1 th , and controls the digital AGC gain G cur Keep the amplitude of S3(k) at state.

[0087] Among them, A S1 The measurement formula is N1 is the length of the statistical average, and in this embodiment, an empirical value of 5000 is taken.

[0088] The above resampling module and digital AGC submodule constitute a scale conversion module.

[0089] 2.3) After the scale transformation is completed in steps 2.1) and 2.2), the normalized bistable Langevin system equation is obtained by the fourth-order Runge-Kutta numerical calculation module: Solve and then obtain the solved digital signal S4(n), which means that the SR preprocessing process is completed.

[0090] In this embodiment, when the signal-to-noise ratio of signal S1(n) is SNR1=-6dB, the noise is Gaussian white noise, preferably the amplitude parameter h=1, the system parameters a=0.0004, b=0.02. Under this condition, the SR preprocessing unit can be in the SR state.

[0091] Figure 4 A set of time domain waveform diagrams of corresponding signals before and after processing by the SR preprocessing unit are shown, wherein (a) is the received signal S3(n), i.e., the time domain waveform diagram before processing by the SR preprocessing unit, and (b) is the signal S4(n) corresponding to the signal S3(n), i.e., the time domain waveform diagram of the output signal S4(n) after processing by the SR preprocessing unit. Figure 5 This is a comparison diagram of the power spectrum density of the signal before and after processing by the SR preprocessing unit. It can be seen that in the low-frequency spectrum area where the effective signal is located, the signal-to-noise ratio of the signal after SR preprocessing is significantly better than that before SR preprocessing. At the same time, the high-frequency noise is significantly suppressed.

[0092] The Runge-Kutta numerical calculation method can be implemented in a variety of equation forms. The equation form used in this embodiment is a more concise specific calculation method that can ensure the calculation results.

[0093] 3) The baseband digital signal after SR preprocessing is then sent to the bit synchronization module in the FEC decoding unit to obtain the synchronous sampling value of signal S4(n), which is output as signal S5(n), where the sampling rate of S5(n) is equal to the data rate R s , and the sampling point is in the middle of the data bit waveform. In this embodiment, the bit synchronization module is implemented using the Gardener algorithm.

[0094] 4) In the symbol hard decision module, according to the preset decision threshold J th Make a hard decision on the symbol, that is, if S5(n)≥J th , then it is judged as symbol 1, if S5(n)<J th , then it is determined to be symbol 0, and a binary data stream S6(n) is obtained. In this embodiment, J can be set th =0.

[0095] 5) In the frame synchronization and data extraction module, a preset data frame header identifier is extracted from the binary data stream S6 (n) after the judgment, that is, frame synchronization is performed, and then according to the data frame header format, the valid data part in the data frame is extracted and sent to the error correction decoding module;

[0096] In this embodiment, the frame header identifier is set to a 32-bit binary sequence 1ACFFC1D, and the frame header is identified and data is synchronously extracted by detecting the sequence.

[0097] 6) The error correction decoding module performs decoding and error correction processing according to the agreed coding type, obtains the original business data and outputs it, completing all receiving and processing functions. In this embodiment, the encoding and decoding format can adopt the RS (255, 239) format.

[0098] like Figure 1 As shown, this embodiment also provides a spatial optical communication FEC decoding system, including an analog processing unit, an SR preprocessing unit and a FEC decoding unit.

[0099] The analog processing unit includes a photoelectric conversion module and an ADC analog-to-digital conversion module. The spatial light signal emitted by the communication terminal received by the optical antenna is coupled into the optical fiber and sent to the photoelectric conversion module. The ADC analog-to-digital conversion module is used to convert the analog electrical signal into a digital electrical signal.

[0100] The SR preprocessing unit includes a scale transformation module and a Runge-Kutta numerical calculation module. The scale transformation module includes a resampling submodule and a digital AGC submodule. The resampling submodule completes the conversion of the sampling rate, and the digital AGC submodule completes the conversion of the input signal amplitude. The Runge-Kutta numerical calculation module performs fitting calculation on the digital signal after the scale transformation to obtain the output signal of the SR preprocessing unit.

[0101] The FEC decoding unit includes a bit synchronization module, a symbol decision module, a frame synchronization and data extraction module, and an error correction decoding module. The bit synchronization module extracts the synchronous sampling value of the baseband digital signal from the input signal. The symbol decision module performs binarization processing according to the preset threshold. The frame synchronization and data extraction module completes the extraction of valid data. The error correction decoding module decodes and corrects the valid data according to the agreed coding type to obtain the original business data.

[0102] The spatial optical communication FEC decoding method based on random resonance of the present invention can improve the signal-to-noise ratio before decoding, and adopts a preset lookup table combined with AGC and resampling to achieve the scale transformation of the input signal to meet the conditions for the generation of random resonance, and has a simple structure and fast response speed. In addition, the processing process is carried out in the digital domain, with high integration, and can be applied to small platform applications with limited volume and weight. It can fully meet the transmission requirements in the context of long-distance laser communication.

[0103] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A spatial optical communication FEC decoding method based on stochastic resonance, characterized in that: The following steps are involved: S1, converts the received spatial optical signal into a baseband digital signal S1(n); S2, resample the baseband digital signal S1(n) and then multiply it by the gain coefficient G cur Perform amplitude conversion to obtain signal S3(n); S3, the absolute value of the amplitude of the signal S3(n) is statistically averaged to obtain Compare and target amplitude threshold A th ,like Then reduce the gain factor G cur ,like Then increase the gain factor G cur , until S4, through the Runge-Kutta numerical calculation method, the signal S3(n) is substituted into the system equation to solve the system equation and obtain the signal S4(n); S5, performs bit synchronization processing on signal S4(n) to obtain a synchronous sampling value of signal S4(n), which is recorded as signal S5(n); S6, according to the preset decision threshold, obtain the binary data stream S6(n) corresponding to the signal S5(n); S7, extracting valid data from the binary data stream S6(n); S8, performing decoding and error correction processing on the valid data according to the preset coding type to obtain the original service data, and completing the spatial optical communication FEC decoding.

2. According to claim 1, a spatial optical communication FEC decoding method based on stochastic resonance is characterized in that: In step S2, the resampling of the baseband digital signal S1(n) is specifically performed as follows: According to the communication data rate and the sampling rate during the conversion in step S1, according to the preset communication symbol rate R s The optimal sampling rate F S_opt , resample the baseband digital signal S1(n).

3. According to claim 2, a spatial optical communication FEC decoding method based on stochastic resonance is characterized in that: In step S2, the resampling of the baseband digital signal S1(n) is specifically performed as follows: The baseband digital signal S1(n) is interpolated according to the following formula to obtain the interpolated value S2(n): Among them, C i (u) represents the interpolation parameter, according to the communication symbol rate R s The optimal sampling rate F S_opt Determine, i = -1, 0, 1, 2, i is the parameter number of the fourth-order interpolation, n is an integer greater than or equal to zero, indicating the sampling time, and u indicates the decimal part of the interpolation offset of the interpolation filter used when interpolating.

4. A spatial optical communication FEC decoding method based on stochastic resonance according to any one of claims 1 to 3, characterized in that: The step S6-7 is included between step S6 and step S7, extracting a preset data frame header identifier from the binary data stream S6(n), and then extracting valid data from the binary data stream S6(n) according to the data frame header format.

5. A spatial optical communication FEC decoding system based on stochastic resonance, used to implement a spatial optical communication FEC decoding method based on stochastic resonance as described in any one of claims 1 to 3, characterized in that: It includes an analog processing unit, an SR pre-processing unit and an FEC decoding unit which are connected in sequence; The analog processing unit input end is connected to an external spatial optical signal receiving component, and is used to convert the received spatial optical signal into a baseband digital signal S1(n); The SR preprocessing unit is used to resample the baseband digital signal S1(n) and then multiply it by the gain coefficient G cur The amplitude is transformed to obtain the signal S3(n); the absolute value of the amplitude of the signal S3(n) is statistically averaged to obtain according to and target amplitude threshold A th Adjust the gain factor G cur ,make Finally, the Runge-Kutta numerical calculation method is used to substitute the signal S3(n) into the system equation to obtain the signal S4(n); The FEC decoding unit is used to perform bit synchronization processing on the signal S4(n) to obtain a synchronous sampling value recorded as the signal S5(n), obtain a binary data stream S6(n) corresponding to the signal S5(n) according to a preset decision threshold, and extract valid data from the binary data stream S6(n).

6. The spatial optical communication FEC decoding system based on stochastic resonance according to claim 5, characterized in that: The analog processing unit includes a photoelectric conversion module and an ADC analog-to-digital conversion module, and the output end of the photoelectric conversion module is connected to the input end of the ADC analog-to-digital conversion module; The input end of the photoelectric conversion module is connected to an external spatial optical signal receiving component, and is used to convert the received spatial optical signal into a baseband electrical signal and send it to the ADC analog-to-digital conversion module; The output end of the ADC analog-to-digital conversion module is connected to the SR preprocessing unit, and is used to convert the baseband electrical signal into a baseband digital signal S1 (n), and send it to the SR preprocessing unit.

7. The spatial optical communication FEC decoding system based on stochastic resonance according to claim 6, characterized in that: The SR preprocessing unit includes a scale transformation module and a Runge-Kutta numerical calculation module, and the output end of the scale transformation module is connected to the input end of the Runge-Kutta numerical calculation module; The input end of the scale conversion module is connected to the output end of the ADC analog-to-digital conversion module, which is used to resample the baseband digital signal S1(n) and then multiply it by the gain coefficient G. cur The amplitude is transformed to obtain the signal S3(n); the absolute value of the amplitude of the signal S3(n) is statistically averaged to obtain according to and target amplitude threshold A th Adjust the gain factor G cur ,make The output end of the Runge-Kutta numerical calculation module is connected to the input end of the FEC decoding unit, and is used to use the Runge-Kutta numerical calculation method to bring in the signal S3(n) to solve the system equation and obtain the signal S4(n).

8. The spatial optical communication FEC decoding system based on stochastic resonance according to claim 7, characterized in that: The scale conversion module includes a resampling submodule and a digital AGC submodule, and the output end of the resampling submodule is connected to the input end of the digital AGC submodule; The resampling submodule adopts an interpolation filter, and the input end of the resampling submodule is connected to the output end of the ADC analog-to-digital conversion module, and is used to resample the baseband digital signal S1(n) according to the optimal sampling rate corresponding to the communication symbol rate of S1(n) in the stored frequency parameter lookup table; The output end of the AGC submodule is connected to the input end of the Runge-Kutta numerical calculation module to multiply the gain coefficient G cur The amplitude is transformed to obtain the signal S3(n); the absolute value of the amplitude of the signal S3(n) is statistically averaged to obtain according to and target amplitude threshold A th Adjust the gain factor G cur ,make 9. The spatial optical communication FEC decoding system based on stochastic resonance according to claim 7, characterized in that: The FEC decoding unit includes a bit synchronization module, a symbol hard decision module, a frame synchronization and data extraction module and an error correction decoding module which are connected in sequence; The input end of the bit synchronization module is connected to the output end of the Runge-Kutta numerical calculation module, and is used to perform bit synchronization processing on the signal S4(n) to obtain a synchronous sampling value recorded as the signal S5(n); The symbol hard decision module is used to obtain a binary data stream S6(n) corresponding to the signal S5(n) according to a preset decision threshold; The frame synchronization and data extraction module is used to extract valid data from the binary data stream S6 (n); The error correction decoding module is used to perform decoding and error correction processing on the valid data according to a preset coding type to obtain original business data.

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