Efficient soft demodulation method and system suitable for pulse position modulation

Abstract

The invention discloses an efficient soft demodulation method and system suitable for pulse position modulation, and relates to the technical field of laser communication. Pulse position modulation signals and preset channel parameters are received, and time slot receiving signals are acquired based on the pulse position modulation signals, the preset channel parameters comprise the optical signal intensity and noise power of a Gaussian channel, the pulse optical signal electron number of a Poisson channel and the electron number of an ambient optical signal; inputting the time slot receiving signal and a preset channel parameter into a pre-established soft demodulation model based on a maximum posteriori and a maximum likelihood criterion, and outputting to obtain a log likelihood ratio LLR of a modulation bit; meanwhile, the index logarithm operation of the LLR is simplified by adopting a max-log method, and the calculation complexity is reduced; aI is adopted to optimize the scaling coefficient for the performance loss caused by soft demodulation calculation simplification to balance the performance loss and the implementation complexity, so that the transmission efficiency of PPM modulation is improved.

Description

Technical Field

[0001] This invention relates to the field of laser communication technology, specifically to a highly efficient soft demodulation method and system suitable for pulse position modulation. Background Technology

[0002] Laser communication between the Earth and the Moon and beyond has extremely long signal transmission distances, resulting in fewer than a few dozen photons being received. It generally employs pulse position modulation with high power efficiency, such as NASA's DSOC and LLCD laser communication systems.

[0003] In the engineering process of PPM modulation and demodulation, hard decision method was generally used in the early stages to reduce implementation complexity. However, this method suffers a 3dB performance loss due to the loss of bit likelihood ratio reliability information, resulting in low transmission efficiency of PPM modulation. Summary of the Invention

[0004] To address the shortcomings mentioned in the background section, the present invention aims to provide an efficient soft demodulation method and system suitable for pulse position modulation.

[0005] Firstly, the objective of this invention can be achieved through the following technical solution: a highly efficient soft demodulation method suitable for pulse position modulation, the method comprising the following steps: The system receives a pulse position modulation signal and preset channel parameters, and obtains a time slot received signal based on the pulse position modulation signal. The preset channel parameters include the optical signal intensity and noise power of the Gaussian channel, and the number of electrons in the pulse optical signal and the number of electrons in the ambient light signal of the Poisson channel. The time-slot received signal and preset channel parameters are input into a pre-established soft demodulation model based on the maximum a posteriori and maximum likelihood criteria, and the log-likelihood ratio (LLR) of the modulation bits is output; wherein, the log-likelihood ratio of the modulation bits is the logarithm of the ratio of bit probability 0 to bit probability 1.

[0006] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: the optical signal strength and noise power of the Gaussian channel are as follows: Under Gaussian channel conditions, M-PPM in M ​​(M=2 n The signals received in each pulse time slot are: in, The pulse time slot position, This indicates whether a pulse signal exists; I represents the intensity of the received optical signal. It is Gaussian white noise with a noise power of .

[0007] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: a direct soft demodulation process for the Gaussian channel, as follows: Direct soft demodulation using the maximum likelihood criterion, bit The LLR containing reliability information is: in, The pulse modulation time slot position is The received signal, I is the received optical signal strength, and the noise power is... , In M-PPM modulation symbols The pulse time slot position.

[0008] Using the max-log approximation formula The simplified LLR can be obtained as: in, In M-PPM modulation symbols The maximum value of all pulse position calculation results.

[0009] Considering M-PPM The soft-value calculation formula contains approximations, leading to performance loss in subsequent decoding. An adjustable scaling factor is added to the formula: scaling factor , It can be optimized through AI training.

[0010] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: a soft demodulation process for the iterative demodulation and decoding processing of the Gaussian channel, as follows: During joint demodulation and decoding, the demodulation bits The probabilities of being 0 and 1 are not equal, and the extrinsic likelihood ratio can be obtained through iterative soft decoding. Then they can unite ,get The first way to represent probability: Multiply the numerator and denominator of the above equation by respectively , can be obtained The second way to represent probability: Based on external information likelihood ratio and The first way to represent probability is to obtain M-PPM bits. The posterior LLR is: in, for pulse position, Pulse position The k-th bit, the unit impulse function .

[0011] Using the max-log approximation formula The simplified posterior LLR is obtained as follows: The input decoding soft demodulation LLR is: The aforementioned LLR contains extrinsic information from the iterative soft decoding output, which can effectively improve the reliability of receiving erroneous bits.

[0012] Based on external information likelihood ratio and The second representation of probability, for the soft demodulation LLR of input decoding, is: in, It is a symbolic function.

[0013] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: within the Poisson channel, assuming the average number of photoelectrons of the pulsed light signal and the ambient light are respectively... and Then the number of photons received in M ​​time slots The probability is: in, , .

[0014] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: a direct soft demodulation process for the Poisson channel, as follows: Under Poisson channel, bits The LLR can be calculated using the following formula: Similarly, using the max-log approximation formula The simplified posterior LLR is obtained as follows: At the same time, an adjustable scaling factor is added to the formula: scaling factor , It can be optimized through AI training.

[0015] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: a soft demodulation process for the demodulation-decoding iterative processing of the Poisson channel, as follows: make The soft demodulation LLR for input decoding under a Poisson channel is obtained as follows: .

[0016] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: the pre-established soft demodulation model based on the maximum a posteriori and maximum likelihood criteria is as follows: Based on the Maximum A posteriori (MAP) criterion, LLR is defined as follows: Where y represents the received signal and H represents the channel. Let the modulation bit be... If the probabilities of 0 and 1 are equal, then the LLR based on the maximum likelihood (ML) criterion can be obtained: .

[0017] Secondly, in order to achieve the above objectives, the present invention discloses a high-efficiency soft demodulation system suitable for pulse position modulation, comprising: The signal processing module is used to receive pulse position modulation signals and preset channel parameters, and to obtain time slot received signals based on the pulse position modulation signals. The preset channel parameters include the optical signal intensity and noise power of the Gaussian channel, and the number of electrons in the pulse optical signal and the number of electrons in the ambient light signal of the Poisson channel. The soft demodulation module is used to input the time slot received signal and preset channel parameters into a pre-established soft demodulation model based on the maximum a posteriori and maximum likelihood criteria, and output the log-likelihood ratio (LLR) of the modulation bits; wherein the log-likelihood ratio of the modulation bits is the logarithm of the ratio of bit probability 0 to bit probability 1.

[0018] In another aspect of the present invention, in order to achieve the above-mentioned objective, a terminal device is disclosed, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. The memory stores the computer program capable of running on the processor. When the processor loads and executes the computer program, it employs an efficient soft demodulation method for pulse position modulation as described above.

[0019] The beneficial effects of this invention are: Based on the maximum a posteriori and maximum likelihood criteria, this invention derives general soft demodulation algorithms for direct demodulation and joint demodulation / decoding processing for Gaussian and Poisson channels, respectively. To address the performance loss caused by the simplification of soft demodulation calculations, this invention balances performance loss with implementation complexity, thereby improving the transmission efficiency of PPM modulation. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Figure 1 This is a schematic diagram of the method flow of the present invention; Figure 2 This is a schematic diagram of the 4-PPM modulation of the present invention; Figure 3 This is a schematic diagram of the system structure of the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Example 1: like Figure 1 As shown, an efficient soft demodulation method suitable for pulse position modulation is proposed, the method comprising the following steps: S101: Receive the pulse position modulation signal and preset channel parameters, and obtain the time slot received signal based on the pulse position modulation signal. The preset channel parameters include the optical signal intensity and noise power of the Gaussian channel, and the number of electrons in the pulse optical signal and the number of electrons in the ambient light signal of the Poisson channel. The optical signal strength and noise power of the Gaussian channel are as follows: Under Gaussian channel conditions, the signals received by 4-PPM in 4 time slots are as follows: in, , I represents the received optical signal strength. It is Gaussian white noise with a noise power of .

[0023] The direct soft demodulation process of a Gaussian channel is as follows: Direct soft demodulation using the maximum likelihood criterion, bit The LLR is: Similarly, bits The LLR is: Using approximation formulas Bit and The LLR can be approximated as: Considering 4-PPM The soft-value calculation formula contains approximations, leading to performance loss in subsequent decoding. An adjustable scaling factor is added to the formula: scaling factor , It can be optimized through AI training.

[0024] The soft demodulation process of the Gaussian channel demodulation decoding iteration is as follows: During joint demodulation and decoding, the demodulation bits The probabilities of being 0 and 1 are not equal, and the extrinsic likelihood ratio can be obtained through iterative soft decoding. Then they can unite ,get The first way to represent probability: Based on the external information likelihood ratio, 4-PPM bits can be obtained. posterior soft value: The input decoding soft demodulation LLR is calculated as follows: Similarly, bits The posterior soft value and soft demodulation LLR are: Within a Poisson channel, let the average number of photoelectrons for the pulsed light signal and the ambient light be respectively... and The number of photons received in the four time slots The probability is: in, , .

[0025] The direct soft demodulation process of a Poisson channel is as follows: Under Poisson channel, bits The LLR can be calculated using the following formula: Similarly, bits The LLR is: Using approximation formulas Bit and The LLR can be approximated as: Meanwhile, considering 4-PPM The soft-value calculation formula contains approximations, leading to performance loss in subsequent decoding. An adjustable scaling factor can be added to the formula. scaling factor , It can be optimized through AI training.

[0026] The soft demodulation process of the demodulation-decoding iterative processing of the Poisson channel is as follows: right The first representation of probability multiplies the numerator and denominator by respectively , can be obtained The second way to represent probability: Based on the external information likelihood ratio, 4-PPM bits can be obtained. posterior soft value: The input decoding soft demodulation LLR is calculated as follows: Similarly, bits The posterior soft value and soft demodulation LLR are: S102: Input the time slot received signal and preset channel parameters into a pre-established soft demodulation model based on the maximum a posteriori and maximum likelihood criteria, and output the maximum likelihood ratio LLR of the modulation bit; wherein, the log-likelihood ratio of the modulation bit is the logarithm of the ratio of bit probability 0 to bit probability 1.

[0027] The pre-established soft demodulation model based on the maximum a posteriori and maximum likelihood criteria is as follows: Based on the Maximum A posteriori (MAP) criterion, LLR is defined as follows: Where y represents the received signal and H represents the channel. Let the modulation bit be... If the probabilities of 0 and 1 are equal, then the LLR based on the maximum likelihood (ML) criterion can be obtained: .

[0028] Based on the maximum likelihood criterion, a general method for deriving the bit LLR with reliability information is given; at the same time, by using the maximum a posteriori criterion, the decoded extrinsic information can be linked with the LLR, effectively improving the reliability of the LLR of the channel transmission error bits.

[0029] Example 2: To achieve the above objective, such as Figure 3 As shown, based on Embodiment 1, this invention discloses a high-efficiency soft demodulation system suitable for pulse position modulation, comprising: The signal processing module 11 is used to receive the pulse position modulation signal and preset channel parameters, and to obtain the time slot received signal based on the pulse position modulation signal. The preset channel parameters include the optical signal intensity and noise power of the Gaussian channel, and the number of electrons in the pulse optical signal and the number of electrons in the ambient light signal of the Poisson channel. The soft demodulation module 12 is used to input the time slot received signal and preset channel parameters into a pre-established soft demodulation model based on the maximum a posteriori and maximum likelihood criteria, and output the log-likelihood ratio (LLR) of the modulation bit; wherein the log-likelihood ratio of the modulation bit is the logarithm of the ratio of bit probability 0 to bit probability 1.

[0030] Based on the same inventive concept, this invention also provides a computer device, comprising: one or more processors, and a memory for storing one or more computer programs; the programs include program instructions, and the processor executes the program instructions stored in the memory. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, used to implement one or more instructions, specifically for loading and executing one or more instructions stored in a computer storage medium to implement the above-described method.

[0031] It should be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium storing a computer program, which, when executed by a processor, performs the above-described method. This storage medium can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0032] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0033] The foregoing has shown and described the basic principles, main features, and advantages of this disclosure. Those skilled in the art should understand that this disclosure is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of this disclosure. Various changes and modifications can be made to this disclosure without departing from its spirit and scope, and all such changes and modifications fall within the scope of this disclosure as claimed.

Claims

1. A highly efficient soft demodulation method suitable for pulse position modulation, characterized in that, The method includes the following steps: The system receives a pulse position modulation signal and preset channel parameters, and obtains a time slot received signal based on the pulse position modulation signal. The preset channel parameters include the optical signal intensity and noise power of the Gaussian channel, and the number of electrons in the pulse optical signal and the number of electrons in the ambient light signal of the Poisson channel. The time-slot received signal and preset channel parameters are input into a pre-established soft demodulation model based on maximum a posteriori and maximum likelihood criteria, and the log-likelihood ratio (LLR) of the modulation bit is output; wherein, the log-likelihood ratio of the modulation bit is the logarithm of the ratio of the probability of bit being 0 to the probability of bit being 1.

2. The efficient soft demodulation method for pulse position modulation according to claim 1, characterized in that, The optical signal strength and noise power of the Gaussian channel are as follows: Under a Gaussian channel, the signal received by M-PPM in M ​​pulse time slots is: in, The pulse time slot position, Is there a flag indicating whether the pulse signal exists? M=2 n， I represents the received optical signal strength. It is Gaussian white noise with a noise power of .

3. The efficient soft demodulation method for pulse position modulation according to claim 2, characterized in that, The direct soft demodulation process of the Gaussian channel is as follows: M-PPM uses direct soft demodulation based on the maximum likelihood criterion. The LLR is: in, The pulse modulation time slot position is The received signal, I is the received optical signal strength, and the noise power is... , In M-PPM modulation symbols The pulse time slot position; Using the max-log approximation formula The simplified LLR can be obtained as: in, In M-PPM modulation symbols The maximum value of all pulse position calculation results; Considering M-PPM The soft-value calculation formula contains approximations, leading to performance loss in subsequent decoding. An adjustable scaling factor is added to the formula: scaling factor , It can be optimized through AI training.

4. The efficient soft demodulation method for pulse position modulation according to claim 3, characterized in that, The soft demodulation process of the Gaussian channel demodulation decoding iteration is as follows: During joint demodulation and decoding, the demodulation bits The probabilities of being 0 and 1 are not equal, and the extrinsic likelihood ratio can be obtained through iterative soft decoding. Then they can unite ,get The first way to represent probability: Multiply the numerator and denominator of the above equation by respectively , can be obtained The second way to represent probability: Based on external information likelihood ratio and The first way to represent probability is to obtain M-PPM bits. The posterior LLR is: in, for pulse position, Pulse position The k-th bit, the unit impulse function . Using the max-log approximation formula The simplified posterior LLR is obtained as follows: The input decoding soft demodulation LLR is: Based on external information likelihood ratio and The second representation of probability, for the soft demodulation LLR of input decoding, is: in, It is a symbolic function.

5. The efficient soft demodulation method for pulse position modulation according to claim 1, characterized in that, Within the Poisson channel, let the average number of photoelectrons of the pulsed light signal and the ambient light be respectively... and Then the number of photons received in M ​​time slots The probability is: in, , .

6. The efficient soft demodulation method for pulse position modulation according to claim 5, characterized in that, The direct soft demodulation process of the Poisson channel is as follows: M-PPM uses direct soft demodulation based on the maximum likelihood criterion. The LLR is: Similarly, using the max-log approximation formula The simplified posterior LLR is obtained as follows: At the same time, an adjustable scaling factor is added to the formula: scaling factor , It can be optimized through AI training.

7. The efficient soft demodulation method for pulse position modulation according to claim 6, characterized in that, The soft demodulation process of the demodulation-decoding iterative processing of the Poisson channel is as follows: make The soft demodulation LLR for input decoding under a Poisson channel is obtained as follows: 。 8. The efficient soft demodulation method for pulse position modulation according to claim 1, characterized in that, The pre-established soft demodulation model based on the maximum a posteriori and maximum likelihood criteria is as follows: Based on the Maximum A posteriori (MAP) criterion, LLR is defined as follows: Where y represents the received signal and H represents the channel. Let the modulation bit be... If the probabilities of 0 and 1 are equal, then the LLR based on the maximum likelihood (ML) criterion can be obtained: 。 9. A high-efficiency soft demodulation system suitable for pulse position modulation, employing the high-efficiency soft demodulation method suitable for pulse position modulation as described in any one of claims 1 to 8, characterized in that, include: The signal processing module is used to receive pulse position modulation signals and preset channel parameters, and to obtain time slot received signals based on the pulse position modulation signals. The preset channel parameters include the optical signal intensity and noise power of the Gaussian channel, and the number of electrons in the pulse optical signal and the number of electrons in the ambient light signal of the Poisson channel. The soft demodulation module is used to input the time slot received signal and preset channel parameters into a pre-established soft demodulation model based on the maximum a posteriori and maximum likelihood criteria, and output the log-likelihood ratio (LLR) of the modulation bits; wherein the LLR of the modulation bits is the logarithm of the ratio of the probability of a bit being 0 to the probability of a bit being 1.

10. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, The memory stores a computer program that can run on the processor. When the processor loads and executes the computer program, it employs an efficient soft demodulation method for pulse position modulation as described in any one of claims 1 to 8.

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