A Multi-User Signal Processing Method for Low-Earth Orbit Satellite Communication

Abstract

This invention belongs to the field of wireless communication technology, specifically relating to a multi-user signal processing method for low-Earth orbit satellite communication. The method includes: acquiring a pre-compensated digital domain hybrid signal y; arranging the standard symbol sets of N users corresponding to y into a combined symbol set of N user combined signals s according to a preset user order; iteratively calculating the likelihood probability of all possible combinations of symbols corresponding to each element in y; and calculating, in the current iteration, the transmitted signal x of user n in the hybrid signal y based on all likelihood probabilities and the prior probability of each user updated through iterative feedback. n The posterior probability of all transmitted bits being 0 is calculated; for each user's posterior probability vector obtained in the current iteration, deinterleaving and channel decoding are performed; if the iteration terminates, a decision is made and the channel-decoded probability is output; otherwise, the channel-decoded probability is used as the new prior probability for that user, and the iteration is repeated. This invention ensures demodulation bit error rate performance.

Description

Technical Field

[0001] This invention belongs to the field of wireless communication technology, and more specifically, relates to a multi-user signal processing method for low-orbit satellite communication. Background Technology

[0002] Low Earth Orbit (LEO) satellites are experiencing rapid development due to their advantages such as low orbital altitude, low construction cost, low power consumption, and short propagation delay. According to ITU satellite system rules and my country's space-ground integrated network plan, accelerating the construction of large-scale LEO satellite networks is an inevitable trend. However, with the increase in the number of LEO satellites and users, multi-satellite beams will lead to beam overlap, exacerbating inter-beam interference and significantly reducing communication quality. Moreover, compared to terrestrial mobile communication and high-orbit satellite communication, LEO satellite communication suffers from inherent defects such as limited onboard resources and high channel dynamics, resulting in severe Doppler effects, making channel state information estimation difficult, and further increasing the complexity of multi-user signal processing.

[0003] In traditional interference cancellation signal detection, Continuous Interference Cancellation (SIC) is commonly used to eliminate interference between signals. However, the SIC algorithm relies on a power difference between the signal and the interfering signal. In satellite communication systems, due to the insignificant differences in channel environments between ground users, the power of the interfering signal can be comparable to or even exceed that of the useful signal. Therefore, traditional interference cancellation schemes are unsuitable for satellite communication systems. Furthermore, while frequency reuse and precoding techniques can mitigate interference between satellites to some extent, they cannot completely suppress it, and the receiver still faces interference from many uncertainties. Additionally, iterative interference cancellation based on forward error correction coding can also alleviate interference to some degree, but it still faces challenges such as low demodulation accuracy and high computational complexity. Summary of the Invention

[0004] In view of the above-mentioned defects or improvement needs of the existing technology, the present invention provides a multi-user signal processing method for low-orbit satellite communication, the purpose of which is to ensure demodulation bit error rate performance when processing mixed signals with equivalent power received by the receiver.

[0005] To achieve the above objectives, according to one aspect of the present invention, a multi-user signal processing method for low-Earth orbit satellite communication is provided, comprising:

[0006] S1. Obtain the pre-compensated time-domain mixed signal, which is a signal formed by mixing multiple pre-compensated user signals at the receiving end; sample the digital domain mixed signal y from the time-domain mixed signal; arrange the standard symbol sets of N users corresponding to the mixed signal y into a combined symbol set of N user combined signals s according to the preset user order;

[0007] S2. Based on the mixed signal y and the corresponding low-orbit satellite channel information H for each user...n The likelihood probability of all possible combinations of symbols corresponding to each element in the mixed signal y is calculated by iterating through the signal y. The possible combinations of symbols are all possible combinations of symbols within the set of symbols.

[0008] S3. Based on the likelihood probabilities of all possible combinations of symbols corresponding to each element in the mixed signal y and the prior probabilities of each user n updated through iterative feedback, calculate the transmitted signal x of user n in the mixed signal y in the current iteration. n The posterior probabilities of all transmitted bits being 0 constitute the posterior probability vector for user n.

[0009] S4. Deinterleave the posterior probability vectors corresponding to each user n obtained in the current iteration; perform channel decoding on the deinterleaved posterior probability vectors; if the iteration termination condition is met, make a decision output on the channel-decoded probabilities to extract and separate the transmitted signal of user n in the mixed signal y; if not, use the channel-decoded probabilities as the new prior probabilities of user n, and repeat S3 to enter the next iteration.

[0010] Furthermore, the time-domain mixed signal is pre-compensated in the following way:

[0011] Based on the parameters of the low-Earth orbit satellite system and the position and elevation angle of each user, the time delay and frequency offset of the user relative to the satellite are calculated. Based on the time delay and frequency offset, the signal to be transmitted by the user is pre-compensated so that the signal to be transmitted by the user is quasi-synchronous at the satellite receiver.

[0012] Furthermore, the likelihood probability in S2 is specifically the likelihood sign probability;

[0013] Wherein, the likelihood symbol probability p(y) among all users corresponding to the i-th element in the mixed signal y is... i |s i,p )for:

[0014]

[0015] In the formula, y i s represents the i-th element in the mixed signal y; i,p This represents the p-th combination symbol corresponding to the i-th element in the combined signal s; s i,p The constituent elements in; σ 2 Indicates the power of Gaussian white noise; H represents the channel matrix of the nth user. n The i-th column.

[0016] Furthermore, in step S4, based on the Bayesian criterion, the transmitted signal x of user n in the mixed signal y is calculated. nThe posterior bit probability of all transmitted bits being 0 is specifically calculated by calculating the posterior bit probability of the q-th bit of each element of the user transmitted signal in each element of the mixed signal y being 0.

[0017] Wherein, from the i-th element y of the mixed signal y i Separate from Posterior bit probability Specifically:

[0018]

[0019] In the formula, This indicates that user n transmits signal x. n The i-th element The q-th bit; P(y) i |s i ) represents a set of combined symbols China makes The combination symbols s corresponding to the qth bit being 0 i The likelihood probability, This indicates that the prior probability information is known. What was obtained The prior sign probability, This indicates that the prior probability information is known. What was obtained The prior sign probability; Indicates for All combinations of symbols s i Other user m included transmits signal x m The i-th element.

[0020] Furthermore, S4 specifically includes:

[0021] For each user n obtained in the current iteration, the posterior bit probability vector Deinterleaving yields the deinterleaved posterior bit probability vector for user n. Where the superscript t represents the iteration number, the subscript b represents the bit, and the subscript c represents the code; the posterior bit probability vector is expressed in the form of bit probabilities. Perform bit probability channel decoding; if the iteration termination condition is met, make a decision output on the bit probability after channel decoding to realize the extraction and separation of the transmitted signal of user n in the mixed signal y; if the iteration termination condition is not met, use the bit probability after channel decoding as the new prior probability of user n, and repeat S3 to enter the next iteration.

[0022] According to another aspect of the present invention, a low-Earth orbit satellite receiver is provided, which extracts and separates the mixed signals of each user on the same resource block from the received mixed signal by executing a low-Earth orbit satellite communication multi-user signal processing method as described above.

[0023] According to another aspect of the present invention, an electronic device is provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of the method described above.

[0024] According to another aspect of the invention, a computer-readable storage medium is provided, the computer-readable storage medium including a stored computer program, wherein, when the computer program is run by a processor, it controls the device where the storage medium is located to perform the steps of the method described above.

[0025] In summary, compared with the prior art, the technical solutions conceived by this invention have the following main advantages:

[0026] 1. A multi-user signal processing method for low-Earth orbit satellites according to the present invention acquires a pre-compensated time-domain mixed signal, which is a signal formed by mixing multiple pre-compensated user signals at the receiving end. The number of mixed users is determined based on the energy intensity of the time-domain mixed signal. Then, a combined symbol set of the mixed signal is constructed according to the number of mixed users in a preset order. The likelihood probability corresponding to each element in the symbol set is solved using the received signal and channel information output by the channel estimation module. After obtaining the likelihood probability, the posterior probability of each user signal is solved one by one by combining the prior probability of each user. The solved posterior probabilities are subjected to bit-channel decoding. After decoding, it is determined whether the termination iteration condition is met. If it is met, the iteration is exited, and the bit probabilities of each user signal after decoding are determined as bits and output to obtain the final output signal. If the termination condition is not met, the decoded signal is re-interleaved as the prior probability of the user signal, and the next iteration begins. This invention solves the likelihood probability of a mixed signal by combining symbols, and then uses the likelihood probability of the mixed signal and the prior probability in parallel to solve the posterior probability of a multi-user signal. Finally, it uses soft-input soft-output iterative detection to detect and correct erroneous bits that may occur during demodulation, which can significantly reduce the mutual influence between signals and improve the detection efficiency of mixed signals.

[0027] 2. In decoding mixed signals, the log-likelihood ratio (LLR) calculation process for solving the posterior probability of multi-user signals is very complex. This invention replaces the LLR with bit probability, which reduces a large number of logarithmic operations when calculating the bit probabilities of multiple signals at the same time, thus reducing the complexity of multi-user signal detection. Attached Figure Description

[0028] Figure 1 This is a flowchart of a multi-user signal processing method for low-Earth orbit satellite communication provided in an embodiment of the present invention;

[0029] Figure 2 This is a model diagram of a low-Earth orbit satellite communication system provided in an embodiment of the present invention;

[0030] Figure 3 This is a simulation diagram comparing the bit error rate performance provided in the embodiments of the present invention;

[0031] Figure 4 This is a block diagram of a low-orbit satellite receiver for multi-user signal processing provided in an embodiment of the present invention. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0033] Example 1

[0034] A multi-user signal processing method for low-Earth orbit satellite communication, such as Figure 1 As shown, it includes:

[0035] S1. Obtain the pre-compensated time-domain mixed signal, which is a signal formed by mixing multiple pre-compensated user signals at the receiving end; sample the digital domain mixed signal y from the time-domain mixed signal; arrange the standard symbol sets of N users corresponding to the mixed signal y into a combined symbol set of N user combined signals s according to the preset user order;

[0036] S2. Based on the mixed signal y and its corresponding low-orbit satellite channel information H of each user. n The likelihood probability of all combinations of symbols among all user signals corresponding to each element in the mixed signal y is calculated by iterating through the signal y. The "all combinations of symbols" refers to all combinations of symbols within the set of symbols.

[0037] S3. Based on the likelihood probabilities of all combinations of symbols among all user signals corresponding to each element in the mixed signal y and the prior probability of each user n updated through iterative feedback, calculate the signal x transmitted by user n separated from the mixed signal y in the current iteration. n The posterior probabilities of the q-th bit being 0 for all elements constitute the posterior probability vector for user n.

[0038] S4. Deinterleave the posterior probability vectors corresponding to each user n obtained in the current iteration; perform channel decoding on the deinterleaved posterior probability vectors; if the iteration termination condition is met, make a decision output on the channel-decoded probabilities to extract and separate the transmitted signal of user n in the mixed signal y; if not, use the channel-decoded probabilities as the new prior probabilities of user n, and repeat S3 to enter the next iteration.

[0039] In S1, the N user combined signals s can be represented as s = {x1 … x N Each vector x represents any transmitted signal of the corresponding user. Furthermore, the number N of mixed users can be determined based on the energy intensity of the received signal after pre-compensation, such as... Figure 2 A model of a low-Earth orbit satellite communication system is shown.

[0040] Mixed signal Among them, H n This represents the channel state information matrix corresponding to user n, where n represents additive white Gaussian noise, N represents the total number of users corresponding to the mixed signal, and x n This represents the transmitted signal of the nth user. Let signal x... n standard symbol set The combined symbol set of the combined signal s is obtained by combining them in a certain order. Among them, the set of combined symbols The construction method is

[0041] This embodiment retains the likelihood probabilities corresponding to all combined symbols when calculating the likelihood probability of the mixed signal, and then fully utilizes the likelihood probabilities of all combined symbols when solving the posterior probability for each user. That is, it preserves complete signal information during the calculation process, reduces information loss due to decision-making, and improves detection accuracy. Furthermore, the iterative processes S3 and S4 described above are performed synchronously for each user.

[0042] As a preferred implementation, the aforementioned time-domain mixed signal is pre-compensated in the following manner:

[0043] Based on the parameters of the low-Earth orbit satellite system and the position and elevation angle of each user, the time delay and frequency offset of the user relative to the satellite are calculated. Based on the time delay and frequency offset, the signal to be transmitted by the user is pre-compensated so that the signal to be transmitted by the user is quasi-synchronous at the satellite receiver.

[0044] Low Earth Orbit (LEO) satellite system parameters include satellite orbital altitude h. hight Satellite orbital speed v, number of antennas M configured on the satellite, etc.

[0045] User n's position is w n =(w n,x ,wn,y The propagation delay and Doppler effect of user n are calculated as follows:

[0046]

[0047] Where c is the speed of light, f n Let n be the center frequency of user n, and v be the satellite's velocity.

[0048] As a preferred embodiment, the likelihood probability in S2 is specifically the likelihood sign probability;

[0049] Wherein, the likelihood symbol probability p(y) among all users corresponding to the i-th element in the mixed signal y is... i |s i,p )for:

[0050]

[0051] In the formula, y i s represents the i-th element in the mixed signal y; i,p This represents the p-th combination symbol corresponding to the i-th element in the combined signal s; s i,p The constituent elements in; σ 2 Indicates the power of Gaussian white noise; H represents the channel matrix of the nth user. n The i-th column.

[0052] Iterate through all possible combinations of symbols for each element in the mixed signal y to calculate the likelihood probability of all possible combinations of symbols for each element in the mixed signal y and store it in an array.

[0053] This implementation does not use the maximum likelihood probability method when calculating the likelihood symbol probability. Instead, it retains the likelihood symbol probabilities corresponding to all combined symbols for calculating the posterior bit probability. This helps to reduce information loss during the decision process, make full use of all received information, reduce information loss caused by the decision, and improve detection accuracy. In particular, when the power of multiple signals is similar, the signals are very likely to interfere with each other and lead to incorrect decisions.

[0054] As a preferred implementation, in S4, the user n transmitted signal x is calculated from the mixed signal y based on the Bayesian criterion. n The posterior bit probability of all elements having the q-th bit as 0 is specifically calculated by separating the posterior bit probability of each user's transmitted signal corresponding to each element from each element of the mixed signal y having the q-th bit as 0.

[0055] Wherein, from the i-th element y of the mixed signal y i Separate from Posterior bit probability Specifically:

[0056]

[0057] In the formula, This indicates that user n transmits signal x. n The i-th element The q-th bit; P(y) i |s i ) represents a set of combined symbols China makes The combination symbols s corresponding to the qth bit being 0 i The likelihood probability, This indicates that the prior probability information is known. What was obtained The prior sign probability, This indicates that the prior probability information is known. What was obtained The prior sign probability; Indicates for All combinations of symbols s i Other user m included transmits signal x m The i-th element.

[0058] To avoid redundant calculations and save computational costs, the posterior bit probabilities of N users are... The calculations can be performed simultaneously.

[0059] In this implementation, a multi-user signal parallel processing method is adopted in the mixed signal processing process. When solving the posterior probability, the mutual influence between multi-user signals (i.e. the likelihood probability of all combined symbols) is considered at the same time. This can avoid the error propagation problem caused by excessive signal power between multiple users and greatly reduce the bit error rate of mixed signal demodulation.

[0060] Define bit probability as follows: The probability of bit b0 being 0 is p(b0 = 0), and the probability of bit b0 being 1 is 1-p(b0 = 0). Similarly, the probability of bit b0 being 1 is also defined as p(b0 = 1), and the probability of bit b0 being 0 is 1-p(b0 = 1).

[0061] Specifically, during the initialization iteration, it is assumed that the probabilities of 0 bits and 1 bits are equal, that is, the prior bit probabilities are all 0.5. The prior symbol probabilities are also equal for each symbol and can be calculated from the prior bit probabilities. Bit probabilities and symbol probabilities can be converted into each other.

[0062] As a preferred implementation method, S4 specifically includes:

[0063] For each user n obtained in the current iteration, the posterior bit probability vector Deinterleaving yields the deinterleaved posterior bit probability vector for user n. Where the superscript t represents the iteration number, the subscript b represents the bit, and the subscript c represents the code; the posterior bit probability vector is expressed in the form of bit probabilities. Perform bit probability channel decoding; if the iteration termination condition is met, make a decision output on the bit probability after channel decoding to realize the extraction and separation of the transmitted signal of user n in the mixed signal y; if the iteration termination condition is not met, use the bit probability after channel decoding as the new prior probability of user n, and repeat S3 to enter the next iteration.

[0064] When decoding mixed signals, the calculation of the log-likelihood ratio (LLR) for simultaneous processing of multiple user signals is very complex. Replacing the LLR with bit probabilities reduces a large number of logarithmic operations when calculating the bit probabilities of multiple signals at the same time, thus reducing the complexity of multi-user signal detection.

[0065] In this preferred embodiment, the operations of deinterleaving, channel decoding, and interleaving all involve bit probabilities. The aforementioned bit decision is also in bit probability form. If the bit probability is defined as the probability that a bit is 0, then the decision method is to classify it as 0 if the bit probability is greater than 0.5, and otherwise as 1. Correspondingly, if the bit probability is defined as the probability that a bit is 1, then the decision method is to classify it as 1 if the bit probability is greater than 0.5, and otherwise as 0.

[0066] In this embodiment, when decoding mixed signals in S4, the soft-input soft-output (SISO) iterative detection method of channel coding is adopted. SISO iterative detection can make full use of bit information and reduce the performance loss caused by hard decision. At the same time, the error correction function of channel coding can correct the bit that has made an error and improve the bit error rate performance. Then, the algorithm converges through iteration to obtain the best bit error rate performance.

[0067] Figure 3 This is a simulation diagram of the bit error rate performance of the method in this embodiment of the invention when processing multi-user signals from low-Earth orbit satellites. It takes a two-user signal mixture as an example, where the power ratios of the two user signals are 1:1 and 2:1, respectively. Figure 3 In the diagram, the horizontal axis represents the signal-to-noise ratio (SNR) in dB, and the vertical axis represents the bit error rate (BER). Figure 3 The left figure shows the bit error rate and signal-to-noise ratio relationship of the detection method proposed in this invention and existing detection methods when the signal power ratio is 1:1. Figure 3The right figure shows the bit error rate and signal-to-noise ratio relationship of the method in the embodiment of the present invention and the existing detection method when the signal power ratio is 2:1. The parameters in the method of the embodiment of the present invention are set as follows: (N r N t Mod) = (16, 16, 4), where N r N represents the number of receiving antennas. t The number of transmit antennas is represented by , and Mod represents the modulation base, which is QPSK modulation in this case. Polar coding is used, with a code length of N = 1024 and a code rate of 1 / 2. Simulation results show that the traditional MMSE-SIC algorithm completely fails when the signal power ratio is 1:1. It can demodulate strong power signals at a signal power ratio of 2:1, but cannot demodulate weak power signals. In this scenario, the method in this embodiment of the invention achieves a performance gain of over 6dB compared to symbol enumeration (SE), and approximately 2dB compared to the soft-input soft-output (Soft-SE) method. Furthermore, it still achieves a bit error rate performance similar to that of strong signals for weak signals. Therefore, the method in this embodiment of the invention has good decoding performance for multi-user mixed signals with different transmit powers and can effectively handle the problem of multi-type user data aliasing under high mobility and wide coverage of low-Earth orbit satellites. Moreover, it is clear that the method in this embodiment of the invention has the same applicability to other communication scenarios that generate stacked data, which will not be elaborated further here.

[0068] Example 2

[0069] A low-Earth orbit (LEO) satellite receiver, by executing a LEO satellite communication multi-user signal processing method as described above, can extract and separate the mixed signals of each user on the same resource block from the received mixed signal.

[0070] like Figure 4 As shown, the low-orbit satellite receiver may include a combined symbol set construction module, a combined symbol likelihood probability solution module, a mixed signal decomposition module, a bit deinterleaving module, a bit channel decoding module, a bit interleaving module, a loop module, and a bit decision and output module.

[0071] The system comprises several modules: a combined symbol set construction module for receiving data, a combined symbol set for the received data, a combined symbol set for all user standard symbols in a specific order based on the energy intensity of the received signal, and a combined symbol set for all user standard symbol sets. A combined symbol likelihood probability calculation module calculates the likelihood bit probability of the combined symbols. Based on the received mixed signal and corresponding channel information, it calculates the likelihood symbol probability for each combined symbol in the combined symbol set and stores the data in an array. A mixed signal decomposition module updates the prior bit probability of the user signals based on iterative feedback. It decomposes the mixed signals one by one according to the combination order of the mixed signals and updates the posterior bit probability of each user signal. A deinterleaving module deinterleaves the posterior bit probabilities of the user signals; the input and output of the deinterleaver are both in bit probability form. A channel decoding module decodes the bit probabilities of the deinterleaved signals using a soft-input soft-output (SISO) decoder. The input and output of the bit-channel decoding module are both in bit probability form. During the decoding process, the calculation of likelihood information (LLR) needs to be changed to bit probability calculation. The interleaving module interleaves the decoded bit probabilities; both the interleaver's input and output are in bit probability form. The looping module iteratively executes the posterior bit probability update module, deinterleaving module, decoding module, and interleaving module until a set number of iterations is reached. The bit decision and output module determines the output bit probability as a bit. Based on the definition of bit probability, it outputs the bit. If the bit probability is defined as the probability that the bit is 0, the decision method is to output 0 if the bit probability is greater than 0.5, and 1 otherwise. Similarly, if the bit probability is defined as the probability that the bit is 1, the decision method is to output 1 if the bit probability is greater than 0.5, and 0 otherwise.

[0072] The relevant technical solutions are the same as above, and will not be repeated here.

[0073] Example 3

[0074] An electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method described above.

[0075] The electronic device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The processor can 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. The memory can be used to store computer programs and / or modules. The processor performs various functions of the electronic device by running or executing the computer programs and / or modules stored in the memory, and by accessing data stored in the memory.

[0076] The relevant technical solutions are the same as above, and will not be repeated here.

[0077] Example 4

[0078] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described above.

[0079] Specifically, the memory may include high-speed random access memory, as well as non-volatile memory, such as hard disks, RAM, plug-in hard disks, smart media cards (SMC), secure digital cards (SD), flash cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.

[0080] The relevant technical solutions are the same as above, and will not be repeated here.

[0081] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A multi-user signal processing method for low-Earth orbit satellite communication, characterized in that, include: S1. Obtain the pre-compensated time-domain mixed signal, which is a signal formed by mixing multiple pre-compensated user signals at the receiving end; A digital domain mixed signal y is obtained by sampling from the time-domain mixed signal; According to the preset user order, the standard symbol sets of N users corresponding to the mixed signal y are combined and arranged into a combined symbol set of N user combined signals s; S2. Based on the mixed signal y and the corresponding low-orbit satellite channel information H for each user... n The likelihood probability of all possible combinations of symbols corresponding to each element in the mixed signal y is calculated by iterating through the signal y. The possible combinations of symbols are all possible combinations of symbols within the set of symbols. S3. Based on the likelihood probabilities of all possible combinations of symbols corresponding to each element in the mixed signal y and the prior probabilities of each user n updated through iterative feedback, calculate the transmitted signal x of user n in the mixed signal y in the current iteration. n The posterior probabilities of all transmitted bits being 0 constitute the posterior probability vector for user n. S4. Deinterleave the posterior probability vectors corresponding to each user n obtained in the current iteration; perform channel decoding on the deinterleaved posterior probability vectors; if the iteration termination condition is met, make a decision output on the channel-decoded probabilities to extract and separate the transmitted signal of user n in the mixed signal y; if not, use the channel-decoded probabilities as the new prior probabilities of user n, and repeat S3 to enter the next iteration.

2. The low-Earth orbit satellite communication multi-user signal processing method as described in claim 1, characterized in that, The time-domain mixed signal is pre-compensated in the following way: Based on the parameters of the low-Earth orbit satellite system and the position and elevation angle of each user, the time delay and frequency offset of the user relative to the satellite are calculated. Based on the time delay and frequency offset, the signal to be transmitted by the user is pre-compensated so that the signal to be transmitted by the user is quasi-synchronous at the satellite receiver.

3. The low-Earth orbit satellite communication multi-user signal processing method as described in claim 1, characterized in that, The likelihood probability in S2 is specifically the likelihood sign probability; Wherein, the likelihood symbol probability p(y) among all users corresponding to the i-th element in the mixed signal y is... i |s i,p )for: In the formula, y i s represents the i-th element in the mixed signal y; i,p This represents the p-th combination symbol corresponding to the i-th element in the combined signal s; s i,p The constituent elements in; σ 2 Indicates the power of Gaussian white noise; H represents the channel matrix of the nth user. n The i-th column.

4. A multi-user signal processing method for low-Earth orbit satellite communication as described in any one of claims 1 to 3, characterized in that, In step S4, the user n transmitted signal x in the mixed signal y is calculated according to the Bayesian criterion. n The posterior bit probability of all transmitted bits being 0 is specifically calculated by calculating the posterior bit probability of the q-th bit of each element of the user transmitted signal in each element of the mixed signal y being 0. Wherein, from the i-th element y of the mixed signal y i middle Posterior bit probability Specifically: In the formula, This indicates that user n transmits signal x. n The i-th element The q-th bit; P(y) i |s i ) represents the set of combined symbols χ such that The combination symbols s corresponding to the qth bit being 0 i The likelihood probability, This indicates that the prior probability information is known. What was obtained The prior sign probability, This indicates that the prior probability information is known. What was obtained The prior sign probability; Indicates for All combinations of symbols s i Other user m included transmits signal x m The i-th element.

5. The low-Earth orbit satellite communication multi-user signal processing method as described in claim 4, characterized in that, Specifically, S4 is: For each user n obtained in the current iteration, the posterior bit probability vector Deinterleaving yields the deinterleaved posterior bit probability vector for user n. Where the superscript t represents the iteration number, the subscript b represents the bit, and the subscript c represents the code; the posterior bit probability vector is expressed in the form of bit probabilities. Perform bit probability channel decoding; if the iteration termination condition is met, make a decision output on the bit probability after channel decoding to realize the extraction and separation of the transmitted signal of user n in the mixed signal y; if the iteration termination condition is not met, use the bit probability after channel decoding as the new prior probability of user n, and repeat S3 to enter the next iteration.

6. A low-orbit satellite receiver, characterized in that, By implementing a low-orbit satellite communication multi-user signal processing method as described in any one of claims 1 to 5, the mixed signals of each user on the same resource block can be extracted and separated from the received mixed signals.

7. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein the computer program, when executed by a processor, controls the device on which the storage medium is located to perform the steps of the method as described in any one of claims 1 to 5.

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