Multi-beam coherent high-reliability merging method and device, electronic equipment and storage medium

Abstract

The invention provides a multi-beam coherent high-reliability merging method and device, electronic equipment and a storage medium, and relates to the technical field of satellite communication, and the method comprises the steps: carrying out the coherent receiving of a multi-path signal forwarded by a satellite, and carrying out the direct sequence spread spectrum modulation of a BPSK symbol sequence of the multi-path signal, in the wave beam overlapping area, the wave beams are sent to the satellite through equal gains of a plurality of different wave beams; based on a cross entropy optimization algorithm, united optimization is carried out on the normalized channel gains corresponding to the multiple beams, and the optimal normalized channel gain corresponding to each beam is obtained; and on the basis of the optimal normalized channel gain corresponding to each beam, weighting and combining the de-spread multi-path signals to obtain a combined signal. According to the invention, adaptive maximum-ratio combination of multiple paths of signals is realized, and the signal-to-noise ratio after signal combination can be obviously improved, so that a communication system can still maintain relatively high communication quality in a weak channel environment, the anti-interference capability and the concealment of the system are enhanced, and the reliability of a link is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of satellite communication, and in particular to a multi-beam coherent high-reliability combining method and device, electronic equipment and a storage medium. BACKGROUND

[0002] In a high-orbit satellite multi-beam communication system, the same information is simultaneously transmitted by multiple frequency beams at the sending end, and is received by a ground gateway station after being forwarded by a satellite. Multi-beam combining is a key technology for improving system performance.

[0003] The weight distribution in the existing Maximum Ratio Combining (MRC) algorithm depends on the individual estimation of each beam, and the result is easily affected by poor quality branches, resulting in a decline in signal combining performance. SUMMARY

[0004] The present application provides a multi-beam coherent high-reliability combining method and device, electronic equipment and a storage medium to solve the problem of declining signal combining performance in the prior art, and to achieve adaptive maximum ratio combining of multiple signals, thereby improving the signal-to-noise ratio at the receiving end, enhancing the system's anti-interference ability and concealment, and improving the reliability of the link.

[0005] The present application provides a multi-beam coherent high-reliability combining method, comprising: Coherently receiving a multi-path signal forwarded by a satellite, wherein the multi-path signal is a BPSK symbol sequence modulated by direct sequence spread spectrum, and is transmitted to the satellite by multiple different beams with equal gain in the beam overlap area; Based on a cross-entropy optimization algorithm, the normalized channel gains corresponding to the multiple beams are jointly optimized to obtain the optimal normalized channel gain corresponding to each beam; Based on the optimal normalized channel gain corresponding to each beam, the despread multi-path signal is weighted and combined to obtain a combined signal.

[0006] In some embodiments, the cross-entropy optimization algorithm is used to jointly optimize the normalized channel gains corresponding to the multiple beams to obtain the optimal normalized channel gain corresponding to each beam, comprising: Iteratively performing the following steps: Based on the number of binary quantization bits and the probability distribution, N C candidate binary quantized channel gains corresponding to each beam are randomly generated; The N C candidate binary quantized channel gains corresponding to each beam are normalized after being converted from binary to decimal to obtain N C candidate normalized channel gains corresponding to each beam; Based on the NC A group of candidate normalized channel gains are used to weight and combine the despread signals to obtain N C combined signals, respectively; wherein the group of candidate normalized channel gains comprises candidate normalized channel gains corresponding to the multiple beams, respectively; According to the N C combined signals, N C combined signal-to-noise ratios are obtained; The N C combined signal-to-noise ratios are sorted from large to small, and N e combined signal-to-noise ratios are selected; According to the N e combined signal-to-noise ratios, N C elite binary quantized channel gains corresponding to each beam are selected from N e candidate binary quantized channel gains corresponding to each beam; According to the N e elite binary quantized channel gains corresponding to each beam, the probability distribution is updated; If the iteration stopping condition is not met, the next iteration is performed based on the updated probability distribution; if the iteration stopping condition is met, the iteration is stopped, and the optimal normalized channel gain corresponding to each beam is obtained based on the updated probability distribution; the iteration stopping condition is that the generation probability of each bit in the updated probability distribution is 0 or 1, or the maximum iteration number is reached.

[0007] In some embodiments, the N C combined signal-to-noise ratios are obtained according to the N C combined signals, comprising: According to the mean and variance of each of the combined signals, one of the combined signal-to-noise ratios is obtained.

[0008] In some embodiments, the method further comprises: The multiple signals are respectively down-converted to obtain multiple down-converted signals.

[0009] In some embodiments, the method further comprises: The multiple down-converted signals are respectively despread according to a spread spectrum pseudo-random code to obtain multiple despread signals.

[0010] In some embodiments, the number of binary quantization bits is 5.

[0011] In some embodiments, the N e is 0.2 times the N C .

[0012] The application further provides a multi-beam coherent high-reliability combining device, comprising: A receiving module is configured to coherently receive a plurality of signals relayed by a satellite, wherein the plurality of signals are BPSK symbol sequences modulated by direct sequence spread spectrum and transmitted to the satellite by a plurality of different beams with equal gain in a beam overlap area; An optimization module is configured to jointly optimize normalized channel gains corresponding to the plurality of beams based on a cross-entropy optimization algorithm to obtain optimal normalized channel gains corresponding to each beam; A weighted combining module is configured to combine the despread plurality of signals after weighting based on the optimal normalized channel gains corresponding to each beam to obtain a combined signal.

[0013] The application further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the multi-beam coherent high-reliability combining method according to any one of the above when executing the computer program.

[0014] The application further provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program is executable on a processor to implement the multi-beam coherent high-reliability combining method according to any one of the above.

[0015] The application further provides a computer program product comprising a computer program, wherein the computer program is executable on a processor to implement the multi-beam coherent high-reliability combining method according to any one of the above.

[0016] The multi-beam coherent high-reliability combining method, device, electronic device, and storage medium provided by the application jointly optimize normalized channel gains corresponding to the plurality of beams based on a cross-entropy optimization algorithm to accurately estimate the normalized channel gains corresponding to each beam, combine the despread plurality of signals after weighting based on the optimal normalized channel gains corresponding to each beam to obtain a combined signal, and implement adaptive maximum ratio combining of the plurality of signals, which can significantly improve the signal-to-noise ratio after signal combining, enable the communication system to maintain high communication quality in a weak channel environment, enhance the anti-interference capability and concealment of the system, and improve the reliability of the link. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the application or the prior art, the following will briefly introduce the drawings needed in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative effort.

[0018] Figure 1Figure 1 is one of flow diagrams of the multi-beam coherent high-reliability combining method provided by the present application.

[0019] Figure 2 Figure 2 is another of flow diagrams of the multi-beam coherent high-reliability combining method provided by the present application.

[0020] Figure 3 Figure 3 is a principle block diagram of the multi-beam coherent high-reliability combining method provided by the present application.

[0021] Figure 4 Figure 4 is a simulation diagram of the multi-beam coherent high-reliability combining method provided by the present application.

[0022] Figure 5 Figure 5 is a structure diagram of the multi-beam coherent high-reliability combining device provided by the present application.

[0023] Figure 6 Figure 6 is a structure diagram of the electronic device provided by the present application. DETAILED DESCRIPTION

[0024] In a high-orbit satellite multi-beam communication system, the same information is simultaneously transmitted by multiple frequency beams at the sending end, and is received by a ground gateway station after being forwarded by a satellite. Due to the wide coverage of the satellite, there is an overlapping area between the beams, and the traditional technology fails to fully utilize the signal diversity characteristics of this area, resulting in limited system performance. In addition, the physical limitations of the satellite transponder and the dynamic environment lead to challenges in signal combining: the radio frequency links of different beams are inconsistent in path loss due to factors such as antenna pointing errors, differences in feed layout, and beam edge effects; the gain and phase response of different frequency channels of the satellite transponder change non-uniformly over time due to influences such as temperature drift and device aging; and the existing technology fails to effectively utilize the spatial diversity characteristics of the beam overlapping area, resulting in insufficient signal redundancy and difficulty in coping with complex interference environments.

[0025] In the traditional solution, channel gain estimation is mostly performed using the least squares (LS) or minimum mean square error (MMSE) algorithm, but there are significant defects in the satellite communication scenario: pilot insertion reduces spectral utilization, and the periodic characteristics are easily detected by the enemy, violating the requirement for covert communication; the time-varying and nonlinear characteristics of the satellite channel lead to large estimation errors of the traditional algorithm, especially in the beam overlapping area, and the signal-to-noise ratio loss can be more than 4 dB; additional spectral resources are required to transmit the pilot, reducing spectral utilization and lacking concealment; the weight allocation in the existing maximum ratio combining algorithm depends on the separate estimation of each beam, and the result is easily affected by poor-quality branches, without considering the joint optimization of multi-beam signals in the overlapping area, and the combining weight allocation is unreasonable.

[0026] In addition, the covert communication in the unlicensed frequency band requires low signal power and covert characteristics, and the existing method is difficult to achieve high-precision channel estimation and combination under the condition of low signal-to-noise ratio. Therefore, a method without pilot, adaptive to nonlinear dynamic channel, and capable of realizing maximum ratio combination is urgently needed.

[0027] To make the objectives, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below in conjunction with the drawings in the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0028] Figure 1 is one of the flowcharts of the multi-beam coherent high-reliability combination method provided by the present application, as shown in Figure 1 The present application provides a multi-beam coherent high-reliability combination method, applied to a receiving end, such as a ground gateway station, comprising: Step 110, coherently receiving the multi-path signals forwarded by the satellite, wherein the multi-path signals are BPSK symbol sequences modulated by direct sequence spread spectrum and transmitted to the satellite by multiple different beams with equal gain in the beam overlap area.

[0029] Specifically, the transmitting end transmits a binary phase shift keying (BPSK) symbol sequence with the same content and length K, which is modulated by direct sequence spread spectrum (DSSS) and transmitted to the satellite by N beams (i.e. N frequency points) with equal gain in the beam overlap area. The spatial diversity characteristics of the beam overlap area are used to improve the signal redundancy, and at the same time, the signal power in a single beam is reduced and the concealment is improved.

[0030] The satellite transponder amplifies and frequency converts the multi-path BPSK symbol sequences modulated by direct sequence spread spectrum and forwards them to the receiving end, wherein the signals in the beam overlap area form multi-path superposition due to spatial diversity. The receiving end coherently receives the multi-path signals (i.e. BPSK symbol sequences modulated by direct sequence spread spectrum) forwarded by the satellite.

[0031] Step 120, based on the cross-entropy optimization algorithm, the normalized channel gains corresponding to the multi-path beams are jointly optimized to obtain the optimal normalized channel gain corresponding to each beam.

[0032] Specifically, the normalized channel gain refers to the channel gain after normalization processing (such as division by a reference value or maximum gain), so that it becomes a dimensionless relative value (for example, in the range of (0, 1] or satisfying a power constraint). Each beam corresponds to a normalized channel gain, and for multiple beams, multiple normalized channel gains correspond.

[0033] The cross-entropy optimization algorithm is used to jointly optimize the multiple normalized channel gains corresponding to the multiple beams, to obtain the optimal normalized channel gain corresponding to each beam, that is, the dynamic channel gains of each frequency point and the overlapping region are jointly optimized by the cross-entropy optimization algorithm.

[0034] In step 130, based on the optimal normalized channel gain corresponding to each beam, the despread multiple signals are weighted and combined to obtain a combined signal.

[0035] Specifically, the despread corresponding signal is weighted using the optimal normalized channel gain corresponding to each beam to obtain a weighted result corresponding to each signal, and then all the weighted results are combined to obtain a combined signal (i.e., a BPSK symbol sequence including K combined symbols). The specific expression of the kth combined symbol in the combined signal is as follows: In the formula, indicates the kth combined symbol, indicates the kth symbol in the despread signal corresponding to the nth beam, and N indicates the number of beams, indicates the optimal normalized channel gain corresponding to the nth beam.

[0036] In time sequence, K combined symbols are obtained in turn, thereby obtaining the combined signal.

[0037] The multi-beam coherent high-reliability combining method provided by the application jointly optimizes the normalized channel gains corresponding to the multiple beams by using the cross-entropy optimization algorithm, accurately estimates the normalized channel gain corresponding to each beam, weights and combines the despread multiple signals based on the optimal normalized channel gain corresponding to each beam to obtain a combined signal, realizes adaptive maximum ratio combining of the multiple signals, can significantly improve the signal-to-noise ratio after signal combining, enables the communication system to maintain high communication quality in a weak channel environment, enhances the system anti-interference ability and concealment, and improves the reliability of the link.

[0038] In some embodiments, the multi-beam coherent high-reliability combining method provided by the application further includes: The multiple signals are respectively down-converted to obtain frequency-converted multiple signals.

[0039] Specifically, the receiving end coherently receives the multi-path signals. For a single-path signal, the expression of the kth symbol in the signal received by the nth beam of the receiving end is as follows: wherein, denotes the kth symbol in the signal received by the nth beam at time t, denotes the channel gain of the nth beam, denotes the transmitting power, denotes the spread spectrum signal corresponding to the kth symbol in the signal transmitted at time t, denotes the nth downlink frequency point forwarded by the satellite, denotes the complex additive white Gaussian noise of the nth beam at time t, obeys the complex Gaussian distribution with mean value 0 and variance , wherein is the standard deviation of , used to measure the amplitude intensity of the noise.

[0040] The receiving end respectively down-converts the multi-path signals to obtain the down-converted multi-path signals. For a single-path signal, the expression of the kth symbol in the down-converted signal corresponding to the nth beam is as follows: wherein, wherein, denotes the kth symbol in the down-converted signal corresponding to the nth beam received at time t, denotes the kth symbol in the signal corresponding to the nth beam received at time t, denotes the nth downlink frequency point forwarded by the satellite, denotes the channel gain of the nth beam, denotes the transmitting power, denotes the spread spectrum signal corresponding to the kth symbol in the signal transmitted at time t, denotes the complex additive white Gaussian noise of the nth beam at time t, denotes the complex additive white Gaussian noise of the down-converted nth beam at time t.

[0041] Since is the complex additive white Gaussian noise, the phase thereof is irrelevant to , thus, is still the zero-mean Gaussian white noise, i.e. obeys the complex Gaussian distribution with mean value 0 and variance .

[0042] The multi-beam coherent high-reliability combining method provided by the application comprises the following steps.

[0043] In some embodiments, the multi-beam coherent high-reliability combining method further comprises: According to the spread spectrum pseudo-random code, the multi-channel signals after frequency conversion are respectively despread to obtain despread multi-channel signals.

[0044] Specifically, the despread is performed on the single-channel signals after frequency conversion according to the spread spectrum pseudo-random code, that is, the spread spectrum pseudo-random code is multiplied by the single-channel signals after frequency conversion and is integrated to obtain the despread single-channel signals.

[0045] In the formula, denotes the kth symbol in the despread signal corresponding to the nth beam, denotes the kth symbol in the signal after frequency conversion corresponding to the nth beam received at time t, denotes the spread spectrum pseudo-random code at time t, denotes the chip period, denotes the channel gain of the nth beam, denotes the transmission power, denotes the spread spectrum signal corresponding to the kth symbol in the signal transmitted at time t, denotes the complex additive white Gaussian noise of the nth beam after frequency conversion at time t.

[0046] The multi-beam coherent high-reliability combining method provided by the application removes the spread spectrum modulation applied by the transmitting end through despread by the spread spectrum pseudo-random code, thereby extracting the narrowband original data signal.

[0047] In some embodiments, Figure 2 is a flowchart two of the multi-beam coherent high-reliability combining method provided by the application, as shown in Figure 2 Based on the cross-entropy optimization algorithm, the normalized channel gains corresponding to the multi-channel beams are jointly optimized to obtain the optimal normalized channel gain corresponding to each beam, comprising: Step 210, based on the binary quantization bit number and the probability distribution, randomly generating N C candidate binary quantized channel gains corresponding to each beam.

[0048] Specifically, the initial probability distribution in the cross-entropy iteration is predefined , each beam corresponds to a probability, the binary quantization bit number D, and the number N CAnd the number N of elite normalized channel gains e N e It is less than N C Positive integers.

[0049] In some embodiments, the binary quantization bits are 5, N e For N C 0.2 times.

[0050] Specifically, experimental verification shows that when the binary quantization bits are 5 and N, e For N C With a time complexity of 0.2 times that of the previous algorithm, the algorithm has low complexity and good iterative convergence.

[0051] In the i-th iteration, based on the binary quantization bit depth D and the probability corresponding to each beam... Randomly generate N corresponding to each beam C There are N candidate binary quantized channel gains, each candidate binary quantized channel gain is composed of D bits of binary encoding, and the N corresponding to the nth beam. C The channel gain expressions for the candidate binary quantizations are as follows: In the formula, Represents the nth beam. Channel gain of candidate binary quantization ( ), Represents the nth beam. The channel gain of the nth candidate binary quantization Bit binary value ( ).

[0052] Step 220, for each beam corresponding to N C The channel gain of each candidate binary quantization is normalized after binary-to-decimal conversion to obtain N for each beam. C One candidate normalized channel gain.

[0053] Specifically, for each beam, for N C The channel gain of each candidate binary quantization is normalized after binary-to-decimal conversion, that is, the binary code is converted back to the actual value, to obtain N. C One candidate normalized channel gain.

[0054] No. The expressions for the candidate normalized channel gain are as follows: In the formula, Represents the nth beam. One candidate normalized channel gain, denotes the number of binary quantization bits, denotes the kth binary value in the channel gain of the nth beam,

[0055] For example, the number of binary quantization bits is 4, is 0101, then is 0.667.

[0056] Step 230, based on the N C group of candidate normalized channel gains, the despread multi-path signals are weighted and combined to obtain N C combined signals; wherein a group of candidate normalized channel gains includes candidate normalized channel gains corresponding to multi-beams respectively.

[0057] Specifically, each beam corresponds to N C candidate normalized channel gains, the candidate normalized channel gains corresponding to N beams form a matrix H, the number of rows of the matrix H is , the number of columns of the matrix H is N, each column of the matrix H is N C candidate normalized channel gains corresponding to a beam, and the expression of the matrix H is as follows: Taking N candidate normalized channel gains in each row of the matrix H as a group, there are N C groups of candidate normalized channel gains, and each group of candidate normalized channel gains includes candidate normalized channel gains corresponding to N beams.

[0058] Taking a group of candidate normalized channel gains as a unit, based on each group of candidate normalized channel gains, the despread multi-path signals are weighted and combined to obtain a combined signal, and N C groups of candidate normalized channel gains can obtain N C combined signals.

[0059] The expression of the kth symbol in the nth signal is as follows: In the formula, denotes the kth symbol in the nth combined signal, denotes the kth candidate normalized channel gain of the nth beam, denotes the kth symbol in the despread signal corresponding to the nth beam, denotes the kth symbol in the despread signal corresponding to the nth beam, denotes the kth symbol in the despread signal corresponding to the nth beam,

[0060] Step 240, according to N C ​​​N C merging SNRs.

[0061] Specifically, SNR evaluation is performed on each of the N C merging SNRs. C merging SNRs.

[0062] Step 250, the N C merging SNRs are sorted in descending order, and the N e merging SNRs are selected.

[0063] Step 260, according to the N e merging SNRs, from the N C candidate binary quantized channel gains corresponding to each beam, N e elite binary quantized channel gains corresponding to each beam are selected.

[0064] Specifically, according to the position of the N e merging SNRs in the N C merging SNRs, from the N C candidate binary quantized channel gains corresponding to each beam, N e elite binary quantized channel gains corresponding to each beam are selected.

[0065] Step 270, according to the N e elite binary quantized channel gains corresponding to each beam, the probability distribution is updated. Specifically, the expression of the updated probability corresponding to the nth beam is as follows: In the formula, denotes the updated probability corresponding to the nth beam, denotes the N th elite binary quantized channel gain corresponding to the nth beam. .

[0066] According to the updated probabilities corresponding to all beams, the updated probability distribution is obtained.

[0067] Step 280, it is judged whether the generation probability of each bit in the updated probability distribution is 0 or 1, or whether the maximum iteration number is reached.

[0068] Specifically, it is judged whether the generation probability of each bit in the updated probability distribution is 0 or 1 (i.e. Each bit is 0 or 1, or the maximum number of iterations is reached as the iteration stopping condition. If the iteration stopping condition is met, the iteration is stopped, and step 290 is performed. If the iteration stopping condition is not met, the updated probability distribution is taken as the probability distribution of the next iteration, and the next iteration is performed, i.e., step 210 is performed again based on the updated probability distribution.

[0069] In step 290, the optimal normalized channel gain corresponding to each beam is obtained based on the updated probability distribution.

[0070] Specifically, the optimal binary quantized channel gain corresponding to each beam is generated according to the updated probability distribution and the number of binary quantization bits, and the optimal binary quantized channel gain corresponding to each beam is normalized to obtain the optimal normalized channel gain corresponding to each beam.

[0071] The multi-beam coherent high-reliability combining method provided by the application can adaptively approximate the optimal channel gain combination by iteratively generating, evaluating and screening candidate normalized channel gains, does not need to rely on accurate initial models or prior knowledge, and is suitable for dynamic channel environment. Meanwhile, the channel gains of multiple beams are optimized, and the overall SNR of the combined signal is improved through cooperative processing, which is better than the scheme of independently optimizing a single beam.

[0072] In some embodiments, according to N C combined signals, N C combined signal-to-noise ratios are obtained, including: According to the mean and variance of each combined signal, one combined signal-to-noise ratio is obtained.

[0073] Specifically, each combined signal includes K combined BPSK symbols, the mean and variance of the K combined BPSK symbols are calculated to obtain the mean and variance of each combined signal. According to the mean and variance of each combined signal, one combined signal-to-noise ratio is obtained.

[0074] The expression of the N th combined signal-to-noise ratio is as follows: In the formula, denotes the N th combined signal-to-noise ratio, denotes the kth combined BPSK symbol in the N th combined signal, denotes taking the mean, denotes taking the variance, and K denotes the number of BPSK symbols included in the combined signal.

[0075] The multi-beam coherent high-reliability combining method provided by the application realizes fast evaluation of the combining signal-to-noise ratio through the mean value and variance of each combining signal.

[0076] Figure 3 is the principle block diagram of the multi-beam coherent high-reliability combining method provided by the application, based on the candidate normalized channel gain, the multi-path signals are weighted and maximum ratio combined to obtain a combining signal; taking the signal-to-noise ratio estimation as a target function, the optimal normalized channel gain is output through cross-entropy iteration.

[0077] Figure 4 is the simulation schematic diagram of the multi-beam coherent high-reliability combining method provided by the application, as shown in Figure 4 , the horizontal axis is the signal-to-noise ratio E b / N0 (dB), E b is the energy of a single symbol, N0 is the noise energy, the vertical coordinate is the bit error rate (BER), the block represents the basic signal, the triangle represents the cross-entropy combining of two-way beam signals (CE Combine-2), the solid point represents the cross-entropy combining of three-way beam signals (CE Combine-3), and the hollow point represents the cross-entropy combining of four-way beam signals (CE Combine-4). As can be seen from Figure 4 , with the increase of the number of beams, the combining performance of the multi-path signals is better.

[0078] Figure 5 is the structural schematic diagram of the multi-beam coherent high-reliability combining device provided by the application, as shown in Figure 5 , the application provides a multi-beam coherent high-reliability combining device, which comprises: a receiving module 510, configured to coherently receive a multi-path signal forwarded by a satellite, wherein the multi-path signal is a BPSK symbol sequence modulated by direct sequence spread spectrum, and transmitted to the satellite by multiple different beams with equal gain in a beam overlap area; an optimization module 520, configured to jointly optimize the normalized channel gains corresponding to the multiple beams based on a cross-entropy optimization algorithm to obtain the optimal normalized channel gain corresponding to each beam; a weighted combining module 530, configured to weight and combine the despread multi-path signals based on the optimal normalized channel gain corresponding to each beam to obtain a combining signal.

[0079] In some embodiments, the optimization module 520 has functions for: iteratively performing the following steps: based on the number of binary quantization bits and the probability distribution, randomly generating N C candidate binary quantized channel gains corresponding to each beam; N C candidate binary quantized channel gains corresponding to each beam are normalized after being converted from binary to decimal, to obtain N C candidate normalized channel gains corresponding to each beam; Based on the N C candidate normalized channel gains, the despread signals are weighted and combined to obtain N C combined signals, wherein a group of candidate normalized channel gains includes candidate normalized channel gains corresponding to beams respectively; According to the N C combined signals, N C combined signal-to-noise ratios are obtained; The N C combined signal-to-noise ratios are sorted from large to small, and N e combined signal-to-noise ratios are selected; According to the N e combined signal-to-noise ratios, N C elite binary quantized channel gains corresponding to each beam are selected from N e candidate binary quantized channel gains corresponding to each beam; According to the N e elite binary quantized channel gains corresponding to each beam, the probability distribution is updated; If the iteration stopping condition is not met, the next iteration is performed based on the updated probability distribution; if the iteration stopping condition is met, the iteration is stopped, and the optimal normalized channel gain corresponding to each beam is obtained based on the updated probability distribution; the iteration stopping condition is that the generation probability of each bit in the updated probability distribution is 0 or 1, or the maximum iteration number is reached.

[0080] In some embodiments, the optimization model is further specifically used for: According to the mean and variance of each combined signal, a combined signal-to-noise ratio is obtained.

[0081] In some embodiments, the device further comprises: A down-conversion module is configured to down-convert the multiple signals respectively to obtain multiple frequency-converted signals.

[0082] In some embodiments, the device further comprises: A despreading module is configured to despread the multiple frequency-converted signals respectively according to a spreading pseudo-random code to obtain multiple despread signals.

[0083] In some embodiments, the number of binary quantization bits is 5.

[0084] In some embodiments, the N e is 0.2 times the N C .

[0085] It should be noted that the above multi-beam coherent high-reliability combining device provided by the present application can realize all the method steps realized by the above method embodiments and achieve the same technical effects, and the same parts and beneficial effects in the present embodiment as the method embodiments will not be described in detail.

[0086] Figure 6 is a structural schematic diagram of an electronic device provided by the present application, as Figure 6 shown, the electronic device can include a processor (processor) 610, a communications interface (Communications Interface) 620, a memory (memory) 630 and a communications bus 640, wherein the processor 610, the communications interface 620, the memory 630 complete the communication between each other through the communications bus 640. The processor 610 can call the logic instructions in the memory 630 to execute the multi-beam coherent high-reliability combining method, which includes: coherently receiving the multi-channel signal relayed by the satellite, the multi-channel signal is a BPSK symbol sequence after direct sequence spread spectrum modulation, and is sent to the satellite through multiple different beams with equal gain in the beam overlap area; based on the cross entropy optimization algorithm, the normalized channel gain corresponding to each beam is jointly optimized to obtain the optimal normalized channel gain corresponding to each beam; based on the optimal normalized channel gain corresponding to each beam, the despread signal is weighted and combined to obtain a combined signal.

[0087] In addition, the logic instructions in the above-mentioned memory 630 can be realized in the form of a software functional unit and sold or used as an independent product, which can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product, and the computer software product stored in a storage medium includes a plurality of instructions for making a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0088] In another aspect, the present application also provides a computer program product comprising a computer program, which can be stored on a non-transitory computer-readable storage medium, and the computer program can be executed by a processor to enable a computer to perform the multi-beam coherent high-reliability combining method provided by the above-mentioned methods, which comprises: coherently receiving a plurality of signals forwarded by a satellite, the plurality of signals being BPSK symbol sequences modulated by direct sequence spread spectrum and transmitted to the satellite by a plurality of different beams with equal gain in a beam overlap area; based on a cross-entropy optimization algorithm, jointly optimizing normalized channel gains corresponding to the plurality of beams respectively to obtain optimal normalized channel gains corresponding to each beam; and based on the optimal normalized channel gains corresponding to each beam, weighting and combining the despread plurality of signals to obtain a combined signal.

[0089] In another aspect, the present application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and the computer program can be executed by a processor to implement the multi-beam coherent high-reliability combining method provided by the above-mentioned methods, which comprises: coherently receiving a plurality of signals forwarded by a satellite, the plurality of signals being BPSK symbol sequences modulated by direct sequence spread spectrum and transmitted to the satellite by a plurality of different beams with equal gain in a beam overlap area; based on a cross-entropy optimization algorithm, jointly optimizing normalized channel gains corresponding to the plurality of beams respectively to obtain optimal normalized channel gains corresponding to each beam; and based on the optimal normalized channel gains corresponding to each beam, weighting and combining the despread plurality of signals to obtain a combined signal.

[0090] The device embodiments described above are merely illustrative, wherein the units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, i.e., they can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment scheme according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0091] From the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be implemented by means of software plus necessary general hardware platforms, and of course can also be implemented by hardware. Based on such understanding, the above technical solutions can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform the methods described in the embodiments or some parts of the embodiments.

[0092] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit the present application; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced by equivalent features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A multi-beam coherent high-reliability combining method, characterized in that, The method comprises the following steps: coherently receiving a plurality of signals forwarded by a satellite, the plurality of signals being BPSK symbol sequences modulated by direct sequence spread spectrum and transmitted to the satellite by a plurality of different beams with equal gain in a beam overlap area; based on a cross-entropy optimization algorithm, jointly optimizing normalized channel gains corresponding to the plurality of beams respectively to obtain optimal normalized channel gains corresponding to each beam; based on the optimal normalized channel gains corresponding to each beam, weighting and combining the plurality of signals after despreading to obtain a combined signal; the step of jointly optimizing the normalized channel gains corresponding to the plurality of beams respectively based on the cross-entropy optimization algorithm to obtain the optimal normalized channel gains corresponding to each beam comprises the following steps: iteratively performing the following steps: Based on the number of binary quantization bits and the probability distribution, N C candidate binary quantized channel gains corresponding to each beam pair are randomly generated; N C candidate binary quantized channel gains corresponding to each beam pair are normalized after being converted from binary to decimal to obtain N C candidate normalized channel gains corresponding to each beam pair; Based on N C A set of candidate normalized channel gains are used to weight and combine the despread signals to obtain N C combined signals, respectively; wherein the set of candidate normalized channel gains includes candidate normalized channel gains corresponding to the multiple beams, respectively. According to N C combining signals, N C combined signal-to-noise ratios are obtained; The N C The N e The N According to the N e merging signal-to-noise ratios, from each beam corresponding to N C candidate binary quantized channel gains, select N e elite binary quantized channel gains corresponding to each beam. According to N e elite binary quantized channel gains corresponding to each beam, update the probability distribution; if the iteration stop condition is not met, performing the next iteration based on the updated probability distribution; if the iteration stop condition is met, stopping the iteration and obtaining the optimal normalized channel gains corresponding to each beam based on the updated probability distribution; the iteration stop condition is that the generation probability of each bit in the updated probability distribution is 0 or 1, or the maximum iteration number is reached.

2. The method of claim 1, wherein, The method according to N C combining signals, obtaining N C combining signal-to-noise ratios, comprising: According to the mean and variance of each combined signal, a combined signal-to-noise ratio is obtained.

3. The method of claim 1, wherein, The method further comprises: down-converting the plurality of signals respectively to obtain a plurality of signals after frequency conversion.

4. The method of claim 3, wherein, The method further comprises: despreading the plurality of signals after frequency conversion respectively according to a spread spectrum pseudo-random code to obtain a plurality of signals after despreading.

5. The method of claim 1, wherein, The number of binary quantization bits is 5.

6. The method of claim 1, wherein, The N e is 0.2 times the N C .

7. A multi-beam coherent high-reliability combining apparatus, characterized by, The method comprises the following steps: a receiving module configured to coherently receive a plurality of signals forwarded by a satellite, the plurality of signals being BPSK symbol sequences modulated by direct sequence spread spectrum and transmitted to the satellite by a plurality of different beams with equal gain in a beam overlap area; an optimization module configured to jointly optimize normalized channel gains corresponding to the plurality of beams respectively based on a cross-entropy optimization algorithm to obtain optimal normalized channel gains corresponding to each beam; a weighting and combining module configured to weight and combine the plurality of signals after despreading based on the optimal normalized channel gains corresponding to each beam to obtain a combined signal; the optimization module is configured to: iteratively perform the following steps: Based on the number of binary quantization bits and the probability distribution, N C candidate binary quantized channel gains corresponding to each beam pair are randomly generated; N C candidate binary quantized channel gains corresponding to each beam pair are normalized after being converted from binary to decimal to obtain N C candidate normalized channel gains corresponding to each beam pair; Based on N C A set of candidate normalized channel gains are used to weight and combine the despread signals to obtain N C combined signals, respectively; wherein the set of candidate normalized channel gains includes candidate normalized channel gains corresponding to the multiple beams, respectively. According to N C combining signals, N C combined signal-to-noise ratios are obtained; The N C merge signal-to-noise ratios are sorted from large to small, and the N e merge signal-to-noise ratios at the front are selected. According to the N e merging signal-to-noise ratios, from each beam corresponding to N C candidate binary quantized channel gains, select N e elite binary quantized channel gains corresponding to each beam; According to N e elite binary quantized channel gains corresponding to each beam, update the probability distribution; if the iteration stop condition is not met, perform the next iteration based on the updated probability distribution; if the iteration stop condition is met, stop the iteration and obtain the optimal normalized channel gains corresponding to each beam based on the updated probability distribution; the iteration stop condition is that the generation probability of each bit in the updated probability distribution is 0 or 1, or the maximum iteration number is reached.

8. An electronic device comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, The processor executes the computer program to implement the multi-beam coherent high-reliability combining method according to any one of claims 1 to 6. 9.A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the multi-beam coherent high-reliability combining method according to any one of claims 1 to 6.

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