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

Abstract

The application provides a kind of multi-beam coherent high reliability combination method, device, electronic equipment and storage medium, it relates to satellite communication technical field, the method comprises: the multi-channel signal of satellite retransmission is received coherently, multi-channel signal is BPSK symbol sequence after direct sequence spread spectrum modulation, in beam overlap area through multiple different beams equal gain is sent to the satellite;Based on cross-entropy optimization algorithm, the normalized channel gain corresponding to each multi-channel beam is jointly optimized, and the optimal normalized channel gain corresponding to each beam is obtained;Based on the optimal normalized channel gain corresponding to each beam, the weighted and combined multi-channel signal after despreading is obtained, and the combined signal is obtained.The application realizes the adaptive maximum ratio combination of multi-channel signal, can significantly improve the signal-to-noise ratio after signal combination, so that the communication system can still maintain high communication quality in weak channel environment, enhance the anti-interference ability and concealment of system, improve the reliability of link.

Description

Technical Field

[0001] This invention relates to the field of satellite communication technology, and in particular to a multi-beam coherent high-reliability combining method, apparatus, electronic device, and storage medium. Background Technology

[0002] In high-orbit satellite multi-beam communication systems, the transmitting end simultaneously sends the same information through multiple frequency beams, which is then relayed by the satellite and received by the ground gateway station. Multi-beam combining is a key technology for improving system performance.

[0003] The weight allocation in the existing Maximum Ratio Combining (MRC) algorithm relies on individual estimation of each beam, and the results are susceptible to poor quality branches, leading to a decline in signal combining performance. Summary of the Invention

[0004] This invention provides a multi-beam coherent high-reliability combining method, apparatus, electronic device, and storage medium to address the shortcomings of signal combining performance degradation in existing technologies, achieve adaptive maximum ratio combining of multiple signals, thereby improving the signal-to-noise ratio at the receiver, enhancing the system's anti-interference capability and concealment, and improving the reliability of the link.

[0005] This invention provides a multi-beam coherent high-reliability combining method, comprising:

[0006] Coherent reception of multiple signals relayed by the satellite, wherein the multiple signals are BPSK symbol sequences that have been modulated by direct sequence spread spectrum and transmitted to the satellite through multiple beams with equal gain in the beam overlap region;

[0007] Based on the cross-entropy optimization algorithm, the normalized channel gain corresponding to each of the multiple beams is jointly optimized to obtain the optimal normalized channel gain for each beam.

[0008] Based on the optimal normalized channel gain corresponding to each beam, the despread multi-channel signals are weighted and then combined to obtain the combined signal.

[0009] In some embodiments, the joint optimization of the normalized channel gains corresponding to each of the multiple beams based on the cross-entropy optimization algorithm to obtain the optimal normalized channel gain for each beam includes:

[0010] Iteratively execute the following steps:

[0011] Based on the binary quantization bit depth and probability distribution, N is randomly generated for each beam. C Channel gain of candidate binary quantization;

[0012] For each beam corresponding to N CThe 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;

[0013] Based on N C The candidate normalized channel gain is used to weight and combine the despread multi-path signals to obtain N. C A combined signal; wherein, a set of candidate normalized channel gains includes candidate normalized channel gains corresponding to each of the multiple beams;

[0014] According to N C The merged signals yield N C Individual signal-to-noise ratio;

[0015] For the N C Sort the combined signal-to-noise ratios from largest to smallest, and select the top N. e Individual signal-to-noise ratio;

[0016] According to the N e The combined signal-to-noise ratio, from the N corresponding to each beam. C From the candidate binary quantized channel gains, select N corresponding to each beam. e Elite binary quantized channel gain;

[0017] According to N corresponding to each beam e The probability distribution is updated using an elite binary quantized channel gain.

[0018] 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 number of iterations is reached.

[0019] In some embodiments, the statement based on N C The merged signals yield N C Each combined signal-to-noise ratio includes:

[0020] A combined signal-to-noise ratio is obtained based on the mean and variance of each of the combined signals.

[0021] In some embodiments, the method further includes:

[0022] The multiple signals are down-converted to obtain the frequency-converted multiple signals.

[0023] In some embodiments, the method further includes:

[0024] Based on the spread spectrum pseudo-random code, the frequency-converted multiple signals are despread separately to obtain the despread multiple signals.

[0025] In some embodiments, the number of binary quantization bits is 5.

[0026] In some embodiments, the N e For the N C 0.2 times.

[0027] The present invention also provides a multi-beam coherent high-reliability combining device, comprising:

[0028] The receiving module is used to coherently receive multiple signals relayed by the satellite. The multiple signals are BPSK symbol sequences that have been directly sequence spread spectrum modulated and then transmitted to the satellite through multiple beams with equal gain in the beam overlap area.

[0029] The optimization module is used to jointly optimize the normalized channel gain corresponding to each of the multiple beams based on the cross-entropy optimization algorithm, so as to obtain the optimal normalized channel gain for each beam.

[0030] The weighted merging module is used to weight and merge the despread multi-channel signals based on the optimal normalized channel gain corresponding to each beam to obtain the merged signal.

[0031] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the multi-beam coherent high-reliability combining method as described above.

[0032] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the multi-beam coherent high-reliability combining method as described above.

[0033] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the multi-beam coherent high-reliability combining method as described above.

[0034] The multi-beam coherent high-reliability combining method, apparatus, electronic device, and storage medium provided by this invention jointly optimize the normalized channel gain corresponding to each of the multiple beams through a cross-entropy optimization algorithm. This achieves accurate estimation of the normalized channel gain corresponding to each beam. Based on the optimal normalized channel gain corresponding to each beam, the despread multi-channel signals are weighted and combined to obtain a combined signal. This achieves adaptive maximum ratio combining of multiple signals, which can significantly improve the signal-to-noise ratio after signal combining. This enables the communication system to maintain high communication quality in weak channel environments, enhances the system's anti-interference capability and concealment, and improves the reliability of the link. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0036] Figure 1 This is one of the flowcharts of the multi-beam coherent high-reliability combining method provided by the present invention.

[0037] Figure 2 This is the second flowchart of the multi-beam coherent high-reliability combining method provided by the present invention.

[0038] Figure 3 This is a block diagram illustrating the principle of the multi-beam coherent high-reliability combining method provided by the present invention.

[0039] Figure 4 This is a simulation diagram of the multi-beam coherent high-reliability combining method provided by the present invention.

[0040] Figure 5 This is a schematic diagram of the structure of the multi-beam coherent high-reliability combining device provided by the present invention.

[0041] Figure 6 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0042] In high-orbit satellite multi-beam communication systems, the transmitter simultaneously sends the same information through multiple frequency beams, which is then received by ground gateway stations after being relayed by the satellite. Due to the wide coverage area of ​​satellites, there are overlapping areas between beams. Traditional technologies have failed to fully utilize the signal diversity characteristics of these areas, resulting in limited system performance. Furthermore, the physical limitations of satellite transponders and the dynamic environment pose challenges to signal combining: the RF links of different beams suffer from inconsistent signal path losses at different frequencies 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 satellite transponders change non-uniformly over time due to temperature drift and device aging; and existing technologies have not effectively utilized the spatial diversity characteristics of beam overlap areas, resulting in insufficient signal redundancy and difficulty in coping with complex interference environments.

[0043] Traditional solutions often employ least squares (LS) or minimum mean square error (MMSE) algorithms for channel gain estimation. However, these methods have significant drawbacks in satellite communication scenarios: pilot insertion reduces spectrum utilization, and the periodicity of these features makes them easily detectable by the enemy, violating the requirements for covert communication; the time-varying and nonlinear characteristics of satellite channels lead to large estimation errors in traditional algorithms, especially under multipath effects in beam overlap areas, where the signal-to-noise ratio loss can reach over 4dB; additional spectrum resources are required to transmit pilots, reducing spectrum utilization and compromising concealment; the weight allocation in existing maximum ratio combining algorithms relies on individual estimation of each beam, making the results susceptible to poor-quality branches, and it does not consider the joint optimization of multi-beam signals in overlap areas, resulting in unreasonable weight allocation.

[0044] Furthermore, covert communication in unlicensed frequency bands requires low signal power and concealed characteristics, making it difficult for existing methods to achieve high-precision channel estimation and combining under low signal-to-noise ratio conditions. Therefore, there is an urgent need for a method that does not require pilots, adapts to nonlinear dynamic channels, and can achieve maximum ratio combining.

[0045] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0046] Figure 1 This is one of the flowcharts illustrating the multi-beam coherent high-reliability combining method provided by this invention, such as... Figure 1 As shown, this invention provides a multi-beam coherent high-reliability combining method, applied at a receiving end, such as a ground gateway station, comprising:

[0047] Step 110: Coherently receive the multiple signals relayed by the satellite. The multiple signals are BPSK symbol sequences that have been directly sequence spread spectrum modulated and then transmitted to the satellite through multiple beams with equal gain in the beam overlap area.

[0048] Specifically, the transmitter sends a sequence of identical binary phase shift keying (BPSK) symbols of length K, which is then modulated using direct sequence spread spectrum (DSSS) and transmitted to the satellite through N beams (i.e., N frequency points) with equal gain in the beam overlap area. This utilizes the spatial diversity characteristics of the beam overlap area to improve signal redundancy while simultaneously reducing signal power within a single beam, thus enhancing stealth.

[0049] The satellite transponder amplifies and frequency-converts the BPSK symbol sequences after direct-sequence spread spectrum distribution, and then forwards them to the receiver. Signals in the beam overlap region are superimposed due to spatial diversity. The receiver coherently receives the multiple signals (i.e., the BPSK symbol sequences after direct-sequence spread spectrum distribution) relayed by the satellite.

[0050] Step 120: Based on the cross-entropy optimization algorithm, the normalized channel gain corresponding to each of the multiple beams is jointly optimized to obtain the optimal normalized channel gain for each beam.

[0051] Specifically, normalized channel gain refers to the channel gain that has been normalized (e.g., divided by a reference value or maximum gain) to become a dimensionless relative value (e.g., within the range of (0,1] or satisfying power constraints). Each beam corresponds to one normalized channel gain, and for multiple beams, there are multiple normalized channel gains.

[0052] The cross-entropy optimization algorithm is used to jointly optimize the normalized channel gains of multiple beams to obtain the optimal normalized channel gain for each beam. In other words, the dynamic channel gain of each frequency point and overlapping region is jointly optimized by the cross-entropy optimization algorithm.

[0053] Step 130: Based on the optimal normalized channel gain corresponding to each beam, the despread multi-channel signals are weighted and then combined to obtain the combined signal.

[0054] Specifically, the despread signals are weighted using the optimal normalized channel gain corresponding to each beam to obtain the weighted result for each signal. Then, all weighted results are combined to obtain the combined signal (i.e., a BPSK symbol sequence including K combined symbols). The specific expression for the k-th combined symbol in the combined signal is shown below:

[0055]

[0056] In the formula, Represents the k-th merging symbol. This represents the k-th symbol in the despread signal corresponding to the n-th beam, where N represents the number of beams. This represents the optimal normalized channel gain corresponding to the nth beam.

[0057] K merging symbols are obtained sequentially according to time order, thus obtaining the merged signal.

[0058] The multi-beam coherent high-reliability combining method provided by this invention performs joint optimization of the normalized channel gain corresponding to each of the multiple beams using a cross-entropy optimization algorithm. This achieves accurate estimation of the normalized channel gain corresponding to each beam. Based on the optimal normalized channel gain corresponding to each beam, the despread signals are weighted and combined to obtain the combined signal. This achieves adaptive maximum ratio combining of multiple signals, which can significantly improve the signal-to-noise ratio after signal combining. This enables the communication system to maintain high communication quality even in weak channel environments, enhances the system's anti-interference capability and concealment, and improves the reliability of the link.

[0059] In some embodiments, the multi-beam coherent high-reliability combining method provided by the present invention further includes:

[0060] The multiple signals are down-converted separately to obtain the frequency-converted multiple signals.

[0061] Specifically, the receiver performs coherent reception of multiple signals. For a single signal, the expression for the k-th symbol in the signal received by the receiver through the n-th beam is as follows:

[0062]

[0063] In the formula, This represents the k-th symbol in the signal corresponding to the n-th beam received at time t. This represents the channel gain of the nth beam. Indicates transmission power. This represents the spread spectrum signal corresponding to the k-th symbol in the signal transmitted at time t. This indicates the nth downlink frequency point relayed by the satellite. This represents the additive white Gaussian noise of the nth beam at time t. The mean is 0 and the variance is . The complex Gaussian distribution, where yes The standard deviation is used to measure the amplitude intensity of noise.

[0064] The receiving end down-converts each of the multiple signals to obtain the converted multiple signals. For a single signal, the expression for the k-th symbol in the converted signal corresponding to the n-th beam is as follows:

[0065]

[0066] in,

[0067]

[0068] In the formula, This represents the k-th symbol in the frequency-converted signal corresponding to the n-th beam received at time t. This represents the k-th symbol in the signal corresponding to the n-th beam received at time t. This indicates the nth downlink frequency point relayed by the satellite. This represents the channel gain of the nth beam. Indicates transmission power. This represents the spread spectrum signal corresponding to the k-th symbol in the signal transmitted at time t. This represents the additive white Gaussian noise of the nth beam at time t. This represents the additive white Gaussian noise of the nth beam after frequency conversion at time t.

[0069] because It is additive white Gaussian noise, and its phase is... Irrelevant, therefore It is still zero-mean Gaussian white noise, that is The mean is 0 and the variance is . The complex Gaussian distribution.

[0070] The multi-beam coherent high-reliability combining method provided by this invention performs down-conversion on multiple signals at the receiving end, thereby converting the high-frequency signals of the satellite into processable low-frequency signals, laying the foundation for subsequent despreading.

[0071] In some embodiments, the multi-beam coherent high-reliability combining method provided by the present invention further includes:

[0072] Based on the spread spectrum pseudo-random code, the frequency-converted multiple signals are despread separately to obtain the despread multiple signals.

[0073] Specifically, taking the frequency-converted single-channel signal as a unit, despreading is performed according to the spread spectrum pseudo-random code, that is, the spread spectrum pseudo-random code is multiplied and integrated with the frequency-converted single-channel signal to obtain the despread single-channel signal.

[0074]

[0075] In the formula, This represents the k-th symbol in the despread signal corresponding to the n-th beam. This represents the k-th symbol in the frequency-converted signal corresponding to the n-th beam received at time t. The spread spectrum pseudo-random code at time t, Indicates the chip cycle, This represents the channel gain of the nth beam. Indicates transmission power. This represents the spread spectrum signal corresponding to the k-th symbol in the signal transmitted at time t. The additive white Gaussian noise of the nth beam after frequency conversion at time t is represented.

[0076] The multi-beam coherent high-reliability combining method provided by the present invention despreads the signal by using a spreading pseudo-random code to remove the spreading modulation applied at the transmitting end, thereby extracting the original narrowband data signal.

[0077] In some embodiments, Figure 2 This is the second schematic diagram of the multi-beam coherent high-reliability combining method provided by the present invention, as shown below. Figure 2 As shown, based on the cross-entropy optimization algorithm, the normalized channel gains corresponding to each of the multiple beams are jointly optimized to obtain the optimal normalized channel gain for each beam, including:

[0078] Step 210: Based on the binary quantization bit depth and probability distribution, randomly generate N corresponding to each beam. C Channel gain of candidate binary quantization.

[0079] Specifically, the initial probability distribution in the predefined cross-entropy iteration is... Each beam corresponds to a probability, with D bits for binary quantization and N number of candidate normalized channel gains. C And the number N of elite normalized channel gains e N e It is less than N C Positive integers.

[0080] In some embodiments, the binary quantization bits are 5, N e For N C 0.2 times.

[0081] 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.

[0082] 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 beamC 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:

[0083]

[0084] 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 ( ).

[0085] 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.

[0086] 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.

[0087] No. The expressions for the candidate normalized channel gain are as follows:

[0088]

[0089] In the formula, Represents the nth beam. One candidate normalized channel gain, Indicates the number of bits in the binary quantization. Represents the nth beam. The channel gain of the nth candidate binary quantization Bit binary value.

[0090] For example, the binary quantization bits are 4. If it is 0101, then It is 0.667.

[0091] Step 230, based on N C The candidate normalized channel gain is used to weight and combine the despread multi-channel signals to obtain N. CA combined signal; wherein, a set of candidate normalized channel gains includes candidate normalized channel gains corresponding to each of the multiple beams.

[0092] Specifically, each beam corresponds to N C N candidate normalized channel gains are used to form a matrix H, which has N rows. The matrix H has N columns, and each column represents one beam. C The expression for the candidate normalized channel gain matrix H is as follows:

[0093]

[0094] If we group the N candidate normalized channel gains from each row of matrix H, then we have N C The candidate normalized channel gain is divided into groups, and each group of candidate normalized channel gains includes the candidate normalized channel gains corresponding to N beams.

[0095] Using a set of candidate normalized channel gains as units, the despread multiple signals are weighted and then combined based on each set of candidate normalized channel gains to obtain a combined signal, N. C The normalized channel gain of the candidate group can be used to obtain N. C A merged signal.

[0096] No. The expression for the k-th symbol in the signal is as follows:

[0097]

[0098] In the formula, Indicates the first The k-th symbol in a merged signal, Represents the nth beam. One candidate normalized channel gain, This represents the k-th symbol in the despread signal corresponding to the n-th beam, where N represents the number of beams.

[0099] Step 240, according to N C The merged signals yield N C The combined signal-to-noise ratio.

[0100] Specifically, a signal-to-noise ratio (SNR) evaluation is performed on each combined signal, that is, the SNR of the K BPSK symbols in each combined signal is evaluated to obtain a combined SNR. N C From the combined signals, we can obtain N C The combined signal-to-noise ratio.

[0101] Step 250, for N CSort the combined signal-to-noise ratios from largest to smallest, and select the top N. e The combined signal-to-noise ratio.

[0102] Step 260, according to N e The combined signal-to-noise ratio, from the N corresponding to each beam. C From the candidate binary quantized channel gains, select N corresponding to each beam. e Elite binary quantized channel gain.

[0103] Specifically, according to N e The combined signal-to-noise ratio in N C The position of each combined noise ratio, from the N corresponding to each beam C From the candidate binary quantized channel gains, select N corresponding to each beam. e Elite binary quantized channel gain.

[0104] Step 270, based on N corresponding to each beam e An elite binary quantized channel gain is used to update the probability distribution;

[0105] Specifically, the expression for the updated probability corresponding to the nth beam is as follows:

[0106]

[0107] In the formula, This represents the updated probability corresponding to the nth beam. Indicates the nth beam corresponding to the th Elite binary quantized channel gain ( ).

[0108] Based on the updated probabilities corresponding to all beams, the updated probability distribution is obtained. .

[0109] Step 280: Determine if the generation probability of each bit in the updated probability distribution is 0 or 1, or if the maximum number of iterations has been reached.

[0110] Specifically, the generation probability of each bit in the updated probability distribution is set to either 0 or 1 (i.e., Each bit in the probability distribution is either 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 stops and step 290 is executed. If the iteration stopping condition is not met, the updated probability distribution is used as the probability distribution for the next iteration, and the next iteration is executed, that is, step 210 is executed again based on the updated probability distribution.

[0111] Step 290: Based on the updated probability distribution, obtain the optimal normalized channel gain for each beam.

[0112] Specifically, based on the updated probability distribution and the number of binary quantization bits, the optimal binary quantization channel gain corresponding to each beam is generated, and the optimal binary quantization channel gain corresponding to each beam is normalized to obtain the optimal normalized channel gain corresponding to each beam.

[0113] The multi-beam coherent high-reliability combining method provided by this invention can adaptively approximate the optimal combination of channel gains by iteratively generating, evaluating and screening candidate normalized channel gains, without relying on precise initial models or prior knowledge, and is suitable for dynamically changing channel environments; at the same time, it optimizes the channel gains of multiple beams and improves the overall SNR of the combined signal through collaborative processing, which is better than the scheme of independently optimizing a single beam.

[0114] In some embodiments, according to N C The merged signals yield N C Each combined signal-to-noise ratio includes:

[0115] A combined signal-to-noise ratio is obtained based on the mean and variance of each combined signal.

[0116] Specifically, each combined signal consists of K combined BPSK symbols. The mean and variance of these K combined BPSK symbols are calculated to obtain the mean and variance of each combined signal. Based on the mean and variance of each combined signal, a combined signal-to-noise ratio is obtained.

[0117] No. The expression for the combined signal-to-noise ratio is as follows:

[0118]

[0119] In the formula, Indicates the first The combined signal-to-noise ratio, Indicates the first The k-th merged BPSK symbol in the merged signals This indicates taking the average. This indicates the variance, and K represents the number of BPSK symbols included in the combined signal.

[0120] The multi-beam coherent high-reliability combining method provided by this invention enables rapid evaluation of the combined signal-to-noise ratio by using the mean and variance of each combined signal.

[0121] Figure 3This is a block diagram of the principle of the multi-beam coherent high-reliability combining method provided by the present invention. Based on the candidate normalized channel gain, multiple signals are weighted and combined by the maximum ratio to obtain the combined signal. The optimal normalized channel gain is output through cross-entropy iteration with signal-to-noise ratio estimation as the objective function.

[0122] Figure 4 This is a simulation diagram of the multi-beam coherent high-reliability combining method provided by the present invention, as shown below. Figure 4 As shown, the horizontal axis represents the signal-to-noise ratio E. b / N0 (dB), E b The vertical axis represents the energy of a single symbol, N0 represents the noise energy, and the vertical axis represents the bit error rate (BER). A box represents the basic signal, a triangle represents cross-entropy combining of two beam signals (CECombine-2), a solid dot represents cross-entropy combining of three beam signals (CE Combine-3), and a hollow dot represents cross-entropy combining of four beam signals (CE Combine-4). Figure 4 It can be seen that as the number of beams increases, the merging performance of multiple signals is better.

[0123] Figure 5 This is a schematic diagram of the structure of the multi-beam coherent high-reliability combining device provided by the present invention, as shown below. Figure 5 As shown, the present invention provides a multi-beam coherent high-reliability combining device, comprising:

[0124] The receiving module 510 is used to coherently receive multiple signals relayed by the satellite. The multiple signals are BPSK symbol sequences that have been directly sequence spread spectrum modulated and then transmitted to the satellite through multiple beams with equal gain in the beam overlap area.

[0125] The optimization module 520 is used to jointly optimize the normalized channel gain corresponding to each of the multiple beams based on the cross-entropy optimization algorithm, so as to obtain the optimal normalized channel gain for each beam.

[0126] The weighted merging module 530 is used to weight and merge the despread multi-channel signals based on the optimal normalized channel gain corresponding to each beam to obtain a merged signal.

[0127] In some embodiments, the optimization module 520 is specifically used for:

[0128] Iteratively execute the following steps:

[0129] Based on the binary quantization bit depth and probability distribution, N is randomly generated for each beam. C Channel gain of candidate binary quantization;

[0130] For each beam corresponding to NC 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;

[0131] Based on N C The candidate normalized channel gain is used to weight and combine the despread multi-path signals to obtain N. C A combined signal; wherein, a set of candidate normalized channel gains includes candidate normalized channel gains corresponding to each of the multiple beams;

[0132] According to N C The merged signals yield N C Individual signal-to-noise ratio;

[0133] For the N C Sort the combined signal-to-noise ratios from largest to smallest, and select the top N. e Individual signal-to-noise ratio;

[0134] According to the N e The combined signal-to-noise ratio, from the N corresponding to each beam. C From the candidate binary quantized channel gains, select N corresponding to each beam. e Elite binary quantized channel gain;

[0135] According to N corresponding to each beam e The probability distribution is updated using an elite binary quantized channel gain.

[0136] 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 number of iterations is reached.

[0137] In some embodiments, the optimization model is further specifically used for:

[0138] A combined signal-to-noise ratio is obtained based on the mean and variance of each of the combined signals.

[0139] In some embodiments, the apparatus further includes:

[0140] The downconversion module is used to downconvert the multiple signals to obtain the frequency-converted multiple signals.

[0141] In some embodiments, the apparatus further includes:

[0142] The despreading module is used to despread the frequency-converted multiple signals according to the spread spectrum pseudo-random code to obtain the despread multiple signals.

[0143] In some embodiments, the number of binary quantization bits is 5.

[0144] In some embodiments, the N e For the N C 0.2 times.

[0145] It should be noted that the multi-beam coherent high-reliability combining device provided by the present invention can implement all the method steps implemented in the above method embodiments and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiments and the beneficial effects will not be described in detail.

[0146] Figure 6 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 6 As shown, the electronic device may include a processor 610, a communications interface 620, a memory 630, and a communication bus 640. The processor 610, communications interface 620, and memory 630 communicate with each other via the communication bus 640. The processor 610 can call logic instructions in the memory 630 to execute a multi-beam coherent high-reliability combining method. This method includes: coherently receiving multiple signals relayed by a satellite, wherein the multiple signals are BPSK symbol sequences modulated by direct sequence spread spectrum and transmitted to the satellite through multiple beams with equal gain in the beam overlap region; jointly optimizing the normalized channel gains corresponding to each of the multiple beams based on a cross-entropy optimization algorithm to obtain the optimal normalized channel gain for each beam; and weighting and combining the despread signals based on the optimal normalized channel gain for each beam to obtain a combined signal.

[0147] Furthermore, the logical instructions in the aforementioned memory 630 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0148] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the multi-beam coherent high-reliability combining method provided by the above methods. The method includes: coherently receiving multiple signals relayed by a satellite, wherein the multiple signals are BPSK symbol sequences that have been directly sequence spread spectrum modulated and transmitted to the satellite through multiple different beams with equal gain in the beam overlap region; jointly optimizing the normalized channel gain corresponding to each of the multiple beams based on a cross-entropy optimization algorithm to obtain the optimal normalized channel gain corresponding to each beam; and combining the despread multiple signals based on the optimal normalized channel gain corresponding to each beam after weighting to obtain a combined signal.

[0149] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the multi-beam coherent high-reliability combining method provided by the above methods. The method includes: coherently receiving multiple signals relayed by a satellite, wherein the multiple signals are BPSK symbol sequences modulated by direct sequence spread spectrum and transmitted to the satellite through multiple beams with equal gain in the beam overlap region; jointly optimizing the normalized channel gain corresponding to each of the multiple beams based on a cross-entropy optimization algorithm to obtain the optimal normalized channel gain corresponding to each beam; and combining the despread multiple signals based on the optimal normalized channel gain corresponding to each beam after weighting to obtain a combined signal.

[0150] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0151] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A highly reliable multi-beam coherent combining method, characterized in that, include: Coherent reception of multiple signals relayed by the satellite, wherein the multiple signals are BPSK symbol sequences that have been modulated by direct sequence spread spectrum and transmitted to the satellite through multiple beams with equal gain in the beam overlap region; Based on the cross-entropy optimization algorithm, the normalized channel gain corresponding to each of the multiple beams is jointly optimized to obtain the optimal normalized channel gain for each beam. Based on the optimal normalized channel gain corresponding to each beam, the despread multi-channel signals are weighted and then combined to obtain the combined signal. The cross-entropy optimization algorithm is used to jointly optimize the normalized channel gain corresponding to each of the multiple beams, obtaining the optimal normalized channel gain for each beam, including: Iteratively execute the following steps: Based on the binary quantization bit depth and probability distribution, N is randomly generated for each beam. C Channel gain of candidate binary quantization; 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; Based on N C The candidate normalized channel gain is used to weight and combine the despread multi-path signals to obtain N. C A combined signal; wherein, a set of candidate normalized channel gains includes candidate normalized channel gains corresponding to each of the multiple beams; According to N C The merged signals yield N C Individual signal-to-noise ratio; For the N C Sort the combined signal-to-noise ratios from largest to smallest, and select the top N. e The combined signal-to-noise ratio; N e It is less than N C Positive integers; According to the N e The combined signal-to-noise ratio, from the N corresponding to each beam C From the candidate binary quantized channel gains, select N corresponding to each beam. e Elite binary quantized channel gain; According to N corresponding to each beam e The probability distribution is updated using an elite binary quantized channel gain. The expression for the updated probability corresponding to the nth beam is as follows: ； In the formula, This represents the updated probability corresponding to the nth beam. N represents the number of beams. Indicates the nth beam corresponding to the nth beam. Elite binary quantized channel gain, ; Based on the updated probabilities corresponding to all beams, the updated probability distribution is obtained. ; 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 number of iterations is reached.

2. The multi-beam coherent high-reliability combining method according to claim 1, characterized in that, According to N C The merged signals yield N C Each combined signal-to-noise ratio includes: A combined signal-to-noise ratio is obtained based on the mean and variance of each of the combined signals.

3. The multi-beam coherent high-reliability combining method according to claim 1, characterized in that, The method further includes: The multiple signals are down-converted to obtain the frequency-converted multiple signals.

4. The multi-beam coherent high-reliability combining method according to claim 3, characterized in that, The method further includes: Based on the spread spectrum pseudo-random code, the frequency-converted multiple signals are despread separately to obtain the despread multiple signals.

5. The multi-beam coherent high-reliability combining method according to claim 1, characterized in that, The number of bits for binary quantization is 5.

6. The multi-beam coherent high-reliability combining method according to claim 1, characterized in that, The N e For the N C 0.2 times.

7. A multi-beam coherent high-reliability combining device, characterized in that, include: The receiving module is used to coherently receive multiple signals relayed by the satellite. The multiple signals are BPSK symbol sequences that have been modulated by direct sequence spread spectrum and then transmitted to the satellite through multiple beams with equal gain in the beam overlap area. The optimization module is used to jointly optimize the normalized channel gain corresponding to each of the multiple beams based on the cross-entropy optimization algorithm, so as to obtain the optimal normalized channel gain for each beam. The weighted merging module is used to weight and merge the despread multi-channel signals based on the optimal normalized channel gain corresponding to each beam to obtain a merged signal. The optimization module is specifically used for: Iteratively execute the following steps: Based on the binary quantization bit depth and probability distribution, N is randomly generated for each beam. C Channel gain of candidate binary quantization; 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; Based on N C The candidate normalized channel gain is used to weight and combine the despread multi-path signals to obtain N. C A combined signal; wherein, a set of candidate normalized channel gains includes candidate normalized channel gains corresponding to each of the multiple beams; According to N C The merged signals yield N C Individual signal-to-noise ratio; For the N C Sort the combined signal-to-noise ratios from largest to smallest, and select the top N. e The combined signal-to-noise ratio; N e It is less than N C Positive integers; According to the N e The combined signal-to-noise ratio, from the N corresponding to each beam C From the candidate binary quantized channel gains, select N corresponding to each beam. e Elite binary quantized channel gain; According to N corresponding to each beam e The probability distribution is updated using an elite binary quantized channel gain. The expression for the updated probability corresponding to the nth beam is as follows: ； In the formula, This represents the updated probability corresponding to the nth beam. N represents the number of beams. Indicates the nth beam corresponding to the nth beam. Elite binary quantized channel gain, ; Based on the updated probabilities corresponding to all beams, the updated probability distribution is obtained. ; 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 number of iterations is reached.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the multi-beam coherent high-reliability combining method as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the multi-beam coherent high-reliability combining method as described in any one of claims 1 to 6.

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