Intelligent dynamic transmission power adjustment method and device, electronic equipment and storage medium

Abstract

The application provides a kind of intelligent dynamic transmission power adjustment method, device, electronic equipment and storage medium, it is related to satellite communication technical field, is applied to sending end, this method includes: receiving the optimal normalized channel gain corresponding to each beam feedback by receiving end;The optimal normalized channel gain corresponding to each beam is obtained based on the joint optimization of the normalized channel gain corresponding to multiple beams respectively by cross-entropy optimization algorithm;According to the optimal normalized channel gain corresponding to each beam, the transmission power of each beam is adjusted.The application adjusts the transmission power of sending end intelligently, so that communication signal is embedded in normal satellite communication as much as possible, and the risk of being detected and disturbed is reduced.

Description

Technical Field

[0001] This invention relates to the field of satellite communication technology, and in particular to an intelligent dynamic transmission power adjustment method, device, electronic device, and storage medium. Background Technology

[0002] In high-orbit satellite multi-beam communication systems, the transmitting end sends the same information through multiple frequency beams to improve transmission reliability.

[0003] Unlicensed frequency band communication requires signal transmission power to be lower than the noise floor and without periodic characteristics. Traditional pilot-based power control schemes are prone to exposing signal characteristics and are difficult to meet the low probability of intercept (LPI) requirement. Summary of the Invention

[0004] This invention provides an intelligent dynamic transmission power adjustment method, device, electronic device, and storage medium to address the shortcomings of existing power control schemes that are easily exposed. It enables intelligent adjustment of the transmission power, allowing communication signals to be embedded as covertly as possible into normal satellite communication, reducing the risk of detection and interference, and improving stealth.

[0005] This invention provides an intelligent dynamic transmission power adjustment method, applied at the transmitting end, comprising:

[0006] The receiver receives the optimal normalized channel gain corresponding to each beam; the optimal normalized channel gain corresponding to each beam is obtained by jointly optimizing the normalized channel gains corresponding to multiple beams based on the cross-entropy optimization algorithm.

[0007] The transmit power of each beam is adjusted based on the optimal normalized channel gain corresponding to each beam.

[0008] In some embodiments, adjusting the transmit power of each beam according to the optimal normalized channel gain corresponding to each beam includes:

[0009] Determine the ratio of the optimal normalized channel gain to the average channel gain for each beam;

[0010] The product of the initial transmit power and the aforementioned ratio is used as the adjusted transmit power for each beam.

[0011] In some embodiments, the method further includes:

[0012] The BPSK symbol sequence modulated by direct sequence spread spectrum is transmitted to the satellite through multiple different beams in the beam overlap area with the same initial transmit power and gain.

[0013] This invention provides an intelligent dynamic transmission power adjustment method, applied at a receiving end, comprising:

[0014] 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.

[0015] The optimal normalized channel gain corresponding to each beam is fed back to the transmitting end; the optimal normalized channel gain corresponding to each beam is used to adjust the transmission power of each beam.

[0016] In some embodiments, the method further includes:

[0017] The system coherently receives multiple signals relayed by the satellite and performs down-conversion and despreading on each of the multiple signals. The multiple signals are BPSK symbol sequences that have been modulated by direct sequence spread spectrum and transmitted to the satellite in the beam overlap region through multiple different beams with the same initial transmit power and equal gain.

[0018] In some embodiments, the method further includes:

[0019] Perform equal-gain merging on the multiple signals after power equalization.

[0020] The present invention also provides an intelligent dynamic transmission power adjustment device, comprising:

[0021] The receiving module is used to receive the optimal normalized channel gain corresponding to each beam fed back by the receiving end; the optimal normalized channel gain corresponding to each beam is obtained by jointly optimizing the normalized channel gains corresponding to multiple beams based on the cross-entropy optimization algorithm.

[0022] The adjustment module is used to adjust the transmission power of each beam according to the optimal normalized channel gain corresponding to each beam.

[0023] The present invention also provides an intelligent dynamic transmission power adjustment device, comprising:

[0024] 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.

[0025] The second transmission module is used to feed back the optimal normalized channel gain corresponding to each beam to the transmitting end; the optimal normalized channel gain corresponding to each beam is used to adjust the transmission power of each beam.

[0026] 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 intelligent dynamic transmission power adjustment method as described above.

[0027] 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 intelligent dynamic transmission power adjustment method as described above.

[0028] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the intelligent dynamic transmission power adjustment method as described above.

[0029] The present invention provides an intelligent dynamic transmission power adjustment method, device, electronic device, and storage medium. The transmitting end receives the optimal normalized channel gain corresponding to each beam fed back by the receiving end. The optimal normalized channel gain corresponding to each beam is obtained by the receiving end through joint optimization of the normalized channel gains corresponding to multiple beams based on the cross-entropy optimization algorithm. The transmitting end adjusts the transmission power of each beam according to the optimal normalized channel gain corresponding to each beam. By intelligently adjusting the transmission power of the transmitting end, the communication signal can be embedded in normal satellite communication as covertly as possible, reducing the risk of detection and interference. Attached Figure Description

[0030] 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.

[0031] Figure 1 This is a schematic diagram of the communication between the user terminal, the satellite, and the ground gateway station.

[0032] Figure 2 This is one of the flowcharts illustrating the intelligent dynamic transmission power adjustment method provided by the present invention.

[0033] Figure 3 This is the second flowchart of the intelligent dynamic transmission power adjustment method provided by the present invention.

[0034] Figure 4 This is the third flowchart of the intelligent dynamic transmission power adjustment method provided by the present invention.

[0035] Figure 5 This is the fourth flowchart of the intelligent dynamic transmission power adjustment method provided by the present invention.

[0036] Figure 6 This is one of the structural schematic diagrams of the intelligent dynamic transmission power adjustment device provided by the present invention.

[0037] Figure 7 This is the second schematic diagram of the intelligent dynamic transmission power adjustment device provided by the present invention.

[0038] Figure 8 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0039] Figure 1 This is a diagram illustrating the communication between the user terminal, the satellite, and the ground gateway station, such as... Figure 1 As shown, user terminals (such as satellite phones, mobile devices, etc.) communicate with satellites (such as GEO satellites) via user links, while satellites communicate with ground gateway stations via feeder links. User terminals transmit data to ground gateway stations via return links, and ground gateway stations transmit data to users via forward links.

[0040] In high-orbit satellite multi-beam communication systems, users transmit the same information through multiple frequency beams to improve transmission reliability. However, due to the physical limitations of satellite transponders, the following problems may arise:

[0041] The edge effects of beams, the highest gain at the beam center point and the decrease in gain at the beam edges, the RF path loss of different beams, the dynamic differences of frequency channels, and the nonlinear effects of high power amplifiers (HPA) cause inconsistencies in the signal-to-noise ratio (SNR) of signals at different frequencies at the receiver, resulting in a significant decrease in the overall SNR after merging. Unlicensed frequency band communication requires signal power to be lower than the noise floor and without periodic characteristics. Traditional pilot-based power control schemes are prone to exposing signal characteristics and are difficult to meet the low probability of intercept (LPI) requirements. Satellite channels are highly time-varying, and existing open-loop power control relies on a fixed link budget, which cannot compensate for nonlinear distortion and dynamic losses in real time, leading to inaccurate power allocation.

[0042] Current Maximum Ratio Combining (MRC) methods typically rely on the receiver's signal weighting and combining of channel gain estimates for each beam. However, in unlicensed communication scenarios, the receiver usually cannot directly obtain accurate single-beam channel gain information, limiting the combining performance of MRC methods. Furthermore, simply relying on the receiver's combining strategy cannot fundamentally solve the problem of signal gain imbalance.

[0043] If the channel gain of each signal can be jointly estimated at the receiver using relevant optimization algorithms, and the estimation results can be fed back to the transmitter, allowing the transmitter to adjust the transmit power of each beam and make the signal-to-noise ratio of the multiple signals received at the receiver more consistent, then the anti-interference capability and stealth of the system can be improved while reducing computational complexity. However, how to accurately estimate the channel gain and formulate a suitable feedback mechanism remains a key technical challenge.

[0044] 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.

[0045] Figure 2 This is one of the flowcharts illustrating the intelligent dynamic transmission power adjustment method provided by the present invention, such as... Figure 2 As shown, the present invention provides an intelligent dynamic transmission power adjustment method, applied to a transmitting end, such as a user terminal, comprising the following steps:

[0046] Step 210: Receive the optimal normalized channel gain corresponding to each beam fed back by the receiver; the optimal normalized channel gain corresponding to each beam is obtained by jointly optimizing the normalized channel gains corresponding to multiple beams based on the cross-entropy optimization algorithm.

[0047] 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 signals, there are multiple normalized channel gains.

[0048] The receiver employs a cross-entropy optimization algorithm to jointly optimize the normalized channel gains corresponding to multiple beams, obtaining the optimal normalized channel gain for each beam. This involves jointly optimizing the dynamic channel gain for each frequency point and overlapping region using the cross-entropy optimization algorithm. The transmitter receives the optimal normalized channel gain for each beam fed back from the receiver.

[0049] Step 220: Adjust the transmit power of each beam according to the optimal normalized channel gain corresponding to each beam.

[0050] Specifically, the transmitting end calculates the optimal transmission power of each beam based on the optimal normalized channel gain corresponding to each beam, and adjusts the transmission power of each beam to the optimal transmission power.

[0051] The intelligent dynamic transmission power adjustment method provided by this invention involves the transmitting end receiving the optimal normalized channel gain corresponding to each beam from the receiving end. The optimal normalized channel gain corresponding to each beam is obtained by the receiving end through joint optimization of the normalized channel gains corresponding to multiple beams based on the cross-entropy optimization algorithm. The transmitting end adjusts the transmission power of each beam according to the optimal normalized channel gain corresponding to each beam. By intelligently adjusting the transmission power of the transmitting end, the communication signal can be embedded in normal satellite communication as covertly as possible, reducing the risk of detection and interference.

[0052] In some embodiments, adjusting the transmit power of each beam according to the optimal normalized channel gain corresponding to each beam includes:

[0053] Determine the ratio of the optimal normalized channel gain to the average channel gain for each beam;

[0054] The product of the initial transmit power and the ratio is used as the adjusted transmit power for each beam.

[0055] Specifically, the expression for the adjusted transmission power of the nth beam is as follows:

[0056]

[0057] In the formula, This represents the transmission power of the nth beam after adjustment. Indicates the initial transmission power. This represents the optimal normalized channel gain corresponding to the nth beam. This represents the average channel gain.

[0058] In some embodiments, the intelligent dynamic transmission power adjustment method provided by the present invention further includes:

[0059] The BPSK symbol sequence modulated by direct sequence spread spectrum is transmitted to the satellite through multiple different beams in the beam overlap area with the same initial transmit power and equal gain.

[0060] 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) in the beam overlap area with the same initial transmit power and equal gain. 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.

[0061] 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.

[0062] Figure 3 This is the second flowchart of the intelligent dynamic transmission power adjustment method provided by the present invention, as shown below. Figure 3 As shown, this invention provides an intelligent dynamic transmission power adjustment method, applied to a receiving end, such as a ground gateway station, comprising the following steps:

[0063] Step 310: 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.

[0064] Step 320: Feedback the optimal normalized channel gain corresponding to each beam to the transmitter; the optimal normalized channel gain corresponding to each beam is used to adjust the transmission power of each beam.

[0065] Specifically, the receiver uses a cross-entropy optimization algorithm 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.

[0066] The receiver feeds back the optimal normalized channel gain corresponding to each beam to the transmitter, so that the transmitter can adjust the transmission power of each beam according to the optimal normalized channel gain corresponding to each beam.

[0067] The intelligent dynamic transmit power adjustment method provided by this invention involves the receiver performing joint optimization of the normalized channel gain corresponding to each of the multiple beams based on the cross-entropy optimization algorithm to obtain the optimal normalized channel gain for each beam. The cross-entropy optimization algorithm is used for channel gain estimation, improving the system's adaptability in complex channel environments and reducing channel estimation errors. The optimal normalized channel gain for each beam is fed back to the transmitter, allowing the transmitter to adjust the transmit power of each beam based on this optimal gain. This ensures that the signal-to-noise ratio of the multiple signals received by the receiver is consistent, thereby optimizing signal combining performance and improving communication reliability.

[0068] In some embodiments, the intelligent dynamic transmission power adjustment method provided by the present invention

[0069] The system coherently receives multiple signals relayed by the satellite and performs down-conversion and despreading on each signal. The multiple signals are BPSK symbol sequences that have been modulated by direct sequence spread spectrum and then transmitted to the satellite in the beam overlap area through multiple different beams with the same initial transmit power and equal gain.

[0070] Specifically, the transmitter sends a BPSK symbol sequence of length K with identical content. After direct sequence spread spectrum modulation, it is transmitted to the satellite through N beams (i.e., N frequency points) in the beam overlap area with the same initial transmission power and equal gain. The spatial diversity characteristics of the beam overlap area are used to improve signal redundancy, while also reducing the signal power within a single beam, thus improving stealth.

[0071] 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.

[0072] 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:

[0073]

[0074] 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.

[0075] 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:

[0076]

[0077] in,

[0078]

[0079] 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.

[0080] 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.

[0081] Using 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.

[0082]

[0083] 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.

[0084] The intelligent dynamic transmission power adjustment method provided by this invention performs down-conversion on multiple signals at the receiving end, converting the high-frequency signals of the satellite into processable low-frequency signals, laying the foundation for subsequent despreading; and performs despreading through a spreading pseudo-random code to remove the spreading modulation applied by the transmitting end, thereby extracting the original narrowband data signal.

[0085] In some embodiments, Figure 4 This is the third flowchart of the intelligent dynamic transmission power adjustment method provided by the present invention, as shown below. Figure 4 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:

[0086] Step 410: Based on the binary quantization bit depth and probability distribution, randomly generate N corresponding to each beam. C Channel gain of candidate binary quantization.

[0087] 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.

[0088] In some embodiments, the quantization bit depth is 5, N. e For N C 0.2 times.

[0089] 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.

[0090] 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:

[0091]

[0092] 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 ( ).

[0093] Step 420, 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.

[0094] 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.

[0095] No. The expressions for the candidate normalized channel gain are as follows:

[0096]

[0097] 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.

[0098] For example, the binary quantization bits are 4. If it is 0101, then It is 0.667.

[0099] Step 430, based on N C The candidate normalized channel gain is used to weight and combine the despread multi-channel 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.

[0100] 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:

[0101]

[0102] 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.

[0103] 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.

[0104] No. The expression for the k-th symbol in the signal is as follows:

[0105]

[0106] 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.

[0107] Step 440, according to N C The merged signals yield N C The combined signal-to-noise ratio.

[0108] 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 The combined signals can yield N C The combined signal-to-noise ratio.

[0109] Step 450, 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.

[0110] Step 460, 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.

[0111] 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.

[0112] Step 470, based on N corresponding to each beam e An elite binary quantized channel gain is used to update the probability distribution.

[0113] Specifically, the expression for the updated probability corresponding to the nth beam is as follows:

[0114]

[0115] In the formula, This represents the updated probability corresponding to the nth beam. Indicates the nth beam corresponding to the nth beam. Elite binary quantized channel gain .

[0116] Based on the updated probabilities corresponding to all beams, the updated probability distribution is obtained. .

[0117] Step 480: 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.

[0118] 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 490 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 410 is executed again based on the updated probability distribution.

[0119] Step 490: Based on the updated probability distribution, obtain the optimal normalized channel gain for each beam.

[0120] 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.

[0121] The intelligent dynamic transmit power adjustment method provided by this invention can adaptively approximate the optimal channel gain combination 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 gain 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.

[0122] In some embodiments, according to N C The merged signals yield N C Each combined signal-to-noise ratio includes:

[0123] A combined signal-to-noise ratio is obtained based on the mean and variance of each combined signal.

[0124] 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.

[0125] No. The expression for the combined signal-to-noise ratio is as follows:

[0126]

[0127] 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.

[0128] The intelligent dynamic transmission power adjustment 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.

[0129] In some embodiments, the intelligent dynamic transmission power adjustment method provided by the present invention further includes:

[0130] Perform equal-gain merging on the multiple signals after power equalization.

[0131] Specifically, after adjusting the transmission power at the transmitting end, with each beam transmitting signals at the optimal transmission power, multiple signals are combined with equal gain, that is, the multiple signals are directly added after phase alignment (without amplitude adjustment) to improve the output signal-to-noise ratio and system performance.

[0132] Figure 5 This is the fourth flowchart of the intelligent dynamic transmission power adjustment method provided by the present invention, as shown below. Figure 5 As shown, the present invention provides an intelligent dynamic transmission power adjustment method, comprising the following steps:

[0133] Step 510: The transmitter transmits the BPSK symbol sequence modulated by direct sequence spread spectrum to the satellite through multiple different beams in the beam overlap area with the same initial transmit power and equal gain.

[0134] Step 520: The receiver performs coherent reception of the multiple signals relayed by the satellite, and performs down-conversion and despreading on the multiple signals respectively; the multiple signals are BPSK symbol sequences that have been modulated by direct sequence spread spectrum and transmitted to the satellite in the beam overlap area through multiple different beams with the same initial transmit power and equal gain.

[0135] Step 530: The receiver performs joint optimization of the normalized channel gain corresponding to each of the multiple beams based on the cross-entropy optimization algorithm to obtain the optimal normalized channel gain for each beam.

[0136] Step 540: The receiver feeds back the optimal normalized channel gain corresponding to each beam to the transmitter.

[0137] Step 550: The transmitting end adjusts the transmission power of each beam according to the optimal normalized channel gain corresponding to each beam.

[0138] Step 560: The receiving end performs equal-gain combining on the power-equalized multi-channel signals.

[0139] The intelligent dynamic transmission power adjustment device provided by the present invention is described below. The intelligent dynamic transmission power adjustment device described below and the intelligent dynamic transmission power adjustment method described above can be referred to in correspondence.

[0140] Figure 6 This is one of the structural schematic diagrams of the intelligent dynamic transmission power adjustment device provided by the present invention, such as... Figure 6 As shown, the present invention provides an intelligent dynamic transmission power adjustment device, comprising:

[0141] The receiving module 610 is used to receive the optimal normalized channel gain corresponding to each beam fed back by the receiving end; the optimal normalized channel gain corresponding to each beam is obtained by jointly optimizing the normalized channel gains corresponding to multiple beams based on the cross-entropy optimization algorithm.

[0142] The adjustment module 620 is used to adjust the transmission power of each beam according to the optimal normalized channel gain corresponding to each beam.

[0143] In some embodiments, the adjustment module 620 is specifically used for:

[0144] Determine the ratio of the optimal normalized channel gain to the average channel gain for each beam;

[0145] The product of the initial transmit power and the aforementioned ratio is used as the adjusted transmit power for each beam.

[0146] In some embodiments, the apparatus further includes:

[0147] The first transmission module is used to transmit the BPSK symbol sequence modulated by direct sequence spread spectrum to the satellite through multiple different beams in the beam overlap area with the same initial transmission power and gain.

[0148] Figure 7 This is a second schematic diagram of the intelligent dynamic transmission power adjustment device provided by the present invention, as shown below. Figure 7 As shown, the present invention provides an intelligent dynamic transmission power adjustment device, comprising:

[0149] The optimization module 710 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 corresponding to each beam.

[0150] The second transmitting module 720 is used to feed back the optimal normalized channel gain corresponding to each beam to the transmitting end; the optimal normalized channel gain corresponding to each beam is used to adjust the transmitting power of each beam.

[0151] In some embodiments, the apparatus further includes:

[0152] The processing module is used to coherently receive multiple signals relayed by the satellite, and to downconvert and despread the multiple signals respectively; the multiple signals are BPSK symbol sequences that have been directly sequence spread spectrum modulated and then transmitted to the satellite in the beam overlap area through multiple different beams with the same initial transmit power and equal gain.

[0153] In some embodiments, the apparatus further includes:

[0154] The merging module is used to merge multiple signals after power equalization with equal gain.

[0155] It should be noted that the intelligent dynamic transmission power adjustment device provided by the present invention can realize 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.

[0156] Figure 8 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 8 As shown, the electronic device may include a processor 810, a communications interface 820, a memory 830, and a communication bus 840. The processor 810, communications interface 820, and memory 830 communicate with each other via the communication bus 840. The processor 810 can call logic instructions in the memory 830 to execute an intelligent dynamic transmit power adjustment method. This method includes: receiving the optimal normalized channel gain corresponding to each beam fed back from the receiver; the optimal normalized channel gain corresponding to each beam is obtained by jointly optimizing the normalized channel gains corresponding to multiple beams based on a cross-entropy optimization algorithm; and adjusting the transmit power of each beam according to the optimal normalized channel gain corresponding to each beam. Alternatively, 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; the optimal normalized channel gain for each beam is fed back to the transmitter; the optimal normalized channel gain for each beam is used to adjust the transmission power of each beam.

[0157] Furthermore, the logical instructions in the aforementioned memory 830 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, 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.

[0158] 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 intelligent dynamic transmission power adjustment method provided by the above methods. This method includes: receiving the optimal normalized channel gain corresponding to each beam fed back from the receiver; the optimal normalized channel gain corresponding to each beam is obtained by jointly optimizing the normalized channel gains corresponding to multiple beams based on a cross-entropy optimization algorithm; adjusting the transmission power of each beam according to the optimal normalized channel gain corresponding to each beam. Alternatively, based on a cross-entropy optimization algorithm, jointly optimizing the normalized channel gains corresponding to multiple beams to obtain the optimal normalized channel gain corresponding to each beam; feeding back the optimal normalized channel gain corresponding to each beam to the transmitter; the optimal normalized channel gain corresponding to each beam is used to adjust the transmission power of each beam.

[0159] 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 intelligent dynamic transmission power adjustment method provided by the above methods. This method includes: receiving the optimal normalized channel gain corresponding to each beam fed back from the receiver; the optimal normalized channel gain corresponding to each beam is obtained by jointly optimizing the normalized channel gains corresponding to multiple beams based on a cross-entropy optimization algorithm; adjusting the transmission power of each beam according to the optimal normalized channel gain corresponding to each beam. Alternatively, based on a cross-entropy optimization algorithm, jointly optimizing the normalized channel gains corresponding to multiple beams to obtain the optimal normalized channel gain corresponding to each beam; feeding back the optimal normalized channel gain corresponding to each beam to the transmitter; the optimal normalized channel gain corresponding to each beam is used to adjust the transmission power of each beam.

[0160] 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.

[0161] 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.

[0162] 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 method for intelligent dynamic transmission power adjustment, characterized in that, Applied to the sending end, including: The receiver receives the optimal normalized channel gain corresponding to each beam; the optimal normalized channel gain corresponding to each beam is obtained by jointly optimizing the normalized channel gains corresponding to multiple beams based on the cross-entropy optimization algorithm. The transmit power of each beam is adjusted according to the optimal normalized channel gain corresponding to each beam. The optimal normalized channel gain corresponding to each beam is obtained by performing an iterative step: 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 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. The iterative steps include: 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-channel 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 Individual signal-to-noise ratio; 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 An elite binary quantized channel gain is used to update the probability distribution.

2. The intelligent dynamic transmission power adjustment method according to claim 1, characterized in that, The step of adjusting the transmit power of each beam according to the optimal normalized channel gain corresponding to each beam includes: Determine the ratio of the optimal normalized channel gain to the average channel gain for each beam; The product of the initial transmit power and the aforementioned ratio is used as the adjusted transmit power for each beam.

3. The intelligent dynamic transmission power adjustment method according to claim 2, characterized in that, The method further includes: The BPSK symbol sequence modulated by direct sequence spread spectrum is transmitted to the satellite through multiple different beams in the beam overlap area with the same initial transmit power and gain.

4. A method for intelligent dynamic transmission power adjustment, characterized in that, Applied to the receiving end, including: 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. The optimal normalized channel gain corresponding to each beam is fed back to the transmitting end; the optimal normalized channel gain corresponding to each beam is used to adjust the transmission power of each beam. 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-channel 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 Individual signal-to-noise ratio; 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. 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.

5. The intelligent dynamic transmission power adjustment method according to claim 4, characterized in that, The method further includes: The system coherently receives multiple signals relayed by the satellite and performs down-conversion and despreading on each of the multiple signals. The multiple signals are BPSK symbol sequences that have been modulated by direct sequence spread spectrum and transmitted to the satellite in the beam overlap region through multiple different beams with the same initial transmit power and equal gain.

6. The intelligent dynamic transmission power adjustment method according to claim 4, characterized in that, The method further includes: Perform equal-gain merging on the multiple signals after power equalization.

7. An intelligent dynamic transmission power adjustment device, characterized in that, include: The receiving module is used to receive the optimal normalized channel gain corresponding to each beam fed back by the receiving end; the optimal normalized channel gain corresponding to each beam is obtained by jointly optimizing the normalized channel gains corresponding to multiple beams based on the cross-entropy optimization algorithm. The adjustment module is used to adjust the transmission power of each beam according to the optimal normalized channel gain corresponding to each beam. The optimal normalized channel gain corresponding to each beam is obtained by performing an iterative step: 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 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. The iterative steps include: 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-channel 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 Individual signal-to-noise ratio; 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 An elite binary quantized channel gain is used to update the probability distribution.

8. An intelligent dynamic transmission power adjustment device, characterized in that, include: 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 second transmission module is used to feed back the optimal normalized channel gain corresponding to each beam to the transmitting end; the optimal normalized channel gain corresponding to each beam is used to adjust the transmission power of each beam. 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-channel 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 Individual signal-to-noise ratio; 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. 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.

9. 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 intelligent dynamic transmission power adjustment method as described in any one of claims 1 to 6.

10. 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 intelligent dynamic transmission power adjustment method as described in any one of claims 1 to 6.

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