Channel detection method, apparatus, device, and storage medium

Abstract

This application provides a channel detection method, apparatus, device, and storage medium, comprising: uniformly spreading point pilot energy using twisted convolution, allowing pilots and data to coexist on the same resource grid point without a guard band, thus eliminating the resource overhead caused by the guard band, maximizing the resource utilization of the delay Doppler domain, and significantly improving spectral efficiency; utilizing mutual ambiguity function processing, eliminating the need for a highly complex iterative interference cancellation algorithm at the receiver, and accurately extracting channel path information from a high-interference background with only a single mutual ambiguity function operation, significantly reducing the computational complexity and processing delay at the receiver; and effectively separating and eliminating aggregation interference generated by multi-satellite pilots based on channel path information, the twisted convolution result of the spread spectrum pilots, and the received signal, thereby accurately recovering the original data transmitted by each satellite, solving the data detection problem caused by severe aliasing of pilots and data in multi-satellite cooperative transmission.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a channel detection method, apparatus, device, and storage medium. Background Technology

[0002] The high-altitude motion of Low Earth Orbit (LEO) satellites generates severe Doppler drift, causing Orthogonal Frequency Division Multiplexing (OFDM) modulation performance to degrade in highly mobile scenarios. Orthogonal Time Frequency Space (OTFS) modulation technology, by modulating the signal in the Delay-Doppler (DD) domain, transforms the time-varying fading channel into a quasi-static channel, thus exhibiting Doppler resistance.

[0003] In multi-satellite cooperative transmission (MSCT) scenarios, multiple satellites simultaneously transmit signals to the same terminal device, and the superposition of spatial dimensions makes the channel environment more complex. For multi-satellite cooperative transmission scenarios with limited on-board resources and high spectral efficiency requirements, current solutions strive to maintain a balance between high spectral efficiency and low complexity. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a channel detection method, apparatus, device and storage medium.

[0005] To achieve the above objectives, this application provides a channel detection method applied at a receiving end, comprising: acquiring a received signal, wherein the received signal is generated by multiple satellites linearly superimposing their respective transmitted signals in the time-delay Doppler domain after power weighting of data signals and spread spectrum pilots according to their respective data transmission power and spread spectrum transmission power, and then spatially superimposing and fusing them after transmission through a wireless channel; the spread spectrum pilot is obtained by performing a twist convolution on a point pilot using a discrete filter to uniformly distribute the signal power of the point pilot on resource grid points in the time-delay Doppler domain; processing the received signal and the spread spectrum pilot using a mutual ambiguity function to estimate channel path information; and obtaining a data estimation signal based on the twist convolution result of the spread spectrum pilot and the received signal according to the channel path information; the data estimation signal is an estimation result of the data signals actually transmitted by the multiple satellites.

[0006] Optionally, the discrete filter is determined based on a rotation factor, the number of resource grid points in the time delay domain, the number of resource grid points in the Doppler domain, the time delay domain index, and the Doppler domain index; the rotation factor is coprime with the number of resource grid points in the time delay domain and the number of resource grid points in the Doppler domain; the rotation factor is used to rotate the self-ambiguity function support region of the spreading pilot to minimize the overlap area in geometric space between the self-ambiguity function support region of the spreading pilot and the self-ambiguity function support region of the data signal.

[0007] Optionally, the received signal and the spreading pilot are processed using a mutual ambiguity function to estimate channel path information, including: calculating the mutual ambiguity function between the received signal and the spreading pilot to obtain a correlation matrix in the time-delay Doppler domain; filtering each element in the correlation matrix using the detection threshold to extract target elements whose elements are greater than the detection threshold; and obtaining the channel path information of the target elements based on the target elements and the spreading transmit power.

[0008] Optionally, obtaining a data estimation signal based on the twisted convolution result of the spreading pilot and the received signal according to the channel path information includes: performing a twisted convolution operation on the spreading pilot and the channel path information to reconstruct a pilot interference component; subtracting the pilot interference component from the received signal to obtain a residual signal; and performing minimum mean square error data detection on the residual signal to obtain the data estimation signal; wherein the minimum mean square error data detection is based on the channel path information, the data transmission power, and the noise variance to construct a detection filter; and the noise variance is obtained from the remaining elements in the correlation matrix excluding the target element.

[0009] Optionally, the expression for the spreading pilot is: , ,in, Indicates spread spectrum pilot, Represents a discrete filter. Represents twisted convolution. This indicates that the coordinates in the time-delay Doppler domain are (k p， l p The point pilot frequency, This represents an index of a delay domain within the delay Doppler domain. This represents a Doppler index in the time-delay Doppler domain. This represents the number of resource grid points in the delay domain. This represents the number of resource grid points in the Doppler domain. The base of the natural logarithm. Represents the imaginary unit. This represents the rotation factor.

[0010] Optionally, the expression for the channel path information is: , ,in, The coordinates in the time-delay Doppler domain are ( Channel path information, Indicates the spread spectrum transmit power. The coordinates in the time-delay Doppler domain are ( The mutual ambiguity function of ) This represents another delay domain index within the delay Doppler domain. This represents another Doppler field index in the time-delay Doppler field. This represents the number of resource grid points in the delay domain. This represents the number of resource grid points in the Doppler domain. The coordinates in the time-delay Doppler domain of the received signal are ( The corresponding received symbol, The coordinates in the time-delay Doppler domain are ( The conjugate result of the spread spectrum pilot, The base of the natural logarithm. It represents the imaginary unit.

[0011] This application provides a channel detection method applied to a satellite, comprising: obtaining the satellite's transmitted signal based on the data signal, data transmission power, spreading pilot, and spreading transmission power; transmitting the transmitted signal to a receiving end; wherein the spreading pilot is obtained by twisting and convolving a point pilot using a discrete filter to uniformly distribute the signal power of the point pilot across resource grid points in the time-delay Doppler domain; the receiving end is used to receive a received signal obtained by superimposing and transmitting the transmitted signals of multiple satellites in the time-delay Doppler domain; estimating channel path information by processing the received signal and the spreading pilot using a mutual ambiguity function; obtaining a data estimation signal based on the twisted and convolved result of the spreading pilot and the received signal according to the channel path information; wherein the data estimation signal is an estimation result of the data signals actually transmitted by the multiple satellites.

[0012] This application provides a detection device, comprising: an acquisition module for acquiring a received signal, wherein the received signal is obtained by superimposing and transmitting transmitted signals from multiple satellites based on data signals, data transmission power, spread spectrum pilots, and spread spectrum transmission power in the time-delay Doppler domain; the spread spectrum pilots are obtained by performing a twist convolution on point pilots using a discrete filter to uniformly distribute the signal power of the point pilots across resource grid points in the time-delay Doppler domain; and a detection module for processing the received signal and the spread spectrum pilots using a mutual ambiguity function to estimate channel path information; and obtaining a data estimation signal based on the twist convolution result of the spread spectrum pilots and the received signal according to the channel path information; wherein the data estimation signal is an estimation result of the data signals actually transmitted by the multiple satellites.

[0013] This application 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 implements the channel detection method when executing the program.

[0014] This application provides a non-transitory computer-readable storage medium that stores computer instructions for causing a computer to execute the channel detection method.

[0015] As can be seen from the above, the channel detection method provided in this application, by utilizing twisted convolution to diffuse the point pilot energy, allows the pilot and data to coexist on the same resource grid point without a guard band, eliminating the resource overhead caused by the guard band, thereby maximizing the resource utilization rate in the time-delay Doppler domain and significantly improving spectral efficiency. Since the spreading pilot is diffused through twisted convolution, it possesses broadband characteristics similar to noise and good autocorrelation properties. Using a mutual ambiguity function, the pilot energy dispersed throughout the time-delay Doppler domain can be coherently accumulated at the correct path location, while simultaneously suppressing data signal interference incoherently as background noise. This eliminates the need for a highly complex iterative interference cancellation algorithm at the receiver; channel path information can be accurately extracted from a high-interference background with just one mutual ambiguity function operation, significantly reducing the computational complexity and processing delay at the receiver. By first estimating the channel path information containing multi-star effects, then using this channel path information to accurately model pilot interference from the twisted convolution result of the spreading pilot, removing the interference from the received signal, and finally recovering the data. This processing logic can effectively separate and eliminate the aggregation interference generated by multi-satellite pilot signals in complex environments where multiple satellite signals are superimposed in the air, thereby accurately recovering the original data transmitted by each satellite and solving the data detection problem caused by severe overlap of pilot signals and data in multi-satellite collaborative transmission. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram illustrating an application scenario of a channel detection method according to an embodiment of this application;

[0018] Figure 2 This is a flowchart illustrating a channel detection method according to an embodiment of this application; Figure 3 This is a data stream diagram of a channel detection method according to an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a detection device according to an embodiment of this application; Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0020] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this application should have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0021] The high-altitude motion of low-Earth orbit satellites generates severe Doppler drift, causing OFDM modulation performance to degrade in highly mobile scenarios. OTFS modulation technology, by modulating the signal in the time-delay Doppler domain, transforms the time-varying fading channel into a quasi-static channel, thus exhibiting Doppler resistance.

[0022] Currently, OTFS channel estimation schemes are mainly divided into two categories: One approach is the embedded pilot scheme, designed for fast-moving low-Earth orbit satellites. This scheme employs OTFS modulation and designs different pilot symbol grid positions for multiple users in the time-delay-Doppler domain. It estimates the total number of paths and the time delay of each path using energy threshold detection, and derives a closed-form expression for channel fading using maximum likelihood estimation. This scheme focuses on multi-user differentiation and path search in the uplink. Its pilot design typically still requires a certain degree of isolation or a specific grid distribution, and it primarily relies on traditional path search methods, without addressing full-domain spread spectrum and data overlay transmission without guard intervals. It necessitates setting large guard intervals around the pilots in the time-delay-Doppler grid to prevent data signal interference with the pilots, significantly reducing spectral efficiency.

[0023] Another approach is the pilot overlay scheme. This scheme estimates the Doppler scale factor based on the designed OTFS frame structure and preamble structure, performs Doppler compensation by resampling the received signal, and estimates the residual Doppler frequency shift based on the empty subcarrier information. The channel is estimated using the orthogonality information of the empty subcarriers. This scheme focuses on Doppler compensation and resampling and relies on the guard interval, sacrificing some spectrum resources. For multi-channel joint estimation in multi-satellite collaborative scenarios, this method may require processing each satellite link separately, resulting in high complexity. Although it improves spectral efficiency, pilots and data interfere with each other, typically requiring highly complex iterative algorithms for interference cancellation.

[0024] In summary, the current solution has the following three problems: ① Low spectral efficiency: To prevent pilot and data interference, a guard interval (or empty subcarrier) is usually required. In the high Doppler scenario of ground orbit, the guard interval needs to be very large, resulting in insufficient data transmission due to excessive protection overhead. ② High computational complexity: If superimposed pilots (without a guard interval) are used, existing technologies usually require multiple iterations to eliminate data interference to the pilots, resulting in a large computational load, which is not suitable for onboard or low-power terminal processing. ③ Difficulty in multi-satellite estimation: In multi-satellite collaborative scenarios, distinguishing the channels of different satellites usually requires orthogonal pilot resources, further compressing the data space.

[0025] In view of this, embodiments of this application provide a channel detection method that uses twisted convolution to diffuse point pilot energy, allowing pilots and data to coexist on the same resource grid point without a guard band. This eliminates the resource overhead caused by the guard band, thereby maximizing resource utilization in the time-delay Doppler domain and significantly improving spectral efficiency. Since the spreading pilot is diffused through twisted convolution, it possesses broadband characteristics similar to noise and good autocorrelation properties. Using a mutual ambiguity function, the pilot energy dispersed throughout the time-delay Doppler domain can be coherently accumulated at the actual path location, while simultaneously suppressing data signal interference incoherently as background noise. This eliminates the need for a complex iterative interference cancellation algorithm at the receiver; channel path information can be accurately extracted from a high-interference background with just one mutual ambiguity function operation, significantly reducing the receiver's computational complexity and processing delay. The method first estimates the channel path information containing multi-star effects, then uses this channel path information to accurately model pilot interference from the twisted convolution result of the spreading pilot, removes the interference from the received signal, and finally recovers the data. This processing logic can effectively separate and eliminate the aggregation interference generated by multi-satellite pilot signals in complex environments where multiple satellite signals are superimposed in the air, thereby accurately recovering the original data transmitted by each satellite and solving the data detection problem caused by severe overlap of pilot signals and data in multi-satellite collaborative transmission.

[0026] refer to Figure 1 This is a schematic diagram illustrating an application scenario of the channel detection method provided in this application embodiment. The application scenario includes a receiver 101 and a low-Earth orbit (LEO) satellite constellation 102. The receiver 101 and the LEO satellite constellation 102 can be connected via a wireless communication link.

[0027] Receiver 101 may include, but is not limited to, handheld satellite phones, vehicle-mounted mobile terminals, shipborne communication stations, airborne communication systems, IoT gateways, fixed ground stations, or other ground terminal equipment capable of receiving and processing satellite signals. The low-Earth orbit (LEO) satellite constellation 102 may consist of multiple LEO satellites in orbit. These satellites can be independent physical satellites or distributed satellite systems forming a coordinated transmission cluster, all serving receiver 101 within the same coverage area. The network management and data processing center 103 may be an independent physical server cluster or a cloud platform providing basic services such as cloud-native network functions, orbit calculation, beam scheduling, channel modeling, big data analysis, and artificial intelligence training to support the coordinated scheduling and parameter configuration of the satellite constellation.

[0028] The low-Earth orbit satellite constellation 102 can be used to provide high-speed data communication services to the receiver 101. In multi-satellite cooperative transmission mode, multiple satellites in the constellation simultaneously transmit signals to the receiver 101. Specifically, each satellite at the transmitter weights the data signal to be transmitted with the spread spectrum pilot according to its respective transmit power, and directly linearly superimposes them in the time-delay Doppler domain to generate the transmitted signal, without setting any guard interval. For example, as... Figure 1 As shown, the Earth-orbiting satellite constellation 102 may include n satellites, each satellite obtaining its own transmission signal based on its own data signal and spreading pilot. These transmission signals are superimposed in space after propagation and are received by the receiver 101 as a mixed received signal. In this embodiment, the spreading pilots of the multiple satellites may be the same or different. If the spreading pilots of the multiple satellites are different, the receiver reconstructs the spreading pilots of the multiple satellites locally; and calculates the estimated data signal based on the multiple spreading pilots.

[0029] After receiving the received signal, receiver 101 can perform a mutual ambiguity function operation on the locally generated spreading pilot and the received signal to extract significant peaks from the noise-like background, thereby estimating the channel path information including multi-satellite effects. Based on the twisted convolution result of this channel path information with the spreading pilot and the received signal, a data estimation signal is obtained. This data estimation signal is the estimation result of the data signals actually transmitted by multiple satellites. This process enables the terminal equipment to achieve high-precision channel estimation and data recovery with low complexity in a high-spectral-efficiency transmission mode without guard intervals.

[0030] This application embodiment may further include a management center, which can be connected to the receiver 101 and the low-Earth orbit satellite constellation 102 via a wireless communication link. The management center can store a large amount of channel scenario data, satellite orbit ephemeris information, and system configuration parameters. Based on historical transmission data or simulation data, it optimizes the parameters of the discrete filter, the position configuration of the point pilot, and the power allocation strategy. The power allocation strategy is the ratio of data transmission power to spread spectrum transmission power. The optimized configuration parameters are then distributed to the low-Earth orbit satellite constellation 102 and the receiver 101. Furthermore, the management center can monitor link quality in real time and dynamically adjust the satellite combination participating in cooperative transmission to ensure the continuity and reliability of communication services.

[0031] The channel detection method of this application can be applied to other high-mobility, high-Doppler-shift wireless communication scenarios such as low-orbit satellite communication, high-speed rail communication, and drone swarm communication.

[0032] The following is combined Figure 1The application scenarios described above are used to illustrate the channel detection method according to exemplary embodiments of this application. It should be noted that the above application scenarios are only shown to facilitate understanding of the spirit and principles of this application, and the embodiments of this application are not limited in any way in this respect. Rather, the embodiments of this application can be applied to any applicable scenario.

[0033] like Figure 2 As shown, a channel detection method is provided, applied at a receiver, including: S1. Acquiring the received signal: The received signal is generated by multiple satellites linearly superimposing their respective transmitted signals in the time-delay Doppler domain after weighting the data signals and spread spectrum pilots according to their respective data transmission power and spread spectrum transmission power, and then transmitting them through the wireless channel and spatially superimposing and fusing them. The spread spectrum pilot is obtained by twisting and convolving the point pilot with a discrete filter to uniformly distribute the signal power of the point pilot on the resource grid points in the time-delay Doppler domain.

[0034] S2. The received signal and spreading pilot are processed using a mutual ambiguity function to estimate the channel path information.

[0035] S3. Based on the channel path information, the twist convolution result of the spread spectrum pilot and the received signal are used to obtain the data estimation signal; the data estimation signal is the estimation result of the data signals actually transmitted by multiple satellites.

[0036] In some embodiments, the received signal at the receiver may refer to the spatial superposition and fusion of the transmitted signals generated by multiple satellite signals after being transmitted through a wireless channel. The received signal may consist of a discrete sequence of received symbols, which can be mapped to [a specific sequence] in the time-delay Doppler domain. The two-dimensional grid structure, in which each resource grid point corresponds to a complex received symbol, which can characterize the signal sample value under a specific time delay and Doppler resolution.

[0037] In one implementation, the expression for the received signal can be represented as: ,in, The signal can be represented by 'q', where 'q' represents the link between the q-th satellite and the receiver. This can represent the effective channel response of link q. It can represent sending a signal. This can be represented as additive white noise in the time-delay Doppler domain. It can represent the twist convolution operation.

[0038] Furthermore, the model can be simplified to a single equivalent channel model, i.e. ,Should This can represent an aggregated channel, which is the total channel response received by the receiver in a multi-satellite cooperative transmission scenario. This total channel response can refer to the linear superposition of the effective channel responses of multiple satellites. Based on this, the expression for the received signal can also be expressed as: .

[0039] Data signal refers to the effective information payload that a satellite wants to send to the receiver. Data transmit power refers to the transmit power that the satellite allocates to the data signal, which determines the proportion of the data signal in the total transmit signal capacity. Spread spectrum pilot refers to the reference signal after the point pilot has been spread using a discrete filter. Spread spectrum transmit power refers to the transmit power that the satellite allocates to the spread spectrum pilot, which determines the proportion of the spread spectrum pilot in the total transmit signal energy.

[0040] The transmitted signal can be obtained based on the data signal, data transmission power, spread spectrum pilot, and spread spectrum transmission power. In the embodiments of this application, the implementation method of the transmitted signal is not limited. In one implementation, reference is made to... Figure 3 As shown, the expression for the transmitted signal can be represented as follows: ,in, It can represent sending a signal. It can represent the data transmission power. It can represent data signals. It can represent spread spectrum transmission power. This can represent a spread spectrum pilot. In the embodiments of this application, the data signal... Data symbol pulses carrying information can be used With the preset discrete time delay-Doppler information signal The signal is obtained by performing a twisted convolution calculation. This transmitted signal is then transmitted to the receiver via the channel for reception. .

[0041] The time-delay Doppler domain can be considered a two-dimensional signal representation domain with time delay on the horizontal axis and Doppler frequency shift on the vertical axis. Operations such as superposition, twisted convolution, and mutual ambiguity function processing are performed in the time-delay Doppler domain. A discrete filter refers to spreading a point pilot signal in the time-delay Doppler domain to distribute the energy of the point pilot signal evenly across the resource grid points of the entire time-delay Doppler domain. The energy at each resource grid point can be 1 / MN of the total energy. This represents the number of resource grid points in the delay domain. This represents the number of resource grid points in the Doppler domain. A point pilot can be represented as a pulse signal on a single resource grid point in the time-delayed Doppler domain, and the coordinates of the point pilot can be agreed upon by the receiver and multiple satellites. Multiple satellites perform twist convolution on point pilots to generate spread spectrum pilots. The receiver reconstructs identical spread spectrum pilots based on the same location and a local discrete filter, which are then used for subsequent mutual ambiguity function calculations. The mutual ambiguity function measures the similarity between the received signal and the spread spectrum pilot under different time delays and Doppler shifts. When the local spread spectrum pilot aligns with the pilot components in the received signal in terms of time delay and Doppler shift (i.e., matches the actual physical path), the mutual ambiguity function will produce a significant peak at the coordinates of the corresponding point pilot. Therefore, by detecting the significant peak and its coordinates, the receiver can directly deduce the time delay spread and Doppler shift experienced by the signal during transmission, thereby accurately estimating the channel path information characterizing the propagation characteristics of the multi-satellite aggregation channel.

[0042] In this embodiment, by utilizing twisted convolution to diffuse the point pilot energy, the pilot and data can coexist on the same resource grid point without a guard band, eliminating the resource overhead caused by the guard band and maximizing the resource utilization of the time-delay Doppler domain, thus significantly improving spectral efficiency. Since the spreading pilot is diffused through twisted convolution, it possesses broadband characteristics similar to noise and good autocorrelation properties. Using a mutual ambiguity function, the pilot energy dispersed throughout the time-delay Doppler domain can be coherently accumulated at the actual path location, while simultaneously suppressing data signal interference incoherently as background noise. This eliminates the need for a highly complex iterative interference cancellation algorithm at the receiver; channel path information can be accurately extracted from a high-interference background with just one mutual ambiguity function operation, significantly reducing the receiver's computational complexity and processing delay. By first estimating the channel path information containing multi-star effects, then using this channel path information to accurately model pilot interference from the twisted convolution result of the spreading pilot, removing the interference from the received signal, and finally recovering the data. This processing logic can effectively separate and eliminate the aggregation interference generated by multi-satellite pilot signals in complex environments where multiple satellite signals are superimposed in the air, thereby accurately recovering the original data transmitted by each satellite and solving the data detection problem caused by severe overlap of pilot signals and data in multi-satellite collaborative transmission.

[0043] In an optional embodiment, the discrete filter is determined based on a rotation factor, the number of resource grid points in the time delay domain, the number of resource grid points in the Doppler domain, the time delay domain index, and the Doppler domain index; the rotation factor is coprime with the number of resource grid points in the time delay domain and the number of resource grid points in the Doppler domain; the rotation factor is used to rotate the self-ambiguity function support region of the spreading pilot to minimize the overlap area in geometric space between the self-ambiguity function support region of the spreading pilot and the self-ambiguity function support region of the data signal.

[0044] This discrete filter can uniformly distribute the energy of the point pilot across the resource grid points in the time-delay Doppler domain, thereby altering the shape of the self-ambiguity function support region of the spreading pilot. This achieves geometric de-overlap with the self-ambiguity function support region of the data signal, reducing mutual interference. The self-ambiguity function support region of the data signal can be represented as a compact cluster centered on the time-delay Doppler origin, reflecting the strong autocorrelation of the data signal at zero time delay and zero Doppler. Due to the introduction of a discrete filter with quadratic phase characteristics, the energy distribution of the self-ambiguity function support region of the spreading pilot is geometrically transformed into a band-shaped region with a specific slope. By setting the frame structure size and a rotation factor coprime to the frame structure size, the tilt angle of this band-shaped region can be precisely controlled, achieving maximum geometric separation between the band-shaped region and the compact cluster of the data signal in the time-delay Doppler domain, i.e., minimizing overlap. This geometric characteristic ensures that even if the pilot component (which can refer to the form of the spread spectrum pilot after transmission through the channel to the receiver) undergoes channel multipath distortion, the cross-correlation energy between the data component (which can refer to the form of the data signal after transmission through the channel to the receiver) and the locally reconstructed spread spectrum pilot cannot be focused, thus exhibiting a noise-like background. That is, the data signal cannot form a concentrated interference peak in the matched filter output of the pilot, thereby ensuring the accurate extraction of channel path information under conditions without guard interval.

[0045] In an optional embodiment, the expression for the spreading pilot can be:

[0046]

[0047] in, It can represent spread spectrum pilot. It can represent a discrete filter. It can represent twisted convolution. It can be represented as coordinates (k) in the time-delayed Doppler domain. p， l p The point pilot frequency, It can represent the time delay domain index of a point in the time delay Doppler domain. It can represent a Doppler index in the time-delay Doppler domain. The number of resource grid points that can represent the delay domain. This can represent the number of resource grid points in the Doppler domain. It can represent the base of the natural logarithm. It can represent the imaginary unit. It can represent the rotation factor, which is carefully selected to meet the weak crystallization condition, ensuring that the channel support region does not overlap with the offset of non-zero resource grid points.

[0048] In one implementation, the expression for the point pilot can be:

[0049] in, It can represent the Kronecker function. It can represent an integer translation index along the time delay axis. It can represent an integer translation index along the Doppler axis, where n, m ∈ Z. This represents the point pilot delay domain index in the delay-Doppler domain. This represents the point pilot Doppler index in the time-delay Doppler domain.

[0050] In an optional embodiment, the received signal and the spreading pilot are processed using a mutual ambiguity function to estimate the channel path information, including: calculating the mutual ambiguity function between the received signal and the spreading pilot to obtain a correlation matrix in the time-delay Doppler domain; filtering each element in the correlation matrix using a detection threshold to extract target elements whose elements are greater than the detection threshold; and obtaining the channel path information of the target elements based on the target elements and the spreading transmit power.

[0051] In this embodiment, the time-delay domain index and Doppler domain index can be traversed to calculate the mutual ambiguity function between the received signal and the local spreading pilot, thus obtaining the correlation matrix in the time-delay Doppler domain. Since the pilot is spread spectrum, the cross-correlation result between the data signal and the spreading pilot appears as a low-amplitude noise-like background in the time-delay Doppler domain. Therefore, the main peak of the mutual ambiguity function can directly correspond to the aggregation channel. The tap coefficients are used. By setting a detection threshold, the channel path information of all satellite links can be directly extracted from the correlation matrix. This channel estimation step is a non-iterative process. Utilizing the characteristics of spread spectrum pilots, the interference of data signals on the pilots is treated as noise background. It eliminates the need for iterative interference cancellation and directly obtains channel state information through the peak value of the mutual ambiguity function, thus improving computational efficiency.

[0052] In one implementation, the expression for each element in the correlation matrix of the time-delay Doppler domain can be:

[0053] in, The coordinates in the correlation matrix can be represented as ( ) elements, This represents another delay domain index within the delay Doppler domain. This represents another Doppler field index within the time-delay Doppler field. This represents the number of resource grid points in the delay domain. This represents the number of resource grid points in the Doppler domain. The coordinates in the time-delay Doppler domain of the received signal can be represented as ( The corresponding received symbol, The coordinates in the time-delay Doppler domain are ( The conjugate result of the spread spectrum pilot, The base of the natural logarithm. It represents the imaginary unit.

[0054] Using a preset detection threshold, each element in the correlation matrix is ​​analyzed. Filtering is performed to extract target elements larger than the detection threshold. Based on the target elements and the spread spectrum transmit power, the channel path information of the target elements is obtained. In one implementation, the expression for the channel path information can be:

[0055] in, The coordinates can be represented as ( Channel path information of the element ) This represents the spread spectrum transmit power. Any target element can be substituted into this formula to calculate the channel path information of that target element.

[0056] In this embodiment, the detection threshold is not limited. In one implementation, the detection threshold can be 2-3 times the noise standard deviation. The noise standard deviation can be obtained from the remaining elements excluding the target element. In one implementation, the noise variance can be the average of the squares of all remaining elements. The noise standard deviation can be the square root of the noise variance.

[0057] In an optional embodiment, obtaining a data estimation signal based on the twisted convolution result of the spreading pilot and the received signal according to the channel path information may include: performing a twisted convolution operation on the spreading pilot and the channel path information to obtain a pilot component; subtracting the pilot component from the received signal to obtain a residual signal; and performing minimum mean square error data detection on the residual signal to obtain the data estimation signal; wherein, the minimum mean square error data detection is based on the channel path information, the data transmission power, and the noise variance to construct a detection filter; the noise variance is obtained from the remaining elements in the correlation matrix excluding the target element.

[0058] In this embodiment, the received signal can be linearly superimposed in the time-delay Doppler domain by pilot components, data components, and additive thermal noise. By performing a subtraction operation, the main pilot interference in the received signal can be eliminated, making the generated residual signal approximately equivalent to a linear combination of the data component and an equivalent noise term. The equivalent noise term includes not only the original additive thermal noise but also the pilot residue caused by channel estimation errors and the weak interference leakage caused by the incomplete cancellation of the cross-correlation between data and pilots.

[0059] In this embodiment, the noise variance can essentially be the equivalent noise power obtained statistically from the background region based on the mutual ambiguity function. Its value represents the sum of the additive thermal noise power and the aforementioned weak residual interference power. By substituting this equivalent noise variance as a key parameter into the minimum mean square error detection filter, the receiver can adaptively balance signal recovery gain and noise / interference suppression strength based on the signal-to-noise ratio (SNR) while compensating for channel distortion in the residual signal. This mechanism ensures that the detection filter not only effectively suppresses background thermal noise but also specifically attenuates weak data interference mixed into the residual signal. Therefore, in complex scenarios with low SNR and unguarded interval superimposed transmission, it maximizes the output SNR, accurately recovers the estimated value of the original data signal, and obtains a highly reliable data estimation signal.

[0060] In summary, the embodiments of this application, by designing a full-domain spread spectrum pilot, eliminate the guard interval and achieve complete superposition transmission of pilot and data in the time-delay-Doppler domain, significantly improving spectral efficiency. Utilizing the characteristics of the spread spectrum sequence, the interference of data to the pilot exhibits noise-like characteristics, allowing channel estimation to be achieved in a single (non-iterative) calculation without complex iterative interference cancellation, thus reducing computational complexity. Taking advantage of the sparsity and distribution differences of multi-satellite channels in the DD domain, an aggregation channel estimation strategy is proposed, capable of simultaneously estimating the equivalent channels of all cooperating satellites.

[0061] Based on the same inventive concept, corresponding to any of the methods in the above embodiments, this application also provides another channel detection method, applied to satellites, which may include: The satellite's transmitted signal is obtained based on the data signal, data transmission power, spreading pilot, and spreading transmission power. This transmitted signal is then sent to the receiving end. The spreading pilot is obtained by twisting and convolving the point pilot using a discrete filter. The receiving end receives the received signal obtained by superimposing the transmitted signals from multiple satellites in the time-delay Doppler domain. Channel path information is estimated by processing the received signal and spreading pilot using a mutual ambiguity function. Based on the twisting and convolving result of the spreading pilot and the received signal using the channel path information, a data estimation signal is obtained. This data estimation signal is an estimate of the actual data signals transmitted by multiple satellites.

[0062] The implementation process of this embodiment can refer to the above content and has the same beneficial effects, so it will not be repeated here.

[0063] It should be noted that the method in this embodiment can be executed by a single device, such as a computer or server. The method can also be applied in a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method in this embodiment, and the multiple devices will interact with each other to complete the method described.

[0064] It should be noted that the above description describes some embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0065] Based on the same inventive concept, corresponding to any of the above-described embodiments, this application also provides a detection device.

[0066] refer to Figure 4 The detection device may include: The acquisition module can be used to acquire the received signal, which is obtained by superimposing and transmitting multiple satellite transmission signals based on data signals, data transmission power, spread spectrum pilots and spread spectrum transmission power in the time-delay Doppler domain; the spread spectrum pilot is obtained by twisting and convolving the point pilot with a discrete filter, so as to uniformly distribute the signal power of the point pilot on the resource grid points in the time-delay Doppler domain.

[0067] The detection module can be used to process the received signal and the spreading pilot using a mutual ambiguity function to estimate the channel path information; based on the twist convolution result of the spreading pilot and the received signal, a data estimation signal is obtained; the data estimation signal is the estimation result of the data signals actually transmitted by multiple satellites.

[0068] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing this application, the functions of each module can be implemented in one or more software and / or hardware.

[0069] The apparatus of the above embodiments is used to implement the corresponding channel detection method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0070] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application 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 program to implement the channel detection method described in any of the above embodiments.

[0071] Figure 5This embodiment illustrates a more specific hardware structure of an electronic device. The device may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.

[0072] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0073] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0074] The input / output interface 1030 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components within the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touchscreens, microphones, various sensors, etc., while output devices may include displays, speakers, vibrators, indicator lights, etc.

[0075] The communication interface 1040 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0076] Bus 1050 includes a pathway for transmitting information between various components of the device, such as processor 1010, memory 1020, input / output interface 1030, and communication interface 1040.

[0077] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0078] The electronic devices described above are used to implement the corresponding channel detection methods in any of the foregoing embodiments and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0079] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the channel detection method as described in any of the above embodiments.

[0080] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0081] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the channel detection method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0082] It should be noted that the embodiments of this application can also be further described in the following ways: A channel detection method, applied at a receiver, includes: acquiring a received signal, wherein the received signal is generated by multiple satellites linearly superimposing their respective transmitted signals in the time-delay Doppler domain after power weighting of their data signals and spread spectrum pilots according to their respective data transmission power and spread spectrum transmission power, and then spatially superimposing and fusing them after transmission through a wireless channel; the spread spectrum pilot is obtained by twisting and convolving a point pilot using a discrete filter to uniformly distribute the signal power of the point pilot on resource grid points in the time-delay Doppler domain; processing the received signal and the spread spectrum pilot using a mutual ambiguity function to estimate channel path information; and obtaining a data estimation signal based on the twisted and convolved result of the spread spectrum pilot and the received signal according to the channel path information; the data estimation signal is an estimation result of the data signals actually transmitted by the multiple satellites.

[0083] Optionally, the method further includes: the discrete filter is determined based on a rotation factor, the number of resource grid points in the time delay domain, the number of resource grid points in the Doppler domain, the time delay domain index, and the Doppler domain index; the rotation factor is coprime with the number of resource grid points in the time delay domain and the number of resource grid points in the Doppler domain; the rotation factor is used to rotate the self-ambiguity function support region of the spreading pilot to minimize the overlap area in geometric space between the self-ambiguity function support region of the spreading pilot and the self-ambiguity function support region of the data signal.

[0084] Optionally, the received signal and the spreading pilot are processed using a mutual ambiguity function to estimate channel path information, including: calculating the mutual ambiguity function between the received signal and the spreading pilot to obtain a correlation matrix in the time-delay Doppler domain; filtering each element in the correlation matrix using the detection threshold to extract target elements whose elements are greater than the detection threshold; and obtaining the channel path information of the target elements based on the target elements and the spreading transmit power.

[0085] Optionally, obtaining a data estimation signal based on the twisted convolution result of the spreading pilot and the received signal according to the channel path information includes: performing a twisted convolution operation on the spreading pilot and the channel path information to reconstruct a pilot interference component; subtracting the pilot interference component from the received signal to obtain a residual signal; and performing minimum mean square error data detection on the residual signal to obtain the data estimation signal; wherein the minimum mean square error data detection is based on the channel path information, the data transmission power, and the noise variance to construct a detection filter; and the noise variance is obtained from the remaining elements in the correlation matrix excluding the target element.

[0086] Optionally, the expression for the spreading pilot is:

[0087]

[0088] in, Indicates spread spectrum pilot, Represents a discrete filter. Represents twisted convolution. This indicates that the coordinates in the time-delay Doppler domain are (k p， l p The point pilot frequency, This represents an index of a delay domain within the delay Doppler domain. This represents a Doppler index in the time-delay Doppler domain. This represents the number of resource grid points in the delay domain. This represents the number of resource grid points in the Doppler domain. The base of the natural logarithm. Represents the imaginary unit. This represents the rotation factor.

[0089] Optionally, the expression for the channel path information is:

[0090]

[0091] in, The coordinates in the time-delay Doppler domain are ( Channel path information, Indicates the spread spectrum transmit power. The coordinates in the time-delay Doppler domain are ( The mutual ambiguity function of ) This represents another delay domain index within the delay Doppler domain. This represents another Doppler field index in the time-delay Doppler field. This represents the number of resource grid points in the delay domain. This represents the number of resource grid points in the Doppler domain. The coordinates in the time-delay Doppler domain of the received signal are ( The corresponding received symbol, The coordinates in the time-delay Doppler domain are ( The conjugate result of the spread spectrum pilot, The base of the natural logarithm. It represents the imaginary unit.

[0092] A channel detection method, applied to a satellite, includes: obtaining the satellite's transmitted signal based on a data signal, data transmission power, spreading pilot, and spreading transmission power; transmitting the transmitted signal to a receiving end; the spreading pilot is obtained by twisting and convolving a point pilot using a discrete filter to uniformly distribute the signal power of the point pilot across resource grid points in the time-delay Doppler domain; the receiving end is used to receive a received signal obtained by superimposing the transmitted signals of multiple satellites in the time-delay Doppler domain; estimating channel path information by processing the received signal and the spreading pilot using a mutual ambiguity function; obtaining a data estimation signal based on the twisted and convolved result of the spreading pilot and the received signal using the channel path information; the data estimation signal is an estimation result of the data signals actually transmitted by the multiple satellites.

[0093] A detection device includes: an acquisition module for acquiring a received signal, wherein the received signal is obtained by superimposing and transmitting transmitted signals from multiple satellites based on data signals, data transmission power, spread spectrum pilots, and spread spectrum transmission power in the time-delay Doppler domain; the spread spectrum pilots are obtained by performing a twist convolution on point pilots using a discrete filter to uniformly distribute the signal power of the point pilots across resource grid points in the time-delay Doppler domain; and a detection module for processing the received signal and the spread spectrum pilots using a mutual ambiguity function to estimate channel path information; and obtaining a data estimation signal based on the twist convolution result of the spread spectrum pilots and the received signal according to the channel path information; wherein the data estimation signal is an estimation result of the data signals actually transmitted by the multiple satellites.

[0094] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the channel detection method.

[0095] A non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the channel detection method.

[0096] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this application (including the claims) is limited to these examples; within the framework of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in the details for the sake of brevity.

[0097] Additionally, to simplify the description and discussion, and to avoid obscuring the embodiments of this application, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring the embodiments of this application, and this also takes into account the fact that the details of the implementation of these block diagram apparatuses are highly dependent on the platform on which the embodiments of this application will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this application, it will be apparent to those skilled in the art that the embodiments of this application can be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0098] Although this application has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0099] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of this application.

Claims

1. A channel detection method, applied at a receiver, comprising: The received signal is obtained by multiple satellites, which respectively weight their data signals and spread spectrum pilots according to their respective data transmission power and spread spectrum transmission power, linearly superimpose them in the time-delay Doppler domain to generate their respective transmitted signals, and then spatially superimpose and fuse them after transmission through a wireless channel; the spread spectrum pilot is obtained by twisting and convolving the point pilot with a discrete filter to uniformly distribute the signal power of the point pilot on the resource grid points in the time-delay Doppler domain; The received signal and the spreading pilot are processed using a mutual ambiguity function to estimate the channel path information; Based on the twist convolution result of the spreading pilot and the received signal according to the channel path information, a data estimation signal is obtained; The data estimation signal is an estimation result of the data signals actually transmitted by the multiple satellites.

2. The method according to claim 1, characterized in that, The discrete filter is determined based on a rotation factor, the number of resource grid points in the time delay domain, the number of resource grid points in the Doppler domain, the time delay domain index, and the Doppler domain index; the rotation factor is coprime to the number of resource grid points in the time delay domain and the number of resource grid points in the Doppler domain. The rotation factor is used to rotate the self-ambiguity function support region of the spreading pilot to minimize the overlap area in geometric space between the self-ambiguity function support region of the spreading pilot and the self-ambiguity function support region of the data signal.

3. The method of claim 1, wherein, The received signal and the spreading pilot are processed using a mutual ambiguity function to estimate channel path information, including: Calculate the mutual ambiguity function between the received signal and the spreading pilot to obtain the correlation matrix in the time-delay Doppler domain; The elements in the correlation matrix are filtered using the detection threshold to extract target elements whose elements are greater than the detection threshold. Based on the target element and the spread spectrum transmit power, the channel path information of the target element is obtained.

4. The method of claim 3, wherein, Based on the twisted convolution result of the spreading pilot and the received signal using the channel path information, a data estimation signal is obtained, including: The pilot interference component is reconstructed by performing a twist convolution operation on the channel path information and the spreading pilot; The pilot interference component is subtracted from the received signal to obtain the residual signal; The residual signal is subjected to minimum mean square error data detection to obtain the data estimation signal; The minimum mean square error data detection is based on the channel path information, the data transmission power, and the noise variance to construct a detection filter; the noise variance is obtained from the remaining elements in the correlation matrix excluding the target element.

5. The method of claim 1, wherein, The expression for the spreading pilot is: ， ， in, Indicates spread spectrum pilot, Represents a discrete filter. Represents twisted convolution. This indicates that the coordinates in the time-delay Doppler domain are (k p， l p The point pilot frequency, This represents an index of a delay domain within the delay Doppler domain. This represents a Doppler index in the time-delay Doppler domain. This represents the number of resource grid points in the delay domain. This represents the number of resource grid points in the Doppler domain. The base of the natural logarithm. Represents the imaginary unit. This represents the rotation factor.

6. The method of claim 1, wherein, The expression for the channel path information is: ， ， in, The coordinates in the time-delay Doppler domain are ( Channel path information, Indicates the spread spectrum transmit power. The coordinates in the time-delay Doppler domain are ( The mutual ambiguity function of ) This represents another delay domain index within the delay Doppler domain. This represents another Doppler field index in the time-delay Doppler field. This represents the number of resource grid points in the delay domain. This represents the number of resource grid points in the Doppler domain. The coordinates in the time-delay Doppler domain of the received signal are ( The corresponding received symbol, The coordinates in the time-delay Doppler domain are ( The conjugate result of the spread spectrum pilot, The base of the natural logarithm. It represents the imaginary unit.

7. A channel detection method, applied to a satellite, comprising: The satellite's transmitted signal is obtained based on the data signal, data transmission power, spread spectrum pilot, and spread spectrum transmission power. The transmitted signal is sent to the receiving end; the spread spectrum pilot is obtained by twisting and convolving the point pilot with a discrete filter to uniformly distribute the signal power of the point pilot on the resource grid points in the time delay Doppler domain. The receiving end is used to receive the received signal obtained by superimposing and transmitting the transmitted signals from multiple satellites in the time-delay Doppler domain; Channel path information is estimated by processing the received signal and the spreading pilot using a mutual ambiguity function; Based on the twist convolution result of the spreading pilot and the received signal according to the channel path information, a data estimation signal is obtained; The data estimation signal is an estimation result of the data signals actually transmitted by the multiple satellites.

8. A detection device, characterized in that, include: The acquisition module is used to acquire the received signal, which is obtained by superimposing and transmitting multiple satellite transmission signals based on data signals, data transmission power, spread spectrum pilots and spread spectrum transmission power in the time-delay Doppler domain. The spread spectrum pilot is obtained by twisting and convolving the point pilot with a discrete filter to uniformly distribute the signal power of the point pilot on the resource grid points in the time-delay Doppler domain. The detection module is used to process the received signal and the spreading pilot using a mutual ambiguity function to estimate the channel path information; Based on the twist convolution result of the spreading pilot and the received signal according to the channel path information, a data estimation signal is obtained; The data estimation signal is an estimation result of the data signals actually transmitted by the multiple satellites.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the method as claimed in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the method of any one of claims 1 to 7.

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