A ris-assisted space-air-ground integrated high-speed mobile communication method and system

Abstract

The application relates to the technical field of wireless communication, and provides a RIS-aided space-air-ground integrated high-speed mobile communication method and system. In the method, a to-be-transmitted information symbol is mapped to a time-delay-Doppler domain of an orthogonal time-frequency space by a transmitting end, is converted into a time-frequency domain signal, is subjected to super-Nyquist signal compression processing by using root-raised cosine pulse shaping, a transmitting signal is generated, and the transmitting signal is sent to a receiving end; a reconfigurable intelligent surface acquires channel state information of a cascade time-delay-Doppler domain from the transmitting end to the reconfigurable intelligent surface and to the receiving end, identifies the strongest propagation path in the channel, adjusts the phases of all reflecting elements so that reflected signals realize constructive interference at the receiving end; the receiving end receives the communication signals reflected by the reconfigurable intelligent surface, performs super-Nyquist matched filtering and sampling, converts the signals into time-delay-Doppler domain signals, performs signal detection in combination with a colored noise covariance matrix introduced by the super-Nyquist signal, and restores original information symbols.

Description

Technical Field

[0001] This application relates to the field of wireless communication technology, and in particular to a RIS-assisted high-speed mobile communication method and system integrating air, space, and ground. Background Technology

[0002] With the development of integrated air-space-ground networks, the requirements for spectral efficiency and reliability of wireless communication in highly mobile scenarios such as high-speed vehicles and low-orbit satellites are continuously increasing. Orthogonal time-frequency spatial modulation can effectively combat the Doppler frequency shift and delay spread caused by high mobility, but its spectral efficiency is limited by the Nyquist criterion. Super-Nyquist signal transmission can overcome the Nyquist limitation and improve spectral efficiency, but it introduces severe inter-symbol interference and colored noise, leading to decreased system reliability and the emergence of faulty circuits.

[0003] Existing technologies that compensate for performance losses by increasing transmit power are severely limited by the input back-off of the power amplifier and the nonlinear characteristics of the peak-to-average power ratio. Summary of the Invention

[0004] This application provides a RIS-assisted high-speed mobile communication method and system integrating air, space, and ground, which aims to solve the problem that existing reconfigurable smart surface-assisted orthogonal time-frequency spatial systems are only used to improve the signal-to-noise ratio, but cannot fundamentally suppress the structured interference of super Nyquist signals, and are difficult to achieve high spectral efficiency and high reliable communication at the same time.

[0005] In a first aspect, embodiments of this application provide a RIS-assisted high-speed air-space-ground integrated mobile communication method, the method comprising: The transmitter maps the information symbols to be transmitted to the time-delay-Doppler domain of the orthogonal time-frequency space, converts them into time-frequency domain signals, performs super Nyquist signal compression processing using root-raised cosine pulse shaping, generates a transmission signal, and sends it to the receiving end. By acquiring cascaded delay-Doppler domain channel state information from the transmitter to itself and then to the receiver through a reconfigurable smart surface, the strongest propagation path in the channel is identified, the optimal quantization phase offset of each reflective element is calculated, and the phase of all reflective elements is adjusted so that the reflected signal achieves constructive interference at the receiver. The receiver receives the communication signal reflected by the reconfigurable smart surface, performs super Nyquist matched filtering and sampling, converts it into a time-delay-Doppler domain signal, and uses a linear minimum mean square error detector combined with the colored noise covariance matrix introduced by the super Nyquist signal to detect the signal and recover the original information symbol.

[0006] In some embodiments, the step of mapping the information symbols to be transmitted to the time-delay-Doppler domain of the orthogonal time-frequency space through the transmitting end and converting them into time-frequency domain signals includes: placing the information symbols to be transmitted sequentially at the corresponding positions of the time-delay-Doppler domain grid in the orthogonal time-frequency space to form a time-delay-Doppler domain symbol matrix, and performing an inverse symplectic fast Fourier transform on the time-delay-Doppler domain symbol matrix to obtain a time-frequency domain signal matrix.

[0007] In some embodiments, the step of using root-raised cosine pulse shaping for super Nyquist signal compression processing to generate a transmit signal and send it to the receiving end includes: convolving each element in the time-frequency domain signal matrix with the root-raised cosine pulse shaping function, arranging the convolved signals according to time intervals smaller than the Nyquist symbol interval, generating a continuous-time transmit signal through Heisenberg transform, and transmitting the transmit signal to the receiving end through a transmit antenna.

[0008] In some embodiments, obtaining the cascaded delay-Doppler domain channel state information from the transmitter to itself and then to the receiver via the reconfigurable smart surface includes: the reconfigurable smart surface obtaining the first link delay-Doppler domain channel response from the transmitter to itself and the second link delay-Doppler domain channel response from itself to the receiver, and cascading and merging the first link channel response and the second link channel response to obtain the cascaded delay-Doppler domain channel state information from the transmitter to the receiver reflected by the reconfigurable smart surface.

[0009] In some embodiments, identifying the strongest propagation path in the channel includes: extracting all non-zero channel gain entries from the concatenated delay-Doppler domain channel state information, calculating the power value of each non-zero channel gain entry, comparing the magnitudes of all power values, and selecting the propagation path corresponding to the non-zero channel gain entry with the largest power value as the strongest propagation path.

[0010] In some embodiments, calculating the optimal quantized phase offset of each reflective element includes: obtaining the total phase value corresponding to the strongest propagation path and the phase value of the strongest propagation path corresponding to each reflective element; subtracting the phase value of the strongest propagation path corresponding to each reflective element from the total phase value of the strongest propagation path to obtain the continuous optimal phase value of each reflective element; quantizing each continuous optimal phase value into a preset discrete phase set to obtain the optimal quantized phase offset of each reflective element.

[0011] In some embodiments, adjusting the phase of all reflective elements to achieve constructive interference of the reflected signals at the receiving end includes: setting the phase of each reflective element of the reconfigurable smart surface to the corresponding optimal quantized phase offset, so that the signals reflected by all reflective elements maintain a consistent phase at the time delay-Doppler position corresponding to the strongest propagation path, thereby achieving constructive interference at the receiving end.

[0012] In some embodiments, the step of receiving the communication signal reflected by the reconfigurable smart surface through the receiving end, performing super Nyquist matched filtering and sampling, and converting it into a time-delay-Doppler domain signal includes: receiving the communication signal reflected by the reconfigurable smart surface through the receiving antenna, performing root-raised cosine matched filtering on the communication signal, performing time-frequency domain sampling on the filtered signal according to the super Nyquist symbol interval to obtain a time-frequency domain received signal matrix, and performing symplectic fast Fourier transform on the time-frequency domain received signal matrix to obtain a time-delay-Doppler domain received signal.

[0013] In some embodiments, the step of using a linear minimum mean square error detector combined with a colored noise covariance matrix introduced by the super Nyquist signal to detect the signal and recover the original information symbols includes: constructing a colored noise covariance matrix based on the pulse shaping characteristics of the super Nyquist signal; constructing a linear minimum mean square error detection matrix by combining the cascaded time-delay-Doppler domain effective channel matrix and the colored noise covariance matrix; using the linear minimum mean square error detection matrix to detect the time-delay-Doppler domain received signal to obtain the estimated information symbols and recover the original information symbols.

[0014] Secondly, this application provides a RIS-assisted integrated air-space-ground high-speed mobile communication system, the system comprising: The signal transmission unit is used to map the information symbols to be transmitted to the time-delay-Doppler domain of the orthogonal time-frequency space through the transmitter, convert them into time-frequency domain signals, perform super Nyquist signal compression processing using root raised cosine pulse shaping, generate a transmission signal and send it to the receiver. The interference adjustment unit is used to obtain the cascaded delay-Doppler domain channel state information from the transmitter to itself and then to the receiver through the reconfigurable smart surface, identify the strongest propagation path in the channel, calculate the optimal quantization phase offset of each reflective element, and adjust the phase of all reflective elements so that the reflected signal achieves constructive interference at the receiver. The symbol recovery unit is used to receive the communication signal reflected by the reconfigurable smart surface through the receiver, perform super Nyquist matched filtering and sampling, convert it into a time-delay-Doppler domain signal, and use a linear minimum mean square error detector combined with the colored noise covariance matrix introduced by the super Nyquist signal to detect the signal and recover the original information symbol.

[0015] This application combines super Nyquist signal transmission with orthogonal time-frequency spatial modulation to transmit more symbols within the same bandwidth and time resources, significantly improving the system's spectral efficiency. By actively reshaping the cascaded delay-Doppler channel through a reconfigurable smart surface, constructive interference of the reflected signal is achieved at the receiver, effectively suppressing structured interference and colored noise introduced by the super Nyquist signal, avoiding faulty backplanes, and ensuring communication reliability in high-mobility scenarios. The passive beamforming gain provided by the reconfigurable smart surface reduces the system's transmit power requirements, expands the available input back-off margin of the power amplifier, reduces nonlinear distortion, and improves system energy efficiency. A discrete phase optimization algorithm based on the strongest propagation path and a linear minimum mean square error detector combined with the colored noise covariance matrix are employed to control computational complexity while ensuring performance.

[0016] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic flowchart illustrating the steps of a RIS-assisted high-speed mobile communication method integrating air, space, and ground, according to an embodiment of this application. Figure 2 This is a schematic diagram illustrating the principle of a RIS-assisted high-speed mobile communication method integrating air, space, and ground, provided in an embodiment of this application. Figure 3 This is a schematic block diagram of a RIS-assisted air-space-ground integrated high-speed mobile communication system provided in one embodiment of this application; Figure 4 This is a schematic block diagram of the structure of a computer device provided in an embodiment of this application.

[0019] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0022] It should be understood that, in order to clearly describe the technical solutions of the embodiments of the present invention, the terms "first" and "second" are used in the embodiments of the present invention to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and the terms "first" and "second" are not necessarily different.

[0023] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0024] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0025] With the rapid development of integrated air-space-ground networks, highly mobile terminals such as high-speed vehicles, low-orbit satellites, and high-altitude platforms place extremely high demands on the spectral efficiency and transmission reliability of wireless communication. Orthogonal Time-Frequency Space (OTFS) modulation technology, by mapping information symbols to the delay-Doppler (DD) domain, can effectively combat Doppler frequency shift and delay spread in highly mobile scenarios, achieving stable channel characterization. However, traditional OTFS systems are limited by the Nyquist criterion, resulting in an inherent upper limit to their spectral efficiency.

[0026] Super Nyquist (FTN) signal transmission technology overcomes the Nyquist rate limit by compressing symbol spacing, enabling the transmission of more symbols within the same bandwidth and significantly improving spectral efficiency. However, the non-orthogonal pulse shaping of FTN signals introduces severe structured inter-symbol interference (ISI) and colored noise, leading to increased system bit error rate and the emergence of error boards. Compensating for performance loss solely by increasing transmit power is severely limited by the nonlinear characteristics of power amplifier (PA) input back-off (IBO) and peak-to-average power ratio (PAPR), which not only reduces energy efficiency but also increases hardware costs.

[0027] Existing OTFS systems assisted by reconfigurable smart surfaces (RIS) only use RIS as a signal-to-noise ratio (SNR) enhancer, improving the received signal power through passive beamforming. This cannot fundamentally suppress the structured interference introduced by FTN signals, making it difficult to achieve both high spectral efficiency and high-reliability communication simultaneously.

[0028] To address the aforementioned technical problems, this invention proposes a RIS-assisted high-speed mobile communication method integrating air, space, and ground. By actively reshaping the cascaded DD domain channel through RIS, FTN signal impairment is suppressed at its source. This method breaks through the upper limit of spectral efficiency without reducing transmission reliability, while simultaneously optimizing the operating conditions of the power amplifier and improving system energy efficiency.

[0029] Please refer to Figure 1 This application provides a RIS-assisted high-speed air-space-ground integrated mobile communication method applied to computer equipment. The computer equipment can be deployed on a single server or a server cluster. It can also be deployed on handheld terminals, laptops, wearable devices, or robots, etc. It should be noted that all information involved in the method provided in this application is extracted with the authorization of the relevant user and in accordance with relevant regulations, and will not infringe on user privacy.

[0030] The RIS-assisted air-space-ground integrated high-speed mobile communication system described in this invention is as follows: Figure 2As shown, the system comprises three core components: a transmitter, a reconfigurable smart surface (RIS), and a receiver. The transmitter performs DD-domain mapping, time-frequency domain conversion, FTN pulse shaping, and signal transmission. Internally, it includes an information symbol mapping module, a time-frequency domain conversion module, an FTN signal compression module, and a transmitting antenna. The reconfigurable smart surface consists of multiple independently adjustable phase-adjustable reflective elements. It acquires cascaded DD-domain channel state information, identifies the strongest propagation path, calculates and adjusts the phase of the reflective elements, enabling constructive interference of the reflected signal at the receiver. Internally, it includes a channel state information acquisition module, a strongest path identification module, an optimal phase calculation module, and a phase adjustment execution module. The receiver performs reflected signal reception, FTN matched filtering, DD-domain conversion, and signal detection. Internally, it includes a receiving antenna, an FTN matched filtering module, a DD-domain conversion module, and a linear minimum mean square error (LMMSE) detection module.

[0031] The system's signal flow is as follows: the transmitter generates an FTN-OTFS signal and transmits it towards the RIS; the RIS adjusts the phase of each reflecting element according to the real-time channel status, reflecting the signal to the receiver; the receiver processes the reflected signal to recover the original information symbols.

[0032] The provided RIS-assisted high-speed air-space-ground integrated mobile communication method includes steps S101 to S103. Details are as follows: Step S101. The information symbols to be transmitted are mapped to the time-delay-Doppler domain of the orthogonal time-frequency space by the transmitter, converted into a time-frequency domain signal, and subjected to super Nyquist signal compression processing using root-raised cosine pulse shaping to generate a transmission signal and send it to the receiver.

[0033] Specifically, the core objective of this step is to convert the binary information to be transmitted into a continuous-time transmit signal conforming to the FTN-OTFS modulation specification, thereby realizing the mapping of information symbols in the DD domain and FTN compressed transmission. The specific implementation process is as follows: Information symbol modulation maps the binary bit stream to be transmitted into complex information symbols according to a preset modulation method (such as binary phase shift keying (BPSK), quadrature amplitude modulation (QAM), etc.), with each complex symbol carrying a fixed number of bits of information.

[0034] DD domain symbol mapping involves sequentially placing modulated complex information symbols into a predefined DD domain grid to form a two-dimensional DD domain symbol matrix. The size of the DD domain grid is determined by the number of delay cells M and the number of Doppler cells N. The rows of the grid correspond to the delay dimension, and the columns correspond to the Doppler dimension. Each grid position corresponds to an independent DD domain resource unit.

[0035] Time-frequency domain conversion transforms the DD domain signal into a time-frequency (TF) domain signal matrix by performing an inverse symplectic fast Fourier transform (ISFFT) on the DD domain symbol matrix. ISFFT is the core transform of OTFS modulation, enabling orthogonal mapping between the DD and TF domains and ensuring distortion-free signal conversion between the two domains.

[0036] FTN pulse shaping and compression achieves signal compression by using a root-raised cosine (RRC) pulse shaping filter to pulse shape each element in the time-frequency domain signal matrix and arranging the pulse-shaped signals at time intervals smaller than the Nyquist symbol interval. The roll-off factor of the RRC filter is typically set to 0.2~0.5, and the symbol period span is set to 6~10 symbol intervals to balance out-of-band radiation and inter-symbol interference.

[0037] The continuous-time signal generation and transmission process converts the discrete time-frequency domain signal into a continuous-time transmission signal through the Heisenberg transform. The continuous-time transmission signal is then amplified by a power amplifier and finally transmitted to the reconfigurable smart surface via a transmitting antenna.

[0038] Step S102. Obtain the cascaded delay-Doppler domain channel state information from the transmitter to itself and then to the receiver through the reconfigurable smart surface, identify the strongest propagation path in the channel, calculate the optimal quantization phase offset of each reflective element, and adjust the phase of all reflective elements so that the reflected signal achieves constructive interference at the receiver.

[0039] Specifically, the core objective of this step is to proactively sense the wireless channel state through RIS, optimize the phase of each reflecting element, reshape the cascaded DD domain channel, and enable constructive interference of the reflected signal at the receiving end, thereby suppressing structured interference introduced by the FTN signal at its source. The specific implementation process is as follows: The RIS (Resonance Information System) uses channel estimation techniques to obtain the first DD domain channel response from the transmitter to the RIS and the second DD domain channel response from the RIS to the receiver. The channel responses of the two links are then concatenated and combined to obtain the concatenated DD domain channel state information from the transmitter to the receiver after reflection by the RIS. Channel estimation can employ a pilot-assisted method, inserting known pilot symbols into the transmitted signal, allowing the receiver to estimate channel parameters using these pilot symbols.

[0040] The strongest propagation path identification involves extracting all non-zero channel gain entries from the cascaded DD domain channel state information, calculating the power value (i.e., the square of the channel gain magnitude) of each non-zero channel gain entry, comparing the magnitudes of all power values, and selecting the propagation path corresponding to the non-zero channel gain entry with the largest power value as the strongest propagation path. The strongest propagation path carries most of the signal energy and is the critical path that determines the system's transmission performance.

[0041] The optimal quantization phase offset calculation is performed by obtaining the total phase value corresponding to the strongest propagation path and the phase value of the strongest propagation path corresponding to each RIS reflector. The total phase value of the strongest propagation path is subtracted from the phase value of the strongest propagation path corresponding to each reflector to obtain the continuous optimal phase value for each reflector. Considering the phase adjustment capability of actual RIS hardware, each continuous optimal phase value is quantized into a preset discrete phase set to obtain the optimal quantization phase offset for each reflector. The size of the discrete phase set is determined by the number of phase quantization bits in the RIS. For example, 3-bit quantization corresponds to 8 discrete phase values: 0, π / 4, π / 2, 3π / 4, π, 5π / 4, 3π / 2, and 7π / 4.

[0042] Phase adjustment of the reflective elements is achieved by setting the phase of each reflective element of the RIS to its corresponding optimal quantized phase offset, ensuring that the signals reflected by all reflective elements maintain phase consistency at the time delay-Doppler position corresponding to the strongest propagation path, thus realizing constructive interference at the receiver. The frequency of phase adjustment is matched with the channel coherence time, maintaining phase invariance within the channel coherence time to reduce control overhead.

[0043] Step S103. Receive the communication signal reflected by the reconfigurable smart surface through the receiver, perform super Nyquist matched filtering and sampling, convert it into a time-delay-Doppler domain signal, and use a linear minimum mean square error detector combined with the colored noise covariance matrix introduced by the super Nyquist signal to detect the signal and recover the original information symbol.

[0044] Specifically, the core objective of this step is to process the received reflected signal, suppress colored noise and inter-symbol interference introduced by the FTN signal, and accurately recover the original information symbols. The specific implementation process is as follows: The reflected signal receiver receives the communication signal reflected by the RIS via a receiving antenna, and then amplifies the received signal by inputting it into a low-noise amplifier to improve the signal-to-noise ratio.

[0045] FTN matched filtering and time-frequency domain sampling: The received signal is matched-filtered using a root-raised cosine matched filter with the same parameters as the transmitter to maximize the output signal-to-noise ratio. The filtered signal is then sampled in the time-frequency domain according to the same super Nyquist symbol interval as the transmitter to obtain a discrete time-frequency domain received signal matrix.

[0046] DD domain conversion converts the time-frequency domain signal into a DD domain received signal by performing a symplectic fast Fourier transform (SFFT) on the received signal matrix. SFFT is the inverse transform of ISFFT, which can map the received signal from the TF domain back to the DD domain, enabling coherent signal reception.

[0047] LMMSE signal detection constructs a colored noise covariance matrix based on the pulse shaping characteristics of the FTN signal, and combines this with the cascaded DD domain effective channel matrix and the colored noise covariance matrix to construct the LMMSE detection matrix. The LMMSE detection matrix is ​​then used to detect the received signal in the DD domain to obtain the estimated information symbols. The LMMSE detector can effectively suppress colored noise and inter-symbol interference introduced by the FTN signal under the minimum mean square error criterion, balancing detection performance and computational complexity.

[0048] Original information symbol recovery involves demodulating the estimated information symbols, converting the complex symbols into a binary bit stream, and recovering the original transmitted information.

[0049] In some embodiments, the step of mapping the information symbols to be transmitted to the time-delay-Doppler domain of the orthogonal time-frequency space through the transmitting end and converting them into time-frequency domain signals includes: placing the information symbols to be transmitted sequentially at the corresponding positions of the time-delay-Doppler domain grid in the orthogonal time-frequency space to form a time-delay-Doppler domain symbol matrix, and performing an inverse symplectic fast Fourier transform on the time-delay-Doppler domain symbol matrix to obtain a time-frequency domain signal matrix.

[0050] This embodiment details the specific implementation of step S101, "mapping the information symbols to be transmitted to the time-delay-Doppler domain of the orthogonal time-frequency space and converting them into time-frequency domain signals." The DD domain grid is defined by pre-defining its size as M×N, where M is the number of delay bins and N is the number of Doppler bins. For example, setting M=32 and N=32 forms a 32×32 DD domain grid, containing 1024 DD domain resource elements. The resolution of the delay bin is Δτ=1 / (MΔf), and the resolution of the Doppler bin is Δν=1 / (NT_F), where Δf is the subcarrier spacing and T_F is the FTN symbol spacing.

[0051] Information symbols are placed sequentially into their corresponding positions in the DD domain grid, either in row-major or column-major order, forming a DD domain symbol matrix X^DD∈C^(M×N). For example, using row-major order, the first symbol is placed in row 0, column 0, the second symbol in row 0, column 1, and so on, until all symbols are placed. If the number of information symbols is less than the number of DD domain resource units, the remaining positions are filled with zero symbols.

[0052] The inverse symplectic fast Fourier transform (ISFFT) is calculated by performing an ISFFT on the DD-domain symbol matrix X^DD to obtain the time-frequency domain signal matrix X∈C^(M×N). The formula for calculating ISFFT is: X[m,n]=(1 / √(MN))×Σ(l=0 to M-1)Σ(k=0 to N-1)x[l,k]×e^(j2π(ml / M-nk / N)); Where m=0,1,...,M-1 is the time index in the time-frequency domain, n=0,1,...,N-1 is the frequency index in the time-frequency domain, and x[l,k] is the element in the l-th row and k-th column of the DD domain symbol matrix.

[0053] The time-frequency domain signal output completes the time-frequency domain conversion process by outputting the calculated time-frequency domain signal matrix X to the subsequent FTN pulse shaping module.

[0054] In some embodiments, the step of using root-raised cosine pulse shaping for super Nyquist signal compression processing to generate a transmit signal and send it to the receiving end includes: convolving each element in the time-frequency domain signal matrix with the root-raised cosine pulse shaping function, arranging the convolved signals according to time intervals smaller than the Nyquist symbol interval, generating a continuous-time transmit signal through Heisenberg transform, and transmitting the transmit signal to the receiving end through a transmit antenna.

[0055] This embodiment details the specific implementation of step S101, "using root-raised cosine pulse shaping for super Nyquist signal compression processing to generate a transmit signal and send it towards the receiver." The root-raised cosine pulse shaping filter design includes: designing a root-raised cosine pulse shaping filter with a roll-off factor β = 0.25 and a symbol period span s = 8, meaning the filter covers 8 symbol intervals. The time-domain expression of the root-raised cosine pulse is: g_tx(t)=(sin(πt(1-β) / T_0)+4βt / T_0×cos(πt(1+β) / T_0)) / (πt / T_0×(1-(4βt / T_0)^2)); Where T_0 is the Nyquist symbol interval.

[0056] FTN signal compression: Set the FTN compression factor α = 0.8, i.e., the FTN symbol interval T_F = αT_0 = 0.8T_0, which is less than the Nyquist symbol interval T_0. Convolve each element X[m,n] in the time-frequency domain signal matrix X with the root-raised cosine pulse g_tx(t) to obtain a pulse-shaped discrete signal sequence. Arrange the convolved signal sequence according to the time interval T_F to achieve FTN signal compression.

[0057] The Heisenberg transform generates continuous-time signals: The Heisenberg transform converts a discrete pulse-shaped signal into a continuous-time transmitted signal s(t). The formula for calculating the Heisenberg transform is: s(t)=Σ(m=0 to M-1)Σ(n=0 to N-1); X[m,n]×g_tx(t-nαT_0)×e^(j2πmΔf(t-nαT_0)); Where Δf is the subcarrier spacing.

[0058] Signal transmission involves amplifying the continuous-time transmitted signal s(t) by inputting it into a power amplifier, and adjusting the gain of the power amplifier to achieve a preset average power of the transmitted signal. The amplified transmitted signal is then transmitted towards the reconfigurable smart surface via a transmitting antenna.

[0059] In some embodiments, obtaining the cascaded delay-Doppler domain channel state information from the transmitter to itself and then to the receiver via the reconfigurable smart surface includes: the reconfigurable smart surface obtaining the first link delay-Doppler domain channel response from the transmitter to itself and the second link delay-Doppler domain channel response from itself to the receiver, and cascading and merging the first link channel response and the second link channel response to obtain the cascaded delay-Doppler domain channel state information from the transmitter to the receiver reflected by the reconfigurable smart surface.

[0060] This embodiment details the specific implementation of step S102, "obtaining the cascaded delay-Doppler domain channel state information from the transmitter to itself and then to the receiver through a reconfigurable smart surface." The first link channel estimation involves the transmitter transmitting a pre-designed pilot signal, with each reflective element of the RIS sequentially set to total reflection (phase 0), and the receiver receiving the pilot signal reflected by the RIS. The first link DD domain channel response h_q^1(τ,ν) from the transmitter to the q-th reflective element of the RIS is estimated using a least squares (LS) or least mean square error (MMSE) channel estimation algorithm, where q = 1, 2, ..., Q, and Q is the total number of reflective elements in the RIS.

[0061] Each reflector of the RIS transmits a pilot signal in sequence (or by reflecting a known pilot signal). The receiver receives the pilot signal transmitted by the RIS and estimates the second link DD domain channel response h_q^2(τ,ν) from the q-th reflector of the RIS to the receiver using the same channel estimation algorithm.

[0062] The cascaded channel response merging is achieved by cascading and merging the first link channel response h_q^1(τ,ν) and the second link channel response h_q^2(τ,ν) to obtain the cascaded DD domain channel response h_q^eff(τ,ν)=h_q^1(τ,ν)×h_q^2(τ,ν) corresponding to the qth reflecting element.

[0063] The total cascaded channel state information is generated by merging the cascaded DD domain channel responses corresponding to all Q reflective elements to obtain the total cascaded DD domain channel state information H^eff(τ,ν)=Σ(q=1 to Q)Φ_q×h_q^eff(τ,ν) from the transmitter to the receiver after RIS reflection, where Φ_q is the reflection coefficient of the q-th reflective element.

[0064] In some embodiments, identifying the strongest propagation path in the channel includes: extracting all non-zero channel gain entries from the concatenated delay-Doppler domain channel state information, calculating the power value of each non-zero channel gain entry, comparing the magnitudes of all power values, and selecting the propagation path corresponding to the non-zero channel gain entry with the largest power value as the strongest propagation path.

[0065] The embodiment details the specific implementation of "identifying the strongest propagation path in the channel" in step S102. Non-zero channel gain entry extraction: Traverse all elements of the total concatenated DD domain channel state information H^eff(τ,ν) to extract all non-zero channel gain entries, forming a non-zero channel gain set {h_tot(k_p,l_p)}, where p=1,2,...,P, P is the number of non-zero channel gain entries, k_p is the Doppler index of the p-th path, and l_p is the delay index of the p-th path.

[0066] Channel gain power is calculated by determining the power value Power[p] = |h_tot(k_p,l_p)|^2 for each non-zero channel gain entry, where | | represents the modulus of a complex number.

[0067] Maximum power value comparison: Compare the power values ​​of all non-zero channel gain entries and find the maximum value Power_max=max{Power[1],Power[2],...,Power[P]}.

[0068] The strongest propagation path is determined by identifying the propagation path corresponding to the non-zero channel gain entry with a power value equal to Power_max, denoted as p*, with its corresponding Doppler index k*=k_p* and delay index l*=l_p*.

[0069] In some embodiments, calculating the optimal quantized phase offset of each reflective element includes: obtaining the total phase value corresponding to the strongest propagation path and the phase value of the strongest propagation path corresponding to each reflective element; subtracting the phase value of the strongest propagation path corresponding to each reflective element from the total phase value of the strongest propagation path to obtain the continuous optimal phase value of each reflective element; quantizing each continuous optimal phase value into a preset discrete phase set to obtain the optimal quantized phase offset of each reflective element.

[0070] This embodiment details the specific implementation of step S102, "calculating the optimal quantized phase offset for each reflecting element." Phase value extraction: Extract the total phase value θ_tot = arg(h_tot(k*,l*)) corresponding to the strongest propagation path, where arg( ) represents the argument of a complex number, with a value range of [0, 2π). Extract the phase value θ_q=arg(h_q^eff(k*,l*)) of the strongest propagation path corresponding to each RIS reflector element, where q=1,2,...,Q.

[0071] The continuous optimal phase value is calculated by taking the q-th reflecting element and calculating its continuous optimal phase value θ_q^opt = θ_tot - θ_q. If the calculated θ_q^opt is less than 0, add 2π to make it fall within the range [0, 2π); if the calculated θ_q^opt is greater than or equal to 2π, subtract 2π to make it fall within the range [0, 2π).

[0072] Discrete phase set generation is achieved by generating a discrete phase set F_B = {0, 2π / 2^B, 2 × 2π / 2^B, ..., (2^B - 1) × 2π / 2^B} based on the number of phase quantization bits B of the RIS. For example, when B = 3, F_3 = {0, π / 4, π / 2, 3π / 4, π, 5π / 4, 3π / 2, 7π / 4}.

[0073] The optimal quantized phase offset is determined by finding the discrete phase value with the smallest difference from the continuous optimal phase value θ_q^opt in the discrete phase set F_B for each reflective element. This discrete phase value is then used as the optimal quantized phase offset θ_q^qua for that reflective element. That is, θ_q^qua = argmin_{θ∈F_B}|θ-θ_q^opt|.

[0074] In some embodiments, adjusting the phase of all reflective elements to achieve constructive interference of the reflected signals at the receiving end includes: setting the phase of each reflective element of the reconfigurable smart surface to the corresponding optimal quantized phase offset, so that the signals reflected by all reflective elements maintain a consistent phase at the time delay-Doppler position corresponding to the strongest propagation path, thereby achieving constructive interference at the receiving end.

[0075] This embodiment details the specific implementation of step S102, "adjusting the phase of all reflective elements to achieve constructive interference of the reflected signals at the receiving end." Phase control command generation: Based on the calculated optimal quantized phase offset θ_q^qua for each reflective element, a corresponding phase control command is generated. The phase control command includes the reflective element's number and its corresponding quantized phase value.

[0076] Phase adjustment commands are issued by sending phase control commands to the RIS's intelligent controller, which then configures the phase adjustment circuit for each reflective element according to the commands.

[0077] The phase configuration of the reflective element is achieved by adjusting the reflection phase of each reflective element to the corresponding optimal quantized phase offset θ_q^qua according to the received control command through the phase adjustment circuit of each reflective element.

[0078] Constructive interference verification involves receiving the pilot signal reflected by the RIS at the receiver and measuring the power of the received signal. If the received signal power reaches a preset threshold, it indicates that the phases of all reflecting elements are correctly configured, and the reflected signal achieves constructive interference at the receiver. If the received signal power does not reach the preset threshold, the channel estimation and phase optimization process is repeated.

[0079] In some embodiments, the step of receiving the communication signal reflected by the reconfigurable smart surface through the receiving end, performing super Nyquist matched filtering and sampling, and converting it into a time-delay-Doppler domain signal includes: receiving the communication signal reflected by the reconfigurable smart surface through the receiving antenna, performing root-raised cosine matched filtering on the communication signal, performing time-frequency domain sampling on the filtered signal according to the super Nyquist symbol interval to obtain a time-frequency domain received signal matrix, and performing symplectic fast Fourier transform on the time-frequency domain received signal matrix to obtain a time-delay-Doppler domain received signal.

[0080] This embodiment details the specific implementation of step S103, "receiving the communication signal reflected by the reconfigurable smart surface through the receiving end, performing super Nyquist matched filtering and sampling, and converting it into a time-delay-Doppler domain signal." The reflected signal is received and amplified as follows: the communication signal y(t) reflected by the RIS is received through the receiving antenna, and the received signal is input to a low-noise amplifier for amplification. The noise figure of the low-noise amplifier is set to be less than 2dB to ensure the signal-to-noise ratio of the received signal.

[0081] FTN matched filtering uses a root-raised cosine matched filter g_rx(t)=g_tx*(-t) with the same parameters as the transmitter to perform matched filtering on the amplified received signal, resulting in the filtered signal y_f(t)=y(t)g_rx(t), where y represents the convolution operation.

[0082] Time-frequency domain sampling is performed on the filtered signal y_f(t) using the same FTN symbol interval T_F and subcarrier interval Δf as the transmitter, resulting in a time-frequency domain received signal matrix Y∈C^(M×N). The sampling time is t=nαT_0, f=mΔf, where m=0,1,...,M-1, n=0,1,...,N-1, i.e., Y[m,n]=y_f(nαT_0)×e^(-j2πmΔfnαT_0).

[0083] The symplectic Fast Fourier Transform (SFFT) is performed on the received signal matrix Y in the time-frequency domain to obtain the received signal matrix Y^DD∈C^(M×N) in the DD domain. The formula for calculating the SFFT is: Y^DD[l,k]=(1 / √(MN))×Σ(m=0 to M-1)Σ(n=0 to N-1)Y[m,n]×e^(-j2π(ml / M-nk / N)); Where l=0,1,...,M-1 is the delayed index of the DD field, and k=0,1,...,N-1 is the Doppler index of the DD field.

[0084] The DD domain signal output completes the DD domain conversion process by outputting the calculated DD domain received signal matrix Y^DD to the subsequent LMMSE detection module.

[0085] In some embodiments, the step of using a linear minimum mean square error detector combined with a colored noise covariance matrix introduced by the super Nyquist signal to detect the signal and recover the original information symbols includes: constructing a colored noise covariance matrix based on the pulse shaping characteristics of the super Nyquist signal; constructing a linear minimum mean square error detection matrix by combining the cascaded time-delay-Doppler domain effective channel matrix and the colored noise covariance matrix; using the linear minimum mean square error detection matrix to detect the time-delay-Doppler domain received signal to obtain the estimated information symbols and recover the original information symbols.

[0086] This embodiment details the specific implementation of step S103, "using a linear minimum mean square error detector combined with a colored noise covariance matrix introduced by the super Nyquist signal for signal detection to recover the original information symbols." The colored noise covariance matrix is ​​constructed as follows: Based on the root-raised cosine pulse shaping characteristics of the FTN signal, a colored noise covariance matrix G∈C^(MN×MN) is constructed. G is a Topplitz matrix, and the element G[i,j] in the i-th row and j-th column is determined by the value of the autocorrelation function of the root-raised cosine pulse at time (ij)T_F, i.e., G[i,j]=R_g((ij)T_F), where R_g(τ)=∫g_tx(t)g_rx(t-τ)dt is the autocorrelation function of the root-raised cosine pulse.

[0087] The effective channel matrix is ​​constructed by using the channel state information of the concatenated DD domain to construct the effective channel matrix H_eff∈C^(MN×MN). The DD domain symbol matrix and the received signal matrix are vectorized to obtain x^DD=vec(X^DD)∈C^(MN×1) and y^DD=vec(Y^DD)∈C^(MN×1). The input-output relationship of the DD domain is then y^DD=H_effx^DD+z^DD, where z^DD is the colored noise vector in the DD domain, and its covariance matrix is ​​Σ_z=σ^2G, where σ^2 is the noise power.

[0088] The LMMSE detection matrix is ​​constructed by constructing the LMMSE detection matrix W=(H_eff^HH_eff+σ^2G)^(-1)H_eff^H, where H_eff^H is the conjugate transpose of H_eff.

[0089] Signal detection is performed by using the LMMSE detection matrix W to detect the received signal vector y^DD in the DD domain, and the estimated information symbol vector x^DD_hat=Wy^DD is obtained.

[0090] Information symbol recovery is achieved by rearranging the estimated information symbol vector x^DD_hat into an M×N matrix form to obtain the estimated DD field symbol matrix X^DD_hat. Demodulation of each element in X^DD_hat converts the complex symbols into a binary bit stream, thus recovering the original transmitted information.

[0091] Please see Figure 3 As shown, Figure 3 This is a schematic diagram of the structure of a RIS-assisted integrated air-space-ground high-speed mobile communication system 200 provided in this application embodiment. The RIS-assisted integrated air-space-ground high-speed mobile communication system 200 is used to execute the steps of the RIS-assisted integrated air-space-ground high-speed mobile communication method shown in the above embodiments. The RIS-assisted integrated air-space-ground high-speed mobile communication system 200 can be a single server or a server cluster, or it can be a terminal, such as a handheld terminal, a laptop computer, a wearable device, or a robot.

[0092] like Figure 3 As shown, the RIS-assisted air-space-ground integrated high-speed mobile communication system 200 includes: The signal transmitting unit 201 is used to map the information symbols to be transmitted to the time delay-Doppler domain of the orthogonal time-frequency space through the transmitting end, convert them into time-frequency domain signals, perform super Nyquist signal compression processing using root raised cosine pulse shaping, generate a transmission signal and send it to the receiving end. Interference adjustment unit 202 is used to obtain cascaded delay-Doppler domain channel state information from the transmitter to itself and then to the receiver through a reconfigurable smart surface, identify the strongest propagation path in the channel, calculate the optimal quantization phase offset of each reflective element, and adjust the phase of all reflective elements so that the reflected signal achieves constructive interference at the receiver. Symbol recovery unit 203 is used to receive the communication signal reflected by the reconfigurable smart surface through the receiver, perform super Nyquist matched filtering and sampling, convert it into a time delay-Doppler domain signal, and use a linear minimum mean square error detector combined with the colored noise covariance matrix introduced by the super Nyquist signal to detect the signal and recover the original information symbol.

[0093] In some embodiments, the step of mapping the information symbols to be transmitted to the time-delay-Doppler domain of the orthogonal time-frequency space through the transmitting end and converting them into time-frequency domain signals includes: placing the information symbols to be transmitted sequentially at the corresponding positions of the time-delay-Doppler domain grid in the orthogonal time-frequency space to form a time-delay-Doppler domain symbol matrix, and performing an inverse symplectic fast Fourier transform on the time-delay-Doppler domain symbol matrix to obtain a time-frequency domain signal matrix.

[0094] In some embodiments, the step of using root-raised cosine pulse shaping for super Nyquist signal compression processing to generate a transmit signal and send it to the receiving end includes: convolving each element in the time-frequency domain signal matrix with the root-raised cosine pulse shaping function, arranging the convolved signals according to time intervals smaller than the Nyquist symbol interval, generating a continuous-time transmit signal through Heisenberg transform, and transmitting the transmit signal to the receiving end through a transmit antenna.

[0095] In some embodiments, obtaining the cascaded delay-Doppler domain channel state information from the transmitter to itself and then to the receiver via the reconfigurable smart surface includes: the reconfigurable smart surface obtaining the first link delay-Doppler domain channel response from the transmitter to itself and the second link delay-Doppler domain channel response from itself to the receiver, and cascading and merging the first link channel response and the second link channel response to obtain the cascaded delay-Doppler domain channel state information from the transmitter to the receiver reflected by the reconfigurable smart surface.

[0096] In some embodiments, identifying the strongest propagation path in the channel includes: extracting all non-zero channel gain entries from the concatenated delay-Doppler domain channel state information, calculating the power value of each non-zero channel gain entry, comparing the magnitudes of all power values, and selecting the propagation path corresponding to the non-zero channel gain entry with the largest power value as the strongest propagation path.

[0097] In some embodiments, calculating the optimal quantized phase offset of each reflective element includes: obtaining the total phase value corresponding to the strongest propagation path and the phase value of the strongest propagation path corresponding to each reflective element; subtracting the phase value of the strongest propagation path corresponding to each reflective element from the total phase value of the strongest propagation path to obtain the continuous optimal phase value of each reflective element; quantizing each continuous optimal phase value into a preset discrete phase set to obtain the optimal quantized phase offset of each reflective element.

[0098] In some embodiments, adjusting the phase of all reflective elements to achieve constructive interference of the reflected signals at the receiving end includes: setting the phase of each reflective element of the reconfigurable smart surface to the corresponding optimal quantized phase offset, so that the signals reflected by all reflective elements maintain a consistent phase at the time delay-Doppler position corresponding to the strongest propagation path, thereby achieving constructive interference at the receiving end.

[0099] In some embodiments, the step of receiving the communication signal reflected by the reconfigurable smart surface through the receiving end, performing super Nyquist matched filtering and sampling, and converting it into a time-delay-Doppler domain signal includes: receiving the communication signal reflected by the reconfigurable smart surface through the receiving antenna, performing root-raised cosine matched filtering on the communication signal, performing time-frequency domain sampling on the filtered signal according to the super Nyquist symbol interval to obtain a time-frequency domain received signal matrix, and performing symplectic fast Fourier transform on the time-frequency domain received signal matrix to obtain a time-delay-Doppler domain received signal.

[0100] In some embodiments, the step of using a linear minimum mean square error detector combined with a colored noise covariance matrix introduced by the super Nyquist signal to detect the signal and recover the original information symbols includes: constructing a colored noise covariance matrix based on the pulse shaping characteristics of the super Nyquist signal; constructing a linear minimum mean square error detection matrix by combining the cascaded time-delay-Doppler domain effective channel matrix and the colored noise covariance matrix; using the linear minimum mean square error detection matrix to detect the time-delay-Doppler domain received signal to obtain the estimated information symbols and recover the original information symbols.

[0101] It should be noted that those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the RIS-assisted air-space-ground integrated high-speed mobile communication system and its modules described above can be referred to the corresponding contents in the various embodiments of the RIS-assisted air-space-ground integrated high-speed mobile communication method, and will not be repeated here.

[0102] The aforementioned RIS-assisted air-space-ground integrated high-speed mobile communication method can be implemented as a computer program, which can be used in, for example... Figure 3 It runs on the device shown.

[0103] Please see Figure 4 , Figure 4 This is a schematic block diagram of the structure of a computer device provided in an embodiment of this application. The computer device includes a processor, a memory, and a network interface connected via a device bus, wherein the memory may include a storage medium and internal memory.

[0104] The storage medium can store operating devices and computer programs. The computer program includes program instructions that, when executed, cause the processor to perform any RIS-assisted high-speed air-space-ground integrated mobile communication method.

[0105] The processor provides computing and control capabilities, supporting the operation of the entire computer device.

[0106] Internal memory provides an environment for the execution of computer programs in non-volatile storage media. When the computer program is executed by the processor, it enables the processor to execute any RIS-assisted high-speed mobile communication method that integrates air, space, and ground.

[0107] This network interface is used for network communication, such as sending assigned tasks. Those skilled in the art will understand that... Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the terminal to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0108] It should be understood that the processor can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among these, a general-purpose processor can be a microprocessor or any conventional processor.

[0109] In one embodiment, the processor is configured to run a computer program stored in memory to perform the following steps: The transmitter maps the information symbols to be transmitted to the time-delay-Doppler domain of the orthogonal time-frequency space, converts them into time-frequency domain signals, performs super Nyquist signal compression processing using root-raised cosine pulse shaping, generates a transmission signal, and sends it to the receiving end. By acquiring cascaded delay-Doppler domain channel state information from the transmitter to itself and then to the receiver through a reconfigurable smart surface, the strongest propagation path in the channel is identified, the optimal quantization phase offset of each reflective element is calculated, and the phase of all reflective elements is adjusted so that the reflected signal achieves constructive interference at the receiver. The receiver receives the communication signal reflected by the reconfigurable smart surface, performs super Nyquist matched filtering and sampling, converts it into a time-delay-Doppler domain signal, and uses a linear minimum mean square error detector combined with the colored noise covariance matrix introduced by the super Nyquist signal to detect the signal and recover the original information symbol.

[0110] In some embodiments, the step of mapping the information symbols to be transmitted to the time-delay-Doppler domain of the orthogonal time-frequency space through the transmitting end and converting them into time-frequency domain signals includes: placing the information symbols to be transmitted sequentially at the corresponding positions of the time-delay-Doppler domain grid in the orthogonal time-frequency space to form a time-delay-Doppler domain symbol matrix, and performing an inverse symplectic fast Fourier transform on the time-delay-Doppler domain symbol matrix to obtain a time-frequency domain signal matrix.

[0111] In some embodiments, the step of using root-raised cosine pulse shaping for super Nyquist signal compression processing to generate a transmit signal and send it to the receiving end includes: convolving each element in the time-frequency domain signal matrix with the root-raised cosine pulse shaping function, arranging the convolved signals according to time intervals smaller than the Nyquist symbol interval, generating a continuous-time transmit signal through Heisenberg transform, and transmitting the transmit signal to the receiving end through a transmit antenna.

[0112] In some embodiments, obtaining the cascaded delay-Doppler domain channel state information from the transmitter to itself and then to the receiver via the reconfigurable smart surface includes: the reconfigurable smart surface obtaining the first link delay-Doppler domain channel response from the transmitter to itself and the second link delay-Doppler domain channel response from itself to the receiver, and cascading and merging the first link channel response and the second link channel response to obtain the cascaded delay-Doppler domain channel state information from the transmitter to the receiver reflected by the reconfigurable smart surface.

[0113] In some embodiments, identifying the strongest propagation path in the channel includes: extracting all non-zero channel gain entries from the concatenated delay-Doppler domain channel state information, calculating the power value of each non-zero channel gain entry, comparing the magnitudes of all power values, and selecting the propagation path corresponding to the non-zero channel gain entry with the largest power value as the strongest propagation path.

[0114] In some embodiments, calculating the optimal quantized phase offset of each reflective element includes: obtaining the total phase value corresponding to the strongest propagation path and the phase value of the strongest propagation path corresponding to each reflective element; subtracting the phase value of the strongest propagation path corresponding to each reflective element from the total phase value of the strongest propagation path to obtain the continuous optimal phase value of each reflective element; quantizing each continuous optimal phase value into a preset discrete phase set to obtain the optimal quantized phase offset of each reflective element.

[0115] In some embodiments, adjusting the phase of all reflective elements to achieve constructive interference of the reflected signals at the receiving end includes: setting the phase of each reflective element of the reconfigurable smart surface to the corresponding optimal quantized phase offset, so that the signals reflected by all reflective elements maintain a consistent phase at the time delay-Doppler position corresponding to the strongest propagation path, thereby achieving constructive interference at the receiving end.

[0116] In some embodiments, the step of receiving the communication signal reflected by the reconfigurable smart surface through the receiving end, performing super Nyquist matched filtering and sampling, and converting it into a time-delay-Doppler domain signal includes: receiving the communication signal reflected by the reconfigurable smart surface through the receiving antenna, performing root-raised cosine matched filtering on the communication signal, performing time-frequency domain sampling on the filtered signal according to the super Nyquist symbol interval to obtain a time-frequency domain received signal matrix, and performing symplectic fast Fourier transform on the time-frequency domain received signal matrix to obtain a time-delay-Doppler domain received signal.

[0117] In some embodiments, the step of using a linear minimum mean square error detector combined with a colored noise covariance matrix introduced by the super Nyquist signal to detect the signal and recover the original information symbols includes: constructing a colored noise covariance matrix based on the pulse shaping characteristics of the super Nyquist signal; constructing a linear minimum mean square error detection matrix by combining the cascaded time-delay-Doppler domain effective channel matrix and the colored noise covariance matrix; using the linear minimum mean square error detection matrix to detect the time-delay-Doppler domain received signal to obtain the estimated information symbols and recover the original information symbols.

[0118] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to implement the steps of the RIS-assisted high-speed mobile communication method for air-space-ground integration as provided in any embodiment of this application.

[0119] The computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiments, such as the hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the computer device.

[0120] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A RIS-assisted high-speed air-space-ground integrated mobile communication method, characterized in that, include: The transmitter maps the information symbols to be transmitted to the time-delay-Doppler domain of the orthogonal time-frequency space, converts them into time-frequency domain signals, performs super Nyquist signal compression processing using root-raised cosine pulse shaping, generates a transmission signal, and sends it to the receiving end. By acquiring cascaded delay-Doppler domain channel state information from the transmitter to itself and then to the receiver through a reconfigurable smart surface, the strongest propagation path in the channel is identified, the optimal quantization phase offset of each reflective element is calculated, and the phase of all reflective elements is adjusted so that the reflected signal achieves constructive interference at the receiver. The receiver receives the communication signal reflected by the reconfigurable smart surface, performs super Nyquist matched filtering and sampling, converts it into a time-delay-Doppler domain signal, and uses a linear minimum mean square error detector combined with the colored noise covariance matrix introduced by the super Nyquist signal to detect the signal and recover the original information symbol.

2. The method according to claim 1, characterized in that, The process of mapping the information symbols to be transmitted to the time-delay-Doppler domain of the orthogonal time-frequency space through the transmitting end, and converting them into time-frequency domain signals, includes: The information symbols to be transmitted are sequentially placed into the corresponding positions of the time-delay-Doppler domain grid in the orthogonal time-frequency space to form a time-delay-Doppler domain symbol matrix; Perform an inverse symplectic fast Fourier transform on the time-delay-Doppler domain symbol matrix to obtain the time-frequency domain signal matrix.

3. The method according to claim 1, characterized in that, The process of using root-raised cosine pulse shaping for super Nyquist signal compression to generate a transmitted signal and send it to the receiving end includes: Each element in the time-frequency domain signal matrix is ​​convolved with the root raised cosine pulse shaping function, and the convolved signals are arranged according to time intervals smaller than the Nyquist symbol interval. A continuous-time transmission signal is generated using the Heisenberg transform, and the transmission signal is sent to the receiving end via the transmitting antenna.

4. The method according to claim 1, characterized in that, The acquisition of cascaded delay-Doppler domain channel state information from the transmitter to itself and then to the receiver via a reconfigurable smart surface includes: The reconfigurable smart surface can obtain the first link delay-Doppler domain channel response from the transmitter to itself and the second link delay-Doppler domain channel response from itself to the receiver. By concatenating and merging the first link channel response and the second link channel response, the cascaded delay-Doppler domain channel state information from the transmitter to the receiver after reflection from the reconfigurable smart surface is obtained.

5. The method according to claim 4, characterized in that, The strongest propagation path in the identification channel includes: Extract all non-zero channel gain entries from the concatenated delay-Doppler domain channel state information and calculate the power value of each non-zero channel gain entry; Compare the magnitudes of all power values ​​and select the propagation path corresponding to the non-zero channel gain entry with the largest power value as the strongest propagation path.

6. The method according to claim 5, characterized in that, The calculation of the optimal quantized phase offset for each reflective element includes: Obtain the total phase value corresponding to the strongest propagation path and the phase value of the strongest propagation path corresponding to each reflective element. Subtract the phase value of the strongest propagation path corresponding to each reflective element from the total phase value of the strongest propagation path to obtain the continuous optimal phase value of each reflective element. Each continuous optimal phase value is quantized into a preset discrete phase set to obtain the optimal quantized phase offset for each reflective element.

7. The method according to claim 6, characterized in that, The adjustment of the phase of all reflecting elements to achieve constructive interference of the reflected signal at the receiving end includes: The phase of each reflective element of the reconfigurable smart surface is set to the corresponding optimal quantized phase offset; This ensures that the signals reflected by all reflecting elements maintain phase at the time delay-Doppler position corresponding to the strongest propagation path, achieving constructive interference at the receiving end.

8. The method according to claim 1, characterized in that, The process of receiving communication signals reflected by a reconfigurable smart surface at the receiving end, performing super Nyquist matched filtering and sampling, and converting them into time-delay-Doppler domain signals includes: The communication signal reflected by the reconfigurable smart surface is received by the receiving antenna, and the communication signal is subjected to root raised cosine matched filtering. The filtered signal is sampled in the time-frequency domain according to the super Nyquist symbol interval to obtain the time-frequency domain received signal matrix; Perform a symplectic fast Fourier transform on the received signal matrix in the time-frequency domain to obtain the received signal in the time-delay-Doppler domain.

9. The method according to claim 1, characterized in that, The method of using a linear minimum mean square error detector combined with the colored noise covariance matrix introduced by the super Nyquist signal for signal detection and recovery of the original information symbols includes: A colored noise covariance matrix is ​​constructed based on the pulse shaping characteristics of the super Nyquist signal. A linear minimum mean square error detection matrix is ​​constructed by combining the cascaded time delay-Doppler domain effective channel matrix and the colored noise covariance matrix. The received signal in the time-delay-Doppler domain is detected using a linear minimum mean square error detection matrix to obtain the estimated information symbols and recover the original information symbols.

10. A RIS-assisted integrated air-space-ground high-speed mobile communication system, used to implement the method as described in any one of claims 1-9, characterized in that, include: The signal transmission unit is used to map the information symbols to be transmitted to the time-delay-Doppler domain of the orthogonal time-frequency space through the transmitter, convert them into time-frequency domain signals, perform super Nyquist signal compression processing using root raised cosine pulse shaping, generate a transmission signal and send it to the receiver. The interference adjustment unit is used to obtain the cascaded delay-Doppler domain channel state information from the transmitter to itself and then to the receiver through the reconfigurable smart surface, identify the strongest propagation path in the channel, calculate the optimal quantization phase offset of each reflective element, and adjust the phase of all reflective elements so that the reflected signal achieves constructive interference at the receiver. The symbol recovery unit is used to receive the communication signal reflected by the reconfigurable smart surface through the receiver, perform super Nyquist matched filtering and sampling, convert it into a time-delay-Doppler domain signal, and use a linear minimum mean square error detector combined with the colored noise covariance matrix introduced by the super Nyquist signal to detect the signal and recover the original information symbol.

Images