OTFS performance analysis method based on 6G universal channel model

Abstract

The invention discloses an OTFS performance analysis method based on a 6G universal channel model, and relates to the technical field of wireless communication, and the method comprises the steps: building an overall framework of an OTFS system suitable for a high-mobility scene; setting a communication scene and channel environment parameters; based on a 6G universal channel model, multipath time delay, multipath power and Doppler frequency shift are calculated according to channel environment parameters; obtaining a channel impulse response of a time delay-Doppler domain required by the OTFS system; on the basis of the overall framework of the OTFS system, a random signal is input at the transmitting end of the OTFS system, a signal is finally output at the receiving end of the OTFS system according to the channel impulse response of the time delay-Doppler domain, and the signal is used for analyzing the error rate performance of the OTFS system under different channel parameters in a high mobility scene. According to the invention, a more accurate error rate analysis result is provided. According to the method, OTFS performance analysis under various typical high mobility scenes can be realized, and a more universal theoretical basis is provided for system optimization.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and in particular to an OTFS performance analysis method based on a 6G universal channel model. Background Art

[0002] With the official commercialization of 5G mobile communication networks, current communication systems can support mobility of up to 500 km / h. To meet growing communication needs, future 6G networks will need to support even higher mobility scenarios, including satellite communications, ultra-high-speed rail communications, and drone communications. In certain specific application scenarios, terminal speeds may reach as high as 1000 km / h. High-mobility scenarios are subject to severe Doppler and multipath effects, resulting in time-frequency dual-selective fading channels. Large Doppler shifts destroy the orthogonality between subcarriers, leading to severe inter-carrier interference. As a result, the advantages of traditional orthogonal frequency division multiplexing (OFDM) technology are eliminated, and system performance is severely degraded. To address this issue, Hadani R et al. proposed an orthogonal time-frequency air modulation scheme that leverages the stability and sparsity of the delay-Doppler domain to achieve effective communication under high mobility.

[0003] There are many key performance indicators in high-mobility communication systems, among which bit error rate (BER) is often used as a key metric for measuring the reliability of OTFS systems. However, current BER simulations for OTFS systems often use standardized channel models from 3GPP, including the Extended Vehicle A Model and the Extended Typical City Model. These channel models have a small number of multipath paths, and the delay and power of each path are fixed. This results in limited flexibility in simulating channel characteristics and the inability to simulate diverse communication scenarios. Furthermore, when calculating Doppler shift, current research often assumes a uniform angle of arrival for each path. Consequently, commonly used models may not be accurate and reliable enough to describe the characteristics of real, complex communication channels. Summary of the Invention

[0004] The technical problem to be solved by this invention is to overcome the shortcomings of the existing technology and provide an OTFS performance analysis method based on the 6G universal channel model. This method can accurately reflect the channel characteristics of time-varying channels in the delay-Doppler domain, is applicable to various high-mobility scenarios, and enables OTFS system reliability analysis in real complex communication environments, thereby resolving the technical problems mentioned in the background technology.

[0005] The present invention adopts the following technical solutions to solve the above technical problems:

[0006] According to the present invention, an OTFS performance analysis method based on a 6G universal channel model includes:

[0007] Step 1: Build the overall framework of the OTFS system suitable for high mobility scenarios;

[0008] Step 2: Set the communication scenario and channel environment parameters;

[0009] Step 3: Based on the 6G universal channel model, calculate the multipath delay, multipath power, and Doppler shift according to the channel environment parameters;

[0010] Step 4: Obtain the channel impulse response in the delay-Doppler domain required by the OTFS system based on the multipath delay, multipath power, and Doppler frequency shift;

[0011] Step 5: Based on the overall framework of the OTFS system, a random signal is input to the transmitter of the OTFS system. Based on the channel impulse response in the delay-Doppler domain, a signal is finally output at the receiver of the OTFS system. This signal is used to analyze the bit error rate performance of the OTFS system under different channel parameters in high-mobility scenarios.

[0012] As a further optimization scheme for the OTFS performance analysis method based on the 6G universal channel model described in the present invention, the overall framework of the OTFS system is as follows:

[0013] Step 1.1: At the transmitter of the OTFS system, the symbol mapper places the input information symbols into the delay-Doppler domain grid to obtain the signal matrix X in the delay-Doppler domain. DD [m,n];

[0014] Step 1.2: Delay-Doppler domain signal matrix X DD [m,n] performs inverse symplectic finite Fourier transform to obtain the time-frequency domain signal matrix X TF [k,l];

[0015]

[0016] Where M is the number of subcarriers, N is the number of symbol periods, e is the natural base, j is the imaginary unit, m and n are the index variables in the delay and Doppler directions, respectively, and k and l are the time index and frequency index, respectively.

[0017] Step 1.3, X TF [k, l] performs Heisenberg transform to obtain the continuous-time signal x(t) for transmission;

[0018]

[0019] Where Δf is the subcarrier spacing, T is the symbol period, t represents time, g tx (t-kT) is the waveform of the transmitting pulse;

[0020] Step 1.4: At the receiving end, x(t) passes through the time-varying channel to obtain y(t);

[0021] y(t)=∫∫h(τ,υ)x(t-τ)e j2πv(t-τ) dτdυ

[0022] Where y(t) is the received signal, h(τ,υ) is the channel impulse response in the delay-Doppler domain, τ and υ represent the delay and Doppler, respectively, and x(t-τ) represents the value of x(t) after being delayed by τ seconds.

[0023] Step 1.5: Use the matched filter to perform OTFS demodulation on y(t) to obtain Y(t,f), and then sample it to obtain the received signal matrix Y TF [k,l];

[0024]

[0025] Y TF [k,l]=Y(t,f)| t＝kT,f＝lΔf

[0026] Among them, Y(t,f) is the demodulated signal, t' represents time, f represents frequency, is the complex conjugate of the received pulse waveform, y(t′) is the value of the received signal y(t) at time t′, and represents the sampling point of the received signal in the matched filtering process;

[0027] The two formulas in step 1.5 are called Wiener transforms;

[0028] Step 1.6, for Y TF [k, l] performs symplectic finite Fourier transform to obtain the delay-Doppler domain signal Y DD [m,n]

[0029]

[0030] Among them, z[m,n] is the noise term.

[0031] As a further optimization scheme of the OTFS performance analysis method based on the 6G universal channel model described in the present invention, the channel environment parameters in step 2 include carrier frequency, subcarrier spacing, initial position and speed of the transmitter and receiver, channel coding, channel equalization algorithm, cluster and subpath related parameters; the communication scenario is set to a high mobility scenario supported by the 6G universal channel model, including high-speed rail communication scenario, satellite communication scenario, and drone communication scenario; the channel coding method is Turbo coding and no coding; the channel equalization algorithm is the minimum mean square error algorithm and the linear minimum mean square error algorithm.

[0032] As a further optimization scheme of the OTFS performance analysis method based on the 6G universal channel model described in the present invention, step 3 includes:

[0033] Step 3.1: Based on the communication scenario set in Step 2, use the 6G universal channel modeling method to obtain large-scale parameters. The large-scale parameters include delay spread and angle spread. Use a dual-cluster channel model to describe small-scale fading, and model the path between the first-hop cluster and the last-hop cluster as a virtual path.

[0034] Step 3.2: Calculate the delay of each path at the initial time based on the delay spread DS.

[0035]

[0036] in, is the delay of the nth path in the mth cluster at the initial time, r τ is the delay distribution proportional factor, X n is a random variable that obeys a uniform distribution on (0,1);

[0037] Subtract the shortest delay and sort in ascending order to obtain the normalized multipath delay

[0038] Step 3.3: Utilize multipath delay Calculate the power of each path;

[0039]

[0040] in, is the power of the nth path in the mth cluster at the initial moment, Z n is the shaded term of the nth cluster in dB, and Z n The mean is 0 and the variance is ζ 2 Normal distribution;

[0041] After normalization, the normalized power of the nth path in the mth cluster at the initial moment is obtained

[0042] Step 3.4, Perform inverse Gaussian transformation on the corresponding angle expansion to obtain the departure / arrival azimuth;

[0043] Step 3.5, Perform Laplace transform on the corresponding angle expansion to obtain the departure / arrival pitch angle;

[0044] Step 3.6: Introduce the distance from the first hop cluster to the transmitter and the distance from the last hop cluster to the receiver Both of them obey exponential distribution; determine whether they meet:

[0045]

[0046] Where c is the speed of light;

[0047] If it is satisfied, the departure / arrival azimuth and departure / arrival elevation angles obtained in steps 3.4 and 3.5 are combined to calculate the scatterer position coordinates; if it is not satisfied, the dual-cluster model degenerates into a single-cluster model and retains Arrival azimuth and arrival elevation angles, and calculation of scatterer position coordinates through geometric relationships;

[0048] Step 3.7: Calculate the Doppler shift of each path by combining the scatterer position coordinates and the initial position and velocity of the receiver set in step 2.

[0049]

[0050] in, is the Doppler shift of the nth path in the mth cluster, υ max is the maximum Doppler shift, is the angle between the propagation path and the direction of motion of the receiving end, v is the relative speed between the transmitting end and the receiving end, and λ is the wavelength;

[0051] Step 3.8: At the next time t1, update the multipath delay, multipath power, multipath angle, and Doppler shift. Combined with the position coordinates of the scatterer, transmitter, and receiver at time t0, as well as the velocity parameters of the cluster, transmitter, and receiver, calculate the distance from the first hop cluster to the transmitter at time t1. and the distance from the last hop cluster to the receiver Determine whether:

[0052]

[0053] in, is the delay of the nth path in the mth cluster at time t1, is the virtual delay of the nth path in the mth cluster at time t1;

[0054] like If it is less than or equal to 0, the two-cluster model degenerates into a single-cluster model, and the Arrival azimuth and arrival elevation angles are used to update the scatterer position coordinates at time t1 through geometric relationships, and step 3.7 is repeated to update the Doppler shift at time t1.

[0055] At each subsequent moment, step 3.8 is repeated to update the multipath delay, multipath power, multipath angle, and Doppler shift.

[0056] As a further optimization scheme of the OTFS performance analysis method based on the 6G universal channel model described in the present invention, in step 3.4, the calculation method of the arrival azimuth angle is

[0057]

[0058] in, is the arrival azimuth of the nth path in the mth cluster at the initial time, ASA is the arrival azimuth extension, C φ is the scaling factor.

[0059] As a further optimization scheme of the OTFS performance analysis method based on the 6G universal channel model described in the present invention, in step 3.5, the calculation method of the arrival pitch angle is:

[0060]

[0061] in, is the arrival pitch angle of the nth path in the mth cluster at the initial moment, ZSA is the arrival pitch angle spread, C θ is the scaling factor.

[0062] As a further optimization scheme of the OTFS performance analysis method based on the 6G universal channel model described in the present invention,

[0063] In step 4, the delay-Doppler domain channel impulse response h(τ,u) is:

[0064]

[0065] in, is the complex amplitude coefficient of the nth path in the mth cluster, is the delay of the nth path in the mth cluster, and δ(·) is the Dirac function.

[0066] As a further optimization scheme of the OTFS performance analysis method based on the 6G universal channel model described in the present invention, analyzing the bit error rate performance of the OTFS system under different channel parameters in a high-mobility scenario includes: comparing the bit error rate (BER) performance under different mobile speeds; comparing the BER performance under different modulation orders; and comparing the BER performance under different frame sizes.

[0067] A computer device includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the computer program, the steps of the OTFS performance analysis method based on the 6G ubiquitous channel model are implemented as described above.

[0068] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned OTFS performance analysis method based on the 6G universal channel model.

[0069] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0070] The present invention can accurately reflect the channel characteristics of time-varying channels in the delay-Doppler domain and is applicable to a variety of high-mobility scenarios. It can realize the reliability analysis of OTFS systems in real complex communication environments and solve the technical problems mentioned in the background technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 A schematic diagram of the process of the OTFS performance analysis method based on the 6G universal channel model provided by the present invention;

[0072] Figure 2 The overall framework of the OTFS system in a high-mobility scenario constructed in an embodiment of the present invention;

[0073] Figure 3 This figure compares the delay spread (DS) of the 6G universal channel model, the commonly used EVA model, and actual measurement data used in the embodiments of the present invention.

[0074] Figure 4 This is a diagram showing the BER comparison results of the OTFS system at different moving speeds in an embodiment of the present invention;

[0075] Figure 5 BER comparison results of the OTFS system under different modulation orders in an embodiment of the present invention;

[0076] Figure 6 This is a diagram comparing the BER results of the OTFS system at different frame sizes in an embodiment of the present invention. DETAILED DESCRIPTION

[0077] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0078] like Figure 1 As shown in FIG, the OTFS system performance analysis method based on the 6G universal channel model specifically includes the following steps:

[0079] Step 1: Build the overall framework of the OTFS system suitable for high mobility scenarios;

[0080] Specifically, if Figure 2 As shown, in this embodiment, this step specifically includes:

[0081] Step 1.1: At the transmitter, the symbol mapper places the information symbols in the delay-Doppler domain grid to obtain the signal matrix X DD [m,n];

[0082] Step 1.2: Delay-Doppler domain signal matrix X DD [m,n] performs inverse symplectic finite Fourier transform to obtain the time-frequency domain signal matrix X TF [k,l]

[0083]

[0084] Where M is the number of subcarriers, N is the number of symbol periods, e is the natural base, j is the imaginary unit, m and n are the index variables in the delay and Doppler directions, respectively, and k and l are the time index and frequency index, respectively.

[0085] Step 1.3, X TF [k, l] performs Heisenberg transform to obtain the continuous time signal x(t) for transmission

[0086]

[0087] Where Δf is the subcarrier spacing, T is the symbol period, t represents time, g tx (t-kT) is the waveform of the transmitting pulse;

[0088] Step 1.4: At the receiving end, x(t) passes through the time-varying channel to obtain y(t);

[0089] y(t)=∫∫h(τ,υ)x(tt)e j2πυ(t-τ) dτdυ

[0090] Where y(t) is the received signal, h(τ,υ) is the channel impulse response in the delay-Doppler domain, τ and υ represent the delay and Doppler, respectively, and x(t-τ) represents the value of x(t) after being delayed by τ seconds.

[0091] Step 1.5: Use the matched filter to perform OTFS demodulation on y(t) to obtain Y(t,f), and then sample it to obtain the received signal matrix Y TF [k,l];

[0092]

[0093] Y TF [k,l]=Y(t,f)| t＝kT,f＝lΔf

[0094] Among them, Y(t,f) is the demodulated signal, t' represents time, f represents frequency, is the complex conjugate of the received pulse waveform, y(t′) is the value of the received signal y(t) at time t′, and represents the sampling point of the received signal in the matched filtering process;

[0095] The two formulas in step 1.5 are called Wiener transforms;

[0096] Step 1.6, for Y TF [k, l] performs symplectic finite Fourier transform to obtain the delay-Doppler domain signal Y DD [m,n]

[0097]

[0098] Among them, z[m,n] is the noise term.

[0099] Step 2: Set the communication scenario and channel environment parameters.

[0100] Specifically, in this embodiment, the channel environment parameters extracted in step 2 include the communication scenario, carrier frequency, subcarrier spacing, initial position and speed of the transmitter and receiver, channel coding, channel equalization algorithm, cluster and subpath related parameters. The communication scenario can be set to a high mobility scenario supported by the 6G universal channel model, including high-speed rail communication scenarios, satellite communication scenarios, drone communication scenarios, etc.; the channel coding methods include turbo coding and no coding; and the channel equalization algorithms include minimum mean square error algorithm and linear minimum mean square error algorithm.

[0101] Step 3: Based on the 6G universal channel model, obtain multipath delay, multipath power, and Doppler shift.

[0102] Specifically, in this embodiment, step 3 includes:

[0103] Step 3.1: Based on the communication scenario set in Step 2, use the 6G universal channel modeling method to obtain large-scale parameters. The large-scale parameters include delay spread and angle spread. Use a dual-cluster channel model to describe small-scale fading, and model the path between the first-hop cluster and the last-hop cluster as a virtual path.

[0104] Step 3.2: Calculate the delay of each path at the initial time based on delay spread (DS).

[0105]

[0106] in, is the delay of the nth path in the mth cluster at the initial time, r τ is the delay distribution proportional factor, X n is a random variable that obeys a uniform distribution on (0,1);

[0107] Subtract the shortest delay and sort in ascending order to obtain the normalized multipath delay

[0108] Step 3.3: Utilize multipath delay Calculate the power of each path

[0109]

[0110] in, is the power of the nth path in the mth cluster at the initial moment, Z n is the shaded term of the nth cluster in dB, and Z n The mean is 0 and the variance is ζ 2 Normal distribution;

[0111] Step 3.4, Perform inverse Gaussian transformation on the corresponding angle expansion to obtain the departure / arrival azimuth. Take the arrival azimuth as an example

[0112]

[0113] in, is the arrival azimuth of the nth path in the mth cluster at the initial time, ASA is the arrival azimuth extension, C ′ is the scaling factor;

[0114] Step 3.5, Perform Laplace transform on the corresponding angle expansion to get the departure / arrival pitch angle, taking the arrival pitch angle as an example;

[0115]

[0116] in, is the arrival pitch angle of the nth path in the mth cluster at the initial moment, ZSA is the arrival pitch angle spread, C θ is the scaling factor;

[0117] Step 3.6: Introduce the distance from the first hop cluster to the transmitter and the distance from the last hop cluster to the receiver Both of them obey exponential distribution. Determine whether they meet:

[0118]

[0119] Where c is the speed of light;

[0120] If it is satisfied, the propagation path angles obtained in steps 3.4 and 3.5 are combined to calculate the scatterer position coordinates; if it is not satisfied, the dual-cluster model degenerates into a single-cluster model and retains The arrival azimuth angle and arrival elevation angle are used to calculate the scatterer position coordinates through geometric relationships.

[0121] Step 3.7: Calculate the Doppler shift of each path by combining the scatterer position and the receiver position and velocity set in step 2.

[0122]

[0123] in, is the Doppler shift of the nth path in the mth cluster, u max is the maximum Doppler shift, is the angle between the propagation path and the direction of motion of the receiving end, v is the relative speed between the transmitting end and the receiving end, and λ is the wavelength;

[0124] Step 3.8: At the next time t1, update the multipath delay, multipath power, multipath angle, and Doppler shift. Combined with the position coordinates of the scatterer and the transmitter and receiver at time t0, as well as the velocity parameters of the cluster and the transmitter and receiver, calculate the distance from the first hop cluster to the transmitter at time t1. and the distance from the last hop cluster to the receiver Determine whether:

[0125]

[0126] in, is the delay of the nth path in the mth cluster at time t1, is the virtual delay of the nth path in the mth cluster at time t1;

[0127] like If it is less than or equal to 0, it degenerates into a single cluster model. The scatterer position coordinates at time t1 are updated through geometric relationships, and step 3.7 is repeated to update the multipath Doppler shift at time t1.

[0128] At each subsequent moment, step 3.8 is repeated to update the multipath delay, multipath power, multipath angle, and Doppler shift.

[0129] Step 4: Obtain the channel impulse response in the delay-Doppler domain required by the OTFS system.

[0130] Specifically, in this embodiment, step 4 includes combining the generated multipath delay, power, and Doppler shift to generate a delay-Doppler domain channel impulse response h(τ,υ):

[0131]

[0132] in, is the complex amplitude coefficient of the nth path in the mth cluster, is the delay of the nth path in the mth cluster, and δ(·) is the Dirac function.

[0133] Step 5: A random signal is input to the transmitter of the OTFS system. Based on the channel impulse response in the delay-Doppler domain, a signal is output at the receiver of the OTFS system. Based on the output signal from the receiver, the bit error rate performance of the OTFS system under different channel parameters in a high-mobility scenario is analyzed.

[0134] Specifically, in this embodiment, step 5 includes: comparing BER performance at different moving speeds; comparing BER performance at different modulation orders; and comparing BER performance at different frame sizes.

[0135] Figure 3 The results show that the 6G universal channel model performs better than the commonly used EVA test channel based on actual measurement data, indicating that the OTFS system performance analysis conclusions based on the 6G universal channel model are more practical. Figure 4 It shows that in the OTFS system, as the terminal's mobile speed increases, the bit error rate at low signal-to-noise ratio (SNR) does not change significantly due to the dominant effect of noise, while the bit error rate at high SNR shows a gradual downward trend due to the influence of Doppler diversity gain. Figure 5 It is shown that the increase in modulation order causes the bit error rate performance of the OTFS system to gradually deteriorate, and its performance advantage over the OFDM system also gradually weakens. Figure 6 The results show that increasing the number of subcarriers M and the number of time symbols N can effectively reduce the bit error rate of the OTFS system, indicating that increasing the resolution in both the delay and Doppler domains is beneficial to improving the reliability of high-mobility communications. The above analysis provides a theoretical basis for the performance optimization of future OTFS systems.

[0136] In summary, the OTFS system performance analysis method based on the 6G ubiquitous channel model proposed in this invention, through the effective combination of OTFS modulation technology and the 6G ubiquitous channel modeling method, can more accurately analyze the OTFS system performance under different parameters in high-mobility scenarios. In this invention, the number of multipath paths in the communication environment can be customized according to the actual scenario. Utilizing the 6G ubiquitous channel modeling method, the delay and power of each path can be calculated and updated at each simulation moment. Furthermore, the specific location coordinates of the scatterer can be obtained through geometric relationships, enabling accurate calculation of the Doppler shift of each path. The delay-Doppler domain channel impulse response is derived based on the aforementioned key parameters. By simulating the bit error rate of the OTFS system, this invention studies the impact of different parameters on the reliability of the high-mobility communication system. This invention has guiding significance for OTFS system design and performance optimization.

[0137] An embodiment of the present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the computer program, the steps of the OTFS performance analysis method based on the 6G ubiquitous channel model as described above are implemented.

[0138] An embodiment of the present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the OTFS performance analysis method based on the 6G universal channel model as described above.

[0139] It will be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention may be implemented in various computer languages, for example, the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0140] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0141] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0142] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0143] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0144] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. An OTFS performance analysis method based on a 6G universal channel model, characterized in that: include: Step 1: Build the overall framework of the OTFS system suitable for high mobility scenarios; Step 2: Set the communication scenario and channel environment parameters; Step 3: Based on the 6G universal channel model, calculate the multipath delay, multipath power, and Doppler shift according to the channel environment parameters; Step 4: Obtain the channel impulse response in the delay-Doppler domain required by the OTFS system based on the multipath delay, multipath power, and Doppler frequency shift; Step 5: Based on the overall framework of the OTFS system, a random signal is input to the transmitter of the OTFS system. Based on the channel impulse response in the delay-Doppler domain, a signal is finally output at the receiver of the OTFS system. This signal is used to analyze the bit error rate performance of the OTFS system under different channel parameters in high-mobility scenarios.

2. The OTFS performance analysis method based on the 6G universal channel model according to claim 1 is characterized in that: The overall framework of the OTFS system is as follows: Step 1.1: At the transmitter of the OTFS system, the symbol mapper places the input information symbols into the delay-Doppler domain grid to obtain the signal matrix X in the delay-Doppler domain. DD [m,n]; Step 1.2: Delay-Doppler domain signal matrix X DD [m,n] performs inverse symplectic finite Fourier transform to obtain the time-frequency domain signal matrix X TF [k,l]; Where M is the number of subcarriers, N is the number of symbol periods, e is the natural base, j is the imaginary unit, m and n are the index variables in the delay and Doppler directions, respectively, and k and l are the time index and frequency index, respectively. Step 1.3, X TF [k, l] performs Heisenberg transform to obtain the continuous-time signal x(t) for transmission; Where Δf is the subcarrier spacing, T is the symbol period, t represents time, g tx (t-kT) is the waveform of the transmitting pulse; Step 1.4: At the receiving end, x(t) passes through the time-varying channel to obtain y(t); y(t)=∫∫h(τ,υ)x(t-τ)e j2πv(t-τ) dtdv Where y(t) is the received signal, h(τ,υ) is the channel impulse response in the delay-Doppler domain, τ and υ represent the delay and Doppler, respectively, and x(t-τ) represents the value of x(t) after being delayed by τ seconds. Step 1.5: Use the matched filter to perform OTFS demodulation on y(t) to obtain Y(t,f), and then sample it to obtain the received signal matrix Y TF [k,l]; Y TF [k,l]=Y(t,f)| t＝kT,f＝l Among them, Y(t,f) is the demodulated signal, t' represents time, f represents frequency, is the complex conjugate of the received pulse waveform, y(t′) is the value of the received signal y(t) at time t′, and represents the sampling point of the received signal in the matched filtering process; The two formulas in step 1.5 are called Wiener transforms; Step 1.6, for Y TF [k, l] performs symplectic finite Fourier transform to obtain the delay-Doppler domain signal Y DD [m,n] Among them, z[m,n] is the noise term.

3. The OTFS performance analysis method based on the 6G universal channel model according to claim 1 is characterized in that: The channel environment parameters in step 2 include carrier frequency, subcarrier spacing, initial position and speed of the transmitter and receiver, channel coding, channel equalization algorithm, cluster and subpath related parameters; the communication scenario is set to the high mobility scenario supported by the 6G universal channel model, including high-speed rail communication scenario, satellite communication scenario, and drone communication scenario; the channel coding method is Turbo coding and no coding; The channel equalization algorithms are the minimum mean square error algorithm and the linear minimum mean square error algorithm.

4. The OTFS performance analysis method based on the 6G universal channel model according to claim 1 is characterized in that: Step 3 includes: Step 3.1: Based on the communication scenario set in Step 2, use the 6G universal channel modeling method to obtain large-scale parameters. The large-scale parameters include delay spread and angle spread. Use a dual-cluster channel model to describe small-scale fading, and model the path between the first-hop cluster and the last-hop cluster as a virtual path. Step 3.2: Calculate the delay of each path at the initial time based on the delay spread DS. in, is the delay of the nth path in the mth cluster at the initial time, r τ is the delay distribution proportional factor, X n is a random variable that obeys a uniform distribution on (0,1); Subtract the shortest delay and sort in ascending order to obtain the normalized multipath delay Step 3.3: Utilize multipath delay Calculate the power of each path; in, is the power of the nth path in the mth cluster at the initial moment, Z n is the shaded term of the nth cluster in dB, and Z n The mean is 0 and the variance is ζ 2 Normal distribution; After normalization, the normalized power of the nth path in the mth cluster at the initial moment is obtained Step 3.4, Perform inverse Gaussian transformation on the corresponding angle expansion to obtain the departure / arrival azimuth; Step 3.5, Perform Laplace transform on the corresponding angle expansion to obtain the departure / arrival pitch angle; Step 3.6: Introduce the distance from the first hop cluster to the transmitter and the distance from the last hop cluster to the receiver Both of them obey exponential distribution; determine whether they meet: Where c is the speed of light; If it is satisfied, the departure / arrival azimuth and departure / arrival elevation angles obtained in steps 3.4 and 3.5 are combined to calculate the scatterer position coordinates; if it is not satisfied, the dual-cluster model degenerates into a single-cluster model and retains Arrival azimuth and arrival elevation angles, and calculation of scatterer position coordinates through geometric relationships; Step 3.7: Calculate the Doppler shift of each path by combining the scatterer position coordinates and the initial position and velocity of the receiver set in step 2. in, is the Doppler shift of the nth path in the mth cluster, v max is the maximum Doppler shift, is the angle between the propagation path and the direction of motion of the receiving end, v is the relative speed between the transmitting end and the receiving end, and λ is the wavelength; Step 3.8: At the next time t1, update the multipath delay, multipath power, multipath angle, and Doppler shift. Combined with the position coordinates of the scatterer, transmitter, and receiver at time t0, as well as the velocity parameters of the cluster, transmitter, and receiver, calculate the distance from the first hop cluster to the transmitter at time t1. and the distance from the last hop cluster to the receiver Determine whether: in, is the delay of the nth path in the mth cluster at time t1, is the virtual delay of the nth path in the mth cluster at time t1; like If it is less than or equal to 0, the two-cluster model degenerates into a single-cluster model, and the Arrival azimuth and arrival elevation angles are used to update the scatterer position coordinates at time t1 through geometric relationships, and step 3.7 is repeated to update the Doppler shift at time t1. At each subsequent moment, step 3.8 is repeated to update the multipath delay, multipath power, multipath angle, and Doppler shift.

5. The OTFS performance analysis method based on the 6G universal channel model according to claim 4 is characterized in that: In step 3.4, the arrival azimuth is calculated as in, is the arrival azimuth of the nth path in the mth cluster at the initial time, ASA is the arrival azimuth extension, C φ is the scaling factor.

6. The OTFS performance analysis method based on the 6G universal channel model according to claim 4 is characterized in that: In step 3.5, the calculation method for the arrival pitch angle is in, is the arrival pitch angle of the nth path in the mth cluster at the initial moment, ZSA is the arrival pitch angle spread, C θ is the scaling factor.

7. The OTFS performance analysis method based on the 6G universal channel model according to claim 4 is characterized in that: In step 4, the delay-Doppler domain channel impulse response h(τ,υ) is: in, is the complex amplitude coefficient of the nth path in the mth cluster, is the delay of the nth path in the mth cluster, and δ(·) is the Dirac function.

8. The OTFS performance analysis method based on the 6G universal channel model according to claim 1, characterized in that: The analysis of the bit error rate performance of the OTFS system under different channel parameters in high mobility scenarios includes: comparing the bit error rate (BER) performance under different mobile speeds; comparing the BER performance under different modulation orders; and comparing the BER performance under different frame sizes.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: When the processor executes the computer program, the steps of the OTFS performance analysis method based on the 6G universal channel model are implemented as described in any one of claims 1 to 8.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the OTFS performance analysis method based on the 6G universal channel model are implemented.

Images