Method for calculating doppler rate of change in a low earth orbit satellite communication system

Abstract

The application relates to a Doppler rate calculation method in a low-orbit satellite communication system and belongs to the field of mobile communication. In view of a low-orbit satellite communication system of a non-ground communication network (NTN), the application aims to solve the problem of Doppler rate calculation without ephemeris information and frequency and timing precision synchronization conditions. By utilizing the OFDM data frame structure features, the cyclic prefix data and the symbol tail data of the OFDM symbol are extracted, the phase offset is obtained through correlation calculation, the Doppler rate is calculated in combination with the OFDM symbol interval time, and the calculation precision is improved through multiple averaging. The application does not need to analyze the data frame content, has low calculation complexity, is convenient for engineering implementation, is suitable for estimation and compensation of the Doppler frequency shift rate in the low-orbit satellite communication, and effectively improves the communication system performance.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of mobile communication, and relates to a Doppler rate calculation method in a low-orbit satellite communication system. BACKGROUND

[0002] Non-Terrestrial Network (NTN) technology is an emerging communication technology that uses satellite constellations to extend the coverage of 5G networks, especially in remote areas where terrestrial networks have difficulty covering. Key features of NTN technology include the use of satellites in different orbits such as Low Earth Orbit (LEO), Medium Earth Orbit (MEO), Geostationary Orbit (GEO), and High Altitude Platforms (HAPs) to provide communication services. These satellites can carry transmission equipment relay nodes or base stations, enabling broadband connectivity worldwide.

[0003] Challenges facing NTN technology include Doppler shift, Doppler rate, and latency changes caused by the high-speed movement of satellites, as well as signal propagation delays caused by long distances between satellites and ground user equipment (UE). To address these issues, NTN technology needs to innovate in time-frequency synchronization, mobility management, beam management, and signal processing.

[0004] As 3GPP continues to advance the standardization of NTN technology, future releases, including Release 18 and beyond, are expected to further enhance NTN technology to support a wider range of applications and services, including support for higher frequency bands (such as Ka band), improved mobility management and network optimization, and more comprehensive support for different types of satellites (including LEO and MEO). These advances will lay the foundation for a global seamless 5G network.

[0005] Among them, low-orbit satellite communication systems show great potential in providing global seamless coverage and enhancing signal quality, but also face a series of technical challenges. First, due to the high-speed movement of low-orbit satellites relative to the ground, significant Doppler shift and Doppler rate will occur, which requires the system to have precise time-frequency synchronization capabilities. Second, the random access process is complicated by the satellite-ground propagation delay and time-frequency offset, and efficient preamble and access strategies need to be designed to reduce access latency and improve access success rate.

[0006] Without any frequency offset compensation, the mobile phone will face tens of kilohertz or even megahertz level Doppler shift, which brings great challenges to the time-frequency synchronization between the mobile phone and the network. The traditional cross-correlation detection algorithm is prone to significantly reduce the performance in the large frequency offset environment, resulting in synchronization failure. In order to solve this problem, an improved coarse synchronization algorithm is proposed, for example, using fast Fourier transform operation instead of summation operation in cross-correlation operation, and at the same time, the corresponding integer multiple frequency offset estimation is obtained from the exponential form frequency offset in the algorithm, which simplifies the subsequent decimal multiple frequency offset estimation, so as to better adapt to the large frequency offset scene.

[0007] The fast time-varying characteristics of Doppler shift in low-orbit satellite communication systems make the channel characteristics more complex, and it is crucial to quickly and accurately predict the time-varying characteristics of Doppler shift. In order to accurately calculate the Doppler shift of low-orbit satellite in real time, a geometric calculation method suitable for low-orbit satellite Doppler shift characteristics of different eccentricities is proposed. This method does not require the latitude and longitude position of the ground terminal and the real-time coordinates of the satellite, but only needs the satellite orbit parameters and the maximum visible elevation angle at the terminal to obtain the Doppler shift characteristics within the current visible window. The algorithm has simple calculation process, low complexity and is easy to program on chip, which can provide prior information for Doppler shift estimation and compensation of satellite communication receivers.

[0008] However, Doppler shift and Doppler rate in low-orbit satellite communication systems are two related but distinct concepts. Doppler shift refers to the phenomenon that the frequency of the wave received by the observer is different from the frequency of the wave emitted by the wave source (such as a satellite) due to the relative motion between the wave source and the observer (such as a ground receiving station). In low-orbit satellite systems, the high-speed motion of the satellite will produce significant Doppler shift, which will change with the relative position between the satellite and the ground station.

[0009] Doppler rate, on the other hand, refers to the rate of change of Doppler shift with time, which reflects the dynamic characteristics of Doppler shift. In low-orbit satellite communication systems, due to the orbital motion of the satellite, the relative velocity with respect to the ground receiving station will change with time, so the Doppler shift will also change rapidly, which leads to the existence of Doppler rate. This rapidly changing Doppler shift poses higher requirements for signal synchronization, tracking and compensation.

[0010] The Doppler shift and Doppler rate in various scenarios of NTN satellite communication are given in TR38.811, as shown in Table 1. From the table, the maximum Doppler rate reaches -8.16 kHz / s. That is, every 1s, the Doppler shift will change by 8.16KHz.

[0011] Table 1

[0012]

[0013] Therefore, in low-orbit satellite communication systems, the Doppler shift and Doppler rate need to be accurately estimated and compensated to ensure the quality of communication signals. This includes developing efficient algorithms to predict the Doppler shift characteristics of satellites and designing receivers and signal processing techniques that can adapt to the Doppler rate.

[0014] The present application proposes a method for calculating in a user terminal based on the characteristics of NTN satellite communication signals to solve the problem of Doppler rate in NTN low-orbit satellite communication systems. SUMMARY

[0015] Therefore, the present application aims to provide a method for calculating the Doppler rate in a low-orbit satellite communication system.

[0016] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0017] For a low-orbit satellite communication system in a non-terrestrial communication network (NTN), the present application proposes a method for calculating the Doppler rate at the receiving end based on the frame structure characteristics of the wireless signal in the communication system. The non-terrestrial communication network (NTN) system belongs to an orthogonal frequency division multiple access (OFDMA) communication system, and the frame structure of wireless communication is composed of multiple OFDM symbols, each OFDM symbol is composed of a cyclic prefix domain (CP) and OFDM symbol data. Assuming that the cyclic prefix length of the OFDM symbol is CPLen, the cyclic prefix data of each OFDM symbol and the CPLen length at the tail of the OFDM symbol data domain are used to perform correlation calculation to obtain the phase rotation angle of the transmission data within an OFDM symbol time length According to the interval time between two OFDM symbols, the Doppler rate ε generated between the two OFDM symbols can be calculated. The Doppler rate is calculated multiple times, and then the average value of the Doppler rate is calculated. As shown in the following formula: Figure 1

[0018] The present application is composed of four modules, namely, an OFDM symbol data module, a phase offset calculation module, a Doppler rate calculation module, and a Doppler rate averaging module.

[0019] The OFDM symbol data module receives a complete wireless communication signal frame after synchronization is completed at the receiving end of the non-terrestrial communication network (NTN) system. The wireless communication signal frame is composed of OFDM symbol data, and each OFDM symbol is composed of an OFDM symbol cyclic prefix domain and an OFDM symbol data domain.

[0020] ​The phase offset module calculates the phase offset of an OFDM symbol from the wireless communication signal data frame, extracts the cyclic prefix data from the cyclic prefix domain of the OFDM symbol, extracts the OFDM symbol data of the cyclic prefix length from the tail of the OFDM symbol data domain, and performs correlation calculation on the two pieces of data to obtain a correlation peak, and the phase of the correlation peak is the phase offset of the OFDM symbol

[0021] The Doppler rate of change module calculates the Doppler rate of change by using the phase offset of two OFDM symbols and the interval between the two OFDM symbols.

[0022] The Doppler rate of change average module calculates the Doppler rate of change once every two OFDM symbols from the wireless communication signal frame data, calculates the Doppler rate of change multiple times by using the same method, and then performs averaging.

[0023] The Doppler rate of change calculation process of the non-terrestrial communication network (NTN) is shown in Figure 2 .

[0024] Step 1: After the base station signal search of the non-terrestrial system is completed, the receiving end completes the downlink timing synchronization process with the base station, that is, the receiving end obtains the frame timing information and the wireless frame structure information. The receiving end receives the wireless frame data stream, denoted as a_rx_waveform. As shown in Figure 2 Step 1.

[0025] Step 2: According to the wireless frame structure parameters, the receiving end extracts multiple OFDM symbols from the wireless frame data stream, each OFDM symbol including OFDM symbol cyclic prefix domain data and OFDM symbol data. Among them, the OFDM symbol is denoted as a_rx_ofdm. As shown in Figure 2 Step 2.

[0026] Step 3: Extract the OFDM symbol cyclic prefix domain data from the OFDM symbol, denoted as a_rx_CpData, and extract the OFDM symbol data of the cyclic prefix length from the tail of the OFDM symbol data domain, denoted as a_rx_OfdmCpData. Perform correlation calculation on a_rx_CpData and a_rx_OfdmCpData to obtain the phase angle of the correlation peak As shown in Figure 2 Step 3.

[0027] The calculation formula is:

[0028] Among them: “angle()” represents the calculation formula of the angle; “conj()” represents the conjugate transpose calculation; “sum()” represents the summation calculation; and “*” represents the matrix multiplication.

[0029] Step 4: assuming that OFDM symbol 1 is taken out from t1 time, and OFDM symbol 2 is taken out from t2 time, the phase angle corresponding to the correlation peak value calculated is And As Figure 2 In 4.

[0030] The calculation formula of the Doppler rate of change is

[0031] Wherein: T is defined as the FFT size of the waveform divided by the sampling rate, indicating the time length of an OFDM symbol;

[0032] Step 5: using the same principle to calculate the Doppler rate of change N times, then a group of epsilon 1, epsilon 2, epsilon 3,..., epsilon N The average of the group is the final Doppler rate of change. As Figure 2 In 4.

[0033] The calculation formula is as follows:

[0034]

[0035] The beneficial effects of the present application are:

[0036] In the low-orbit satellite communication system, not only the influence of the Doppler shift on the communication needs to be considered, but also the influence of the Doppler frequency shift rate needs to be considered, which is different from the ground system, only the Doppler frequency shift compensation can be performed, the influence of the Doppler rate of change on the communication is very small, and the Doppler rate of change can be ignored, and the present application provides a calculation method for calculating the Doppler frequency shift rate at the receiving end.

[0037] Firstly, in the low-orbit satellite communication, the ephemeris information in the system message is usually used by the receiving end to calculate the Doppler frequency shift and the Doppler rate of change, and the present application provides a method for calculating the Doppler rate of change without the ephemeris information in the system message.

[0038] Secondly, in the process of calculating the Doppler rate of change, the frequency precise synchronization and the timing precise synchronization between the receiving end and the sending end are not needed, and the Doppler rate of change can be calculated by using the relationship between the frame data before and after the receiving signal.

[0039] Thirdly, in the process of calculating the Doppler rate of change, only the time domain signal is needed to participate in the calculation, so that the calculation complexity is greatly simplified, and this is beneficial to the actual engineering implementation.

[0040] Fourthly, the present application does not need to analyze the specific content in the wireless communication data frame, but only the cyclic prefix of each symbol can be used to realize, and each OFDM symbol can be used as sample data to calculate, so that it is beneficial to calculate multiple times and then take the average value, and the precision of calculating the Doppler rate of change is improved.

[0041] Other advantages, objects, and features of the present invention will be described in part in the following description and, in part, will be apparent to those skilled in the art upon examination of the following description or may be learned from practice of the present invention. The objects and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to make the purpose, 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, in which:

[0043] Figure 1 The calculation method of Doppler change rate for OFDM system;

[0044] Figure 2 The calculation process of Doppler change rate for OFDM system;

[0045] Figure 3 Schematic diagram of cyclic prefix and symbol data of a single OFDM symbol;

[0046] Figure 4 Schematic diagram of calculating the Doppler change rate for any two OFDM symbols;

[0047] Figure 5 Simulating links for low-orbit satellite communication systems;

[0048] Figure 6 is the Doppler change rate accuracy under different signal-to-noise ratio scenarios;

[0049] Figure 7 is the Doppler change rate accuracy under different synchronization deviations;

[0050] Figure 8 It is the Doppler change rate accuracy in different low-orbit satellite communication channel scenarios. DETAILED DESCRIPTION

[0051] The following describes the embodiments of the present invention by means of specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0052] The drawings are only used for exemplary illustration, and the representation is only a schematic diagram, not a physical diagram, and cannot be understood as a limitation on the present application; in order to better illustrate the embodiments of the present application, some components of the drawings will be omitted, enlarged or reduced, and do not represent the size of the actual product; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings can be omitted.

[0053] The same or similar reference numerals in the drawings of the embodiments of the present application correspond to the same or similar components; in the description of the present application, it should be understood that if the terms "upper", "lower", "left", "right", "front", "back" and the like indicate the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, therefore the terms describing the positional relationship in the drawings are only used for exemplary illustration, and cannot be understood as a limitation on the present application, for those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0054] In this embodiment, first, the mathematical derivation process of the present application is explained from the principle, and then the actual link simulation is explained.

[0055] In the low-orbit satellite communication in the NTN communication system, OFDM modulation mode is used for transmission, and each OFDM symbol structure is as shown in Figure 3 A complete OFDM symbol has two parts, OFDM symbol cyclic prefix domain and OFDM symbol data domain. The OFDM symbol cyclic prefix domain data and the tail of the OFDM symbol data domain are the same. The OFDM symbol cyclic prefix domain is denoted as a_rx_CpData; the tail data of the OFDM symbol data domain is denoted as a_rx_OfdmCpData.

[0056] Suppose the mathematical expression of the CP data sent by the sending end is s(t), and the mathematical expression of the received signal is:

[0057]

[0058] Where Δf represents the Doppler shift; ε represents the Doppler rate of change.

[0059] According to the cyclic prefix principle of the OFDM system, the mathematical expression of the data after T time is:

[0060]

[0061] Where T represents the length of an OFDM symbol.

[0062] Correlation calculation is performed on the two cyclic prefixes, where t1 represents the start time of the cyclic prefix calculation

[0063]

[0064] Then Δφ1 can be expressed as:

[0065] Δφ1 = 2π(Δf + εt1)t1 - j2π(Δf + ε(t1 + T))(t1 + T) = -4πεt1T - 2πΔfT - 2πεT2

[0066] From the above equation, in the terrestrial mobile communication system, assuming that the Doppler rate ε is 0, it is the typical Doppler shift calculation formula.

[0067] Δφ1 = -2πΔfT

[0068]

[0069] In the low-orbit satellite communication system, since the Doppler rate ε is not 0, it cannot be directly assumed to be 0 for processing. Then in the following equation, there are two unknown variables, namely the Doppler shift Δf and the Doppler rate ε.

[0070] Δφ1 = -4πεt1T - 2πΔfT - 2πεT2

[0071] In order to calculate the Doppler shift Δf and the Doppler rate ε, another OFDM cyclic prefix data needs to be calculated. As shown in Figure 4 .

[0072] Similarly, the principle is expressed as:

[0073] Δφ2 = -4πεt2T - 2πΔfT - 2πεT2

[0074] Combine the two equations into an equation group

[0075]

[0076] Subtract the two expressions, and the following equation can be obtained.

[0077] Δφ1 - Δφ2 = -4πεt1T - 4πεt2T = -4πε(t1 - t2)T

[0078] That is:

[0079]

[0080] Where: (t1 - t2) is the time difference between two OFDM symbols.

[0081] In this embodiment, the calculation formula derivation process of calculating the Doppler rate is provided above, and the Matlab link is used below to simulate the performance analysis of the present application in the specific embodiment.

[0082] Figure 5 The Matlab simulation link of calculating the Doppler rate is given. In the simulation, the subcarrier spacing of the OFDM symbol is set to 15 kHz, the FFT size of the OFDM symbol is 4096, denoted as fft_Size, and 2 frames (20 ms) of data, i.e. 20 slots, are simulated. Each slot has 14 OFDM signals, and the CP length of each slot is [320 288 288 288 288 288 288 320 288 288 288 288 288 288], a total of 280 OFDM signals, and the sampling rate is 4096*15000, denoted as sampleRate.

[0083] In this embodiment, the Doppler rate is calculated once every 20 ms. The signal-to-noise ratio range is set to -20 dB to 30 dB, denoted as snr.

[0084] According to Figure 5 The Matlab simulation process is introduced below.

[0085] Step 1: Bit data module, randomly generate bit data stream, length 24576 bits (4096x6=24576), denoted as a_tx_bitData. A total of 4096 subcarriers are used, and a 64QAM modulation mode is used, and each modulation symbol carries 6 bits of data.

[0086] Step 2: Perform 64QAM modulation on the bit data, i.e. modulate the 24576 bits of data into 4096 modulation symbols, denoted as a_txModSymbolSig.

[0087] Step 3: Map the 4096 modulation symbols to the 4096 subcarriers, perform inverse Fourier transform (IFFT), and select 4096 IFFT points to obtain the time domain data of an OFDM symbol, denoted as a_ofdm_waveform.

[0088] Step 4: According to the position of the OFDM symbol in a slot, add the corresponding CP length data. The specific CP data length is [320 288 288 288 288 288 288 320 288 288 288 288 288 288], wherein 320 represents the CP length of the first OFDM symbol in the slot.

[0089] Step 5: The performance evaluation is not affected by the specific bit data carried, so the bit data carried by each OFDM symbol can be the same. Repeat the 14 OFDM symbol data, and add CP to the 14 OFDM symbols in turn to form a complete time slot data. Repeat the time slot data 20 times, that is, get 280 symbols (20 ms), that is, the time domain data of 2 frame length. Denoted as a_tx_waveform.

[0090] Step 6: The prepared a_tx_waveform time domain data is passed through the NTN Channel channel model, which is completed by using the NTN library function of Matlab, denoted as a_channel_waveform.

[0091] Step 7: Based on the output of the NTN Channel, the Doppler shift and the Doppler rate are added to the transmitted signal.

[0092]

[0093] Wherein, a_channel_waveform represents the input and output signal; Δf represents the Doppler shift; ε represents the Doppler rate; T c Indicates the reciprocal of the OFDM symbol sampling frequency.

[0094] Step 8: Add Gaussian white noise to the a_channel_waveform signal, which is completed by using the awgn function of Matlab, denoted as a_rx_waveform. Used to evaluate the accuracy of calculating the Doppler rate under different signal-to-noise ratios.

[0095] Step 9: Simulate the synchronization offset module. In the simulation of the embodiment, the default is a completely synchronized scene. In order to verify the influence of synchronization deviation on the performance of calculating the Doppler rate, a fixed synchronization deviation is added. That is, 0 is added in front of the a_rx_waveform sequence, indicating the number of points of the synchronization deviation, denoted as a_rx_offSyncWaveform

[0096] Step 10: Complete the OFDM signal reception. Receive 20ms of time domain waveform data, that is, two frame data time domain length, get 280 symbols of time domain data. Record as a_rx_ofdm array, which represents the time domain data of each OFDM symbol.

[0097] Note: Because the CP length of each OFDM symbol is different, not all OFDM symbol time domain data lengths are the same.

[0098] Step 11: Take out the CP data of the head of each OFDM symbol from the a_rx_ofdm array, and mark it as a_rx_CpData, and take out the data of the length CP from the tail of the OFDM symbol, and mark it as a_rx_OfdmCpData. Calculate the angle offset value of 14 OFDM symbols corresponding to each two time slots in turn, a total of 19 groups of data. Then sum and average to obtain a group of average angle offset values.

[0099]

[0100] Wherein: "angle()" represents the calculation of the angle formula; "conj()" represents the calculation of the conjugate transpose; "sum()" represents the summation calculation; "*" represents matrix multiplication.

[0101] Step 12: Calculate a group of Doppler rate values using the group of average angle offset values. Assuming that OFDM symbol 1 is taken out from t1 time and OFDM symbol 2 is taken out from t2 time. The phase angle corresponding to the calculation of the correlation peak value is and

[0102] The calculation formula of the Doppler rate is

[0103] Wherein: T represents the time length of the OFDM symbol, for reference Figure 4 .

[0104] Step 13: Calculate the average of the obtained group of Doppler rate values, and then obtain the final Doppler rate.

[0105]

[0106] In order to illustrate the performance of the Doppler rate calculated in the present embodiment, the following several scenarios will be described.

[0107] Scenario 1: Performance of Doppler rate under different signal-to-noise ratios.

[0108] The simulation sets the Doppler rate to 8KHz, and evaluates the algorithm performance under the Gaussian white noise in the range of-20 to 30dB. The simulation results are shown in Figure 6 . The fluctuation of the calculated Doppler rate under different signal-to-noise ratios.

[0109] When the signal-to-noise ratio is in the range of -20dB to -4dB, the calculated Doppler rate is quite different from the initial value 8kHz, and the fluctuation is significant. This shows that in the low signal-to-noise ratio condition, due to the poor signal quality affected by noise, the accuracy of signal feature extraction at the receiving end is reduced, resulting in a large calculation error, and the estimated Doppler rate deviates from the actual value. Noise interference can affect the phase recovery of the symbol, resulting in a large and unstable fluctuation of the estimated Doppler shift. Therefore, in the low signal-to-noise ratio environment, the estimation accuracy of the Doppler shift is insufficient, and the system performance is limited.

[0110] Compared with the above, when the signal-to-noise ratio is increased to the range of -4dB to 30dB, the calculated Doppler rate fluctuates slightly around 8kHz, indicating that the calculation accuracy is significantly improved, and the estimated Doppler rate is closer to its true value. After the signal-to-noise ratio is improved, the noise interference on the signal is significantly reduced, and the receiving end can more accurately recover the phase change of the signal, thereby improving the estimation accuracy of the Doppler shift. In this range, the system has strong anti-interference ability and can effectively cope with the influence of channel fading and noise, ensuring that the estimation performance of the Doppler rate is ideal.

[0111] Therefore, the signal-to-noise ratio is one of the important factors affecting the algorithm. In the low signal-to-noise ratio environment, noise will have a great influence on phase recovery and frequency offset estimation, resulting in large fluctuations and high errors in the calculation results; while in the environment with high signal-to-noise ratio, the calculation error is significantly reduced, and the algorithm can provide more accurate and stable Doppler rate estimation values.

[0112] In actual engineering, when the signal-to-noise ratio is -4dB, the signal-to-noise ratio requirement of the low-orbit satellite communication system is met.

[0113] Scenario 2: Influence of synchronization deviation on Doppler rate estimation performance

[0114] In actual engineering implementation, the Doppler rate calculation is performed immediately after coarse synchronization is completed, so at this moment the receiving end cannot be in an accurate synchronization state, so in this embodiment the influence of synchronization deviation on the performance of Doppler rate calculation will be evaluated.

[0115] In the simulation, the offset is set to 0:30:600. Assuming that the fixed signal-to-noise ratio is 20dB, the Doppler rate under different synchronization deviations is calculated, and the preset true value 8kHz is subtracted to output the graph. The simulation result is shown in Figure 7 .

[0116] When the receiving delay is within the CP length, the cyclic prefix of the symbol can well play a protective role. Due to the periodic characteristics of the OFDM symbol, the cyclic prefix serves as a repeated part of the symbol, so that even if there is a small amount of synchronization delay, the receiving end can still calculate the phase offset of the symbol through the correlation of the CP. Such a synchronization mechanism ensures that when the delay does not exceed the CP length, the estimation accuracy of the system to the phase offset will not be significantly affected, and the calculated Doppler shift rate change still has high accuracy.

[0117] When the receiving delay is close to the maximum length of the CP but does not exceed it, the symbol phase offset angle calculated according to the correlation peak has a large error. Therefore, in this case, the method has failed to accurately estimate the Doppler shift rate change.

[0118] When the receiving delay exceeds the CP length, the periodic characteristics of the symbol in the signal will be destroyed, resulting in inaccurate estimation of the phase offset of the OFDM symbol, which in turn affects the calculation of the Doppler shift rate change and the demodulation performance of the symbol. In this case, the system can no longer rely on the cyclic prefix to correct the error caused by the offset, which will result in a significant increase in interference and a significant decrease in calculation accuracy. In actual communication systems, the CP length in the signal is greater than the maximum delay of the system, which can ensure the calculation accuracy of the present application.

[0119] Scenario 3: Influence of channel scene on Doppler rate estimation performance

[0120] In a low-orbit satellite communication system, only the Gaussian white noise channel model does not have representative performance, so this embodiment uses the satellite channel model function provided by Matlab to evaluate the performance under different satellite communication models.

[0121] NTN channel parameter initialization: carrier frequency is 2GHz, orbit elevation angle is 50°, satellite orbit height is 600km, orbit speed is 7562.2m / s, mobile end speed is 0.83m / s, etc. The downlink model in the simulation of terminal and satellite communication. In this embodiment, the channel model is composed of three parts: configuration parameters, setting channel model parameters, and simulation using channel model.

[0122] The simulation results are as follows Figure 8The four simulation curves represent the simulation results of the mean square error of the estimated Doppler shift rate under different signal-to-noise ratios (SNRs) for four different channel scenarios (NTN-TDL-A, NTN-TDL-B, NTN-TDL-C, and NTN-TDL-D). The horizontal axis represents the signal-to-noise ratio, from -20 dB to 30 dB, and the vertical axis represents the mean square error (MSE) of the Doppler shift rate. The higher the MSE, the less accurate the channel estimation of the Doppler shift rate. Blue represents the NTN-TDL-A channel, orange represents the NTN-TDL-B channel, yellow represents the NTN-TDL-C channel, and purple represents the NTN-TDL-D channel.

[0123] As can be seen from Figure 8 In the low SNR interval, each curve has a large fluctuation and a high error. As the SNR increases to -5 dB, the MSE begins to decrease significantly. The mean square error of most channels in this interval decreases, and the error fluctuation gradually stabilizes. In the high SNR interval, the estimation of the Doppler shift rate fluctuates linearly, and the calculation accuracy is high. NTN-TDL-A exhibits a certain fluctuation in the lower SNR interval, but its overall trend is that the error decreases as the SNR increases. NTN-TDL-C and NTN-TDL-D exhibit relatively better stability after the SNR increases, especially NTN-TDL-D (purple curve), whose error quickly decreases after -5 dB.

[0124] Therefore, the algorithm exhibits stable Doppler rate estimation performance under different channel models.

[0125] Finally, it should be pointed out that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the purpose and scope of the technical solutions, and they should be included in the scope of the claims of the present application.

Claims

1. A method for calculating Doppler rate in a low earth orbit satellite communication system, the method comprising the steps of: Step 1: After the receiving end completes the base station signal search of the non-ground system, the downlink timing synchronization process with the base station is completed, that is, the receiving end obtains the frame timing information and the wireless frame structure information; the receiving end receives a wireless frame data stream, denoted as a_rx_waveform; Step 2: According to the wireless frame structure parameters, the receiving end takes a plurality of orthogonal frequency division multiplexing (OFDM) symbols from the wireless frame data stream, each OFDM symbol including an OFDM symbol cyclic prefix domain data and an OFDM symbol data domain, denoted as a_rx_ofdm; Step 3: Take out OFDM symbol cyclic prefix domain data from the OFDM symbol, denoted as a_rx_CpData, take out OFDM symbol data of cyclic prefix length from the tail of OFDM symbol data domain, denoted as a_rx_OfdmCpData, and perform correlation calculation on a_rx_CpData and a_rx_OfdmCpData to obtain the phase angle of correlation peak The calculation formula is: Wherein, angle() represents the calculation of the angle formula; conj() represents the conjugate transpose calculation; sum() represents the summation calculation; * represents matrix multiplication; Step 4: Assuming that OFDM symbol 1 is taken out from time t1, and OFDM symbol 2 is taken out from time t2; the phase angle of the correlation peak is calculated as and The formula for calculating the Doppler rate is Wherein: T represents the time length of one OFDM symbol data domain; Step 5: Calculate the Doppler rate of change N times using the same principle, and then obtain a set of ε1, ε2, ε3,..., εN N The average of this set is the final Doppler rate of change; The calculation formula of the Doppler rate is as follows:

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