OTFS high-precision channel estimation method, device and system based on uniform disturbance

Abstract

The invention relates to an OTFS high-precision channel estimation method, device and system based on uniform disturbance. The method comprises the following steps: acquiring and generating an OTFS sending signal at a transmitting end; according to symplectic inverse Fourier transform and Hisenberg transform, a sending signal is converted from a time delay-Doppler domain to a time delay-time domain, and after a time domain sending signal is obtained, the time domain sending signal is sent through an antenna; at a receiving end, a receiving signal is acquired by using an antenna, and Wigner transform and Sextile Fourier transform are sequentially carried out to obtain a time delay-Doppler domain signal; on the one hand, time delay-Doppler signals are uniformly scrambled and compared with sent signals to obtain integer taps of time delay and Doppler, the integer taps are averaged, and the obtained average value is a high-precision fractional time delay and Doppler estimation value, so that channel equalization and data decoding can be realized, and on the other hand, the average value can be directly used for navigation positioning and speed measurement. By adopting the method, the OTFS channel estimation precision can be effectively improved, and the complexity of hardware implementation is reduced.

Description

Technical Field

[0001] The present application relates to the field of satellite Internet technology, and in particular to an OTFS high-precision channel estimation method, device and system based on uniform disturbance. Background Art

[0002] The services provided to mobile phone users around the world mainly come from ground communication networks, but they only cover about 6% of the earth's surface. In order to achieve the goal of "anyone, anytime, anywhere" being able to communicate, satellite Internet has become a hot spot for integrated network applications for the general public. At the same time, low-orbit satellites can provide more accurate positioning services due to their advantages of high landing level and low latency, and are an important supplement to traditional satellite navigation systems. Both communication and navigation systems are developing in the direction of low-orbit satellites. However, low-orbit satellites move fast and have large channel dynamics. When using traditional orthogonal frequency division multiplexing (OFDM) signals, serious inter-subcarrier interference is likely to occur, and performance deteriorates sharply.

[0003] Fortunately, a new waveform that has recently emerged - Orthogonal Time-Frequency Space Modulation (OTFS) modulates data in the delay-Doppler domain. Compared with the additional transformation process added to the traditional OFDM waveform, it has been proven to be very robust to high dynamic channels. Therefore, it is considered to be one of the important alternative waveforms for the future 6G low-orbit satellite Internet.

[0004] In satellite communications, channel estimation is one of the most important links. It is not only a prerequisite for channel equalization and data decoding, but can also be used for navigation, positioning and speed measurement, because the physical quantities corresponding to delay and Doppler are distance and speed. In traditional OTFS communications, embedded pilots are used for channel estimation, and its estimation accuracy is limited to integer magnitude. Especially for delay estimation, since the accuracy requirements for delay estimation are relatively low during the communication process, integer delay estimation can fully meet the needs of the communication system, but it is difficult to meet the needs of applying the results of channel estimation to navigation and positioning at the same time. In addition, improving the accuracy of OTFS channel estimation and increasing the estimation order from integer to fractional can further reduce the communication bit error rate and improve the robustness of OTFS in low-orbit high-dynamic channels.

[0005] Therefore, designing a new OTFS high-precision channel estimation method and improving the estimation accuracy from integer level to fractional level has great practical significance for OTFS to realize integrated communication and navigation signals and enable the integrated construction of 6G space-air-ground. Summary of the invention

[0006] Based on this, it is necessary to provide an OTFS high-precision channel estimation method, device and system based on uniform perturbation that can improve channel estimation in response to the above technical problems.

[0007] An OTFS high-precision channel estimation method based on uniform disturbance, the method comprising: The transmission data is obtained at the transmitting end and a pseudo-random sequence is generated; the pseudo-random sequence is channel-coded and modulated and mapped, and then inputted into the OTFS-based delay-Doppler domain grid together with the embedded pilot to generate an OTFS transmission signal; The OTFS transmission signal is converted from the delay-Doppler domain to the time-frequency domain according to the symplectic inverse Fourier transform to obtain the time-frequency domain transmission signal; According to the Heisenberg transformation, the time-frequency domain transmission signal is converted from the time-frequency domain to the delay-time domain, and a parallel-serial conversion is performed to obtain the OTFS time-domain transmission signal and then send it using an antenna; At the receiving end, the antenna is used to collect the transmitted OTFS time domain transmission signal to obtain the received signal, and the received signal is subjected to Wigner transform and sigma Fourier transform in sequence to transform the received signal into the delay-Doppler domain to obtain the delay-Doppler domain matrix; The delay-Doppler matrix is ​​uniformly scrambled and tapped, and compared with the pilot signal of the OTFS transmission signal to obtain integer taps of delay and Doppler; The integer taps of delay and Doppler are summed and averaged, and the average value is a high-precision fractional delay and Doppler estimation value; the high-precision fractional delay and Doppler estimation value is used to achieve channel equalization and data decoding as well as navigation positioning and speed measurement.

[0008] An OTFS high-precision channel estimation device based on uniform disturbance, the device comprising: A signal generation module is used to obtain transmission data and generate a pseudo-random sequence; after channel coding and modulation mapping of the pseudo-random sequence, the pseudo-random sequence is input into the OTFS-based delay-Doppler domain grid together with the embedded pilot to generate an OTFS transmission signal; The signal transmission module is used to convert the OTFS transmission signal from the delay-Doppler domain to the time-frequency domain according to the symplectic inverse Fourier transform to obtain the time-frequency domain transmission signal; convert the time-frequency domain transmission signal from the time-frequency domain to the delay-time domain according to the Heisenberg transform, and perform parallel-serial conversion to obtain the OTFS time-domain transmission signal and then transmit it using the antenna; The signal acquisition module is used to collect the OTFS time domain transmission signal sent by the antenna to obtain the received signal, and perform Wigner transform and sigma Fourier transform on the received signal in sequence to transform the received signal into the delay-Doppler domain to obtain the delay-Doppler domain matrix; The channel estimation module is used to uniformly scramble and tap the delay-Doppler matrix, and compare it with the pilot signal of the OTFS transmission signal to obtain the integer taps of the delay and Doppler, sum the integer taps of the delay and Doppler and take the average value, and the average value is a high-precision fractional delay and Doppler estimation value; Data demodulation module, used to achieve channel equalization and data decoding, including communication service data and navigation message data, using high-precision fractional delay and Doppler estimation values; The navigation and positioning module is used to achieve high-precision navigation positioning and speed measurement by using high-precision fractional delay and Doppler estimation values ​​and navigation message data.

[0009] An OTFS high-precision channel estimation system based on uniform disturbance, the system comprises a receiving end and a transmitting end; a signal generating module and a sending module are arranged in the transmitting end; a signal collecting module, a channel estimation module, a data demodulation module and a navigation positioning module are arranged in the receiving end; A signal generation module is used to obtain transmission data and generate a pseudo-random sequence; after channel coding and modulation mapping of the pseudo-random sequence, the pseudo-random sequence is input into the OTFS-based delay-Doppler domain grid together with the embedded pilot to generate an OTFS transmission signal; The signal transmission module is used to convert the OTFS transmission signal from the delay-Doppler domain to the time-frequency domain according to the symplectic inverse Fourier transform to obtain the time-frequency domain transmission signal; convert the time-frequency domain transmission signal from the time-frequency domain to the delay-time domain according to the Heisenberg transform, and perform parallel-serial conversion to obtain the OTFS time-domain transmission signal and then transmit it using the antenna; The signal acquisition module is used to collect the OTFS time domain transmission signal sent by the antenna to obtain the received signal, and perform Wigner transform and sigma Fourier transform on the received signal in sequence to transform the received signal into the delay-Doppler domain to obtain the delay-Doppler domain matrix; The channel estimation module is used to uniformly scramble and tap the delay-Doppler matrix, and compare it with the pilot signal of the OTFS transmission signal to obtain the integer taps of the delay and Doppler, sum the integer taps of the delay and Doppler and take the average value, and the average value is a high-precision fractional delay and Doppler estimation value; Data demodulation module, used to achieve channel equalization and data decoding, including communication service data and navigation message data, using high-precision fractional delay and Doppler estimation values; The navigation and positioning module is used to achieve high-precision navigation positioning and speed measurement by using high-precision fractional delay and Doppler estimation values ​​and navigation message data.

[0010] The above-mentioned OTFS high-precision channel estimation method, device and system based on uniform perturbation, the present application adds uniformly distributed artificial disturbances to the delay and Doppler of the received signal at the receiving end, so that the delay and Doppler taps at the receiving end present a uniform distribution with the real delay and Doppler as the mean, and by averaging the integer delay and Doppler taps at the receiving end, a high-precision fractional delay and Doppler estimation can be obtained. When the traditional algorithm updates the estimation performance gradually approaching the limit, this method expands the Cramer-Rao lower bound of the OTFS channel estimation process by adding new information, providing a new increment and angle for fractional channel estimation, greatly improving the channel estimation accuracy of OTFS. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 A schematic diagram of a flow chart of an OTFS high-precision channel estimation method based on uniform disturbance in one embodiment; Figure 2 A schematic diagram of integer delay taps in one embodiment; Figure 3 A simulation comparison diagram of the present application and other methods in one embodiment; Figure 4 It is a structural block diagram of an OTFS high-precision channel estimation device based on uniform disturbance in one embodiment; Figure 5 FIG. 4 is a structural diagram of an OTFS high-precision channel estimation system based on uniform perturbation in an embodiment. DETAILED DESCRIPTION

[0012] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0013] In one embodiment, Figure 1 As shown, a high-precision channel estimation method based on uniform perturbation OTFS is provided, comprising the following steps: Step 102, at the transmitting end, the transmission data is obtained and a pseudo-random sequence is generated; after channel coding and modulation mapping, the pseudo-random sequence is input into the OTFS-based delay-Doppler domain grid together with the embedded pilot to generate an OTFS transmission signal.

[0014] The transmission data is obtained at the transmitting end and a pseudo-random sequence is generated. The pseudo-random sequence has randomness and good statistical characteristics. After subsequent standardized operations such as channel coding and modulation mapping, it is input into the OTFS-based delay-Doppler domain grid together with the embedded pilot to generate the OTFS transmission signal, which lays the foundation for subsequent accurate signal transmission and channel estimation. The embedded pilot can play a key reference role in the subsequent channel estimation and comparison link. Standardized coding and mapping can ensure the accuracy and identifiability of the signal.

[0015] Step 104: convert the OTFS transmission signal from the delay-Doppler domain to the time-frequency domain according to the symplectic inverse Fourier transform to obtain a time-frequency domain transmission signal.

[0016] Step 106, convert the time-frequency domain transmission signal from the time-frequency domain to the delay-time domain according to the Heisenberg transform, perform parallel-serial conversion, obtain the OTFS time-domain transmission signal, and then transmit it using an antenna.

[0017] The OTFS transmission signal is converted from the delay-Doppler domain to the time-frequency domain using the symplectic inverse Fourier transform, and the transmission signal is converted from the time-frequency domain to the delay-time domain using the Heisenberg transform and then the parallel-serial conversion is performed to obtain the OTFS time-domain transmission signal before transmission. The conversion between different domains can characterize the signal from different angles, so that the signal can be transmitted in the channel in a suitable form, reducing the loss or distortion of information during the transmission process, and indirectly helping to improve the accuracy of channel estimation.

[0018] Step 108, at the receiving end, the OTFS time domain transmission signal is collected by using an antenna to obtain a received signal, and the received signal is sequentially subjected to Wigner transform and sigma Fourier transform to transform the received signal into a delay-Doppler domain to obtain a delay-Doppler domain matrix.

[0019] At the receiving end, after the antenna is used to collect the received signal, the Wigner transform and the sigmoid Fourier transform are performed in sequence to transform the received signal into the delay-Doppler domain, so that the received signal can return to the domain corresponding to the initial signal construction at the transmitting end, which is convenient for subsequent comparison and analysis with the transmitting end signal (through the pilot), and the impact of the channel on the signal is restored, thereby providing a basis for accurate channel estimation.

[0020] Step 110, uniformly scramble and tap the delay-Doppler matrix, and compare it with the pilot signal of the OTFS transmission signal to obtain integer taps of delay and Doppler.

[0021] The key to this application is to uniformly scramble the delay-Doppler matrix of the received signal. By adding uniformly distributed artificial disturbances, the delay and Doppler taps at the receiving end are uniformly distributed with the real delay and Doppler as the mean. This method cleverly introduces more information changes, breaks the limitations of integer delay and Doppler taps in traditional estimation, and is no longer limited to the original integer order of magnitude estimation, creating conditions for obtaining more accurate fractional level estimation.

[0022] Step 112, summing the integer taps of the delay and Doppler and taking an average value, the average value is a high-precision fractional delay and Doppler estimation value; the high-precision fractional delay and Doppler estimation value is used to achieve channel equalization and data decoding as well as navigation positioning and speed measurement.

[0023] The integer taps of delay and Doppler are summed and averaged to obtain high-precision fractional delay and Doppler estimates. Due to the previous uniform scrambling operation, the integer taps at this time already carry more information about the actual delay and Doppler. By taking the average, the error caused by the disturbance can be "smoothed" to a certain extent, and the actual fractional delay and Doppler situation can be more accurately approached, thereby achieving an improvement from integer-level estimation accuracy to fractional-level estimation accuracy.

[0024] In the above-mentioned OTFS high-precision channel estimation method based on uniform perturbation, the present application adds uniformly distributed artificial disturbances to the delay and Doppler of the received signal at the receiving end, so that the delay and Doppler taps at the receiving end present a uniform distribution with the real delay and Doppler as the mean. By averaging the integer delay and Doppler taps at the receiving end, high-precision fractional delay and Doppler estimation can be obtained. When the traditional algorithm updates and estimates performance gradually approaches the limit, this method expands the Cramer-Rao lower bound of the OTFS channel estimation process by adding new information, providing a new increment and angle for fractional channel estimation, greatly improving the channel estimation accuracy of OTFS.

[0025] In one embodiment, channel coding and modulation mapping are performed on the pseudo-random sequence and then inputted into the OTFS-based delay-Doppler domain grid together with the embedded pilot to generate the OTFS transmission signal, including: After channel coding and modulation mapping of the pseudo-random sequence, it is input into the OTFS-based delay-Doppler domain grid together with the embedded pilot to generate the OTFS transmission signal , where k and l represent the grid indices of delay and Doppler, respectively, and , , N and M represent the total number of delay and Doppler grids, respectively.

[0026] In one of the embodiments, converting the OTFS transmission signal from the delay-Doppler domain to the time-frequency domain according to the symplectic inverse Fourier transform to obtain the time-frequency domain transmission signal includes: The delay-Doppler domain is discretized into an M×N grid, and the OTFS transmission signal is converted from the delay-Doppler domain to the time-frequency domain according to the symplectic inverse Fourier transform to obtain the time-frequency domain transmission signal ;

[0027] in, Indicates that OTFS sends a signal, where k and l represent the grid indices of delay and Doppler, respectively, and , , N and M represent the total number of delay and Doppler grids, respectively.

[0028] In one embodiment, the time-frequency domain transmission signal is converted from the time-frequency domain to the delay-time domain according to the Heisenberg transform, and parallel-to-serial conversion is performed to obtain the OTFS time-domain transmission signal, including: According to the Heisenberg transform, the time-frequency domain transmission signal is converted from the time-frequency domain to the delay-time domain, and then the parallel-serial conversion is performed to obtain the OTFS time-domain transmission signal:

[0029] in, Represents the signal transmitted in the time-frequency domain, m and n Represents the grid index of time and frequency respectively, N and M represent the total number of delay and Doppler grids respectively, represents the transmit shaping filter, t represents time, T and denote the sampling period and subcarrier spacing respectively, and The delay-Doppler domain channel spread function is expressed as , where They represent the delay and Doppler caused by the channel, In one embodiment, at the receiving end, an antenna is used to collect the transmitted OTFS time domain transmission signal to obtain a received signal, and the received signal is sequentially subjected to Wigner transform and sigma Fourier transform to transform the received signal into a delay-Doppler domain, including: The OTFS time domain transmission signal is collected by the antenna at the receiving end. Through the channel The received signal can be expressed as:

[0030] After sampling, the actual delay and Doppler at the receiving end can be expressed as:

[0031] in, and Respectively represent i The delay and Doppler tap of each path, due to the limited sampling grid, there is also a fractional part , then the time-frequency domain signal obtained after Wigner transform is:

[0032] in:

[0033] represents the cross fuzzy function, Further transform to the delay-Doppler domain through symplectic Fourier transform

[0034] Then the input-output relationship of OTFS in the delay-Puller domain can be expressed as

[0035] in, Indicates that OTFS sends a signal, where k and l represent the grid indices of delay and Doppler, respectively, and , , N and M represent the total number of delay and Doppler grids, respectively. and represent the delay and Doppler grid index of the received signal respectively, is a sampled version of the impulse response function,:

[0036] in, It is the circular convolution of the channel response and the window function in the time-frequency domain.

[0037] In one embodiment, the delay-Doppler matrix is ​​uniformly scrambled and tapped, and compared with the pilot signal of the OTFS transmission signal to obtain integer taps of the delay and Doppler, including: The delay-Doppler matrix is ​​uniformly scrambled and tapped, and compared with the pilot signal of the OTFS transmission signal to obtain integer taps of delay and Doppler. and for

[0038]

[0039] in, and Respectively represent i The delay and Doppler tap of each path, due to the limited sampling grid, there is also a fractional part , Both indicate adding uniform disturbance at the receiving end.

[0040] In a specific embodiment, according to It can be found that the received signal All sent signals Considering the sparsity of the channel function, the channel function can be further expressed as

[0041] in and Represent the sampling matrices of the channel on the delay axis and Doppler axis respectively. , hour, It can be further expressed as

[0042] It is not difficult to find that when hour

[0043] The above formula shows that when the delay is an integer, the tap of the DD domain grid point at the receiving end is either 0 or M. For the single pilot estimation method, as long as the peak value is found at the DD grid point at the receiving end, the accurate delay estimate can be uniquely determined. However, due to the uncertainty of the channel, integer delay usually does not exist. To achieve fractional channel estimation, this method adds uniform perturbations at the receiving end. , then for a certain path i, the delay and Doppler integer taps after adding uniform disturbance can be expressed as:

[0044]

[0045] in, and Respectively represent i The delay and Doppler tap of each path, due to the limited sampling grid, there is also a fractional part , Both indicate adding uniform disturbance at the receiving end.

[0046] In one embodiment, summing and averaging the integer taps of delay and Doppler further comprises: Average the quantized values ​​after adding uniform disturbances multiple times, and set for After adding uniform disturbance The delay quantization value, whose average is recorded as , then the high-precision fractional delay estimate is:

[0047] Similarly, suppose for After adding uniform disturbance Doppler quantization values, whose mean is recorded as , then the high-precision fractional Doppler estimation is: .

[0048] In a specific embodiment, Figure 3 The delay estimation simulation comparison diagram of this application and the traditional solution is shown. The solution of this paper applies the OTFS high-precision channel estimation method based on uniform perturbation proposed in this application, and completes the OTFS fractional channel estimation wirelessly through MATLAB software. The simulation conditions are set to embedded single pilot, the delay-Doppler domain grid size is set to M = 64, N = 30, and the subcarrier spacing is Ignoring the multipath effect for now, the path gain is , the integer part of the delay is , the cumulative number of times is Unless otherwise specified, the simulation units in this application are all the unit length "1" of the delay axis in the delay-Doppler domain, that is, s. Comparison scheme 1: Traditional single-tap integer delay estimation. Comparison scheme 2: Message passing method. Comparison scheme 3: Improved message passing method.

[0049] It can be seen from the test results that this comparison scheme is compared with the present application under the same configuration: It can be clearly seen from the figure that when the correlation peak cannot be obtained, all kinds of methods cannot perform channel estimation. After finding the correlation peak, the method in this paper improves the delay resolution by 2-3 orders of magnitude compared to the classic comparison scheme 1. With the increase of SNR, the more authoritative comparison schemes 2 and 3 gradually approach the estimation limit and achieve better performance. However, after finding the peak position, the shape of the correlation peak will not affect the performance of the proposed method, reducing the requirements for the signal-to-noise ratio. More importantly, with the increase in the number of accumulations, the method in this paper can expand the performance lower limit of traditional methods and bring new increments.

[0050] To summarize, the present application has the following advantages: the present application adds uniformly distributed disturbances at the physical layer, which is equivalent to adding new information to the estimation process from the perspective of information theory, thereby expanding the performance limit of channel estimation; compared with other methods that increase the amount of calculation to approach the performance limit, the present application reduces the complexity of hardware implementation and has higher practicality; the present application can be used as an independent increment and directly superimposed on the existing method to further improve the accuracy of channel estimation and achieve a new breakthrough in channel estimation.

[0051] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0052] In one embodiment, Figure 4 As shown, a high-precision OTFS channel estimation device based on uniform disturbance is provided, including: a signal generation module 402, a signal sending module 404, a signal acquisition module 406, a channel estimation module 408, a data demodulation module 410 and a navigation positioning module 412, wherein: The signal generation module 402 is used to obtain the transmission data and generate a pseudo-random sequence; after channel coding and modulation mapping of the pseudo-random sequence, the pseudo-random sequence is input into the OTFS-based delay-Doppler domain grid together with the embedded pilot to generate an OTFS transmission signal; The signal transmission module 404 is used to convert the OTFS transmission signal from the delay-Doppler domain to the time-frequency domain according to the symplectic inverse Fourier transform to obtain the time-frequency domain transmission signal; convert the time-frequency domain transmission signal from the time-frequency domain to the delay-time domain according to the Heisenberg transform, and perform parallel-serial conversion to obtain the OTFS time-domain transmission signal and then transmit it using the antenna; The signal acquisition module 406 is used to acquire the OTFS time domain transmission signal transmitted by the antenna to obtain the received signal, and perform Wigner transform and sigma Fourier transform on the received signal in sequence to transform the received signal into the delay-Doppler domain to obtain the delay-Doppler domain matrix; The channel estimation module 408 is used to uniformly scramble and tap the delay-Doppler matrix, and compare it with the pilot signal of the OTFS transmission signal to obtain integer taps of the delay and Doppler, sum the integer taps of the delay and Doppler and take the average value, and the average value is a high-precision fractional delay and Doppler estimation value; Data demodulation module 410, used to achieve channel equalization and data decoding using high-precision fractional delay and Doppler estimation values, including communication service data and navigation message data; The navigation and positioning module 412 is used to realize high-precision navigation and positioning and speed measurement by using high-precision fractional delay and Doppler estimation values ​​and navigation message data.

[0053] For the specific definition of the OTFS high-precision channel estimation device based on uniform perturbation, please refer to the definition of the OTFS high-precision channel estimation method based on uniform perturbation above, which will not be repeated here. Each module in the above-mentioned OTFS high-precision channel estimation device based on uniform perturbation can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0054] In one embodiment, Figure 5 As shown, a high-precision OTFS channel estimation system based on uniform disturbance is provided, the system includes a receiving end and a transmitting end; a signal generating module and a sending module are arranged in the transmitting end; a signal acquisition module, a channel estimation module, a data demodulation module and a navigation positioning module are arranged in the receiving end; A signal generation module is used to obtain transmission data and generate a pseudo-random sequence; after channel coding and modulation mapping of the pseudo-random sequence, the pseudo-random sequence is input into the OTFS-based delay-Doppler domain grid together with the embedded pilot to generate an OTFS transmission signal; The signal transmission module is used to convert the OTFS transmission signal from the delay-Doppler domain to the time-frequency domain according to the symplectic inverse Fourier transform to obtain the time-frequency domain transmission signal; convert the time-frequency domain transmission signal from the time-frequency domain to the delay-time domain according to the Heisenberg transform, and perform parallel-serial conversion to obtain the OTFS time-domain transmission signal and then transmit it using the antenna; The signal acquisition module is used to collect the OTFS time domain transmission signal sent by the antenna to obtain the received signal, and perform Wigner transform and sigma Fourier transform on the received signal in sequence to transform the received signal into the delay-Doppler domain to obtain the delay-Doppler domain matrix; The channel estimation module is used to uniformly scramble and tap the delay-Doppler matrix, and compare it with the pilot signal of the OTFS transmission signal to obtain the integer taps of the delay and Doppler, sum the integer taps of the delay and Doppler and take the average value, and the average value is a high-precision fractional delay and Doppler estimation value; Data demodulation module, used to achieve channel equalization and data decoding, including communication service data and navigation message data, using high-precision fractional delay and Doppler estimation values; The navigation and positioning module is used to achieve high-precision navigation positioning and speed measurement by using high-precision fractional delay and Doppler estimation values ​​and navigation message data.

[0055] For the specific definition of the OTFS high-precision channel estimation system based on uniform perturbation, please refer to the definition of the OTFS high-precision channel estimation method based on uniform perturbation above, which will not be repeated here. Each module in the above-mentioned OTFS high-precision channel estimation system based on uniform perturbation can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0056] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0057] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. An OTFS high-precision channel estimation method based on uniform perturbation, characterized in that: The method comprises: The transmission data is obtained at the transmitting end and a pseudo-random sequence is generated; the pseudo-random sequence is channel-coded and modulated and mapped, and then inputted into the OTFS-based delay-Doppler domain grid together with the embedded pilot to generate an OTFS transmission signal; The OTFS transmission signal is converted from the delay-Doppler domain to the time-frequency domain according to the symplectic inverse Fourier transform to obtain the time-frequency domain transmission signal; According to the Heisenberg transformation, the time-frequency domain transmission signal is converted from the time-frequency domain to the delay-time domain, and a parallel-serial conversion is performed to obtain the OTFS time-domain transmission signal and then send it using an antenna; At the receiving end, the antenna is used to collect the transmitted OTFS time domain transmission signal to obtain the received signal, and the received signal is subjected to Wigner transform and sigma Fourier transform in sequence to transform the received signal into the delay-Doppler domain to obtain the delay-Doppler domain matrix; The delay-Doppler matrix is ​​uniformly scrambled and tapped, and compared with the pilot signal of the OTFS transmission signal to obtain integer taps of the delay and Doppler; The integer taps of delay and Doppler are summed and averaged, and the average is a high-precision fractional delay and Doppler estimation value; the high-precision fractional delay and Doppler estimation value is used to achieve channel equalization and data decoding as well as navigation positioning and speed measurement.

2. The method according to claim 1, characterized in that After channel coding and modulation mapping of the pseudo-random sequence, the pseudo-random sequence is input into the OTFS-based delay-Doppler domain grid together with the embedded pilot to generate an OTFS transmission signal, including: After channel coding and modulation mapping of the pseudo-random sequence, it is input into the OTFS-based delay-Doppler domain grid together with the embedded pilot to generate the OTFS transmission signal , where k and l represent the grid indices of delay and Doppler, respectively, and , , N and M represent the total number of delay and Doppler grids, respectively.

3. The method according to claim 1, characterized in that The OTFS transmission signal is converted from the delay-Doppler domain to the time-frequency domain according to the symplectic inverse Fourier transform to obtain the time-frequency domain transmission signal, including: The delay-Doppler domain is discretized into an M×N grid, and the OTFS transmission signal is converted from the delay-Doppler domain to the time-frequency domain according to the symplectic inverse Fourier transform to obtain the time-frequency domain transmission signal ; in, Indicates that OTFS sends a signal, where k and l represent the grid indices of delay and Doppler, respectively, and , , N and M represent the total number of delay and Doppler grids, respectively.

4. The method according to claim 1, characterized in that According to the Heisenberg transform, the time-frequency domain transmission signal is converted from the time-frequency domain to the delay-time domain, and parallel-to-serial conversion is performed to obtain the OTFS time-domain transmission signal, including: According to the Heisenberg transform, the time-frequency domain transmission signal is converted from the time-frequency domain to the delay-time domain, and then the parallel-serial conversion is performed to obtain the OTFS time-domain transmission signal: in, Represents the signal transmitted in the time-frequency domain, m and n Represents the grid index of time and frequency respectively, N and M represent the total number of delay and Doppler grids respectively, represents the transmit shaping filter, t represents time, T and denote the sampling period and subcarrier spacing respectively, and .

5. The method according to claim 1, characterized in that At the receiving end, the antenna is used to collect the transmitted OTFS time domain transmission signal to obtain the received signal, and the received signal is sequentially subjected to Wigner transform and sigma Fourier transform to transform the received signal into the delay-Doppler domain, including: The OTFS time domain transmission signal is collected by the antenna at the receiving end. Through the channel The received signal can be expressed as: After sampling, the actual delay and Doppler at the receiving end can be expressed as: in, and Respectively represent i The delay and Doppler tap of each path, due to the limited sampling grid, there is also a fractional part , then the time-frequency domain signal obtained after Wigner transform is: in: represents the cross fuzzy function, Further transform to the delay-Doppler domain through symplectic Fourier transform Then the input-output relationship of OTFS in the delay-Puller domain can be expressed as in, Indicates that OTFS sends a signal, where k and l represent the grid indices of delay and Doppler, respectively, and , , N and M represent the total number of delay and Doppler grids, respectively. and represent the delay and Doppler grid index of the received signal respectively, is the sampled version of the impulse response function.

6. The method according to claim 1, characterized in that The delay-Doppler matrix is ​​uniformly scrambled and tapped, and compared with the pilot signal of the OTFS transmission signal to obtain integer taps of the delay and Doppler, including: The delay-Doppler matrix is ​​uniformly scrambled and tapped, and compared with the pilot signal of the OTFS transmission signal to obtain integer taps of delay and Doppler and for in, and Respectively represent i The delay and Doppler tap of each path, due to the limited sampling grid, there is also a fractional part , Both indicate adding uniform disturbance at the receiving end.

7. The method according to claim 1, characterized in that The integer taps of delay and Doppler are summed and averaged, including: Average the quantized values ​​after adding uniform disturbances multiple times, and set for After adding uniform disturbance The delay quantization value, its mean is recorded as , then the high-precision fractional delay estimate is: Similarly, suppose for After adding uniform disturbance Doppler quantization values, whose mean is recorded as , then the high-precision fractional Doppler estimation is: 。 8. An OTFS high-precision channel estimation device based on uniform perturbation, characterized in that: The device comprises: A signal generation module is used to obtain transmission data and generate a pseudo-random sequence; after channel coding and modulation mapping of the pseudo-random sequence, the pseudo-random sequence is input into the OTFS-based delay-Doppler domain grid together with the embedded pilot to generate an OTFS transmission signal; The signal transmission module is used to convert the OTFS transmission signal from the delay-Doppler domain to the time-frequency domain according to the symplectic inverse Fourier transform to obtain the time-frequency domain transmission signal; convert the time-frequency domain transmission signal from the time-frequency domain to the delay-time domain according to the Heisenberg transform, and perform parallel-serial conversion to obtain the OTFS time-domain transmission signal and then transmit it using the antenna; The signal acquisition module is used to collect the OTFS time domain transmission signal sent by the antenna to obtain the received signal, and perform Wigner transform and sigma Fourier transform on the received signal in sequence to transform the received signal into the delay-Doppler domain to obtain the delay-Doppler domain matrix; A channel estimation module is used to uniformly scramble and tap the delay-Doppler matrix, and compare it with the pilot signal of the OTFS transmission signal to obtain integer taps of the delay and Doppler, sum the integer taps of the delay and Doppler and take an average value, wherein the average value is a high-precision fractional delay and Doppler estimation value; Data demodulation module, used to achieve channel equalization and data decoding, including communication service data and navigation message data, using high-precision fractional delay and Doppler estimation values; The navigation and positioning module is used to achieve high-precision navigation positioning and speed measurement by using high-precision fractional delay and Doppler estimation values ​​and navigation message data.

9. An OTFS high-precision channel estimation system based on uniform disturbance, the system comprising a receiving end and a transmitting end; a signal generation module and a sending module are arranged in the transmitting end; a signal acquisition module, a channel estimation module, a data demodulation module and a navigation positioning module are arranged in the receiving end; A signal generation module, used to obtain transmission data and generate a pseudo-random sequence; After channel coding and modulation mapping of the pseudo-random sequence, the pseudo-random sequence is input into the OTFS-based delay-Doppler domain grid together with the embedded pilot to generate an OTFS transmission signal; The signal transmission module is used to convert the OTFS transmission signal from the delay-Doppler domain to the time-frequency domain according to the symplectic inverse Fourier transform to obtain the time-frequency domain transmission signal; convert the time-frequency domain transmission signal from the time-frequency domain to the delay-time domain according to the Heisenberg transform, and perform parallel-serial conversion to obtain the OTFS time-domain transmission signal and then transmit it using the antenna; The signal acquisition module is used to collect the OTFS time domain transmission signal sent by the antenna to obtain the received signal, and perform Wigner transform and sigma Fourier transform on the received signal in sequence to transform the received signal into the delay-Doppler domain to obtain the delay-Doppler domain matrix; A channel estimation module is used to uniformly scramble and tap the delay-Doppler matrix, and compare it with the pilot signal of the OTFS transmission signal to obtain integer taps of the delay and Doppler, sum the integer taps of the delay and Doppler and take an average value, wherein the average value is a high-precision fractional delay and Doppler estimation value; Data demodulation module, used to achieve channel equalization and data decoding, including communication service data and navigation message data, using high-precision fractional delay and Doppler estimation values; The navigation and positioning module is used to achieve high-precision navigation positioning and speed measurement by using high-precision fractional delay and Doppler estimation values ​​and navigation message data.

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