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

Abstract

The present application relates to a high-precision OTFS channel estimation method, device, and system based on uniform perturbation. The method comprises: obtaining and generating an OTFS transmit signal at the transmitting end; converting the transmit signal from the delay-Doppler domain to the delay-time domain based on the sigmoid inverse Fourier transform and the Heisenberg transform, obtaining a time-domain transmit signal, and then transmitting it via an antenna; acquiring the received signal at the receiving end using the antenna, and sequentially performing a Wigner transform and a sigmoid Fourier transform to obtain a delay-Doppler domain signal; uniformly scrambling the delay-Doppler signal, comparing it with the transmit signal, obtaining integer taps of the delay and Doppler, and taking the average value. The obtained average value is a high-precision fractional delay and Doppler estimate, which can achieve channel equalization and data decoding, and can also be directly used for navigation positioning and speed measurement. The use of this method can effectively improve the accuracy of OTFS channel estimation and reduce the complexity of hardware implementation.

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 perturbation. Background Art

[0002] Mobile phone users worldwide primarily rely on terrestrial communication networks, which cover only approximately 6% of the Earth's surface. To achieve the goal of "anyone, anytime, anywhere" communication, satellite internet has become a popular space-ground integrated network application for the general public. Furthermore, low-orbit satellites, with their high landing level and low latency, offer higher-precision positioning services, making them a valuable complement to traditional satellite navigation systems. Both communication and navigation systems are moving towards low-orbit satellites. However, the high speed of low-orbit satellites and the high channel dynamics make them prone to severe inter-carrier interference when using traditional orthogonal frequency division multiplexing (OFDM) signals, resulting in a sharp decline in performance.

[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 traditional OFDM waveform, which adds an additional transformation process, it has been proven to be very robust to highly dynamic channels. Therefore, it is considered to be one of the important alternative waveforms for the future 6G low-orbit satellite Internet.

[0004] Channel estimation, one of the most critical steps in satellite communications, is not only a prerequisite for channel equalization and data decoding but also for navigation, positioning, and velocity measurement. This is because the physical quantities corresponding to delay and Doppler are distance and velocity. Traditional OTFS communications use embedded pilots for channel estimation, but their accuracy is limited to integer orders of magnitude. This is particularly true for delay estimation. Due to the relatively low accuracy requirements for delay estimation during communication, integer delay estimation fully meets the needs of communication systems, but struggles to simultaneously apply the channel estimation results to navigation and positioning. Furthermore, improving OTFS channel estimation accuracy, shifting the estimation order from integer to fractional, can further reduce the communication bit error rate and enhance OTFS's robustness in highly dynamic channels in low-Earth orbits.

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

[0007] A high-precision channel estimation method based on OTFS with uniform perturbation, the method comprising:

[0008] At the transmitter, the transmission data is acquired 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.

[0009] 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;

[0010] The time-frequency domain transmission signal is converted from the time-frequency domain to the time delay-time domain according to the Heisenberg transform, and then parallel-to-serial conversion is performed to obtain the OTFS time-domain transmission signal, which is then transmitted using the antenna;

[0011] At the receiving end, the antenna is used to collect the transmitted OTFS time domain signal to obtain the received signal, and the received signal is sequentially subjected to Wigner transform and sigmoid Fourier transform to transform the received signal into the delay-Doppler domain to obtain the delay-Doppler domain matrix.

[0012] 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;

[0013] The integer taps of delay and Doppler are summed and averaged to obtain high-precision fractional delay and Doppler estimates. These high-precision fractional delay and Doppler estimates are used to implement channel equalization and data decoding, as well as navigation positioning and speed measurement.

[0014] An OTFS high-precision channel estimation device based on uniform perturbation, the device comprising:

[0015] A signal generation module is used to obtain transmission data and generate a pseudo-random sequence; after performing channel coding and modulation mapping on 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;

[0016] 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 a 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, perform parallel-serial conversion, obtain the OTFS time-domain transmission signal, and then transmit it using the antenna;

[0017] 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 sigmoid 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;

[0018] The channel estimation module is used to uniformly scramble and tap the delay-Doppler matrix, compare it with the pilot signal of the OTFS transmission signal, and obtain the integer taps of the delay and Doppler. The integer taps of the delay and Doppler are summed and averaged, and the average value is a high-precision fractional delay and Doppler estimate;

[0019] 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;

[0020] 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.

[0021] An OTFS high-precision channel estimation system based on uniform perturbation, the system includes a receiving end and a transmitting end; a signal generation module and a sending module are provided in the transmitting end; a signal acquisition module, a channel estimation module, a data demodulation module and a navigation and positioning module are provided in the receiving end;

[0022] A signal generation module is used to obtain transmission data and generate a pseudo-random sequence; after performing channel coding and modulation mapping on 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;

[0023] 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 a 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, perform parallel-serial conversion, obtain the OTFS time-domain transmission signal, and then transmit it using the antenna;

[0024] 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 sigmoid 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;

[0025] The channel estimation module is used to uniformly scramble and tap the delay-Doppler matrix, compare it with the pilot signal of the OTFS transmission signal, and obtain the integer taps of the delay and Doppler. The integer taps of the delay and Doppler are summed and averaged, and the average value is a high-precision fractional delay and Doppler estimate;

[0026] 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;

[0027] 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.

[0028] The above-mentioned OTFS high-precision channel estimation method, device, and system based on uniform perturbation adds uniformly distributed artificial perturbations to the delay and Doppler of the received signal at the receiving end, so that the delay and Doppler taps at the receiving end are uniformly distributed with the true delay and Doppler as the mean. By averaging the integer delay and Doppler taps at the receiving end, high-precision fractional delay and Doppler estimates can be obtained. When the performance of traditional algorithm updates 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 1 is a flow chart of a uniform perturbation-based OTFS high-precision channel estimation method in one embodiment;

[0030] Figure 2 Schematic diagram of integer delay taps in one embodiment;

[0031] Figure 3 A simulation comparison diagram of the present application and other methods in one embodiment;

[0032] Figure 4 1 is a structural block diagram of an OTFS high-precision channel estimation device based on uniform perturbation in one embodiment;

[0033] Figure 5 FIG. 4 is a structural diagram of an OTFS high-precision channel estimation system based on uniform perturbation in one embodiment. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0035] In one embodiment, Figure 1 As shown, a high-precision channel estimation method based on OTFS with uniform perturbation is provided, comprising the following steps:

[0036] Step 102: The transmitting end obtains the transmission data and generates a pseudo-random sequence; performs channel coding and modulation mapping on the pseudo-random sequence and inputs it together with the embedded pilot into the OTFS-based delay-Doppler domain grid to generate an OTFS transmission signal.

[0037] At the transmitter, the transmit data is acquired and a pseudo-random sequence is generated. This pseudo-random sequence exhibits randomness and good statistical properties. After standardized operations such as channel coding and modulation mapping, it is input into the OTFS-based delay-Doppler domain grid along with the embedded pilot to generate the OTFS transmit signal. This lays the foundation for subsequent accurate signal transmission and channel estimation. The embedded pilot serves as a key reference in the subsequent channel estimation and comparison process. Standardized coding and mapping ensure signal accuracy and recognizability.

[0038] 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.

[0039] Step 106 , converting the time-frequency domain transmission signal from the time-frequency domain to the delay-time domain according to the Heisenberg transform, and performing parallel-to-serial conversion to obtain the OTFS time-domain transmission signal, which is then transmitted using an antenna.

[0040] The OTFS transmit signal is converted from the delay-Doppler domain to the time-frequency domain using the symplectic inverse Fourier transform. The Heisenberg transform is then used to convert the transmit signal from the time-frequency domain to the delay-time domain, followed by parallel-to-serial conversion. This conversion between different domains allows for different signal representations, enabling the signal to be transmitted in an appropriate form across the channel. This reduces information loss or distortion during transmission and indirectly improves channel estimation accuracy.

[0041] In step 108, at the receiving end, the 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 sigmoid Fourier transform to transform the received signal into the delay-Doppler domain to obtain a delay-Doppler domain matrix.

[0042] At the receiving end, after the antenna collects 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. This allows the received signal to return to the domain corresponding to the initial signal construction at the transmitting end. This facilitates subsequent comparison and analysis with the transmitting end signal (via the pilot signal), restoring the impact of the channel on the signal, and thus providing a basis for accurate channel estimation.

[0043] 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.

[0044] The key to this application is uniformly scrambling the delay-Doppler matrix of the received signal. By adding uniformly distributed artificial perturbations, the delay and Doppler taps at the receiver are uniformly distributed, with the true delay and Doppler as their mean. This approach cleverly incorporates more information variation, breaking the limitations of traditional estimation of integer delay and Doppler taps. This allows for more accurate fractional-level estimates, rather than being limited to integer-order estimates.

[0045] In step 112, the integer taps of the 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.

[0046] 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 now carry more information about the actual delay and Doppler. Averaging can "smooth" out the errors caused by the disturbance to a certain extent, while more accurately approximating the actual fractional delay and Doppler conditions, thus achieving an improvement in estimation accuracy from integer to fractional levels.

[0047] In the above-mentioned OTFS high-precision channel estimation method based on uniform perturbation, this application adds uniformly distributed artificial perturbations to the delay and Doppler of the received signal at the receiving end, resulting in a uniform distribution of delay and Doppler taps with the true delay and Doppler as the mean. By averaging the integer delay and Doppler taps at the receiving end, high-precision fractional delay and Doppler estimates can be obtained. When the performance of traditional algorithm updates 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.

[0048] In one embodiment, channel coding and modulation mapping are performed on a pseudo-random sequence, and then the sequence is inputted together with an embedded pilot into an OTFS-based delay-Doppler domain grid to generate an OTFS transmission signal, including:

[0049] 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 the OTFS transmission signal. , where k and lrepresent the grid indices of delay and Doppler respectively, and , , N and M represent the total number of delay and Doppler grids, respectively.

[0050] In one embodiment, converting the OTFS transmit signal from the delay-Doppler domain to the time-frequency domain according to a symplectic inverse Fourier transform to obtain a time-frequency domain transmit signal includes:

[0051] 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 ;

[0052]

[0053] 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.

[0054] In one embodiment, converting the time-frequency domain transmission signal from the time-frequency domain to the delay-time domain according to the Heisenberg transform and performing parallel-serial conversion to obtain the OTFS time-domain transmission signal includes:

[0055] According to the Heisenberg transform, the time-frequency domain transmission signal is converted from the time-frequency domain to the delay-time domain, and the parallel-serial conversion is performed to obtain the OTFS time domain transmission signal:

[0056]

[0057] 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 Indicates time, T and represent the sampling period and subcarrier spacing respectively, and The delay-Doppler domain channel spread function is expressed as , where They represent the time delay and Doppler caused by the channel,

[0058] In one embodiment, at a receiving end, an antenna is used to collect a transmitted OTFS time domain transmission signal to obtain a received signal, and the received signal is sequentially subjected to Wigner transform and sigmoid Fourier transform to transform the received signal into a delay-Doppler domain, including:

[0059] The OTFS time domain signal is collected by the antenna at the receiving end. Through the channel The received signal can be expressed as:

[0060]

[0061] After sampling, the actual delay and Doppler at the receiving end can be expressed as:

[0062]

[0063] in, and Respectively represent i The delay and Doppler tap of each path have a fractional part due to the limited sampling grid. , then the time-frequency domain signal obtained by Wigner transform is:

[0064]

[0065] in:

[0066]

[0067] represents the cross fuzzy function, Further transform to delay-Doppler domain through symplectic Fourier transform

[0068]

[0069] Then the input-output relationship of OTFS in the delay-Puller domain can be expressed as

[0070]

[0071] 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,

[0072]

[0073] in, It is the circular convolution of the channel response and the window function in the time-frequency domain.

[0074] In one embodiment, uniformly scrambling and tapping the delay-Doppler matrix and comparing it with the pilot signal of the OTFS transmission signal to obtain integer taps of the delay and Doppler include:

[0075] The delay-Doppler matrix is ​​uniformly scrambled and tapped, and compared with the pilot signal of the OTFS transmission signal to obtain the integer taps of delay and Doppler and for

[0076]

[0077]

[0078] in, and Respectively represent i The delay and Doppler tap of each path have a fractional part due to the limited sampling grid. , Both indicate adding uniform disturbance at the receiving end.

[0079] In a specific embodiment, according to It can be found that the receiving signal All sent signals Considering the sparsity of the channel function, the channel function can be further expressed as

[0080]

[0081] in and Represent the sampling matrices of the channel on the delay axis and Doppler axis respectively. , hour, It can be further expressed as

[0082]

[0083] It is not difficult to find that when hour

[0084]

[0085] 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 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:

[0086]

[0087]

[0088] in, and Respectively represent i The delay and Doppler tap of each path have a fractional part due to the limited sampling grid. , Both indicate adding uniform disturbance at the receiving end.

[0089] In one embodiment, summing and averaging integer taps of delay and Doppler further comprises:

[0090] 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 estimation is:

[0091]

[0092] Similarly, suppose for After adding uniform disturbance Doppler quantization values, whose mean is recorded as , then the high-precision fractional Doppler estimation is:

[0093] .

[0094] In a specific embodiment, Figure 3 The delay estimation simulation comparison diagram of this application and the traditional solution is shown. The proposed solution uses 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 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.

[0095] From the test results, it can be seen that the 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 with 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 the peak position is found, the shape of the correlation peak will not affect the performance of the proposed method, which reduces the requirements for the signal-to-noise ratio. More importantly, as the number of accumulations increases, the method in this paper can expand the performance lower limit of the traditional method and bring new increments.

[0096] To sum up, 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.

[0097] 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. In addition, 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.

[0098] In one embodiment, Figure 4 As shown, a high-precision OTFS channel estimation device based on uniform perturbation is provided, comprising: a signal generation module 402, a signal transmission module 404, a signal acquisition module 406, a channel estimation module 408, a data demodulation module 410 and a navigation and positioning module 412, wherein:

[0099] The signal generation module 402 is configured to obtain transmission data and generate a pseudo-random sequence; perform channel coding and modulation mapping on the pseudo-random sequence, and then input the sequence together with the embedded pilot into the OTFS-based delay-Doppler domain grid to generate an OTFS transmission signal;

[0100] The signal transmission module 404 is configured to convert the OTFS transmission signal from the delay-Doppler domain to the time-frequency domain according to a symplectic inverse Fourier transform to obtain a time-frequency domain transmission signal; convert the time-frequency domain transmission signal from the time-frequency domain to the delay-time domain according to a Heisenberg transform, perform parallel-to-serial conversion on the signal, obtain an OTFS time-domain transmission signal, and then transmit the signal via an antenna;

[0101] The signal acquisition module 406 is configured to acquire the OTFS time-domain transmission signal transmitted by the antenna to obtain a received signal, and perform Wigner transform and sigmoid Fourier transform on the received signal in sequence to transform the received signal into the delay-Doppler domain to obtain a delay-Doppler domain matrix.

[0102] Channel estimation module 408 is configured to uniformly scramble and tap the delay-Doppler matrix, compare it with the pilot signal of the OTFS transmission signal to obtain integer taps of delay and Doppler, sum and average the integer taps of delay and Doppler, and use the average value as a high-precision fractional delay and Doppler estimate.

[0103] Data demodulation module 410, 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;

[0104] The navigation and positioning module 412 is used to achieve high-precision navigation and positioning and speed measurement by using high-precision fractional delay and Doppler estimation values ​​and navigation message data.

[0105] 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. The various modules 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 hardware form, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0106] In one embodiment, Figure 5 As shown, an OTFS high-precision channel estimation system based on uniform perturbation is provided, the system includes a receiving end and a transmitting end; a signal generation module and a sending module are set in the transmitting end; a signal acquisition module, a channel estimation module, a data demodulation module and a navigation and positioning module are set in the receiving end;

[0107] A signal generation module is used to obtain transmission data and generate a pseudo-random sequence; after performing channel coding and modulation mapping on 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;

[0108] 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 a 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, perform parallel-serial conversion, obtain the OTFS time-domain transmission signal, and then transmit it using the antenna;

[0109] 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 sigmoid 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;

[0110] The channel estimation module is used to uniformly scramble and tap the delay-Doppler matrix, compare it with the pilot signal of the OTFS transmission signal, and obtain the integer taps of the delay and Doppler. The integer taps of the delay and Doppler are summed and averaged, and the average value is a high-precision fractional delay and Doppler estimate;

[0111] 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;

[0112] 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.

[0113] 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 hardware form, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0114] The technical features of the above embodiments can 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.

[0115] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and such modifications and improvements are intended to fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A high-precision channel estimation method based on OTFS with uniform perturbation, characterized in that: The method comprises: At the transmitter, the transmission data is acquired 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. 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; The time-frequency domain transmission signal is converted from the time-frequency domain to the time delay-time domain according to the Heisenberg transform, and then parallel-to-serial conversion is performed to obtain the OTFS time-domain transmission signal, which is then transmitted using the antenna; At the receiving end, the antenna is used to collect the transmitted OTFS time domain signal to obtain the received signal, and the received signal is sequentially subjected to Wigner transform and sigmoid Fourier transform to transform the received signal into the delay-Doppler domain to obtain the delay-Doppler domain matrix. 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; The integer taps of the delay and Doppler are summed and averaged, where the average value is a high-precision fractional delay and Doppler estimate; the high-precision fractional delay and Doppler estimate is used to implement channel equalization and data decoding as well as navigation positioning and speed measurement; 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 have a fractional part due to the limited sampling grid. , Both indicate adding uniform disturbance at the receiving end; 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: 。 2. The method according to claim 1, characterized in that Channel coding and modulation mapping are performed on the pseudo-random sequence, and the sequence is input together with the embedded pilot into the OTFS-based delay-Doppler domain grid to generate the OTFS transmission signal, including: 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 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, wherein 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 parallel-to-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 Indicates time, T and represent the sampling period and subcarrier spacing respectively, and .

5. The method according to claim 1, wherein At the receiving end, the antenna is used to collect the transmitted OTFS time domain signal to obtain the received signal. The received signal is then subjected to Wigner transform and sigmoid Fourier transform in sequence to transform the received signal into the delay-Doppler domain, including: The OTFS time domain 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 have a fractional part due to the limited sampling grid. , then the time-frequency domain signal obtained by Wigner transform is: in: represents the cross fuzzy function, Further transform to the delay-Doppler domain through sigmoid 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. 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 performing channel coding and modulation mapping on 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 a 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, perform parallel-serial conversion, 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 sigmoid 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 configured to uniformly scramble and tap the delay-Doppler matrix, compare the results 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, where the average value is a high-precision fractional delay and Doppler estimation value; uniformly scramble and tap the delay-Doppler matrix, and compare the results 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 have a fractional part due to the limited sampling grid. , Both indicate adding uniform disturbance at the receiving end; 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: ； 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.

7. A high-precision OTFS channel estimation system based on uniform perturbation, comprising a receiving end and a transmitting end; the transmitting end is provided with a signal generation module and a sending module; the receiving end is provided with a signal acquisition module, a channel estimation module, a data demodulation module, and a navigation and positioning module; A signal generation module is used to obtain the transmission data and generate a pseudo-random sequence; After channel coding and modulation mapping, the pseudo-random sequence is input together with the embedded pilot into the OTFS-based delay-Doppler domain grid to generate the 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 a 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, perform parallel-serial conversion, 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 sigmoid 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 configured to uniformly scramble and tap the delay-Doppler matrix, compare the resulting delay and Doppler integer taps with the pilot signal of the OTFS transmission signal, and sum and average the integer taps of the delay and Doppler, where the average value is a high-precision fractional delay and Doppler estimate. 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 have a fractional part due to the limited sampling grid. , Both indicate adding uniform disturbance at the receiving end; 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: ； 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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