A channel estimation method, apparatus, device and medium

Abstract

This application discloses a channel estimation method, apparatus, device, and medium in the field of mobile communication system technology. The method includes: sequentially sending each original sequence to a target channel, and simultaneously sending a training sequence to a channel estimator; the original sequences sequentially include a training sequence and a data sequence; the training sequence sequentially includes a cyclic prefix and a training UW sequence; inputting each target sequence, the sum of each output sequence of the target channel and Gaussian white noise, into the channel estimator; determining the target UW sequence and the training UW sequence respectively from the latest obtained target sequence and training sequence based on the cyclic prefix by the channel estimator, and performing channel estimation based on the target UW sequence and the training UW sequence to obtain the channel impulse response of the target channel. Therefore, the presence of the cyclic prefix in this application makes the acquisition of the target UW sequence and the training UW sequence more accurate, further improving the accuracy of channel estimation.

Description

Technical Field

[0001] This invention relates to the field of mobile communication system technology, and in particular to a channel estimation method, apparatus, device, and medium. Background Technology

[0002] Currently, wireless channels suffer from harsh propagation environments, leading to inter-symbol interference and severe signal distortion in received signals. This characteristic of wireless channels results in significant randomness, making channel estimation and prediction essential.

[0003] Channel estimation based on training sequences is the main method for channel estimation in SCFDE (Single Carrier Frequency Domain Equalization) systems. Its basic idea is to send training data at the transmitter, and then, at the receiver, after removing the data portion, perform calculations with the sent training sequence to obtain the channel estimate. The simplest channel estimation method is pilot-assisted, with the frame structure as follows: Figure 1 As shown, pilot signals and data are transmitted in a certain ratio, and a cyclic prefix (CP) is also needed to address the impact of inter-symbol interference. In low- and medium-speed communication systems, pilot-based channel estimation methods are generally used because these systems occupy narrow channel bandwidths, resulting in fewer symbols per data block. Therefore, using the entire data block as a pilot for channel estimation is a reasonable approach.

[0004] For medium- and high-speed communication systems, the channel bandwidth is relatively wide, and the number of symbols in each data block is large. Using the entire data block as a pilot for channel estimation presents two problems: first, the data transmission efficiency is low due to the simultaneous presence of pilots and CPs; second, the influence of residual frequency offset cannot be overcome, leading to a cumulative residual frequency offset effect and limiting the system's bit error rate performance. To address these issues, many researchers have conducted in-depth studies on the training data of medium- and high-speed SCFDE systems, finding that the unique word (UW)-based method is more suitable for SCFDE systems. Its channel estimation process consists of two steps: first, calculating the ratio of the received UW sequence to the transmitted UW sequence in the frequency domain; second, interpolation calculation. This method is simple to implement and has low computational complexity, and has been adopted by mainstream wireless communication protocols such as IEEE 802.16 and LTE (Long Term Evolution). However, the unique word-based method can lead to inaccurate channel estimation.

[0005] In conclusion, improving the accuracy of channel estimation is a pressing issue that needs to be addressed. Summary of the Invention

[0006] In view of this, the purpose of this invention is to provide a channel estimation method, apparatus, device, and medium that can improve the accuracy of channel estimation. The specific solution is as follows:

[0007] In a first aspect, this application discloses a channel estimation method, including:

[0008] Each original sequence is sent sequentially to the target channel, and a training sequence is sent simultaneously to the channel estimator; the original sequences sequentially include a training sequence and a data sequence; the training sequence sequentially includes a cyclic prefix and a training UW sequence.

[0009] The target sequence, consisting of the sum of each output sequence of the target channel and Gaussian white noise, is sequentially input into the channel estimator.

[0010] The channel estimator determines the target UW sequence and the training UW sequence from the latest obtained target sequence and the training sequence respectively based on the cyclic prefix, and performs channel estimation based on the target UW sequence and the training UW sequence to obtain the channel impulse response of the target channel.

[0011] Optionally, the number of symbols corresponding to the cyclic prefix is ​​not less than the number of symbols corresponding to the synchronization error; the synchronization error is the time error between the time when the channel estimator acquires the target sequence and the estimated time; the number of symbols corresponding to the synchronization error is the product of the time error and the transmission time of a single symbol.

[0012] Optionally, the number of symbols corresponding to the training sequence is not less than the sum of the number of symbols corresponding to the synchronization error and the number of symbols corresponding to the maximum delay of the target channel; the number of symbols corresponding to the maximum delay is the product of the maximum delay and the transmission time of a single symbol.

[0013] Optionally, the channel estimation method further includes:

[0014] When the step of sequentially sending each original sequence to the target channel ends, the training sequence is simultaneously sent to the channel estimator and the target channel once.

[0015] Optionally, the training UW sequence is a CHU sequence or a Frank-Zadoff sequence.

[0016] Optionally, the step of obtaining the channel impulse response of the target channel by performing channel estimation based on the target UW sequence and the training UW sequence includes:

[0017] The training UW sequence and the target UW sequence are subjected to Fourier transform to obtain a first UW sequence and a second UW sequence, and the ratio of the second UW sequence to the first UW sequence is calculated to obtain the frequency response estimate corresponding to the target channel.

[0018] The frequency response estimate is subjected to an inverse Fourier transform to obtain the time-domain impulse response, and the time-domain impulse response is padded with zeros to obtain the zero-padded response.

[0019] The frequency response value obtained by performing a Fourier transform on the zero-padding response is used as the channel impulse response.

[0020] Optionally, the step of performing an inverse Fourier transform on the frequency response estimate to obtain the time-domain impulse response, and then padding the time-domain impulse response with zeros to obtain the zero-padded response, includes:

[0021] The frequency response estimate is subjected to an inverse Fourier transform to obtain a time-domain impulse response containing a first number of symbols, and the time-domain impulse response is padded with zeros to obtain a zero-padded response containing a second number of symbols; the first number is the number of symbols corresponding to the training UW sequence; the second number is the number of symbols corresponding to the original sequence.

[0022] Secondly, this application discloses a channel estimation apparatus, comprising:

[0023] A sequence transmission module is used to sequentially transmit each original sequence to the target channel and simultaneously transmit a training sequence to the channel estimator; the original sequence sequentially includes a training sequence and a data sequence; the training sequence sequentially includes a cyclic prefix and a training UW sequence.

[0024] The sequence input module is used to sequentially input each output sequence of the target channel and each target sequence consisting of the sum of Gaussian white noise into the channel estimator;

[0025] The channel estimation module is used to determine the target UW sequence and the training UW sequence from the latest obtained target sequence and the training sequence respectively based on the cyclic prefix by the channel estimator, and to perform channel estimation based on the target UW sequence and the training UW sequence to obtain the channel impulse response of the target channel.

[0026] Thirdly, this application discloses an electronic device, including:

[0027] Memory, used to store computer programs;

[0028] A processor is configured to execute the computer program to implement the aforementioned disclosed channel estimation method.

[0029] Fourthly, this application discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned disclosed channel estimation method.

[0030] As can be seen, this application sequentially sends each original sequence to the target channel and simultaneously sends a training sequence to the channel estimator. The original sequences sequentially include a training sequence and a data sequence; the training sequence sequentially includes a cyclic prefix and a training UW sequence. The target sequence, consisting of the sum of each output sequence of the target channel and Gaussian white noise, is sequentially input to the channel estimator. The channel estimator determines the target UW sequence and the training UW sequence from the latest obtained target sequence and the training sequence, respectively, based on the cyclic prefix, and performs channel estimation based on the target UW sequence and the training UW sequence to obtain the channel impulse response of the target channel. Therefore, this application determines the target UW sequence and the training UW sequence based on the cyclic prefix. The presence of the cyclic prefix makes the acquisition of the target UW sequence and the training UW sequence more accurate, avoiding the situation where part of the data sequence is incorrectly acquired when acquiring the UW sequence, and further improving the accuracy of channel estimation. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0032] Figure 1 This is a schematic diagram of the data frame structure of an existing pilot-based channel estimation method;

[0033] Figure 2 This is a flowchart of a channel estimation method disclosed in this application;

[0034] Figure 3 This is a schematic diagram of the data frame structure for an existing channel estimation method based on unique words;

[0035] Figure 4 This is a schematic diagram of the data frame structure of a channel estimation method disclosed in this application;

[0036] Figure 5 This is a block diagram of a channel estimation principle disclosed in this application;

[0037] Figure 6 This is a flowchart of a specific channel estimation method disclosed in this application;

[0038] Figure 7This is a schematic diagram of a channel estimation process disclosed in this application;

[0039] Figure 8 This is a schematic diagram of a time-domain point and a frequency-domain point with a length of 8 disclosed in this application;

[0040] Figure 9 This is a schematic diagram of a time-domain point and a frequency-domain point with a length of 32 disclosed in this application;

[0041] Figure 10 This is a schematic diagram of the structure of a channel estimation device disclosed in this application;

[0042] Figure 11 This is a structural diagram of an electronic device disclosed in this application. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] Currently, many researchers have conducted in-depth studies on the training data of medium- and high-speed SCFDE systems, finding that the unique word-based method is more suitable for SCFDE systems. The channel estimation process consists of two steps: the first step is to calculate the ratio of the received UW sequence to the transmitted UW sequence in the frequency domain; the second step is interpolation calculation. This method is simple to implement and has low computational complexity, and has been adopted by mainstream wireless communication protocols such as IEEE 802.16 and LTE. However, the unique word-based method can lead to inaccurate channel estimation.

[0045] Therefore, this application proposes a channel estimation scheme that can improve the accuracy of channel estimation.

[0046] This application discloses a channel estimation method, see [link to relevant documentation] Figure 2 As shown, the method includes:

[0047] Step S11: Send each original sequence to the target channel in sequence, and simultaneously send the training sequence to the channel estimator; the original sequence includes the training sequence and the data sequence in sequence; the training sequence includes the cyclic prefix and the training UW sequence in sequence.

[0048] In this embodiment, each original sequence is sequentially sent to the target channel, and the original sequence sequentially includes a training sequence and a data sequence. Specifically, this application sequentially and alternately sends the training sequence and the data sequence to the target channel. In this embodiment, when the step of sequentially sending each original sequence to the target channel ends, the training sequence is simultaneously sent to both the channel estimator and the target channel once. It should be noted that when the data transmission ends, the transmitted sequence ends with the training sequence, and no further data sequences are sent.

[0049] It should be noted that the existing channel estimation methods based on unique characters correspond to data frame structures such as... Figure 3 As shown, the data sequence contains D symbols, the UW sequence contains M symbols, the total length of the data block is N = D + M, and the total duration of the transport block is T. FFT =NT, where T is the symbol period, i.e., the transmission time of a single symbol; where, in the data frame structure corresponding to the existing channel estimation method, there is no cyclic prefix in the entire UW sequence (training sequence).

[0050] In this embodiment of the application, the specific structure of the data frame composed of each original sequence is as follows: Figure 4 The diagram shows the data frame structure for channel estimation in this application. Since strict symbol-level synchronization is difficult to achieve in practical systems, a cyclic prefix (CP) needs to be introduced in the UW (Usage Wrapper) section to overcome the impact of timing synchronization deviations. The data sequence (DATA) contains D symbols, meaning the data length is D. The entire UW section (training sequence) contains M symbols, of which the UW sequence contains P symbols and the CP (cyclic prefix) contains L symbols. Each transmission block consists of the cyclic prefix, the training UW sequence, and the data sequence. The total transmission length is N = D + M, and the total duration of the transmission block is T. FFT =NT, where T is the symbol period, or the transmission time of a single symbol.

[0051] It should be noted that existing channel estimation methods based on unique characters correspond to data frame types, s Data,i (t) is used to represent the data portion (data sequence) of the i-th transport block (original sequence), and UW(t) represents the UW portion (UW sequence), the i-th transport block s i (t) is represented as:

[0052]

[0053] This application adds a cyclic prefix to the channel estimation data frame, and the i-th transport block after adding the cyclic prefix... Represented as:

[0054]

[0055] Where M is the number of symbols in the training sequence; and T FFT =NT is the total transmission time of the original sequence; N is the number of symbols in the original sequence; T is the symbol period, i.e., the transmission time of a single symbol; t is time; UW(t+T) FFT ) is a cyclic prefix.

[0056] Step S12: Input each output sequence of the target channel and each target sequence, which is the sum of Gaussian white noise, into the channel estimator in sequence.

[0057] In this embodiment, after the original sequence is input to the target channel, the linear convolution of the i-th transport block with the channel impulse response becomes a circular convolution due to the presence of the cyclic prefix. Therefore, the output sequence of the target channel for the i-th transport block can be represented as: The target channel can be represented as: Where n(t) represents Gaussian white noise, Let h(t) represent circular convolution, and h(t) be the channel impulse response.

[0058] Step S13: The channel estimator determines the target UW sequence and the training UW sequence from the latest obtained target sequence and the training sequence respectively based on the cyclic prefix, and performs channel estimation based on the target UW sequence and the training UW sequence to obtain the channel impulse response of the target channel.

[0059] In this embodiment of the application, each target sequence is sequentially input to the channel estimator, and the channel estimator determines the target UW sequence and the training UW sequence from the latest acquired target sequence and the training sequence, respectively, to perform channel estimation. Thus, it can be seen that this application performs channel estimation once for each original sequence.

[0060] It should be noted that, strictly speaking, the channel is constantly changing. However, if channel estimation is performed at every moment, it will cause the channel to be unable to transmit. Therefore, a channel coherence time is usually defined, and channel estimation can be performed once within the channel coherence time. In this application, each original sequence needs to be estimated once. The channel estimated by the UW part represents the channel of the DATA part. Therefore, this application can be used for fast-changing channels with short channel coherence times.

[0061] In this embodiment, since the Unique Word (UW) sequence is known (the channel estimator has acquired the training sequence), the UW can be used for channel estimation. At this time, it is necessary to stipulate that the number of symbols corresponding to the cyclic prefix is ​​not less than the number of symbols corresponding to the synchronization error. The synchronization error is the time error between the time the channel estimator acquires the target sequence and the expected time. The number of symbols corresponding to the synchronization error is the product of the time error and the transmission time of a single symbol. It is understood that only when the number of symbols corresponding to the cyclic prefix is ​​not less than the number of symbols corresponding to the synchronization error can the channel estimator acquire the correct target UW sequence, preventing the acquisition of only a portion of the data sequence.

[0062] It should be noted that the number of symbols corresponding to the training sequence is not less than the sum of the number of symbols corresponding to the synchronization error and the number of symbols corresponding to the maximum delay of the target channel; the number of symbols corresponding to the maximum delay is the product of the maximum delay and the transmission time of a single symbol. It is understood that only when the number of symbols corresponding to the training sequence is not less than the sum of the number of symbols corresponding to the synchronization error and the number of symbols corresponding to the maximum delay of the target channel can the interference of the previous frame data (previous data sequence) on the current frame data (current data sequence) be eliminated.

[0063] In this embodiment, when the UW sequence is used for channel estimation, it is required to have a stable frequency response and good correlation and bandwidth. The IEEE 802.16a protocol proposes two UW sequences suitable for SCFDE systems: the CHU sequence and the Frank-Zadoff sequence. Both of these sequences have stable frequency responses and good correlation characteristics; therefore, the training UW sequence is either the CHU sequence or the Frank-Zadoff sequence.

[0064] In the embodiments of this application, see Figure 5 The diagram shown illustrates the principle of channel estimation. The overall process is as follows: (An original sequence includes a training sequence and a data sequence) The training sequence and the data sequence are alternately sent to the channel. Simultaneously, the training sequence is sent to the channel estimator. A target sequence is obtained by summing the output sequence after channel input and Gaussian white noise from an original sequence. The target sequence is sent to the channel estimator, which then performs channel estimation based on the target sequence and the training sequence. It should be noted that... (See also...) Figure 3 As shown, since the training sequence is sent to both the channel and the channel estimator simultaneously, rather than being a fixed training sequence determined during channel estimation, the training sequences sent in different sessions can be different.

[0065] As can be seen, this application sequentially sends each original sequence to the target channel and simultaneously sends a training sequence to the channel estimator. The original sequences sequentially include a training sequence and a data sequence; the training sequence sequentially includes a cyclic prefix and a training UW sequence. The target sequence, consisting of the sum of each output sequence of the target channel and Gaussian white noise, is sequentially input to the channel estimator. The channel estimator determines the target UW sequence and the training UW sequence from the latest obtained target sequence and the training sequence, respectively, based on the cyclic prefix, and performs channel estimation based on the target UW sequence and the training UW sequence to obtain the channel impulse response of the target channel. Therefore, this application determines the target UW sequence and the training UW sequence based on the cyclic prefix. The presence of the cyclic prefix makes the acquisition of the target UW sequence and the training UW sequence more accurate, avoiding the situation where part of the data sequence is incorrectly acquired when acquiring the UW sequence, and further improving the accuracy of channel estimation.

[0066] This application discloses a specific channel estimation method. Compared with the previous embodiment, this embodiment further explains and optimizes the technical solution. See also... Figure 6 As shown, it specifically includes:

[0067] Step S21: Send each original sequence to the target channel in sequence, and simultaneously send the training sequence to the channel estimator; the original sequence includes the training sequence and the data sequence in sequence; the training sequence includes the cyclic prefix and the training UW sequence in sequence.

[0068] For a more detailed description of the process of step S21, please refer to the relevant content disclosed in the foregoing embodiments, which will not be repeated here.

[0069] Step S22: Input each output sequence of the target channel and each target sequence, which is the sum of Gaussian white noise, into the channel estimator in sequence.

[0070] For a more detailed description of the process of step S22, please refer to the relevant content disclosed in the foregoing embodiments, which will not be repeated here.

[0071] Step S23: Perform Fourier transform on the training UW sequence and the target UW sequence to obtain a first UW sequence and a second UW sequence, and calculate the ratio of the second UW sequence to the first UW sequence to obtain the frequency response estimate corresponding to the target channel.

[0072] In this embodiment of the application, the step of performing Fourier transform on the training UW sequence and the target UW sequence to obtain the first UW sequence and the second UW sequence specifically involves: assuming the UW sequence {x} m The length of} is P, and after passing through the channel, it becomes {y}. m}, perform FFT (Fourier Transform) on the received sequence to obtain {Y} m}, the corresponding sending sequence {x m The FFT transform of} is {X} m}

[0073] In this embodiment of the application, the step of calculating the ratio of the second UW sequence to the first UW sequence to obtain the frequency response estimate of the target channel specifically involves: calculating the channel frequency response estimate using a calculation formula. The calculation formula can be expressed as:

[0074]

[0075] Where m is the length of the training sequence (number of symbols).

[0076] Step S24: Perform an inverse Fourier transform on the frequency response estimate to obtain the time-domain impulse response, and perform zero-padding on the time-domain impulse response to obtain the zero-padding response; perform a Fourier transform on the zero-padding response to obtain the frequency response value as the channel impulse response.

[0077] In this embodiment of the application, the step of performing an inverse Fourier transform on the frequency response estimate to obtain the time-domain impulse response specifically involves: [The text abruptly ends here, likely due to an incomplete or corrupted source.] By performing an IFFT (Inverse Fourier Transform) operation at point P, the corresponding channel time-domain impulse response can be obtained. The length of the channel time-domain impulse response is P.

[0078] In this embodiment of the application, the step of performing an inverse Fourier transform on the frequency response estimate to obtain a time-domain impulse response, and then performing a zero-padding operation on the time-domain impulse response to obtain a zero-padding response, includes: performing an inverse Fourier transform on the frequency response estimate to obtain a time-domain impulse response containing a first number of symbols, and then performing a zero-padding operation on the time-domain impulse response to obtain a zero-padding response containing a second number of symbols; the first number is the number of symbols corresponding to the training UW sequence; and the second number is the number of symbols corresponding to the original sequence.

[0079] It should be noted that the zero-padding operation on the time-domain impulse response yields a zero-padding response; the Fourier transform of the zero-padding response yields the frequency response value as the channel impulse response, specifically: Perform trailing zero padding to make The length is N, which is the number of FFT operation points at the receiving end (i.e., the length of the original sequence), and then... By performing an N-point FFT operation, the frequency response value can be obtained. The frequency response value is used as the channel impulse response.

[0080] It should be noted that the frequency response value calculated using the current UW sequence can be used to recover the next data sequence. The reason for padding with zeros to N is that the length of each original sequence is N.

[0081] In this embodiment of the application, the specific channel estimation process is as follows: Figure 7 As shown, the target UW sequence is taken as the pre-circular UW sequence, and the known UW sequence is the training UW sequence. Both are subjected to P-point Fourier transform (FFT) and the ratio after transformation (frequency response estimate) is calculated. The ratio is then subjected to P-point inverse Fourier transform to obtain the time-domain impulse response. The time-domain impulse response at P points is then zero-padded and interpolated to N points. Finally, the N-point Fourier transform is performed to obtain the frequency response value as the channel impulse response.

[0082] See Figure 8 The diagram shows a time-domain point and a frequency-domain point of length 8. The diagram includes a time-domain point of length 8 (top left) and a frequency-domain point of length 8 (top right). See [link / reference]. Figure 9 The diagram shows a time-domain point and a frequency-domain point of length 32. The diagram includes a time-domain point of length 32 (top left) and a frequency-domain point of length 32 (top right). When the time-domain data length is P = 8 and the interpolated data length is N = 32, the time-domain point of data with length P = 8 is first transformed to the frequency domain, and the amplitude in the frequency domain is observed (to obtain...). Figure 8 Next, zero-padding is performed on the time-domain points of data where P=8 until N=32. Finally, the data where N=32 is transformed from the time domain to the frequency domain (to obtain...). Figure 9 It should be noted that, through Figure 8 and Figure 9 The simulation experiments show that the amplitude changes in the frequency domain are basically the same after zero-padding, which verifies the feasibility of the interpolation method.

[0083] As can be seen, this application determines the target UW sequence and the training UW sequence based on the cyclic prefix. The existence of the cyclic prefix makes the acquisition of the target UW sequence and the training UW sequence more accurate, avoiding the situation of erroneously acquiring part of the data sequence when acquiring the UW sequence, and further improving the accuracy of channel estimation; the zero-padding operation satisfies the requirements for calculating the channel impulse response at N points.

[0084] Accordingly, embodiments of this application also disclose a channel estimation device, see [link to relevant documentation]. Figure 9 As shown, the device includes:

[0085] The sequence transmission module 11 is used to sequentially transmit each original sequence to the target channel, and simultaneously transmit a training sequence to the channel estimator; the original sequence sequentially includes a training sequence and a data sequence; the training sequence sequentially includes a cyclic prefix and a training UW sequence;

[0086] The sequence input module 12 is used to sequentially input each output sequence of the target channel and each target sequence consisting of the sum of Gaussian white noise into the channel estimator;

[0087] The channel estimation module 13 is used to determine the target UW sequence and the training UW sequence from the latest obtained target sequence and the training sequence respectively based on the cyclic prefix by the channel estimator, and to perform channel estimation based on the target UW sequence and the training UW sequence to obtain the channel impulse response of the target channel.

[0088] For more detailed information on the working process of each of the above modules, please refer to the relevant content disclosed in the foregoing embodiments, which will not be repeated here.

[0089] As can be seen, this application sequentially sends each original sequence to the target channel and simultaneously sends a training sequence to the channel estimator. The original sequences sequentially include a training sequence and a data sequence; the training sequence sequentially includes a cyclic prefix and a training UW sequence. The target sequence, consisting of the sum of each output sequence of the target channel and Gaussian white noise, is sequentially input to the channel estimator. The channel estimator determines the target UW sequence and the training UW sequence from the latest obtained target sequence and the training sequence, respectively, based on the cyclic prefix, and performs channel estimation based on the target UW sequence and the training UW sequence to obtain the channel impulse response of the target channel. Therefore, this application determines the target UW sequence and the training UW sequence based on the cyclic prefix. The presence of the cyclic prefix makes the acquisition of the target UW sequence and the training UW sequence more accurate, avoiding the situation where part of the data sequence is incorrectly acquired when acquiring the UW sequence, and further improving the accuracy of channel estimation.

[0090] Furthermore, embodiments of this application also provide an electronic device. Figure 11 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application.

[0091] Figure 11This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a display screen 23, an input / output interface 24, a communication interface 25, a power supply 26, and a communication bus 27. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the channel estimation method disclosed in any of the foregoing embodiments. Alternatively, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0092] In this embodiment, the power supply 26 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 25 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 24 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0093] Furthermore, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk, or optical disk, etc. The resources stored thereon may include computer programs 221, and the storage method may be temporary storage or permanent storage. The computer programs 221 may include, in addition to computer programs capable of performing the channel estimation method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, computer programs capable of performing other specific tasks.

[0094] Furthermore, embodiments of this application also disclose a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned disclosed channel estimation method.

[0095] For the specific steps of this method, please refer to the relevant content disclosed in the foregoing embodiments, which will not be repeated here.

[0096] The various embodiments in this application are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. For the same or similar parts between the various embodiments, refer to each other. As for the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and relevant parts can be referred to in the method section.

[0097] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0098] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0099] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0100] The channel estimation method, apparatus, device, and storage medium provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A channel estimation method, characterized in that, include: The original sequences are sent to the target channel in sequence, and the training sequences are sent to the channel estimator at the same time. The original sequence comprises a training sequence and a data sequence in sequence; the training sequence comprises a cyclic prefix and a training UW sequence in sequence. The target sequence, consisting of the sum of each output sequence of the target channel and Gaussian white noise, is sequentially input into the channel estimator. The channel estimator determines the target UW sequence and the training UW sequence from the latest obtained target sequence and the training sequence respectively based on the cyclic prefix, and performs channel estimation based on the target UW sequence and the training UW sequence to obtain the channel impulse response of the target channel; Wherein, the number of symbols corresponding to the cyclic prefix is ​​not less than the number of symbols corresponding to the synchronization error; the synchronization error is the time error between the time when the channel estimator acquires the target sequence and the estimated time; the number of symbols corresponding to the synchronization error is the product of the time error and the transmission time of a single symbol; Wherein, the number of symbols corresponding to the training sequence is not less than the sum of the number of symbols corresponding to the synchronization error and the number of symbols corresponding to the maximum delay of the target channel; the number of symbols corresponding to the maximum delay is the product of the maximum delay and the transmission time of a single symbol.

2. The channel estimation method according to claim 1, characterized in that, Also includes: When the step of sequentially sending each original sequence to the target channel ends, the training sequence is simultaneously sent to the channel estimator and the target channel once.

3. The channel estimation method according to claim 1, characterized in that, The training UW sequence is a CHU sequence or a Frank-Zadoff sequence.

4. The channel estimation method according to any one of claims 1 to 3, characterized in that, The process of obtaining the channel impulse response of the target channel by channel estimation based on the target UW sequence and the training UW sequence includes: The training UW sequence and the target UW sequence are subjected to Fourier transform to obtain a first UW sequence and a second UW sequence, and the ratio of the second UW sequence to the first UW sequence is calculated to obtain the frequency response estimate corresponding to the target channel. The frequency response estimate is subjected to an inverse Fourier transform to obtain the time-domain impulse response, and the time-domain impulse response is padded with zeros to obtain the zero-padded response. The frequency response value obtained by performing a Fourier transform on the zero-padding response is used as the channel impulse response.

5. The channel estimation method according to claim 4, characterized in that, The step of performing an inverse Fourier transform on the frequency response estimate to obtain the time-domain impulse response, and then padding the time-domain impulse response with zeros to obtain the zero-padded response, includes: The frequency response estimate is subjected to an inverse Fourier transform to obtain a time-domain impulse response containing a first number of symbols, and the time-domain impulse response is padded with zeros to obtain a zero-padded response containing a second number of symbols; the first number is the number of symbols corresponding to the training UW sequence; the second number is the number of symbols corresponding to the original sequence.

6. A channel estimation device, characterized in that, include: The sequence transmission module is used to sequentially transmit each original sequence to the target channel and simultaneously transmit the training sequence to the channel estimator. The original sequence comprises a training sequence and a data sequence in sequence; the training sequence comprises a cyclic prefix and a training UW sequence in sequence. The sequence input module is used to sequentially input each output sequence of the target channel and each target sequence consisting of the sum of Gaussian white noise into the channel estimator; The channel estimation module is used to determine the target UW sequence and the training UW sequence from the latest obtained target sequence and the training sequence respectively based on the cyclic prefix by the channel estimator, and to perform channel estimation based on the target UW sequence and the training UW sequence to obtain the channel impulse response of the target channel; Wherein, the number of symbols corresponding to the cyclic prefix is ​​not less than the number of symbols corresponding to the synchronization error; the synchronization error is the time error between the time when the channel estimator acquires the target sequence and the estimated time; the number of symbols corresponding to the synchronization error is the product of the time error and the transmission time of a single symbol; Wherein, the number of symbols corresponding to the training sequence is not less than the sum of the number of symbols corresponding to the synchronization error and the number of symbols corresponding to the maximum delay of the target channel; the number of symbols corresponding to the maximum delay is the product of the maximum delay and the transmission time of a single symbol.

7. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the channel estimation method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, Used to store a computer program; wherein, when the computer program is executed by a processor, it implements the channel estimation method as described in any one of claims 1 to 5.

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