Channel Estimation System, Method, Medium, Program Product and Terminal

Abstract

The present application provides a channel estimation system, method, medium, program product and terminal. By using PDP information to process specified multipaths, compared with traditional methods, the present invention can save one IFFT transformation, greatly reduce the amount of computation, and has more advantages when the number of specified multipaths is small. The present invention directly sets the positions outside the specified multipaths to zero for noise reduction, which can effectively reduce the complexity. The present invention can also estimate the signal-to-noise ratio by calculating the total power of the initial frequency-domain channel and subtracting the sum of the powers of the specified multipaths, and the signal-to-noise ratio estimation result is more accurate and efficient.

Description

Technical Field

[0001] This application relates to the technical field of channel estimation, and particularly to a channel estimation system, method, medium, program product, and terminal. Background Art

[0002] Currently, in modern wireless communication systems, Orthogonal Frequency Division Multiplexing (OFDM) technology has been widely applied to communication standards such as 4G, 5G, and WIFI due to its high data transmission rate and high anti-interference ability against multipath effects. The OFDM system performs channel estimation by transmitting known sequences, such as Demodulation Reference Signals (DMRS), in frequency and time resources, which is a crucial step to ensure correct signal decoding and system performance optimization.

[0003] In a traditional OFDM system, the receiver extracts DMRS resource element information on the symbol frequency carrier carrying DMRS and performs a conjugate multiplication operation with a locally known sequence to obtain a preliminary frequency-domain channel estimation. Subsequently, this channel estimation is processed through an Inverse Fast Fourier Transform (IFFT) to be converted into the time domain and undergoes noise reduction processing to improve the quality of the channel estimation.

[0004] However, existing channel estimation methods have some limitations. Since the width of the multipath power spectrum (PDP) of the wireless channel is limited, and the IFFT processing converts the frequency-domain channel estimation into the time domain, it may introduce unnecessary computational complexity, especially when dealing with multipath components in the time domain. This conversion is not always economical because it may involve processing multipath components outside the channel window, and these components contribute little to signal decoding. Summary of the Invention

[0005] In view of the above disadvantages of the prior art, the present invention provides a channel estimation system, method, medium, program product, and terminal, which are used to solve the problems of excessive computational amount and high computational complexity in the prior art channel estimation methods.

[0006] To achieve the above and other related objectives, a first aspect of the present application provides a channel estimation system, including: a first fast Fourier transform module, configured to receive a time-domain received signal and perform fast Fourier transform processing on the time-domain received signal to obtain a frequency-domain received signal; a signal extraction module, connected to the first fast Fourier transform module, configured to perform symbol extraction processing on the frequency-domain received signal to obtain a DMRS signal; an arithmetic processing module, connected to the signal extraction module, configured to perform calculations based on the DMRS signal using a frequency-domain channel estimation model to obtain an initial frequency-domain channel estimation value; a phase rotation module, connected to the arithmetic processing module, configured to perform phase rotation processing on the initial frequency-domain channel estimation value to obtain a sub-vector set of time-domain channel estimation values corresponding to each multipath; an averaging processing module, connected to the phase rotation module, configured to perform averaging processing on the sub-vector set of time-domain channel estimation values corresponding to each multipath respectively to obtain a time-domain channel estimation value corresponding to each multipath; a serial-parallel processing module, connected to the averaging processing module, configured to perform serial-parallel processing on the time-domain channel estimation values corresponding to each multipath to form a time-domain channel estimation value vector set; a zero-padding processing module, connected to the serial-parallel processing module, configured to perform zero-padding processing on the time-domain channel estimation value vector set to obtain a noise-reduced time-domain channel estimation value vector set; a second fast Fourier transform module, connected to the zero-padding processing module, configured to perform fast Fourier transform processing on the noise-reduced time-domain channel estimation value vector set to obtain a noise-reduced frequency-domain channel estimation result.

[0007] In some embodiments of the first aspect of the present application, the system includes: a reference signal sequence module, connected to the arithmetic processing module, configured to provide a corresponding preset training signal to the arithmetic processing module.

[0008] In some embodiments of the first aspect of the present application, the system further includes: a power spectrum configuration module, connected to the phase rotation module, configured to provide preset configuration information to the phase rotation module to instruct the phase rotation module to perform phase rotation processing and obtain a sub-vector set of time-domain channel estimation values corresponding to each multipath respectively.

[0009] In some embodiments of the first aspect of the present application, the phase rotation module is divided into a plurality of Cordic rotation units according to the preset configuration information of the power spectrum configuration module; each Cordic rotation unit processes to obtain a sub-vector set of time-domain channel estimation values corresponding to each multipath respectively; each Cordic rotation unit is respectively connected to each averaging sub-processing unit in the averaging processing module.

[0010] In some embodiments of the first aspect of the present application, the system further includes: a control configuration module, connected to the zero-insertion processing module, for providing channel length configuration information to the zero-insertion processing module for performing zero-insertion processing on the received time-domain channel estimation value vector set.

[0011] In some embodiments of the first aspect of the present application, the system further includes: a control configuration module, connected to the zero-insertion processing module, for providing channel length configuration information to the zero-insertion processing module for performing zero-insertion processing on the received time-domain channel estimation value vector set.

[0012] To achieve the above object and other related objects, a second aspect of the present application provides a channel estimation method, which is applied to the channel estimation system as described above. The method includes: receiving a time-domain received signal and performing fast Fourier transform processing on the time-domain received signal to obtain a frequency-domain received signal; performing symbol extraction processing on the frequency-domain received signal to obtain a DMRS signal; calculating an initial frequency-domain channel estimation value based on the DMRS signal using a frequency-domain channel estimation model; performing phase rotation processing on the initial frequency-domain channel estimation value to obtain a time-domain channel estimation value sub-vector set corresponding to each multipath; performing an averaging process on each time-domain channel estimation value sub-vector set corresponding to each multipath to obtain a time-domain channel estimation value corresponding to each multipath; performing serial-parallel processing on the time-domain channel estimation values corresponding to each multipath to form a time-domain channel estimation value vector set; performing zero-insertion processing on the time-domain channel estimation value vector set to obtain a noise-reduced time-domain channel estimation value vector set; and performing fast Fourier transform processing on the noise-reduced time-domain channel estimation value vector set to obtain a noise-reduced frequency-domain channel estimation result.

[0013] To achieve the above object and other related objects, a third aspect of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the channel estimation method is implemented.

[0014] To achieve the above object and other related objects, a fourth aspect of the present application provides a computer program product, which includes computer program code. When the computer program code runs on a computer, the computer implements the channel estimation method.

[0015] To achieve the above object and other related objects, a fifth aspect of the present application provides an electronic terminal, including a memory, a processor, and a computer program stored on the memory; the processor executes the computer program to implement the channel estimation method.

[0016] As described above, the channel estimation system, method, medium, program product, and terminal provided by the present application have the following beneficial effects:

[0017] By using PDP information to process specified multipaths, the present invention can save one IFFT transformation compared with traditional methods, greatly reduce the computational complexity, and has more advantages when the number of specified multipaths is small. The present invention directly sets to zero the positions outside the specified multipaths for noise reduction, which can effectively reduce the complexity. The present invention can also estimate the signal-to-noise ratio by calculating the total power of the initial frequency-domain channel and subtracting the sum of the powers of the specified multipaths, and the signal-to-noise ratio estimation result is more accurate and efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It shows a schematic structural diagram of a channel estimation system in an embodiment of the present application.

[0019] Figure 2 It shows a schematic diagram of the computational simulation comparison between the algorithm of the present invention and the traditional algorithm in an embodiment of the present application.

[0020] Figure 3 It shows a schematic flowchart of a channel estimation method in an embodiment of the present application.

[0021] Figure 4 It shows a schematic structural diagram of an electronic terminal in an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] The following uses specific specific examples to illustrate the embodiments of the present application. Those skilled in the art can easily understand other advantages and effects of the present application from the content disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0023] Before further elaborating on the present invention, the nouns and terms involved in the embodiments of the present invention are described. The nouns and terms involved in the embodiments of the present invention are applicable to the following explanations:

[0024] <1> Inverse Fast Fourier Transform: IFFT is a mathematical calculation method that can convert a frequency-domain signal into a time-domain signal, facilitating time-domain analysis of the signal. This technology has extensive applications in the fields of signal processing, image processing, speech processing, audio processing, etc.

[0025] <2> Fast Fourier Transform (FFT): It is an algorithm for quickly calculating the Fourier transform and is developed based on the Fourier transform. The FFT algorithm is widely used in fields such as digital signal processing, image processing, sound processing, convolution operations, and analytic geometry. Its high efficiency and real-time performance make it an indispensable part of the current computer science field.

[0026] <3> Power Delay Profile (PDP): It refers to the relationship between the power of the signal received at the receiving end and the arrival time delay in a wireless channel. PDP is an important parameter in wireless channel modeling and plays an important role in wireless communication system design, channel estimation, multipath fading processing, etc.

[0027] For ease of understanding the embodiments of the present application, first in combination with Figure 1 detailed description, Figure 1 FIG. shows a schematic structural diagram of a channel estimation system in an embodiment of the present invention. The channel estimation system in this embodiment includes a first fast Fourier transform module 110, a signal extraction module 120, an arithmetic processing module 130, a phase rotation module 140, an averaging processing module 150, a serial-parallel processing module 160, a zero insertion processing module 170, and a second fast Fourier transform module 180.

[0028] In one embodiment, the first fast Fourier transform module 110 is configured to receive a time-domain received signal and perform fast Fourier transform processing on the time-domain received signal to obtain a frequency-domain received signal.

[0029] For example, the first fast Fourier transform module 110 receives the time-domain received signal of the receiving end to be subjected to channel estimation , and realizes the transformation of the time-domain received signal from the time domain to the frequency domain through fast Fourier transform processing to obtain a frequency-domain received signal . The frequency-domain received signal can be used to represent the amplitude and phase information of the time-domain received signal at different frequencies.

[0030] In one embodiment, the signal extraction module 120, which is connected to the first fast Fourier transform module 110, is configured to perform symbol extraction processing on the frequency-domain received signal to obtain a DMRS signal.

[0031] Specifically, the signal extraction module 120 is a timing and frequency controller (TFC). Through the TFC, DMRS symbol extraction can be realized for each symbol of the data on the frequency-domain pattern, that is, the frequency-domain received signal is subjected to symbol extraction to obtain a DMRS signal The positions of the DMRS signals in the frequency-domain received signals are preset, which facilitates the accurate identification and extraction of these signals. The DMRS signals provide necessary reference information and can be used for channel estimation, signal demodulation, etc.

[0032] In one embodiment, the operation processing module 130 is connected to the signal extraction module 120 and is configured to calculate an initial frequency-domain channel estimation value based on the DMRS signals by using a frequency-domain channel estimation model.

[0033] Specifically, after obtaining the DMRS signals, initial frequency-domain channel estimation can be further performed. The initial frequency-domain channel estimation can be obtained by calculating according to the calculation formula of the DMRS signals. The calculation formula of the DMRS signals is:

[0034] ; (Formula 1)

[0035] Wherein, is the DMRS signal, is the initial frequency-domain channel estimation value, is the locally known frequency-domain channel training code, is the frequency-domain Gaussian white noise, is the corresponding th subcarrier. Further processing the above formula, the calculation formula of the frequency-domain channel estimation model can be obtained as:

[0036] ; (Formula 2)

[0037] Wherein, is the initial frequency-domain channel estimation value, is the DMRS signal, is the locally known frequency-domain channel training code. The training code is usually the normalized modulation symbol, and the normalization process of the denominator can be omitted at this time. For example, for the symbol modulated by QPSK, takes the value of .

[0038] In one embodiment, the channel estimation system further includes a reference signal sequence module 131, which is connected to the operation processing module 130 and is configured to provide a corresponding preset training signal to the operation processing module 130.

[0039] It should be noted that when calculating the initial frequency-domain channel estimation value by using the frequency-domain channel estimation model, according to the calculation formula of the frequency-domain channel estimation model, the locally known frequency-domain channel training code is required. In this embodiment, the corresponding preset training signal is provided by the reference signal sequence module 131, and the preset training signal is the locally known frequency-domain channel training code , one-to-one correspondence with .

[0040] In one embodiment, the phase rotation module 140 is connected to the operation processing module 130 and is configured to perform phase rotation processing on the initial frequency-domain channel estimation value to obtain a sub-vector set of time-domain channel estimation values corresponding to each multipath respectively.

[0041] In one embodiment, the system further includes: a power spectrum configuration module 141, connected to the phase rotation module 140, for providing preset configuration information to the phase rotation module 140 to instruct the phase rotation module 140 to perform phase rotation processing and respectively obtain a sub-vector set of time-domain channel estimation values corresponding to each multipath.

[0042] In one embodiment, the averaging processing module 150 is connected to the phase rotation module 140 and is configured to perform averaging processing on the sub-vector sets of time-domain channel estimation values corresponding to each multipath respectively to obtain the time-domain channel estimation values corresponding to each multipath.

[0043] In one embodiment, the phase rotation module 140 is divided into a plurality of Cordic rotation units according to the preset configuration information of the power spectrum configuration module 141; each of the Cordic rotation units processes to obtain a sub-vector set of time-domain channel estimation values corresponding to each multipath; each of the Cordic rotation units is respectively connected to each averaging sub-processing unit in the averaging processing module.

[0044] It should be noted that after obtaining the initial frequency-domain channel estimation value, it is necessary to further optimize the initial frequency-domain channel estimation value to improve the quality of channel estimation. In this embodiment, the phase rotation module 140 and the averaging processing module 150 are used to convert the initial frequency-domain channel estimation value into a time-domain channel estimation value.

[0045] Specifically, first, the phase rotation module 140 is divided into a plurality of Cordic rotation units according to the preset configuration information of the power spectrum configuration module 141. The preset configuration information of the power spectrum configuration module 141 is a known channel power spectrum pattern or historical channel power spectrum information PDP. The configured plurality of Cordic rotation units are respectively Cordic rotation unit 1, Cordic rotation unit 2,..., Cordic rotation unit L, that is, L multipaths are selected, and each multipath corresponds to a Cordic rotation unit.

[0046] Input the initial frequency-domain channel estimation value into each Cordic rotation unit to perform phase rotation processing. The specific processing formula is:

[0047] ; (Equation 3)

[0048] Wherein, is the initial frequency-domain channel estimation value, is the corresponding th multipath, is the time-domain channel estimation value sub-vector after phase rotation. Each Cordic rotation unit obtains a set of time-domain channel estimation value sub-vectors corresponding to each multipath after processing. That is, Cordic rotation unit 1 obtains a set of time-domain channel estimation value sub-vectors for the first multipath, Cordic rotation unit 2 obtains a set of time-domain channel estimation value sub-vectors for the second multipath, and after sequential processing, Cordic rotation unit L obtains a set of time-domain channel estimation value sub-vectors for the Lth multipath.

[0049] It should be emphasized that after obtaining the initial frequency-domain channel estimation value in the traditional way, an IFFT is usually performed once to convert from the frequency domain to the time domain. This method does not use the prior PDP information. For example, the scale of the direct IFFT transformation is K, which will result in a large amount of computation. In this embodiment, according to the preset configuration information in the power spectrum configuration module 141, that is, the PDP information configures the specified multipath window width as L, and the multipath window width L is much smaller than the scale K of the direct IFFT transformation. Further, after phase rotation by the phase rotation module 140 respectively, channel estimation calculations are performed on the limited L time-domain multipaths. Compared with the traditional method of using IFFT (scale K) to perform channel estimation calculations by converting from the frequency domain to the time domain, the amount of computation is greatly reduced, and it will be more advantageous in the case of fewer multipaths.

[0050] Furthermore, the averaging processing module 150 includes a number of averaging sub-processing units corresponding one-to-one to each Cordic rotation unit. Each Cordic rotation unit is connected to the corresponding averaging sub-processing unit. For example, Cordic rotation unit 1 is connected to averaging sub-processing unit 1, Cordic rotation unit 2 is connected to averaging sub-processing unit 2, and so on. Cordic rotation unit L is connected to averaging sub-processing unit L.

[0051] The set of time-domain channel estimation value sub-vectors of each multipath obtained by each Cordic rotation unit is sent to the corresponding averaging sub-processing unit. That is, the set of time-domain channel estimation value sub-vectors of the first multipath of Cordic rotation unit 1 is sent to the corresponding averaging sub-processing unit 1, the set of time-domain channel estimation value sub-vectors of the second multipath of Cordic rotation unit 2 is sent to the corresponding averaging sub-processing unit 2, and so on. The set of time-domain channel estimation value sub-vectors of the Lth multipath of Cordic rotation unit L is sent to the corresponding averaging sub-processing unit L.

[0052] In each averaging sub-processing unit, averaging processing is respectively performed to obtain the time-domain channel estimation values corresponding to each multipath. The calculation formula for the averaging processing is as follows:

[0053] ; (Formula 4)

[0054] Among them, is the time-domain channel estimation value corresponding to the th multipath. The time-domain channel estimation value of the first multipath is obtained through calculation , the time-domain channel estimation value of the second multipath , and so on, to obtain the time-domain channel estimation value of the Lth multipath .

[0055] In an embodiment, the serial-parallel processing module 160 is connected to the averaging processing module 150 and is used to perform serial-parallel processing on the time-domain channel estimation values corresponding to each multipath to form a time-domain channel estimation value vector set.

[0056] The averaging processing module 150 respectively obtains the time-domain channel estimation value of the first multipath , the time-domain channel estimation value of the second multipath , ……, the time-domain channel estimation value of the Lth multipath , and then transmits the data to the serial-parallel processing module 160. By serially arranging the obtained channel multipath components in the serial-parallel processing module 160, a time-domain channel estimation value vector set is formed. The serial-parallel processing method helps to integrate the scattered channel information into a unified data structure for subsequent processing.

[0057] In an embodiment, the zero-insertion processing module 170 is connected to the serial-parallel processing module 160 and is used to perform zero-insertion processing on the time-domain channel estimation value vector set to obtain a denoised time-domain channel estimation value vector set.

[0058] In an embodiment, the system further includes: a control configuration module 171, which is connected to the zero-insertion processing module 170 and is used to provide channel length configuration information to the zero-insertion processing module 170 for performing zero-insertion processing on the received time-domain channel estimation value vector set.

[0059] It should be noted that in addition to obtaining the channel estimations of each multipath, the channel estimations at other time-domain positions may have noise because no channel estimation is performed. In this embodiment, the denoising processing of the channel estimation is performed by directly setting to zero. The zero-insertion processing refers to inserting zero values at the end of the vector to increase the length of the vector. In the zero-insertion processing module 170, according to the channel length configuration information provided by the control configuration module 171, the received time-domain channel estimation value vector set Zero-padding is performed. In this embodiment, the time-domain channel estimation value vector set is extended to a vector set with a length of K, that is, the time-domain channel estimation value vector set after noise reduction is obtained . Among them, the length K is configured according to the known channel length configuration information provided by the control configuration module 171. For example, in this embodiment, it is assumed that the total length is K, and this length K can be set and configured according to the actual situation, and it is not limited in this embodiment

[0060] In one embodiment, the second fast Fourier transform module 180 is connected to the zero-padding processing module 170, and is used to perform fast Fourier transform processing on the time-domain channel estimation value vector set after noise reduction to obtain the frequency-domain channel estimation result after noise reduction

[0061] It should be noted that the second fast Fourier transform module 180 receives the time-domain channel estimation value vector set after noise reduction, and performs fast Fourier transform processing on it to realize the transformation from the time domain to the frequency domain, so as to obtain the frequency-domain channel estimation result after noise reduction

[0062] In one embodiment, the system further includes: a signal-to-noise ratio estimation module 190, which is respectively connected to the operation processing module 130 and the serial-parallel processing module 160, and is used to calculate based on the initial frequency-domain channel estimation value and the time-domain channel estimation value vector set by using the signal-to-noise ratio estimation calculation formula to obtain the signal-to-noise ratio estimation result

[0063] In this embodiment, in addition to performing channel estimation, the signal-to-noise ratio can also be estimated according to the calculation results in the channel estimation process. The specific signal-to-noise ratio estimation calculation method is to calculate the total power of the frequency-domain channel according to the initial frequency-domain channel estimation value, and then subtract the sum of the powers of L multipaths in the time-domain channel estimation value vector set, so as to calculate the noise power, and then calculate the signal-to-noise ratio estimation result

[0064] For example, the initial frequency-domain channel estimation value and the time-domain channel estimation value vector set are sent to the signal-to-noise ratio estimation module 190, and SNR signal-to-noise ratio estimation is performed in the signal-to-noise ratio estimation module 190. The specific signal-to-noise ratio estimation calculation formula is as follows

[0065] ; (Formula 5)

[0066] ; (Formula 6)

[0067] ; (Formula 7)

[0068] ; (Formula 8)

[0069] Among them, is the total power of the initial frequency-domain channel, is the sum of the powers of L multipaths, is the noise power, is the SNR estimation result.

[0070] It should be noted that the SNR estimation system provided by the present invention obtains the channel estimation result of the specified multipath in the time domain by performing Cordic phase rotation and then averaging according to the specified PDP information, and directly sets to zero the other time-domain positions outside the specified multipath to perform noise reduction processing on the channel estimation, and finally obtains the noise-reduced time-domain channel estimation result; the present invention can also perform SNR estimation by calculating the total power of the initial frequency-domain channel and subtracting the sum of the powers of the specified multipaths.

[0071] It should be emphasized that in the traditional channel estimation method, after obtaining the channel estimation in the initial frequency domain, an IFFT transform is performed once to convert the frequency domain to the time domain, and then the multipath extension is framed according to the PDP, and the other positions are directly forced to zero for noise reduction, and finally the noise-reduced frequency-domain channel estimation result is obtained by FFT. In the channel estimation method provided in the embodiments of the present invention, by using the PDP information to process the specified multipaths, compared with the traditional method, one IFFT transform can be saved, the amount of computation can be greatly reduced, and it is more advantageous when the number of specified multipaths is small; the present invention directly sets to zero the positions outside the specified multipaths for noise reduction, which can effectively reduce the complexity; the present invention can also perform SNR estimation by calculating the total power of the initial frequency-domain channel and subtracting the sum of the powers of the specified multipaths, and the SNR estimation result is more accurate and the efficiency is higher.

[0072] To facilitate the description of the advantages of the channel estimation method of the present invention and the differences from the traditional channel estimation method, the following specific embodiments are provided for illustration.

[0073] Figure 2 is shown as a schematic diagram of the computational simulation comparison between the algorithm of the present invention and the traditional algorithm. Combining Figure 2 it is illustrated that at a lower SNR, it is difficult to accurately set the noise threshold in the traditional IFFT-based filtering method to remove noise, resulting in a slight gap in the channel estimation performance between the traditional method and the algorithm of the present invention at a lower SNR. However, as the SNR increases, the performance of the traditional algorithm is basically the same as that of the present invention, as Figure 2The shown performance curves gradually overlap. The algorithm of the present invention is similar to the traditional algorithm, both meeting the performance requirements of the 3GPP protocol and having a margin of approximately 3.7 dB. The method provided by the present invention can achieve the same channel estimation performance as the traditional method. However, the algorithm provided by the present invention has a significantly lower computational complexity than the traditional algorithm in the case of fewer multipaths, especially in the Gaussian white noise scenario. As shown in Table 1 below, it shows the comparison of the computational complexity between the algorithm of the present invention and the traditional algorithm under the same conditions (fewer multipaths).

[0074]

[0075] It should be noted that by comparing the computational complexity of the algorithm of the present invention and the traditional algorithm under the same conditions, it can be clearly obtained that the computational complexity of the algorithm of the present invention is significantly reduced in the single-path or fewer multipath scenarios. For example, in the Gaussian white noise channel or the single-path model, the complexity of complex multiplication can be reduced by about 35% to 50%, and the complexity of complex addition can be reduced to about 40% to 45%.

[0076] In the embodiments of the present application, terms such as "first" and "second" are used to distinguish identical or similar items with basically the same functions and effects, and do not limit their sequence. Those skilled in the art can understand that terms such as "first" and "second" do not limit the quantity and execution order, and terms such as "first" and "second" do not necessarily mean different.

[0077] It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" represent examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present relevant concepts in a specific manner.

[0078] In the embodiments of the present application, "at least one" means one or more, and "a plurality" means two or more. "And / or" describes the association relationship of associated objects and indicates that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after. "At least one (item)" or its similar expression refers to any combination of these items, including any combination of single item (item) or plural items (items). For example, at least one (item) of a, b or c can represent: a, b, c, a - b, a - c, b - c or a - b - c, where a, b, c can be single or multiple.

[0079] Figure 3It is a schematic block diagram of the channel estimation method provided by an embodiment of the present application. The channel estimation method is applied to the above-mentioned channel estimation system, as Figure 3 shown, the channel estimation method includes:

[0080] Step S31: Receive the time-domain received signal and perform fast Fourier transform processing on the time-domain received signal to obtain a frequency-domain received signal;

[0081] Step S32: Perform symbol extraction processing on the frequency-domain received signal to obtain a DMRS signal;

[0082] Step S33: Calculate based on the DMRS signal using a frequency-domain channel estimation model to obtain an initial frequency-domain channel estimation value;

[0083] Step S34: Perform phase rotation processing on the initial frequency-domain channel estimation value to obtain a set of sub-vectors of time-domain channel estimation values corresponding to each multipath;

[0084] Step S35: Perform averaging processing on each set of sub-vectors of time-domain channel estimation values corresponding to each multipath to obtain time-domain channel estimation values corresponding to each multipath;

[0085] Step S36: Perform serial-parallel processing on the time-domain channel estimation values corresponding to each multipath to form a set of time-domain channel estimation value vectors;

[0086] Step S37: Perform zero-padding processing on the set of time-domain channel estimation value vectors to obtain a set of time-domain channel estimation value vectors after noise reduction;

[0087] Step S38: Perform fast Fourier transform processing on the set of time-domain channel estimation value vectors after noise reduction to obtain a frequency-domain channel estimation result after noise reduction.

[0088] It should be understood that the specific processes of each module of the system executing the above corresponding steps have been described in detail in the above embodiments. For the sake of brevity, they will not be repeated here.

[0089] It should also be understood that the division of modules in the embodiments of the present application is schematic, merely a logical function division. In actual implementation, there may be other division methods. In addition, in each embodiment of the present application, each functional module may be integrated in a processor, may also exist alone physically, or two or more modules may be integrated in one module. The above integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0090] Figure 4 It is a schematic block diagram of an electronic terminal provided by an embodiment of the present application. As Figure 4As shown, the computer device includes: at least one processor 401, a memory 402, at least one network interface 403, and a user interface 405. Each component in the device is coupled together through a bus system 404. It can be understood that the bus system 404 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 404 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clear illustration, in Figure 4 all kinds of buses are labeled as the bus system.

[0091] Among them, the user interface 405 may include a display, a keyboard, a mouse, a trackball, a click gun, a key, a button, a touchpad, or a touch screen, etc.

[0092] It can be understood that the memory 402 may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM, Read Only Memory), a programmable read-only memory (PROM, Programmable Read-Only Memory), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM, Static Random Access Memory), synchronous static random access memory (SSRAM, Synchronous Static Random Access Memory). The memory described in the embodiments of the present invention is intended to include but not limited to these and any other suitable categories of memories.

[0093] The memory 402 in the embodiments of the present invention is used to store various categories of data to support the operation of the electronic terminal 400. Examples of these data include: any executable program for operating on the electronic terminal 400, such as an operating system 4021 and application programs 4022; the operating system 4021 contains various system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks. The application programs 4022 may include various application programs, such as a media player (Media Player), a browser (Browser), etc., for implementing various application services. Implementing the channel estimation method provided by the embodiments of the present invention may be included in the application programs 4022.

[0094] The method disclosed in the embodiments of the present invention above can be applied to the processor 401 or implemented by the processor 401. The processor 401 may be an integrated circuit chip with signal processing capabilities. In the implementation process, the steps of the above method can be completed by the integrated logic circuit in the hardware of the processor 401 or instructions in the form of software. The above-mentioned processor 401 may be a general-purpose processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 401 can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor 401 may be a microprocessor or any conventional processor, etc. Combining the steps of the accessory optimization method provided in the embodiments of the present invention can be directly embodied as being executed and completed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium, and this storage medium is located in the memory. The processor reads the information in the memory and combines its hardware to complete the steps of the foregoing method.

[0095] In an exemplary embodiment, the electronic terminal 400 may be one or more application-specific integrated circuits (ASICs, Application Specific Integrated Circuit), DSPs, programmable logic devices (PLDs, ProgrammableLogic Device), complex programmable logic devices (CPLDs, Complex Programmable Logic Device) for executing the foregoing method.

[0096] According to the method provided in the embodiments of the present application, the present application further provides a computer program product, which includes: computer program code, when the computer program code runs on a computer, enabling the computer to execute the channel estimation method of any one of the illustrated embodiments.

[0097] According to the method provided in the embodiments of the present application, the present application further provides a computer-readable storage medium, which stores program code, and when the program code runs on a computer, enabling the computer to execute the channel estimation method of any one of the illustrated embodiments.

[0098] As used in this specification, the terms "component", "module", "system", etc. are used to represent computer-related entities, hardware, firmware, combinations of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, and / or a computer. By way of illustration, both an application running on a computing device and the computing device can be components. One or more components can reside in a process and / or an execution thread, and a component can be located on one computer and / or distributed between two or more computers. In addition, these components can execute from various computer-readable media on which various data structures are stored. A component can communicate, for example, through signals with other systems via local and / or remote processes according to one or more data packets (e.g., data from two components interacting with another component between a local system, a distributed system, and / or a network, e.g., the Internet interacting with other systems through signals).

[0099] Those of ordinary skill in the art will appreciate that the various illustrative logical blocks and steps described in connection with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether such functions are implemented in hardware or software depends upon the particular application and design constraints of the technical solution. Skilled artisans may implement the described functions in different ways for each particular application, but such implementation should not be considered to exceed the scope of this application.

[0100] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be described herein again.

[0101] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the couplings or direct couplings or communication connections shown or discussed with each other can be through some interfaces, and the indirect couplings or communication connections of devices or units can be in electrical, mechanical, or other forms.

[0102] The unit described as a separation component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0103] In addition, in each embodiment of the present application, each functional unit can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0104] In the above embodiments, the functions of each functional unit can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions (programs). When the computer program instructions (programs) are loaded and executed on a computer, the processes or functions according to the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from a website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that the computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a high-definition digital video disc (DVD)), or a semiconductor medium (for example, a solid state disk (SSD), etc.).

[0105] If a function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0106] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0107] In summary, this application provides a channel estimation system, method, medium, program product, and terminal. By using PDP information to process specified multipaths, compared with traditional methods, this invention can save one IFFT transformation, greatly reduce the amount of computation, and is more advantageous when the number of specified multipaths is small; this invention directly sets the positions outside the specified multipaths to zero for noise reduction, which can effectively reduce the complexity; this invention can also estimate the signal-to-noise ratio by calculating the total power of the initial frequency-domain channel and subtracting the sum of the powers of the specified multipaths, and the signal-to-noise ratio estimation result is more accurate and the efficiency is higher. Therefore, this application effectively overcomes various disadvantages in the prior art and has high industrial utilization value.

[0108] The above embodiments are only illustrative of the principles and effects of this application and are not used to limit this application. Any person familiar with this technology can modify or change the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or changes completed by those with ordinary knowledge in the technical field without departing from the spirit and technical idea disclosed in this application should still be covered by the claims of this application.

Claims

1. A channel estimation system, characterized in that: include: A first fast Fourier transform module, configured to receive a time domain received signal and perform a fast Fourier transform process on the time domain received signal to obtain a frequency domain received signal; A signal extraction module, connected to the first fast Fourier transform module, configured to perform symbol extraction processing on the frequency domain received signal to obtain a DMRS signal; An operation processing module, connected to the signal extraction module, and configured to perform calculation based on the DMRS signal using a frequency domain channel estimation model to obtain an initial frequency domain channel estimation value; The process of obtaining the initial frequency domain channel estimation value is as follows: after obtaining the DMRS signal, further perform the initial frequency domain channel estimation, and obtain the initial frequency domain channel estimation by calculating the calculation formula of the DMRS signal. The calculation formula of the DMRS signal is: R DMRS (k)=H raw (k)S(k)+N(k); Among them, R DMRS (k) is the DMRS signal, H raw (k) is the initial frequency domain channel estimation value, S(k) is the locally known frequency domain channel training code, N(k) is the frequency domain Gaussian white noise, and k is the corresponding kth subcarrier; the above formula is further processed to obtain the calculation formula of the frequency domain channel estimation model: Among them, H raw (k) is the initial frequency domain channel estimation value, R DMRS (k) is the DMRS signal, S(k) is the locally known frequency domain channel training code; S(k) is A phase rotation module, connected to the operation processing module, for performing phase rotation processing on the initial frequency domain channel estimation value to obtain a time domain channel estimation value sub-vector set corresponding to each multipath; An averaging processing module, connected to the phase rotation module, for performing averaging processing on the time domain channel estimation value sub-vector sets corresponding to each multipath, so as to obtain the time domain channel estimation value corresponding to each multipath; A serial-to-parallel processing module, connected to the average processing module, for performing serial-to-parallel processing on the time-domain channel estimation values ​​corresponding to each multipath to form a time-domain channel estimation value vector set; A zero-insertion processing module, connected to the serial-parallel processing module, configured to perform zero-insertion processing on the time-domain channel estimation value vector set to obtain a noise-reduced time-domain channel estimation value vector set; The second fast Fourier transform module is connected to the zero insertion processing module and is used to perform fast Fourier transform processing on the noise-reduced time domain channel estimation value vector set to obtain a noise-reduced frequency domain channel estimation result.

2. The channel estimation system according to claim 1, characterized in that The system comprises: a reference signal sequence module connected to the operation processing module and used for providing a corresponding preset training signal to the operation processing module.

3. The channel estimation system according to claim 1, characterized in that The system further comprises: A power spectrum configuration module is connected to the phase rotation module and is used to provide preset configuration information to the phase rotation module to instruct the phase rotation module to perform phase rotation processing and obtain a time domain channel estimation value sub-vector set corresponding to each multipath.

4. The channel estimation system according to claim 3, characterized in that The phase rotation module is divided into a number of Cordic rotation units according to the preset configuration information of the power spectrum configuration module; each of the Cordic rotation units processes and obtains a set of time domain channel estimation value sub-vectors corresponding to each multipath; each of the Cordic rotation units is connected to each averaging sub-processing unit in the averaging processing module.

5. The channel estimation system according to claim 1, characterized in that The system further comprises: A control configuration module is connected to the zero insertion processing module and is used to provide channel length configuration information to the zero insertion processing module so as to perform zero insertion processing on the received time domain channel estimation value vector set.

6. The channel estimation system according to claim 1, characterized in that The system further comprises: The signal-to-noise ratio estimation module is connected to the operation processing module and the serial-to-parallel processing module respectively, and is used to calculate based on the initial frequency domain channel estimation value and the time domain channel estimation value vector set using a signal-to-noise ratio estimation formula to obtain a signal-to-noise ratio estimation result.

7. A channel estimation method, characterized in that: Applied to the channel estimation system according to any one of claims 1 to 6, the method comprising: Receiving a time domain received signal and performing a fast Fourier transform process on the time domain received signal to obtain a frequency domain received signal; Performing symbol extraction processing on the frequency domain received signal to obtain a DMRS signal; Based on the DMRS signal, a frequency domain channel estimation model is used to perform calculation to obtain an initial frequency domain channel estimation value; The process of obtaining the initial frequency domain channel estimation value is as follows: after obtaining the DMRS signal, further perform the initial frequency domain channel estimation, and obtain the initial frequency domain channel estimation by calculating the calculation formula of the DMRS signal. The calculation formula of the DMRS signal is: R DMRS (k)=H raw (k)S(k)+N(k); Among them, R DMRS (k) is the DMRS signal, H raw (k) is the initial frequency domain channel estimation value, S(k) is the locally known frequency domain channel training code, N(k) is the frequency domain Gaussian white noise, and k is the corresponding kth subcarrier; the above formula is further processed to obtain the calculation formula of the frequency domain channel estimation model: Among them, H raw (k) is the initial frequency domain channel estimation value, R DMRS (k) is the DMRS signal, S(k) is the locally known frequency domain channel training code; S(k) is Performing phase rotation processing on the initial frequency domain channel estimation value to obtain a time domain channel estimation value sub-vector set corresponding to each multipath; Averaging the time domain channel estimation value sub-vector sets corresponding to each multipath to obtain the time domain channel estimation value corresponding to each multipath; Performing serial and parallel processing on the time domain channel estimation values ​​corresponding to each multipath to form a time domain channel estimation value vector set; Performing zero insertion processing on the time domain channel estimation value vector set to obtain a noise-reduced time domain channel estimation value vector set; The denoised time-domain channel estimation value vector set is subjected to fast Fourier transform processing to obtain the denoised frequency-domain channel estimation result.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the channel estimation method according to claim 7 is implemented.

9. A computer program product, characterized in that The computer program product includes computer program codes, and when the computer program codes are run on a computer, the computer is enabled to implement the channel estimation method according to claim 7.

10. An electronic terminal comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the channel estimation method according to claim 7.

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