Channel estimation system, method, medium, program product and terminal

Abstract

The invention provides a channel estimation system, a channel estimation method, a medium, a program product and a terminal, which can save one time of IFFT (Inverse Fast Fourier Transform) and greatly reduce the operand by processing specified multipath by using PDP (Plasma Data Processing) information compared with a traditional method, and has more advantages under the condition of less specified multipath; according to the method, the position outside the specified multipath is directly zeroed for noise reduction, so that the complexity can be effectively reduced; in addition, the signal-to-noise ratio estimation can be carried out by calculating the total power of the initial frequency domain channel and subtracting the power sum of the specified multiple paths, the signal-to-noise ratio estimation result is more accurate, and the efficiency is higher.

Description

Technical Field

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

[0002] At present, in modern wireless communication systems, Orthogonal Frequency Division Multiplexing (OFDM) technology is widely used in communication standards such as 4G, 5G and WIFI due to its high data transmission rate and high anti-interference to multipath effects. OFDM systems perform channel estimation by sending known sequences such as demodulation reference signals (DMRS) on frequency and time resources, which is a key step to ensure correct signal decoding and system performance optimization.

[0003] In a traditional OFDM system, the receiver extracts the DMRS resource element information on the symbol frequency carrier carrying the DMRS and performs conjugate multiplication with a locally known sequence to obtain a preliminary frequency domain channel estimate. The channel estimate is then converted to the time domain through an inverse fast Fourier transform (IFFT) and subjected to noise reduction to improve the quality of the channel estimate.

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

[0005] In view of the above-mentioned shortcomings 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 calculation amount and high calculation complexity of the channel estimation method in the prior art.

[0006] To achieve the above-mentioned purpose and other related purposes, the first aspect of the present application provides a channel estimation system, including: a first fast Fourier transform module, used 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, used 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, used to calculate 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 operation processing module, used to perform phase rotation processing on the initial frequency domain channel estimation value to obtain the time domain channel corresponding to each multipath respectively. An estimation value sub-vector set; an averaging processing module, connected to the phase rotation module, for averaging the time domain channel estimation value sub-vector sets corresponding to each multipath respectively, so as to obtain the time domain channel estimation value corresponding to each multipath; a serial-to-parallel processing module, connected to the averaging processing module, for serial-to-parallel processing the time domain channel estimation value corresponding to each multipath to form a time domain channel estimation value vector set; a zero insertion processing module, connected to the serial-to-parallel processing module, for performing zero insertion processing on the time domain channel estimation value vector set to obtain the time domain channel estimation value vector set after noise reduction; a second fast Fourier transform module, connected to the zero insertion processing module, for performing 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.

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

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

[0009] In some embodiments of the first aspect of the present application, the phase rotation module is divided into several Cordic rotation units according to the preset configuration information of the power spectrum configuration module; each of the Cordic rotation units respectively processes to obtain a set of time domain channel estimation value sub-vectors corresponding to each multipath; and each of the Cordic rotation units 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 also 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 zero insertion processing of the received time domain channel estimation value vector set.

[0011] In some embodiments of the first aspect of the present application, the system also 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 zero insertion processing of the received time domain channel estimation value vector set.

[0012] To achieve the above-mentioned purpose and other related purposes, the second aspect of the present application provides a channel estimation method, which is applied to the channel estimation system as described above, and 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; using a frequency domain channel estimation model to calculate based on the DMRS signal to obtain an initial frequency domain channel estimation value; 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 averaging processing on the 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 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 denoised time domain channel estimation value vector set; performing fast Fourier transform processing on the denoised time domain channel estimation value vector set to obtain a denoised frequency domain channel estimation result.

[0013] To achieve the above-mentioned purpose and other related purposes, the third aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, and the computer program implements the channel estimation method when executed by a processor.

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

[0015] To achieve the above-mentioned purpose and other related purposes, the fifth aspect of the present application provides an electronic terminal, including a memory, a processor and a computer program stored in 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] The present invention processes the designated multipath by using PDP information, which can save one IFFT transformation and greatly reduce the amount of calculation compared with the traditional method, and is more advantageous when the designated multipath is small; the present invention directly sets the position outside the designated multipath to zero for noise reduction, which can effectively reduce the complexity; the present invention can also calculate the total power of the initial frequency domain channel and subtract the power sum of the designated multipath to estimate the signal-to-noise ratio, and the signal-to-noise ratio estimation result is more accurate and more efficient. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0019] Figure 2 Shown is a schematic diagram of a computational simulation comparison between the algorithm of the present invention and a traditional algorithm in one embodiment of the present application.

[0020] Figure 3 Shown is a flow chart of a channel estimation method in one embodiment of the present application.

[0021] Figure 4 Shown is a schematic diagram of the structure of an electronic terminal in one embodiment of the present application. DETAILED DESCRIPTION

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

[0023] Before further describing the present invention in detail, the nouns and terms involved in the embodiments of the present invention are explained. The nouns and terms involved in the embodiments of the present invention are applicable to the following interpretations:

[0024] <1> Inverse Fast Fourier Transform: IFFT is a mathematical calculation method that can convert frequency domain signals into time domain signals, making it easier to perform time domain analysis on signals. This technology has a wide range of applications in signal processing, image processing, speech processing, audio processing, and other fields.

[0025] <2> Fast Fourier Transform (FFT): is an algorithm for fast calculation of Fourier transform, which is developed on the basis of Fourier transform. FFT algorithm is widely used in digital signal processing, image processing, sound processing, convolution operation, analytic geometry and other fields. Its high efficiency and real-time performance make it an indispensable part of today's computer science.

[0026] <3> Power Delay Profile (PDP): refers to the relationship between the power of the signal received by the receiver and the arrival time delay in the 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] To facilitate understanding of the embodiments of the present application, first Figure 1 To elaborate, Figure 1 The schematic diagram of the structure of a channel estimation system in an embodiment of the present invention is shown. The channel estimation system in this embodiment includes a first fast Fourier transform module 110, a signal extraction module 120, an operation processing module 130, a phase rotation module 140, an average processing module 150, a serial-to-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 used 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.

[0029] For example, the first fast Fourier transform module 110 receives a time domain received signal of a receiving end for channel estimation. , the time domain received signal is transformed from the time domain to the frequency domain through fast Fourier transform processing to obtain the 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 is connected to the first fast Fourier transform module 110, and is used 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 time-frequency domain control unit (Timing and Frequency Controller, TFC), through which the DMRS symbol extraction of data symbol by symbol in the frequency domain pattern can be realized, that is, the frequency domain received signal Perform symbol extraction to obtain the DMRS signal The position of the DMRS signal in the frequency domain received signal is pre-set, which can facilitate accurate identification and extraction of these signals. The DMRS signal provides necessary reference information and can be used for channel estimation and signal demodulation.

[0032] In one embodiment, the operation processing module 130 is connected to the signal extraction module 120, and is used to perform calculations based on the DMRS signal using a frequency domain channel estimation model to obtain an initial frequency domain channel estimation value.

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

[0034] ;(Formula 1)

[0035] in, is the DMRS signal, is the initial frequency domain channel estimate, is the locally known frequency domain channel training code, is a Gaussian white noise in the frequency domain, For the corresponding Subcarriers. Further processing the above formula, we can get the calculation formula of the frequency domain channel estimation model:

[0036] ;(Formula 2)

[0037] in, is the initial frequency domain channel estimate, is the DMRS signal, is a frequency domain channel training code known locally. Usually it is the normalized modulation symbol, in which case the normalization of the denominator can be omitted. For example, the symbol modulated by QPSK, The value is .

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

[0039] It should be explained that when the frequency domain channel estimation model is used to calculate the initial frequency domain channel estimation value, 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 reference signal sequence module 131 provides a corresponding preset training signal, and the preset training signal is a locally known frequency domain channel training code. ,and One-to-one correspondence.

[0040] In one embodiment, the phase rotation module 140 is connected to the operation processing module 130, and is used to perform 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.

[0041] In one embodiment, the system also includes: a power spectrum configuration module 141, which is connected to the phase rotation module 140, and is used to provide preset configuration information to the phase rotation module 140 to instruct the phase rotation module 140 to perform phase rotation processing and obtain a set of time domain channel estimation value sub-vectors corresponding to each multipath respectively.

[0042] In one embodiment, the averaging processing module 150 is connected to the phase rotation module 140 and is used to perform averaging processing on 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.

[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 and obtains a set of time domain channel estimation value sub-vectors corresponding to each multipath; and each of the Cordic rotation units is connected to each averaging sub-processing unit in the averaging processing module.

[0044] It should be explained that after obtaining the initial frequency domain channel estimation value, the initial frequency domain channel estimation value needs to be further optimized to improve the quality of channel estimation. In this embodiment, a phase rotation module 140 and an average processing module 150 are used to convert the initial frequency domain channel estimation value into a time domain channel estimation value.

[0045] Specifically, the phase rotation module 140 is first divided into several 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 several Cordic rotation units are Cordic rotation unit 1, Cordic rotation unit 2, ..., Cordic rotation unit L, that is, L multipaths are screened out, and each multipath corresponds to a Cordic rotation unit.

[0046] Input the initial frequency domain channel estimate into each Cordic rotation unit Perform phase rotation processing, the specific processing formula is:

[0047] ;(Formula 3)

[0048] in, is the initial frequency domain channel estimate, For the corresponding Multipath, is the time domain channel estimation value subvector after phase rotation, and each Cordic rotation unit obtains the time domain channel estimation value subvector set corresponding to each multipath after processing. That is, Cordic rotation unit 1 obtains the time domain channel estimation value subvector set of the first multipath, Cordic rotation unit 2 obtains the time domain channel estimation value subvector set of the second multipath, and after sequential processing, Cordic rotation unit L obtains the time domain channel estimation value subvector set of the Lth multipath.

[0049] It should be emphasized that after the traditional acquisition of the initial frequency domain channel estimation value, an IFFT is usually performed to convert the frequency domain to the time domain. This method does not use a priori PDP information. For example, the scale of the IFFT direct transformation is K, which will result in a large amount of calculation. In this embodiment, according to the preset configuration information in the power spectrum configuration module 141, that is, the PDP information configuration specifies that the multipath window width is L, and the multipath window width L is much smaller than the scale K of the IFFT direct transformation. The phase rotation module 140 is further used to perform phase rotations respectively and then perform channel estimation calculations on the limited L time domain multipaths. Compared with the traditional use of IFFT (scale K) to convert from the frequency domain to the time domain for channel estimation calculation, the amount of calculation is greatly reduced, and it will be more advantageous when there are fewer multipaths.

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

[0051] The time domain channel estimation value sub-vector set of each multipath obtained by each Cordic rotation unit is sent to the corresponding averaging sub-processing unit, that is, the time domain channel estimation value sub-vector set of the first multipath of Cordic rotation unit 1 is sent to the corresponding averaging sub-processing unit 1, and the time domain channel estimation value sub-vector set of the second multipath of Cordic rotation unit 2 is sent to the corresponding averaging sub-processing unit 2, and so on, and the time domain channel estimation value sub-vector set 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, an averaging process is performed to obtain the time domain channel estimation value corresponding to each multipath. The calculation formula for the averaging process is as follows:

[0053] ;(Formula 4)

[0054] in, For the The time domain channel estimation value corresponding to the first multipath is obtained by calculation , the time domain channel estimate of the second multipath , and so on, we get the time domain channel estimation value of the Lth multipath .

[0055] In one embodiment, the serial-to-parallel processing module 160 is connected to the average processing module 150 and is used to perform 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.

[0056] The average processing module 150 obtains the time domain channel estimation value of the first multipath , the time domain channel estimate of the second multipath , ..., the time domain channel estimation value of the Lth multipath After that, the data is transmitted to the serial-to-parallel processing module 160, and a time domain channel estimation value vector set is formed by serially arranging the acquired channel multipath components in the serial-to-parallel processing module 160. The serial-parallel processing method helps to integrate the scattered channel information into a unified data structure for subsequent processing.

[0057] In one embodiment, the zero-insertion processing module 170 is connected to the serial-to-parallel processing module 160, and is used 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.

[0058] In one embodiment, the system further includes: a control configuration module 171, connected to the zero insertion processing module 170, for providing 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 the channel estimation of each multipath obtained above, the channel estimation at other time domain positions may be noisy. Since no channel estimation is performed, this embodiment performs noise reduction processing on the channel estimation by directly setting zeros. Zero insertion processing refers to inserting a zero value at the end of a 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 The vector set with an extended length of K is the vector set of time domain channel estimation value after noise reduction. 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. The length K can be set and configured according to actual conditions and is not limited in this embodiment.

[0060] In one embodiment, the second fast Fourier transform module 180 is connected to the zero insertion processing module 170 and is used to perform fast Fourier transform processing on the denoised time domain channel estimation value vector set to obtain a denoised frequency domain channel estimation result.

[0061] It should be noted that the second fast Fourier transform module 180 receives the denoised time domain channel estimation value vector set and performs fast Fourier transform processing on it to achieve conversion from time domain to frequency domain, so as to obtain the denoised frequency domain channel estimation result.

[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-to-parallel processing module 160, and is used to perform calculations 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.

[0063] In addition to performing channel estimation in this embodiment, signal-to-noise ratio estimation can also be performed based on 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 based on the initial frequency domain channel estimation value, and then subtract the power sum of L multipaths in the time domain channel estimation value vector set 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 is sent to the signal-to-noise ratio estimation module 190 And the time domain channel estimation value vector set , the SNR signal-to-noise ratio estimation module 190 performs SNR signal-to-noise ratio estimation, and 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] in, is the total power of the initial frequency domain channel, is the power sum of L multipaths, is the noise power, is the signal-to-noise ratio estimation result.

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

[0071] It should be emphasized that after obtaining the channel estimation in the initial frequency domain, the traditional channel estimation method performs an IFFT transformation to convert the frequency domain to the time domain, and then frames the multipath extension according to the PDP, and directly forces other positions to be zeroed to perform noise reduction. Finally, the time domain is converted to the frequency domain through FFT to obtain the frequency domain channel estimation result after noise reduction. The channel estimation method provided in the embodiment of the present invention saves one IFFT transformation and greatly reduces the amount of calculation compared with the traditional method by using PDP information to process the specified multipath. At the same time, it is more advantageous when there are fewer specified multipaths. The present invention directly sets the positions outside the specified multipath to zero for noise reduction, which can effectively reduce the complexity. The present invention can also calculate the total power of the initial frequency domain channel and subtract the power sum of the specified multipath to perform signal-to-noise ratio estimation. The signal-to-noise ratio estimation result is more accurate and efficient.

[0072] In order to explain the advantages of the channel estimation method of the present invention and the difference from the traditional channel estimation method, the following specific embodiments are provided for illustration.

[0073] Figure 2 The figure shows a comparison diagram of the computational simulation of the algorithm of the present invention and the traditional algorithm. Figure 2 It can be seen that, under low signal-to-noise ratio, it is difficult to set the noise threshold accurately for the traditional IFFT filtering method to remove noise, which results in a slight gap between the channel estimation performance under low signal-to-noise ratio and the channel estimation performance of the algorithm of the present invention. However, as the signal-to-noise ratio increases, the performance of the traditional algorithm and the algorithm of the present invention are basically the same. Figure 2The performance curves shown gradually overlap. The algorithm of the present invention is similar to the traditional algorithm, both meet the performance requirements of the 3GPP protocol, and have a margin of about 3.7dB. The method provided by the present invention can achieve the same channel estimation performance as the traditional method. However, the computational complexity of the algorithm provided by the present invention is significantly lower than that of the traditional algorithm when the number of multipaths is small, especially in the Gaussian white noise scenario. As shown in Table 1 below, the computational complexity comparison between the algorithm of the present invention and the traditional algorithm under the same situation (small number of multipaths) is shown.

[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 circumstances, it can be clearly concluded that the computational complexity of the algorithm of the present invention is significantly reduced in single-path or less multipath scenarios. For example, in a Gaussian white noise channel or a single-path model, the complex multiplication complexity can be reduced by about 35% to 50%, and the complex addition complexity can be reduced to about 40% to 45%.

[0076] In the embodiments of the present application, words such as "first" and "second" are used to distinguish the same or similar items with substantially the same functions and effects, and do not limit their order. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit them to be 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 descriptions. Any embodiment or design described as "exemplary" or "for example" in the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0078] In the embodiments of the present application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: the existence of A alone, the existence of A and B at the same time, and the existence of B alone, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can represent: a, b, c, ab, ac, bc or abc, where a, b, c can be single or multiple.

[0079] Figure 3is a schematic block diagram of a channel estimation method provided in an embodiment of the present application. The channel estimation method is applied to the channel estimation system described above, such as Figure 3 As shown, the channel estimation method includes:

[0080] Step S31: 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;

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

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

[0083] Step S34: 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;

[0084] Step S35: 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;

[0085] Step S36: 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;

[0086] Step S37: 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;

[0087] Step S38: Perform fast Fourier transform processing on the denoised time domain channel estimation value vector set to obtain a denoised frequency domain channel estimation result.

[0088] It should be understood that the specific process of each module of the system executing the above corresponding steps has been described in detail in the above embodiments, and for the sake of brevity, it 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 and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional module in each embodiment of the present application may be integrated into a processor, or may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0090] Figure 4 is a schematic block diagram of an electronic terminal provided in an embodiment of the present application. 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. The various components in the device are coupled together through a bus system 404. It can be understood that the bus system 404 is used to achieve 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 clarity, Figure 4 In the specification, various buses are labeled as bus systems.

[0091] The user interface 405 may include a display, a keyboard, a mouse, a trackball, a click gun, keys, buttons, a touch pad or a touch screen.

[0092] It is understood that the memory 402 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM) or a programmable read-only memory (PROM), 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) and synchronous static random access memory (SSRAM). The memory described in the embodiments of the present invention is intended to include but is not limited to these and any other suitable categories of memory.

[0093] The memory 402 in the embodiment of the present invention is used to store various types 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 an application 4022; the operating system 4021 includes 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 4022 may include various applications, such as a media player (Media Player), a browser (Browser), etc., for implementing various application services. The channel estimation method provided in the embodiment of the present invention may be included in the application 4022.

[0094] The method disclosed in the above embodiment of the present invention 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, each step of the above method can be completed by the hardware integrated logic circuit in the processor 401 or the instruction in the form of software. The above processor 401 may be a general processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 401 can implement or execute the methods, steps and logic block diagrams disclosed in the embodiment of the present invention. The general processor 401 may be a microprocessor or any conventional processor, etc. In combination with the steps of the accessory optimization method provided in the embodiment of the present invention, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0095] In an exemplary embodiment, the electronic terminal 400 may be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD) to execute the aforementioned method.

[0096] According to the method provided by the embodiments of the present application, the present application also provides a computer program product, which includes: computer program code, when the computer program code is run on a computer, the computer executes the channel estimation method of any embodiment of the illustrated embodiments.

[0097] According to the method provided by the embodiments of the present application, the present application also provides a computer-readable storage medium, which stores program code. When the program code runs on a computer, the computer executes the channel estimation method of any one of the embodiments shown.

[0098] The terms "component", "module", "system", etc. used in this specification are used to represent computer-related entities, hardware, firmware, a combination of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process, a processor, an object, an executable file, an execution thread, a program and / or a computer running on a processor. By way of illustration, both applications and computing devices running on a computing device can be components. One or more components may reside in a process and / or an execution thread, and a component may be located on a computer and / or distributed between two or more computers. In addition, these components may be executed from various computer-readable media having various data structures stored thereon. Components may, for example, communicate through local and / or remote processes according to signals having 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, such as 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 conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel may 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.

[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 aforementioned method embodiments and will not be repeated here.

[0101] In the several embodiments provided in the present 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 only schematic. For example, the division of units is only a logical function division. There may 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0102] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0103] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into 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 process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated. Available media may be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., high-density digital video discs (DVDs), or semiconductor media (e.g., solid state disks (SSDs)).

[0105] If the 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 the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0106] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0107] In summary, the present application provides a channel estimation system, method, medium, program product and terminal. The present invention uses PDP information to process the specified multipath. Compared with the traditional method, it can save one IFFT transformation and greatly reduce the amount of calculation. At the same time, it is more advantageous when the specified multipath is small. The present invention directly sets the position outside the specified multipath to zero for noise reduction, which can effectively reduce the complexity. The present invention can also calculate the total power of the initial frequency domain channel and subtract the power sum of the specified multipath to perform signal-to-noise ratio estimation. The signal-to-noise ratio estimation result is more accurate and efficient. Therefore, the present application effectively overcomes various shortcomings in the prior art and has a high industrial utilization value.

[0108] The above embodiments are merely illustrative of the principles and effects of the present application and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed in the present application shall still be covered by the claims of the present 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; 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; 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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