Channel estimation method and device based on wireless communication system

Abstract

The present invention belongs to the technical field of power systems, and discloses a channel estimation method and device based on a wireless communication system, the method comprising: obtaining an observation vector and a sensor matrix according to the pilot type of the wireless communication system, and then obtaining an estimation result of the pilot vector channel through an iterative loop algorithm based on the observation vector, the sensor matrix and a preset step size, and then obtaining a preliminary channel estimation result in the time domain according to the estimation result. In this way, the method and device provided by the present invention are based on the principle of compressed sensing, and the SAMP algorithm is applied to reduce the number of pilots, thereby improving the spectrum efficiency and estimation accuracy, and solving the problem of low channel estimation efficiency and estimation accuracy in the prior art.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a channel estimation method and device based on a wireless communication system. Background Art

[0002] With the development of new power systems, some platforms and terminals have gradually adopted wireless technologies with better performance. In the context of 5G, power Internet of Things services have become a trend in technology development. Compared with traditional OFDM (Orthogonal Frequency Division Multiplexing) technology, FBMC (Filter Bank Multicarrier) technology can solve the problems of out-of-band leakage and low spectrum efficiency of OFDM technology. However, since the filter bank of FBMC increases the computational complexity and its modulation method produces imaginary interference, the computational efficiency and estimation accuracy are low.

[0003] Therefore, in the context of FBMC, how to improve the channel estimation efficiency and estimation accuracy of wireless communication systems is a problem that needs to be solved urgently. Summary of the invention

[0004] The embodiments of the present invention provide a channel estimation method and device based on a wireless communication system to solve the problem of low channel estimation efficiency and estimation accuracy in the prior art. In order to have a basic understanding of some aspects of the disclosed embodiments, a simple summary is given below. This summary is not a general review, nor is it intended to identify key / important components or describe the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a preface to the detailed description that follows.

[0005] According to a first aspect of an embodiment of the present invention, a channel estimation method based on a wireless communication system is provided.

[0006] In some embodiments, the method comprises:

[0007] According to the pilot type of the wireless communication system, an observation vector and a sensing matrix are obtained;

[0008] Based on the observation vector, the sensing matrix and a preset step size, an estimation result of a pilot vector channel is obtained through an iterative loop algorithm;

[0009] According to the estimation result, a preliminary channel estimation result in the time domain is obtained.

[0010] In some embodiments, an observation vector and a sensing matrix are obtained according to a pilot type of the wireless communication system, and the method further includes:

[0011] Acquire a demodulated signal from a receiving end of the wireless communication system;

[0012] A pilot type of the wireless communication system is determined according to the demodulated signal.

[0013] In some embodiments, based on the observation vector, the sensing matrix and the preset step size, an estimation result of the pilot vector channel is obtained through an iterative loop algorithm, specifically including:

[0014] Start the iteration loop and calculate the residual r between the sensor matrix Θ and the previous iteration k-1 The correlation coefficient θ T r k-1 , where the index S of the first L maximum values k Incorporate into the existing support set F k-1 and update the candidate set to C k =F k-1 ∪S k ;

[0015] Compute the least squares solution Select the L largest indexes from them and store them in set F, and update the residual Among them, Y is the observation vector, k is the number of iterations;

[0016] If the residual is less than the iteration threshold, the pilot vector channel estimation is obtained. If ||r k ||2≥||r k-1 ||2, L = L + λ, otherwise, update the residual Update the support set F k =F, k=k+1, recalculate the correlation coefficient;

[0017] After the termination condition is met, the above cycle ends and the estimation result of the pilot vector channel is obtained as follows:

[0018] In some embodiments, before starting the iteration loop, the method further comprises:

[0019] Input initial residual r0=Y, initial support set Initial candidate set The number of pre-selected atoms is L=λ and the number of iterations is k=1.

[0020] In some embodiments, obtaining a preliminary channel estimation result in the time domain according to the estimation result specifically includes:

[0021] Obtaining a preliminary channel estimate of the pilot position including position information according to the estimation result;

[0022] Interpolate the preliminary channel estimate at the pilot position to obtain a complete preliminary channel estimate at the receiving end;

[0023] The complete preliminary channel estimate at the receiving end is subjected to an inverse fast Fourier transform to obtain a preliminary channel estimate result in the time domain.

[0024] In some embodiments, a preliminary channel estimation result in the time domain is obtained according to the estimation result, and then the method further includes:

[0025] The preliminary channel estimation result is screened to obtain a final channel estimation result.

[0026] In some embodiments, the preliminary channel estimation result is screened to obtain a final channel estimation result, specifically including:

[0027] Perform threshold screening on the preliminary channel estimation results in the time domain;

[0028] The channel estimation result in the time domain after threshold screening is subjected to fast Fourier transform to obtain the final channel estimation result.

[0029] In some embodiments, threshold screening is performed on the preliminary channel estimation result in the time domain, specifically including:

[0030] Based on the preset threshold screening formula, the values ​​in the preliminary channel estimation results in the time domain that are less than the preset threshold are set to zero, and the values ​​in the preliminary channel estimation results in the time domain that are greater than or equal to the preset threshold are retained to complete the threshold screening.

[0031] In some embodiments, the threshold screening formula is based on the performance of bit error rate and mean square error in different signal-to-noise ratios in the channel estimation simulation experiment results of the FBMC system.

[0032] In some embodiments, the threshold screening formula is:

[0033] α1=5.54e -0.11SNR (20≤SNR≤30)

[0034] α2=0.78e -0.09SNR (0≤SNR≤30)

[0035] Wherein, α1 is the first threshold, α2 is the second threshold, and SNR is the signal-to-noise ratio.

[0036] In some embodiments, the preset threshold includes a first threshold, and the first threshold is a threshold that minimizes the bit error rate;

[0037] In the threshold screening formula, the first threshold α1=5.54e -0.11SNR (20≤SNR≤30), where SNR is the signal-to-noise ratio.

[0038] In some embodiments, the preset threshold includes a second threshold, and the second threshold is a threshold that minimizes the mean square error;

[0039] In the threshold screening formula, the second threshold α2 = 0.78e -0.09SNR (0≤SNR≤30), where SNR is the signal-to-noise ratio.

[0040] In some embodiments, the wireless communication system is a FBMC system.

[0041] In some embodiments, the channel estimation method adopts a pilot-based channel estimation algorithm.

[0042] According to a second aspect of an embodiment of the present invention, a channel estimation device based on a wireless communication system is provided.

[0043] In some embodiments, the apparatus comprises:

[0044] A data acquisition unit, configured to obtain an observation vector and a sensing matrix according to a pilot type of the wireless communication system;

[0045] An iterative loop unit, used to obtain an estimation result of a pilot vector channel through an iterative loop algorithm based on the observation vector, the sensor matrix and a preset step size;

[0046] The result output unit is used to obtain a preliminary channel estimation result in the time domain according to the estimation result.

[0047] According to a third aspect of an embodiment of the present invention, a computer device is provided.

[0048] In some embodiments, the computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0049] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0050] The channel estimation method based on the wireless communication system provided by the present invention obtains the observation vector and the sensing matrix according to the pilot type of the wireless communication system, and then obtains the estimation result of the pilot vector channel through an iterative cycle algorithm based on the observation vector, the sensing matrix and the preset step size, and then obtains the preliminary channel estimation result in the time domain according to the estimation result. In this way, the method provided by the present invention is based on the principle of compressed sensing and applies the SAMP algorithm to reduce the number of pilots, thereby improving the spectrum efficiency and estimation accuracy, and solving the problem of low channel estimation efficiency and estimation accuracy in the prior art.

[0051] Furthermore, according to the estimation result, a preliminary channel estimation result in the time domain is obtained, and then the preliminary channel estimation result is screened to obtain a final channel estimation result. The preliminary channel estimation result in the time domain is threshold screened, and the channel estimation result in the time domain that has been threshold screened is fast Fourier transformed to obtain a final channel estimation result. In this way, the present invention uses a threshold screening algorithm to filter a part of the time domain noise interference, and reduces the noise interference as much as possible on the basis of retaining useful information through a threshold formula, thereby further effectively improving the accuracy of channel estimation.

[0052] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0054] Figure 1 is one of the flow charts of a channel estimation method based on a wireless communication system according to an exemplary embodiment;

[0055] Figure 2 is a second flowchart of a channel estimation method based on a wireless communication system according to an exemplary embodiment;

[0056] Figure 3 is a third flowchart of a channel estimation method based on a wireless communication system according to an exemplary embodiment;

[0057] Figure 4 is a fourth flowchart of a channel estimation method based on a wireless communication system according to an exemplary embodiment;

[0058] Figure 5 is a structural diagram of a channel estimation device based on a wireless communication system according to an exemplary embodiment;

[0059] Figure 6 The figure is a schematic diagram showing the structure of a computer device according to an exemplary embodiment.

[0060] Reference numerals:

[0061] 510 - data acquisition unit, 520 - iteration loop unit, 530 - result output unit. DETAILED DESCRIPTION

[0062] The following description and accompanying drawings fully illustrate the specific embodiments of this article so that those skilled in the art can practice them. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. The scope of the embodiments of this article includes the entire scope of the claims, as well as all available equivalents of the claims. Herein, the terms "first", "second", etc. are only used to distinguish one element from another, without requiring or implying any actual relationship or order between these elements. In fact, the first element can also be called the second element, and vice versa. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the structure, device or equipment including a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also include elements inherent to such structure, device or equipment. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the structure, device or equipment including the elements. Each embodiment is described in a progressive manner herein, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the embodiments can be referred to each other.

[0063] The terms "longitudinal", "lateral", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc. in this document indicate the orientation or position relationship based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing this document and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In the description of this document, unless otherwise specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a mechanical connection or an electrical connection, it can also be the internal communication of two elements, it can be a direct connection, or it can be an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0064] As used herein, the term "plurality" means two or more than two, unless otherwise specified.

[0065] In this document, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0066] In this article, the term "and / or" is a description of the association relationship between objects, indicating that three relationships may exist. For example, A and / or B means: A or B, or, A and B.

[0067] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0068] Please refer to Figure 1 , Figure 1 The flowchart of a channel estimation method based on a wireless communication system is shown according to an exemplary embodiment.

[0069] In a specific implementation, the channel estimation method based on the wireless communication system provided by the present invention comprises the following steps:

[0070] S110: According to the pilot type of the wireless communication system, an observation vector and a sensing matrix are obtained. Specifically, the observation vector is composed of the value of the received signal at the pilot position, and the sensing matrix is ​​composed of the observation vector and the size of the pilot. The wireless communication system is an FBMC system.

[0071] S120: Based on the observation vector, the sensing matrix and a preset step size, an estimation result of a pilot vector channel is obtained through an iterative loop algorithm;

[0072] S130: According to the estimation result, a preliminary channel estimation result in the time domain is obtained; the channel estimation method adopts a pilot-based channel estimation algorithm. The wireless channel is generally a sparse multipath channel. The compressed sensing algorithm can reconstruct the sparse signal, thereby reducing the number of pilots and improving the estimation efficiency.

[0073] Specifically, Figure 2 As shown, in order to improve the accuracy of the obtained observation vector and the sensing matrix, the observation vector and the sensing matrix are obtained according to the pilot type of the wireless communication system, and the following steps are also included:

[0074] S210: Acquire a demodulated signal of a receiving end of the wireless communication system;

[0075] S220: Determine the pilot type of the wireless communication system according to the demodulated signal, where the pilot type is divided into block pilot, comb pilot, grid pilot, etc.

[0076] In the above step S120, based on the observation vector, the sensing matrix and the preset step size, an estimation result of the pilot vector channel is obtained through an iterative loop algorithm, which specifically includes:

[0077] Start the iteration loop and calculate the residual r between the sensor matrix Θ and the previous iteration k-1 The correlation coefficient θ T r k-1 , where the index of the first L maximum values ​​is S k Incorporate into the existing support set F k-1 and update the candidate set to Ck =F k-1 ∪S k ;

[0078] Compute the least squares solution Select the L largest indexes from them and store them in set F, and update the residual Where Y is the observation vector and k is the number of iterations;

[0079] If the residual is less than the iteration threshold, the pilot vector channel estimation is obtained. If ||r k ||2≥||r k-1 ||2, L = L + λ, otherwise, update the residual Update the support set F k =F, k=k+1, recalculate the correlation coefficient;

[0080] After the termination condition is met, the above cycle ends and the estimation result of the pilot vector channel is obtained as follows:

[0081] Before starting the iteration cycle, the method further includes:

[0082] Input initial residual r0=Y, initial support set Initial candidate set The number of pre-selected atoms is L=λ and the number of iterations is k=1.

[0083] In step S130, Figure 3 As shown, according to the estimation result, a preliminary channel estimation result in the time domain is obtained, which specifically includes the following steps:

[0084] S310: Obtaining a preliminary channel estimate of the pilot position including position information according to the estimation result;

[0085] S320: interpolating the preliminary channel estimate of the pilot position to obtain a complete preliminary channel estimate at the receiving end;

[0086] S330: Perform an inverse fast Fourier transform on the complete preliminary channel estimation at the receiving end to obtain a preliminary channel estimation result in the time domain.

[0087] Further, according to the estimation result, a preliminary channel estimation result in the time domain is obtained, and then the method further includes:

[0088] The preliminary channel estimation result is screened to obtain a final channel estimation result.

[0089] That is to say, after obtaining the preliminary channel estimation result in the time domain, in order to improve the accuracy, the estimation result can also be screened. The preliminary channel estimation result in the time domain is threshold screened, and the channel estimation result in the time domain that has been threshold screened is fast Fourier transformed to obtain the final channel estimation result. In this way, the present invention uses the threshold screening algorithm to filter a part of the time domain noise interference, and reduces the noise interference as much as possible on the basis of retaining useful information through the threshold formula, thereby further effectively improving the accuracy of channel estimation.

[0090] In some embodiments, the preliminary channel estimation result is screened to obtain a final channel estimation result, specifically comprising the following steps:

[0091] Perform threshold screening on the preliminary channel estimation results in the time domain;

[0092] Specifically, based on a preset threshold screening formula, values ​​in the time domain preliminary channel estimation results that are less than a preset threshold are set to zero, and values ​​in the time domain preliminary channel estimation results that are greater than or equal to the preset threshold are retained to complete the threshold screening.

[0093] The channel estimation result in the time domain after threshold screening is subjected to fast Fourier transform to obtain the final channel estimation result.

[0094] The above threshold screening formula is based on the channel estimation simulation experiment results of the FBMC system, where the bit error rate and mean square error are fitted according to the performance of different signal-to-noise ratios.

[0095] Specifically, the threshold screening formula is:

[0096] α1=5.54e -0.11SNR (20≤SNR≤30)

[0097] α2=0.78e -0.09SNR (0≤SNR≤30)

[0098] Wherein, α1 is the first threshold, α2 is the second threshold, and SNR is the signal-to-noise ratio.

[0099] The preset threshold includes a first threshold, which is a threshold that minimizes the bit error rate;

[0100] In the threshold screening formula, the first threshold α1=5.54e -0.11SNR (20≤SNR≤30), where SNR is the signal-to-noise ratio.

[0101] The preset threshold includes a second threshold, and the second threshold is a threshold that minimizes the mean square error;

[0102] In the threshold screening formula, the second threshold α2 = 0.78e -0.09SNR (0≤SNR≤30), where SNR is the signal-to-noise ratio.

[0103] For ease of understanding, the method provided by the present invention is briefly described below using a specific usage scenario as an example.

[0104] like Figure 4 As shown, the channel estimation method based on the wireless communication system provided by the present invention comprises the following steps:

[0105] Obtain the demodulated signal at the receiving end;

[0106] Obtain the observation vector Y and the sensing matrix Θ according to the pilot type;

[0107] Input the step size λ of the sparse adaptive matching pursuit algorithm;

[0108] Start the iteration loop and calculate the residual r between the sensor matrix Θ and the previous iteration k-1 The correlation coefficient θ T r k-1 , where the index of the first L maximum values ​​is S k Incorporate into the existing support set F k-1 Therefore, the candidate set is updated to C k =F k-1 ∪S k ;

[0109] Compute the least squares solution Select the L largest indexes from them and store them in set F, and update the residual

[0110] If the residual is less than the iteration threshold, the pilot vector channel estimation is obtained. If ||r k ||2≥||r k-1 ||2, L = L + λ, otherwise, update the residual Update the support set F k =F, k=k+1, recalculate the correlation coefficient;

[0111] After the termination condition is met, the above cycle ends and the pilot vector channel estimation is obtained.

[0112] Obtaining a preliminary channel estimate of the pilot position including position information according to the algorithm estimation result;

[0113] Interpolate the preliminary channel estimate at the pilot position to obtain a complete preliminary channel estimate at the receiving end;

[0114] Perform an inverse fast Fourier transform on the complete preliminary channel estimate at the receiving end to obtain a preliminary channel estimate in the time domain;

[0115] Based on the threshold formula, the values ​​in the preliminary channel estimation in the time domain that are less than the threshold are set to zero, and the remaining values ​​that are not noise interference are retained, completing the threshold screening;

[0116] Perform fast Fourier transform on the time domain channel estimate after threshold screening to obtain the final channel estimate;

[0117] In the above specific implementation, the channel estimation method based on the wireless communication system provided by the present invention obtains the observation vector and the sensing matrix according to the pilot type of the wireless communication system, and then obtains the estimation result of the pilot vector channel based on the observation vector, the sensing matrix and the preset step size through an iterative loop algorithm, and then obtains the preliminary channel estimation result in the time domain according to the estimation result. In this way, the method provided by the present invention is based on the principle of compressed sensing and applies the SAMP algorithm to reduce the number of pilots, thereby improving the spectrum efficiency and estimation accuracy, and solving the problem of low channel estimation efficiency and estimation accuracy in the prior art.

[0118] According to a second aspect of an embodiment of the present invention, a channel estimation device based on a wireless communication system is provided.

[0119] like Figure 5 As shown, the device comprises:

[0120] A data acquisition unit 510, configured to obtain an observation vector and a sensing matrix according to a pilot type of the wireless communication system;

[0121] An iterative loop unit 520, configured to obtain an estimation result of a pilot vector channel through an iterative loop algorithm based on the observation vector, the sensing matrix and a preset step size;

[0122] The result output unit 530 is used to obtain a preliminary channel estimation result in the time domain according to the estimation result.

[0123] In some embodiments, an observation vector and a sensing matrix are obtained according to a pilot type of the wireless communication system, and the method further includes:

[0124] Acquire a demodulated signal from a receiving end of the wireless communication system;

[0125] A pilot type of the wireless communication system is determined according to the demodulated signal.

[0126] In some embodiments, based on the observation vector, the sensing matrix and the preset step size, an estimation result of the pilot vector channel is obtained through an iterative loop algorithm, specifically including:

[0127] Start the iteration loop and calculate the residual r between the sensor matrix Θ and the previous iterationk-1 The correlation coefficient θ T r k-1 , where the index S of the first L maximum values k Incorporate into the existing support set F k-1 and update the candidate set to C k =F k-1 ∪S k ;

[0128] Compute the least squares solution Select the L largest indexes from them and store them in set F, and update the residual

[0129] If the residual is less than the iteration threshold, the pilot vector channel estimation is obtained. If ||r k ||2≥||r k-1 ||2, L = L + λ, otherwise, update the residual Update the support set F k =F, k=k+1, recalculate the correlation coefficient;

[0130] After the termination condition is met, the above cycle ends and the estimation result of the pilot vector channel is obtained as follows:

[0131] In some embodiments, before starting the iteration loop, the method further comprises:

[0132] Input initial residual r0=Y, initial support set Initial candidate set The number of pre-selected atoms is L=λ and the number of iterations is k=1.

[0133] In some embodiments, obtaining a preliminary channel estimation result in the time domain according to the estimation result specifically includes:

[0134] Obtaining a preliminary channel estimate of the pilot position including position information according to the estimation result;

[0135] Interpolate the preliminary channel estimate at the pilot position to obtain a complete preliminary channel estimate at the receiving end;

[0136] The complete preliminary channel estimate at the receiving end is subjected to an inverse fast Fourier transform to obtain a preliminary channel estimate result in the time domain.

[0137] In some embodiments, a preliminary channel estimation result in the time domain is obtained according to the estimation result, and then the method further includes:

[0138] The preliminary channel estimation result is screened to obtain a final channel estimation result.

[0139] In some embodiments, the preliminary channel estimation result is screened to obtain a final channel estimation result, specifically including:

[0140] Perform threshold screening on the preliminary channel estimation results in the time domain;

[0141] The channel estimation result in the time domain after threshold screening is subjected to fast Fourier transform to obtain the final channel estimation result.

[0142] In some embodiments, threshold screening is performed on the preliminary channel estimation result in the time domain, specifically including:

[0143] Based on the preset threshold screening formula, the values ​​in the preliminary channel estimation results in the time domain that are less than the preset threshold are set to zero, and the values ​​in the preliminary channel estimation results in the time domain that are greater than or equal to the preset threshold are retained to complete the threshold screening.

[0144] In some embodiments, the threshold screening formula is based on the performance of bit error rate and mean square error in different signal-to-noise ratios in the channel estimation simulation experiment results of the FBMC system.

[0145] In some embodiments, the threshold screening formula is:

[0146] α1=5.54e -0.11SNR (20≤SNR≤30)

[0147] α2=0.78e -0.09SNR (0≤SNR≤30)

[0148] Wherein, α1 is the first threshold, α2 is the second threshold, and SNR is the signal-to-noise ratio.

[0149] In some embodiments, the preset threshold includes a first threshold, and the first threshold is a threshold that minimizes the bit error rate;

[0150] In the threshold screening formula, the first threshold α1=5.54e -0.11SNR (20≤SNR≤30), where SNR is the signal-to-noise ratio.

[0151] In some embodiments, the preset threshold includes a second threshold, and the second threshold is a threshold that minimizes the mean square error;

[0152] In the threshold screening formula, the second threshold α2 = 0.78e -0.09SNR (0≤SNR≤30), where SNR is the signal-to-noise ratio.

[0153] In some embodiments, the wireless communication system is a FBMC system.

[0154] In some embodiments, the channel estimation method adopts a pilot-based channel estimation algorithm.

[0155] In the above specific implementation, the channel estimation device based on the wireless communication system provided by the present invention obtains the observation vector and the sensing matrix according to the pilot type of the wireless communication system, and then obtains the estimation result of the pilot vector channel based on the observation vector, the sensing matrix and the preset step size through an iterative loop algorithm, and then obtains the preliminary channel estimation result in the time domain according to the estimation result. In this way, the method provided by the present invention is based on the principle of compressed sensing and applies the SAMP algorithm to reduce the number of pilots, thereby improving the spectrum efficiency and estimation accuracy, and solving the problem of low channel estimation efficiency and estimation accuracy in the prior art.

[0156] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in the above method embodiment are implemented.

[0157] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0158] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiment when executing the computer program.

[0159] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiment are implemented.

[0160] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0161] The present invention is not limited to the structures which have been described above and shown in the drawings, and various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A channel estimation method based on a wireless communication system, characterized in that: The method comprises: According to the pilot type of the wireless communication system, an observation vector and a sensing matrix are obtained; Based on the observation vector, the sensing matrix and the preset step size, an estimation result of the pilot vector channel is obtained through an iterative cycle algorithm, specifically including: Before starting the iteration cycle, input the initial residual r0 = Y, the initial support set Initial candidate set Preselect the number of atoms L = λ and the number of iterations k = 1; start the iteration cycle and calculate the residual r between the sensor matrix Θ and the previous iteration k-1 The correlation coefficient θ T r k-1 , where the index S of the first L maximum values k Incorporate into the existing support set F k-1 and update the candidate set to C k =F k-1 ∪S k ; Compute the least squares solution Select the L largest indexes from them and store them in set F, and update the residual Where Y is the observation vector and k is the number of iterations; If the residual is less than the iteration threshold, the pilot vector channel estimation is obtained. If ||r k ||2≥||r k-1 ||2, L = L + λ, otherwise, update the residual Update the support set F k =F, k=k+1, recalculate the correlation coefficient; After the termination condition is met, the above cycle ends and the estimation result of the pilot vector channel is obtained as follows: According to the estimation result, a preliminary channel estimation result in the time domain is obtained; and further comprising: The preliminary channel estimation result is screened to obtain a final channel estimation result, specifically including: threshold screening of the preliminary channel estimation result in the time domain, specifically including: based on a preset threshold screening formula, setting the values ​​in the preliminary channel estimation result in the time domain that are less than the preset threshold to zero, retaining the values ​​in the preliminary channel estimation result in the time domain that are greater than or equal to the preset threshold, to complete the threshold screening, the threshold screening formula is based on the channel estimation simulation experiment results of the FBMC system, the bit error rate and the mean square error are fitted according to the performance of different signal-to-noise ratios, and the threshold screening formula is: α1=5.54e -0.11SNR (20≤SNR≤30) α2=0.78e -0.09SNR (0≤SNR≤30) Wherein, α1 is the first threshold, α2 is the second threshold, and SNR is the signal-to-noise ratio; The preset threshold includes a first threshold, and the first threshold is a threshold that minimizes the bit error rate; In the threshold screening formula, the first threshold α1=5.54e -0.11SNR (20≤SNR≤30), where SNR is the signal-to-noise ratio; The preset threshold includes a second threshold, and the second threshold is a threshold that minimizes the mean square error; In the threshold screening formula, the second threshold α2 = 0.78e -0.09SNR (0≤SNR≤30), where SNR is the signal-to-noise ratio; The channel estimation result in the time domain after threshold screening is subjected to fast Fourier transform to obtain the final channel estimation result.

2. The channel estimation method based on a wireless communication system according to claim 1, characterized in that: According to the pilot type of the wireless communication system, an observation vector and a sensing matrix are obtained, which also includes: Acquire a demodulated signal from a receiving end of the wireless communication system; A pilot type of the wireless communication system is determined according to the demodulated signal.

3. The channel estimation method based on a wireless communication system according to claim 1, characterized in that: According to the estimation result, a preliminary channel estimation result in the time domain is obtained, which specifically includes: Obtaining a preliminary channel estimate of the pilot position including position information according to the estimation result; Interpolate the preliminary channel estimate at the pilot position to obtain a complete preliminary channel estimate at the receiving end; The complete preliminary channel estimate at the receiving end is subjected to an inverse fast Fourier transform to obtain a preliminary channel estimate result in the time domain.

4. The channel estimation method based on a wireless communication system according to any one of claims 1 to 3, characterized in that: The wireless communication system is a FBMC system.

5. The channel estimation method based on a wireless communication system according to any one of claims 1 to 3, characterized in that: The channel estimation method adopts a pilot-based channel estimation algorithm.

6. A channel estimation device based on a wireless communication system, characterized in that: The device comprises: A data acquisition unit, configured to obtain an observation vector and a sensing matrix according to a pilot type of the wireless communication system; The iterative loop unit is used to obtain an estimation result of the pilot vector channel through an iterative loop algorithm based on the observation vector, the sensor matrix and a preset step size, specifically including: Before starting the iteration cycle, input the initial residual r0 = Y, the initial support set Initial candidate set Preselect the number of atoms L = λ and the number of iterations k = 1; start the iteration cycle and calculate the residual r between the sensor matrix Θ and the previous iteration k-1 The correlation coefficient θ T r k-1 , where the index of the first K maximum values ​​is S k Incorporate into the existing support set F k-1 and update the candidate set to C k =F k-1 ∪S k ; Compute the least squares solution Select the L largest indexes from them and store them in set F, and update the residual Where Y is the observation vector and k is the number of iterations; If the residual is less than the iteration threshold, the pilot vector channel estimation is obtained. If ||r k ||2≥||r k-1 ||2, L = L + λ, otherwise, update the residual Update the support set F k =F, k=k+1, recalculate the correlation coefficient; After the termination condition is met, the above cycle ends and the estimation result of the pilot vector channel is obtained as follows: A result output unit, used to obtain a preliminary channel estimation result in the time domain according to the estimation result, further comprising: The preliminary channel estimation result is screened to obtain a final channel estimation result, specifically including: threshold screening of the preliminary channel estimation result in the time domain, specifically including: based on a preset threshold screening formula, setting the values ​​in the preliminary channel estimation result in the time domain that are less than the preset threshold to zero, retaining the values ​​in the preliminary channel estimation result in the time domain that are greater than or equal to the preset threshold, to complete the threshold screening, the threshold screening formula is based on the channel estimation simulation experiment results of the FBMC system, the bit error rate and the mean square error are fitted according to the performance of different signal-to-noise ratios, and the threshold screening formula is: α1=5.54e -0.11SNR (20≤SNR≤30) α2=0.78e -0.09SNR (0≤SNR≤30) Wherein, α1 is the first threshold, α2 is the second threshold, and SNR is the signal-to-noise ratio; The preset threshold includes a first threshold, and the first threshold is a threshold that minimizes the bit error rate; In the threshold screening formula, the first threshold α1=5.54e -0.11SNR (20≤SNR≤30), where SNR is the signal-to-noise ratio; The preset threshold includes a second threshold, and the second threshold is a threshold that minimizes the mean square error; In the threshold screening formula, the second threshold α2 = 0.78e -0.09SNR (0≤SNR≤30), where SNR is the signal-to-noise ratio; The channel estimation result in the time domain after threshold screening is subjected to fast Fourier transform to obtain the final channel estimation result.

7. The channel estimation device based on a wireless communication system according to claim 6, characterized in that: According to the pilot type of the wireless communication system, an observation vector and a sensing matrix are obtained, which also includes: Acquire a demodulated signal from a receiving end of the wireless communication system; A pilot type of the wireless communication system is determined according to the demodulated signal.

8. The channel estimation device based on a wireless communication system according to claim 6, characterized in that: According to the estimation result, a preliminary channel estimation result in the time domain is obtained, which specifically includes: Obtaining a preliminary channel estimate of the pilot position including position information according to the estimation result; Interpolate the preliminary channel estimate at the pilot position to obtain a complete preliminary channel estimate at the receiving end; The complete preliminary channel estimate at the receiving end is subjected to an inverse fast Fourier transform to obtain a preliminary channel estimate result in the time domain.

9. The channel estimation device based on a wireless communication system according to any one of claims 6 to 8, characterized in that: The wireless communication system is a FBMC system.

10. The channel estimation device based on a wireless communication system according to any one of claims 6 to 8, characterized in that: The channel estimation method adopts a pilot-based channel estimation algorithm.

11. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, a channel estimation method based on a wireless communication system is implemented, and the method includes the following steps: According to the pilot type of the wireless communication system, an observation vector and a sensing matrix are obtained; Based on the observation vector, the sensing matrix and the preset step size, an estimation result of the pilot vector channel is obtained through an iterative cycle algorithm, specifically including: Before starting the iteration cycle, input the initial residual r0 = Y, the initial support set Initial candidate set Preselect the number of atoms L = λ and the number of iterations k = 1; start the iteration cycle and calculate the residual r between the sensor matrix Θ and the previous iteration k-1 The correlation coefficient θ T r k-1 , where the index S of the first L maximum values k Incorporate into the existing support set F k-1 and update the candidate set to C k =F k-1 ∪S k ; Compute the least squares solution Select the L largest indexes from them and store them in set F, and update the residual Where Y is the observation vector and k is the number of iterations; If the residual is less than the iteration threshold, the pilot vector channel estimation is obtained. If ||r k ||2≥||r k-1 ||2, L = L + λ, otherwise, update the residual Update the support set F k =F, k=k+1, recalculate the correlation coefficient; After the termination condition is met, the above cycle ends and the estimation result of the pilot vector channel is obtained as follows: According to the estimation result, a preliminary channel estimation result in the time domain is obtained; and further comprising: The preliminary channel estimation result is screened to obtain a final channel estimation result, specifically including: threshold screening of the preliminary channel estimation result in the time domain, specifically including: based on a preset threshold screening formula, setting the values ​​in the preliminary channel estimation result in the time domain that are less than the preset threshold to zero, retaining the values ​​in the preliminary channel estimation result in the time domain that are greater than or equal to the preset threshold, to complete the threshold screening, the threshold screening formula is based on the channel estimation simulation experiment results of the FBMC system, the bit error rate and the mean square error are fitted according to the performance of different signal-to-noise ratios, and the threshold screening formula is: α1=5.54e -0.11SNR (20≤SNR≤30) α2=0.78e -0.09SNR (0≤SNR≤30) Wherein, α1 is the first threshold, α2 is the second threshold, and SNR is the signal-to-noise ratio; The preset threshold includes a first threshold, and the first threshold is a threshold that minimizes the bit error rate; In the threshold screening formula, the first threshold α1=5.54e -0.11SNR (20≤SNR≤30), where SNR is the signal-to-noise ratio; The preset threshold includes a second threshold, and the second threshold is a threshold that minimizes the mean square error; In the threshold screening formula, the second threshold α2 = 0.78e -0.09SNR (0≤SNR≤30), where SNR is the signal-to-noise ratio; The channel estimation result in the time domain after threshold screening is subjected to fast Fourier transform to obtain the final channel estimation result.

12. The computer device according to claim 11, characterized in that According to the pilot type of the wireless communication system, an observation vector and a sensing matrix are obtained, which also includes: Acquire a demodulated signal from a receiving end of the wireless communication system; A pilot type of the wireless communication system is determined according to the demodulated signal.

13. The computer device according to claim 11, characterized in that According to the estimation result, a preliminary channel estimation result in the time domain is obtained, which specifically includes: Obtaining a preliminary channel estimate of the pilot position including position information according to the estimation result; Interpolate the preliminary channel estimate at the pilot position to obtain a complete preliminary channel estimate at the receiving end; The complete preliminary channel estimate at the receiving end is subjected to an inverse fast Fourier transform to obtain a preliminary channel estimate result in the time domain.

14. The computer device according to any one of claims 11 to 13, characterized in that: The wireless communication system is a FBMC system.

15. The computer device according to any one of claims 11 to 13, characterized in that: The channel estimation method adopts a pilot-based channel estimation algorithm.

Images