Base station correction method, electronic device, program product and storage medium

Abstract

The invention discloses a base station correction method, electronic equipment, a program product and a storage medium. The base station correction method comprises the steps that a first receiving signal and a second receiving signal received by a base station are acquired, the first receiving signal does not comprise a correction signal sent by a test terminal, and the second receiving signal comprises a correction signal sent by the test terminal; determining a radio frequency gain amplitude estimation value according to the first receiving signal; determining a radio frequency gain phase estimation value according to the first receiving signal, the radio frequency gain amplitude estimation value and the second receiving signal; and correcting the base station according to the radio frequency gain amplitude estimation value and the radio frequency gain phase estimation value. According to the invention, the technical problem of how to accurately estimate the channel radio frequency gain in the multipath environment so as to improve the correction precision of the channel radio frequency gain is solved.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and in particular, to a base station calibration method, an electronic device, a program product, and a storage medium. Background Art

[0002] The shortwave skywave large-scale MIMO (Multiple-Input Multiple-Output) communication technology is an important part of the future global coverage of wireless networks. It realizes over-the-horizon communication through ionospheric reflection and has advantages such as flexible deployment and high anti-attack performance compared with satellite communication. In a shortwave skywave large-scale MIMO system, for a time-division duplexing (TDD) system, the reciprocity of the uplink and downlink channels is the basis for the effectiveness of the precoding algorithm. However, differences in analog circuits in the base station transceiver link can lead to amplitude and phase differences between channels, destroying the reciprocity of the end-to-end channel of the TDD system and thus reducing the precoding performance. Therefore, in order to ensure the effectiveness of technologies such as precoding in the TDD system, it is necessary to perform absolute calibration on the amplitude and phase differences in the base station transceiver link to ensure that the radio frequency gains of each channel are consistent in amplitude and phase.

[0003] Traditional calibration schemes, such as calibration based on signals measured in an anechoic chamber, cannot be effectively implemented in a shortwave skywave large-scale MIMO system because when the number of base station antennas reaches dozens or even hundreds, the array size can be up to hundreds of meters, and accurate calibration cannot be performed in an anechoic chamber environment. In this case, in-air calibration in an outdoor environment has become a necessary means to solve the absolute calibration of a shortwave skywave large-scale MIMO array. However, for in-air calibration in a shortwave skywave environment in an outdoor scenario, especially in a scenario with rich scatterers between the calibration terminal and the base station, it is difficult to ensure an ideal single-path environment between the terminal and the base station. In a multipath environment, the problem faced by in-air calibration is that the multipath effect will couple the calibration coefficient and the channel coefficient, and the current decoupling methods are often sensitive to the initial value and it is difficult to ensure the global optimal solution, thus affecting the calibration accuracy and system performance. Therefore, how to accurately estimate the radio frequency gain of channels in a multipath environment to improve the calibration accuracy of the radio frequency gain of channels is one of the important technical problems in the related technical field.

[0004] In view of the above problems, no effective solution has been proposed yet. Summary of the Invention

[0005] Embodiments of the present invention provide a base station calibration method, an electronic device, a program product, and a storage medium to at least solve the technical problem of how to accurately estimate the radio frequency gain of channels in a multipath environment to improve the calibration accuracy of the radio frequency gain of channels.

[0006] According to one aspect of an embodiment of the present invention, a base station calibration method is provided, including: obtaining a first received signal and a second received signal received by the base station, where the first received signal does not include a calibration signal sent by a test terminal, and the second received signal includes the calibration signal sent by the test terminal; determining an estimated value of the RF gain amplitude according to the first received signal; determining an estimated value of the RF gain phase according to the first received signal, the estimated value of the RF gain amplitude, and the second received signal; and calibrating the base station according to the estimated value of the RF gain amplitude and the estimated value of the RF gain phase.

[0007] Optionally, determining the estimated value of the RF gain amplitude according to the first received signal includes: determining a first covariance matrix corresponding to the first received signal according to the first received signal; determining a first covariance estimation matrix according to a plurality of first received signals; and determining the estimated value of the RF gain amplitude according to the first covariance matrix and the first covariance estimation matrix.

[0008] Optionally, determining the estimated value of the RF gain amplitude according to the first covariance matrix and the first covariance estimation matrix includes: determining an expression for estimating the RF gain amplitude according to the first covariance matrix; and determining the estimated value of the RF gain amplitude according to the first covariance estimation matrix and the expression for estimating the RF gain amplitude.

[0009] Optionally, determining the estimated value of the RF gain amplitude according to the first covariance estimation matrix and the expression for estimating the RF gain amplitude includes: sequentially substituting the diagonal element values in the first covariance estimation matrix into the expression for estimating the RF gain amplitude to obtain the estimated value of the RF gain amplitude, where the estimated value of the RF gain amplitude includes a plurality of sub-estimated values of the RF gain amplitude.

[0010] Optionally, determining the estimated value of the RF gain phase according to the first received signal, the estimated value of the RF gain amplitude, and the second received signal includes: determining a first covariance matrix corresponding to the first received signal according to the first received signal; determining a second covariance matrix corresponding to the second received signal according to the second received signal; determining a first covariance estimation matrix according to a plurality of first received signals; determining a second covariance estimation matrix according to a plurality of second received signals; determining a third covariance estimation matrix according to the first covariance matrix, the second covariance matrix, the first covariance estimation matrix, and the second covariance estimation matrix; and determining the estimated value of the RF gain phase according to the third covariance estimation matrix and the estimated value of the RF gain amplitude.

[0011] Optionally, determining a third covariance estimation matrix according to the first covariance matrix, the second covariance matrix, the first covariance estimation matrix, and the second covariance estimation matrix includes: determining an expression of a third covariance matrix according to the first covariance matrix and the second covariance matrix; determining an expression of the third covariance estimation matrix according to the expression of the third covariance matrix; substituting the first covariance estimation matrix and the second covariance estimation matrix into the expression of the third covariance estimation matrix to determine the third covariance estimation matrix.

[0012] Optionally, determining a radio frequency gain phase estimation value according to the third covariance estimation matrix and the radio frequency gain amplitude estimation value includes: performing eigenvalue decomposition on the third covariance estimation matrix to obtain a fourth matrix; performing spectral peak search on a first spectral function to obtain an arrival angle estimation value, where the first spectral function is constructed based on the fourth matrix; determining the radio frequency gain phase estimation value according to the arrival angle estimation value, the radio frequency gain amplitude estimation value, and a preset cost function expression.

[0013] Optionally, performing spectral peak search on the first spectral function to obtain an arrival angle estimation value includes: performing spectral peak search on the first spectral function within a preset range to determine a preset number of peaks of the first spectral function to obtain the arrival angle estimation value, where the preset number is determined based on the number of multipaths of the channel.

[0014] Optionally, determining the radio frequency gain phase estimation value according to the arrival angle estimation value, the radio frequency gain amplitude estimation value, and the preset cost function expression includes: substituting the arrival angle estimation value and the radio frequency gain amplitude estimation value into the preset cost function expression to obtain a target cost function expression; using a preset algorithm to perform iterative minimization on the target cost function expression to obtain the radio frequency gain phase estimation value.

[0015] According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including: a memory storing an executable program; a processor configured to run the executable program, where when the executable program runs, it executes the base station calibration method in any one of the above.

[0016] According to another aspect of the embodiments of the present invention, there is also provided a computer program product, including a computer program, where when the computer program is executed by a processor, it implements the base station calibration method in any one of the above.

[0017] According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, where the computer-readable storage medium includes a stored executable program, and when the executable program runs, it controls the device where the computer-readable storage medium is located to execute the base station calibration method in any one of the above.

[0018] In an embodiment of the present invention, a first received signal and a second received signal received by a base station are obtained, where the first received signal does not include a calibration signal sent by a test terminal, and the second received signal includes the calibration signal sent by the test terminal; an estimated value of the radio frequency gain amplitude is determined according to the first received signal; an estimated value of the radio frequency gain phase is determined according to the first received signal, the estimated value of the radio frequency gain amplitude, and the second received signal; and the base station is calibrated according to the estimated value of the radio frequency gain amplitude and the estimated value of the radio frequency gain phase. The present invention uses the first received signal to accurately estimate the radio frequency gain amplitude, and at the same time, based on the first received signal, the second received signal, and the already estimated radio frequency gain amplitude, effectively estimates the radio frequency gain phase, ensuring that the radio frequency gain of the channel is calibrated based on the accurate estimated values of the channel radio frequency gain amplitude and the radio frequency gain phase. Since the present invention separates the amplitude calibration and the phase calibration, it avoids the problem that the calibration accuracy cannot be guaranteed due to sensitivity to the initial parameters during the decoupling process, thereby solving the technical problem of how to accurately estimate the channel radio frequency gain in a multipath environment to improve the calibration accuracy of the channel radio frequency gain. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The illustrative embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0020] Figure 1 is a flowchart of a base station calibration method according to an embodiment of the present invention;

[0021] Figure 2 is a schematic model diagram of a base station calibration method according to an embodiment of the present invention;

[0022] Figure 3 is a structural block diagram of a base station calibration method according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] In order to enable those skilled in the art of the present technology to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0024] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of the present invention are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention described here can be implemented in an order different from those illustrated or described here. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0025] According to an embodiment of the present invention, an embodiment of a base station calibration method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system including at least a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that here.

[0026] This method embodiment can also be executed in an electronic device including a memory and a processor, a similar control device or in the cloud. Taking the electronic device as an example, the electronic device may include one or more processors and a memory for storing data. Optionally, the above-mentioned electronic device may further include a communication device for communication functions and a display device. Those of ordinary skill in the art can understand that the above structural description is only illustrative and does not limit the structure of the above-mentioned electronic device. For example, the electronic device may further include more or fewer components than the above structural description, or have a configuration different from the above structural description.

[0027] The processor may include one or more processing units. For example, the processor may include a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processing (DSP) chip, a microcontroller unit (MCU), a field-programmable gate array (FPGA), a neural-network processing unit (NPU), a tensor processing unit (TPU), an artificial intelligent (AI) type processor, and other processing devices. Among them, different processing units may be independent components or integrated in one or more processors. In some instances, the electronic device may also include one or more processors.

[0028] The memory can be used to store computer programs. For example, it stores the computer program corresponding to the base station calibration method in the embodiments of the present invention. The processor realizes the above base station calibration method by running the computer program stored in the memory. The memory may include a high-speed random access memory and may also include a non-volatile memory, such as one or more magnetic storage devices, a flash memory, or other non-volatile solid-state memories. In some instances, the memory may further include a memory remotely set relative to the processor, and these remote memories can be connected to the electronic device through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and their combinations.

[0029] The communication device is used to receive or send data via a network. Specific examples of the above network may include a wireless network provided by the communication provider of the mobile terminal. In one instance, the communication device includes a network interface controller (NIC), which can be connected to other network devices through a base station and thus communicate with the Internet. In one instance, the communication device may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly. In some embodiments of this solution, the communication device is used to connect to mobile devices such as mobile phones and tablets, and can send instructions to the electronic device through the mobile devices.

[0030] The display device can be a touch-screen liquid crystal display (LCD) and a touch display (also known as a "touch screen" or "touch display screen"). The liquid crystal display enables a user to interact with the user interface of an electronic device. In some embodiments, the above-mentioned electronic device has a graphical user interface (GUI), and the user can perform human-computer interaction with the GUI by touching a finger on the touch-sensitive surface and / or making gestures. The executable instructions for performing the above human-computer interaction functions are configured / stored in a computer program product or a readable storage medium executable by one or more processors.

[0031] Figure 1 is a flowchart of a base station calibration method according to an embodiment of the present invention, as Figure 1 shown, the method includes the following steps:

[0032] Step S101, obtain a first received signal and a second received signal received by the base station, where the first received signal does not include a calibration signal sent by a test terminal, and the second received signal includes a calibration signal sent by the test terminal.

[0033] First of all, it should be noted that the present invention discusses the absolute calibration scheme of the base station in the short-wave skywave large-scale MIMO system.

[0034] Specifically, the first received signal refers to the signal received by the base station during the period when the test terminal does not send a calibration signal.

[0035] Since the test terminal does not send a calibration signal, the first received signal mainly includes environmental noise and internal thermal noise.

[0036] It should be noted that the short-wave skywave frequency band has relatively large environmental noise, which comes from natural lightning, solar wind, cosmic rays, as well as man-made electrical equipment, industrial machines, etc., and its intensity is usually much greater than the thermal noise generated by the internal components of the base station.

[0037] The second received signal refers to the signal received by the base station when the test terminal sends a calibration signal. The calibration signal sent by the test terminal propagates to the base station through the ground wave, aiming to provide a known signal source. The second received signal includes both environmental noise, internal thermal noise, and the calibration signal sent by the test terminal.

[0038] Step S102, determine an estimated value of the RF gain amplitude according to the first received signal.

[0039] During the period when the test terminal does not send a calibration signal, the first received signal received by the base station mainly consists of environmental noise and contains a small amount of thermal noise generated by internal devices. Environmental noise is an inherent characteristic of the channel, with generally large intensity and certain statistical characteristics. Based on this characteristic, by analyzing the first received signal, an estimated value of the RF gain amplitude can be obtained.

[0040] Among them, the RF gain amplitude of the base station receiving channel refers to the absolute value of the gain of each channel's RF link, which reflects the degree of amplification or attenuation of the signal after passing through the RF link. In a TDD (Time-Division Duplexing) system, the amplitude consistency of the transceiver link is crucial for maintaining the reciprocity of the uplink and downlink channels, and thus affects the performance of signal processing technologies such as precoding and beamforming.

[0041] It can be understood that this application can efficiently and accurately estimate the RF gain amplitude of the base station receiving channel by utilizing the statistical characteristics of environmental noise when the test terminal does not send a calibration signal. This processing method not only avoids the dependence on additional calibration signals but also reduces the complexity and cost of the calibration process.

[0042] Step S103: Determine an estimated value of the RF gain phase based on the first received signal, the estimated value of the RF gain amplitude, and the second received signal.

[0043] The first received signal is mainly used to estimate amplitude information, and the second received signal contains a known calibration signal, which is the key to phase estimation. Based on the already determined estimated value of the RF gain amplitude, by comprehensively analyzing and processing the first received signal and the second received signal, an estimated value of the RF gain phase is determined.

[0044] Among them, the RF gain phase of the base station receiving channel refers to the change in the signal phase when the signal passes through the RF receiving link of the base station due to the non-ideal characteristics of various components (such as mixers, amplifiers, filters, etc.) in the RF link, and this change amount is the RF gain phase.

[0045] It should be noted that signal processing technologies such as precoding and beamforming rely on channel state information (CSI, Channel State Information), especially accurate phase information. If the RF gain phase is inconsistent among different channels, the performance of these technologies will be greatly reduced. Therefore, it is necessary to accurately estimate the RF gain phase, thereby correcting the RF gain phase to ensure that the phase change is consistent among all receiving channels, and further ensuring that signal processing algorithms (such as precoding, beamforming, etc.) can work effectively.

[0046] Step S104: Calibrate the base station according to the estimated RF gain amplitude and the estimated RF gain phase.

[0047] Specifically, for each receiving channel of the base station, calculate an RF gain compensation factor according to the estimated RF gain amplitude and the estimated RF gain phase. This compensation factor contains amplitude and phase information and is used to offset the gain effect brought by the RF link during the subsequent signal processing. Further, when the base station receives a signal, multiplying it by the RF gain compensation factor of its corresponding channel can eliminate the non-ideal effects of the RF link and ensure that the signals between different channels are consistent in amplitude and phase.

[0048] It should be noted that the calibration adopted in this application refers to estimating and compensating the channel RF gain to make the RF gain amplitude and phase consistent between channels, which is an absolute calibration scheme. The relative calibration in the prior art refers to estimating the transmit RF gain and the receive RF gain or the ratio of the two to make the uplink and downlink RF gains reciprocal. That is to say, relative calibration does not pursue absolute channel consistency but only focuses on the reciprocity between the base station receive link and the transmit link.

[0049] Through the above absolute calibration, the base station can perform operations such as precoding and beamforming more accurately, improving the communication quality of the system. Especially in the short-wave skywave massive MIMO system, absolute calibration has a significant effect on improving key applications such as positioning accuracy, channel power spectrum extraction, and precoding algorithms based on statistical channel models.

[0050] In the embodiment of the present invention, obtain the first received signal and the second received signal received by the base station, where the first received signal does not contain the calibration signal sent by the test terminal, and the second received signal contains the calibration signal sent by the test terminal; determine the estimated RF gain amplitude according to the first received signal; determine the estimated RF gain phase according to the first received signal, the estimated RF gain amplitude, and the second received signal; calibrate the base station according to the estimated RF gain amplitude and the estimated RF gain phase. The present invention uses the first received signal to accurately estimate the RF gain amplitude, and at the same time, based on the first received signal, the second received signal, and the already estimated RF gain amplitude, effectively estimate the RF gain phase, ensuring that the channel RF gain is calibrated based on the accurate estimated values of the channel RF gain amplitude and the RF gain phase. Since the present invention separates the amplitude calibration and the phase calibration, it avoids the problem that the calibration accuracy cannot be guaranteed due to sensitivity to the initial parameters during the decoupling process, thus solving the technical problem of how to accurately estimate the channel RF gain in a multipath environment to improve the calibration accuracy of the channel RF gain.

[0051] Optionally, determining the estimated RF gain amplitude according to the first received signal includes the following steps:

[0052] Step S1021: Determine a first covariance matrix corresponding to the first received signal according to the first received signal;

[0053] Figure 2 It is a schematic diagram of a model of a base station calibration method according to an embodiment of the present invention. The following will be combined with Figure 2 to explain the present invention in detail.

[0054] It should be noted that in the embodiments of the present application, the calibration of the channel receiving radio frequency gain is mainly described. The calibration of the transmitting radio frequency gain can be achieved by using reciprocity.

[0055] Such as Figure 2 shown, a TDD short-wave skywave massive MIMO system is defined, where the number of base station antennas is M, and the air interface auxiliary calibration terminal is a single antenna. In order to improve the signal-to-noise ratio of the calibration signal, the calibration signal is mainly transmitted through the ground wave, that is, the distance between the air interface auxiliary terminal and the base station is within the ground wave coverage range. At a certain carrier frequency, for the multipath scenario, the channel between the terminal k and the base station at time t can be expressed as:

[0056]

[0057] where L k represents the number of multipaths of the channel, θ k,l represents the angle of arrival (AoA) of the l-th path of the terminal k, the complex scalar g k,l (t) represents the channel gain of the l-th path, and a(θ k,l ) is the steering vector.

[0058] For a uniform linear array (ULA), the expression of a(θ k,l ) is:

[0059]

[0060] where λ c represents the wavelength corresponding to the carrier frequency, and d represents the antenna spacing.

[0061] When the terminal does not send a calibration signal, due to the existence of relatively large external environmental noise, the first received signal can be expressed as:

[0062]

[0063] where the diagonal matrix D β = diag{β1, β2, …, β M}, which is used to represent the channel receiving gain, and z kz(t)=[z1(t),z2(t),…,z M (t)] T , which is used to represent the external environmental noise, n k (t)=[n1(t),n2(t),…,n M (t)] T , which is used to represent the thermal noise generated by internal devices.

[0064] The first covariance matrix is a statistic used to describe the statistical correlation between the elements in the first received signal. For the first received signal received by the base station, the covariance matrix is calculated to reveal the spatial distribution characteristics of the signal.

[0065] Define the covariance matrix of the internal noise (i.e., the thermal noise generated by internal devices) as:

[0066]

[0067] where denotes taking the expectation of the variable in the parentheses, and (·) H denotes the conjugate transpose of the matrix.

[0068] Define the covariance matrix of the external environmental noise as:

[0069]

[0070] Define the covariance matrix corresponding to the first received signal as:

[0071]

[0072] Combined with the first received signal expression (3), the first covariance matrix corresponding to the first received signal can be expressed as:

[0073]

[0074] where D β represents the channel reception gain, R z represents the covariance matrix of the external environmental noise, and R n represents the covariance matrix of the internal noise.

[0075] Step S1022, determine the first covariance estimation matrix according to multiple first received signals;

[0076] Assume that there are T measurements of the noise signal, and multiple first received signals are expressed as

[0077] According to multiple first received signals, the first covariance estimation matrix can be expressed as:

[0078]

[0079] Step S1023: Determine the estimated value of the RF gain amplitude according to the first covariance matrix and the first covariance estimation matrix.

[0080] The first covariance matrix is calculated based on a theoretical model, which contains the power distribution and signal correlation information of the ambient noise signal among the base station's receiving channels in an ideal environment (where the RF gain amplitudes and phases of all receiving channels of the base station are exactly the same).

[0081] The first covariance estimation matrix is the actual covariance matrix obtained by the base station through statistical analysis and calculation of the actually received noise signal set (the first test signal set). The first covariance estimation matrix reflects the actual power distribution and signal correlation of the ambient noise signal among different receiving channels in the actual system due to hardware non-ideality (such as RF gain amplitude differences) and the influence of the multipath propagation environment.

[0082] Perform comprehensive analysis and calculation on the first covariance matrix and the first covariance estimation matrix to determine the estimated value of the RF gain amplitude.

[0083] Optionally, determining the estimated value of the RF gain amplitude according to the first covariance matrix and the first covariance estimation matrix includes the following steps:

[0084] Step S10231: Determine the estimated expression of the RF gain amplitude according to the first covariance matrix;

[0085] Assume that the noise is uncorrelated between channels, then R z and R n can be respectively expressed as where is the external ambient noise variance, is the internal noise variance, and I is the identity matrix.

[0086] Combined with formula (7), the first covariance matrix can be rewritten as:

[0087]

[0088] Assume that the RF gain of channel m can be written as β m = r m exp(jφ m ), where r m is the amplitude and φ m is the phase. Then the first covariance matrix can be further expressed as:

[0089]

[0090] where

[0091] Assume that the internal noise of the receiver is known (generally measurable by an instrument), and the internal noise estimate is Then the expression for estimating the RF gain amplitude can be expressed as:

[0092]

[0093] Where, is the estimated value of the RF gain amplitude, is the first covariance estimation matrix The m-th diagonal element.

[0094] It should be noted that the formula (10) is transformed to obtain the calculation expression of the RF gain amplitude, and then the true value in the expression is replaced by the corresponding estimated value to obtain formula (11).

[0095] It should be noted that the estimated value of the RF gain amplitude and the true value r of the RF gain amplitude m There is a common parameter σ between them z , that is For channel correction, only consistency is required, so the existence of a common parameter does not affect the correction result.

[0096] Step S10232, determine the estimated value of the RF gain amplitude according to the first covariance estimation matrix and the RF gain amplitude estimation expression.

[0097] According to the first covariance estimation matrix and the RF gain amplitude estimation expression, the estimated value of the RF gain amplitude can be determined for subsequent correction calculations.

[0098] Optionally, determining the estimated value of the RF gain phase according to the first received signal, the estimated value of the RF gain amplitude, and the second received signal includes the following steps:

[0099] Specifically, by substituting the diagonal element values of the first covariance estimation matrix, that is, the power of the noise signal received by each channel, into the RF gain amplitude estimation expression, the estimated value of the RF gain amplitude can be obtained.

[0100] Wherein, the estimated value of the RF gain amplitude contains multiple estimated sub-values of the RF gain amplitude, which means that the RF gain amplitude of each receiving channel can be estimated and corrected separately.

[0101] Optionally, determining the estimated value of the RF gain phase according to the first received signal, the estimated value of the RF gain amplitude, and the second received signal includes the following steps:

[0102] Step S1031: Determine the first covariance matrix corresponding to the first received signal according to the first received signal;

[0103] The expression of the first covariance matrix corresponding to the first received signal is as shown in formula (7).

[0104] Step S1032: Determine the second covariance matrix corresponding to the second received signal according to the second received signal;

[0105] Assume that the radio frequency complex gain coefficient of the m-th channel of the base station is β m , and the calibration signal sent by the terminal is 1. Then, for air interface assisted calibration, the second received signal containing the calibration signal received by the base station can be expressed as:

[0106] y k (t) = D β A k g k (t) + D β z k (t) + n k (t) (12)

[0107] where the diagonal matrix D β = diag{β1, β2, …, β M}, which is used to represent the channel reception gain, the matrix is used to represent the steering matrix, the vector is used to represent the channel gain vector, z k (t) = [z1(t), z2(t), …, z M (t)] T , which is used to represent the external environmental noise, n k (t) = [n1(t), n2(t), …, n M (t)] T , which is used to represent the thermal noise generated by internal devices, diag{·} represents a diagonal matrix with the elements in the curly brackets as the diagonal elements, represents the complex domain.

[0108] Define the covariance matrix of the channel gain as:

[0109]

[0110] Define the second covariance matrix corresponding to the second received signal as:

[0111]

[0112] Combined with the second received signal expression (12), the second covariance matrix corresponding to the second received signal can be expressed as:

[0113]

[0114] Step S1033: Determine the first covariance estimation matrix according to multiple first received signals;

[0115] Assume that there are T measurements of the first received signal, and multiple first received signals are expressed as

[0116] Based on multiple first received signals, the first covariance estimation matrix can be expressed as shown in formula (8).

[0117] Step S1034: Determine the second covariance estimation matrix according to multiple second received signals;

[0118] Assume that there are T measurements of the second received signal, and multiple second received signals are expressed as {y k (t), t = 1, 2, …, T}.

[0119] The second covariance estimation matrix can be expressed as:

[0120]

[0121] Step S1035: Determine the third covariance estimation matrix according to the first covariance matrix, the second covariance matrix, the first covariance estimation matrix, and the second covariance estimation matrix;

[0122] Determine the third covariance estimation matrix according to the already determined first covariance matrix, second covariance matrix, first covariance estimation matrix, and second covariance estimation matrix. Among them, the third covariance estimation matrix is the basis for subsequent radio frequency gain phase estimation.

[0123] Step S1036: Determine the radio frequency gain phase estimation value according to the third covariance estimation matrix and the radio frequency gain amplitude estimation value.

[0124] The third covariance estimation matrix contains information on the radio frequency gain phase difference. By combining it with the radio frequency gain amplitude estimation value, the radio frequency gain phase estimation value can be determined, providing a basis for subsequent phase correction.

[0125] Optionally, determining the third covariance estimation matrix according to the first covariance matrix, the second covariance matrix, the first covariance estimation matrix, and the second covariance estimation matrix includes the following steps:

[0126] Step S10351: Determine the third covariance matrix expression according to the first covariance matrix and the second covariance matrix;

[0127] Define the third covariance matrix corresponding to the calibration signal:

[0128]

[0129] According to the first covariance matrix and the second covariance matrix, the third covariance matrix corresponding to the calibration signal can be expressed as:

[0130]

[0131] where, R y is the second covariance matrix, is the first covariance matrix.

[0132] Step S10352, determine the expression of the third covariance estimation matrix according to the expression of the third covariance matrix;

[0133] According to the determined expression of the third covariance matrix, that is, formula (18), further determine the expression of the third covariance estimation matrix as:

[0134]

[0135] where, is the second covariance estimation matrix, is the first covariance estimation matrix.

[0136] Step S10353, substitute the first covariance estimation matrix and the second covariance estimation matrix into the expression of the third covariance estimation matrix to determine the third covariance estimation matrix.

[0137] Based on the determined expression of the third covariance estimation matrix, substitute the calculated first covariance estimation matrix and the second covariance estimation matrix into the expression of the third covariance estimation matrix, and the third covariance estimation matrix can be calculated.

[0138] Optionally, determining the RF gain phase estimation value according to the third covariance estimation matrix and the RF gain amplitude estimation value includes the following steps:

[0139] Step S10361, perform eigenvalue decomposition on the third covariance estimation matrix to obtain the fourth matrix;

[0140] Assume that the eigenvalues and eigenvectors of the third covariance matrix P k are λ k,m , u k,m , m = 1, 2,..., M, that is, P k u k,m = λ k,m u k,m , m = 1, 2,..., M. The third covariance matrix P khas a rank of L k , L k is the number of multipaths of the channel, then there is matrix D β A k the matrix composed of the column vectors and eigenvectors of is orthogonal.

[0141] Using the same processing method, perform eigenvalue decomposition on the third covariance estimation matrix to obtain that is, the fourth matrix.

[0142] Step S10362, perform spectral peak search on the first spectral function to obtain the angle of arrival estimation value, where the first spectral function is constructed based on the fourth matrix;

[0143] Based on the fourth matrix, construct the first spectral function, and the expression of the first spectral function is as follows:

[0144]

[0145] where i is the number of iterations, a(θ) is the steering vector, and D β is the channel reception gain.

[0146] The first spectral function is a function of the angle θ. Perform spectral peak search on the first spectral function to obtain the angle of arrival estimation value.

[0147] Theoretically, in the case of only one angle of arrival, when θ = θ k,l , the first spectral function has a maximum value.

[0148] Step S10363, determine the RF gain phase estimation value according to the angle of arrival estimation value, the RF gain amplitude estimation value, and the preset cost function expression.

[0149] Substitute the angle of arrival estimation value and the RF gain amplitude estimation value into the preset cost function expression, and further minimize the cost function to solve for the RF gain phase estimation value.

[0150] Optionally, performing spectral peak search on the first spectral function to obtain the angle of arrival estimation value includes: within a preset range, performing spectral peak search on the first spectral function, determining a preset number of peaks of the first spectral function, and obtaining the angle of arrival estimation value, where the preset number is determined based on the number of multipaths of the channel.

[0151] Based on the determined expression of the first spectral function, within a preset range, perform spectral peak search, identify a preset number of peaks in the first spectral function, and further determine the angle of arrival estimation value.

[0152] The preset range is the search angle range preset by the base station. The selection of the preset range should cover all possible arrival angles to ensure that the main paths of the signal are not missed.

[0153] In a preferred embodiment, the preset range is (0, π).

[0154] In addition, based on the number of multipaths of the channel, the base station determines the number of first spectral function peaks to be searched. The setting of the preset number is to ensure that the arrival angles of all effective arrival paths can be accurately estimated without affecting the estimation accuracy due to too many or too few peaks.

[0155] Optionally, according to the arrival angle estimation value, the radio frequency gain amplitude estimation value, and the preset cost function expression, determine the radio frequency gain phase estimation value, including the following steps:

[0156] Step S103631, substitute the arrival angle estimation value and the radio frequency gain amplitude estimation value into the preset cost function expression to obtain the target cost function expression;

[0157] Define the preset cost function expression as:

[0158]

[0159] Further transform the preset cost function expression, and represent the preset cost function as follows:

[0160]

[0161] where β = [β1, β2, …, β M T , Q k,l = diag{a(θ k,l )}.

[0162] Let φ = [expφ1, expφ2, …, expφ M T , Γ = diag{r1, r2, …, r M}, and the preset cost function can be further represented as follows:

[0163]

[0164] where Γ is a diagonal matrix, and the diagonal elements are radio frequency gain amplitude values, and Q k,l is also a diagonal matrix, and the diagonal elements are the steering vectors a(θ k,l ).

[0165] Replace the diagonal elements of the diagonal matrix Γ in formula (23) with the corresponding radio frequency gain amplitude estimation values, and replace Q k,l ​​The angle of arrival θ included in k,l is replaced with the corresponding estimated angle of arrival value to obtain the target cost function expression.

[0166] Step S103632: Use a preset algorithm to perform iterative minimization on the target cost function expression to obtain the RF gain phase estimation value.

[0167] It should be noted that solving φ by minimizing the target cost function expression is actually estimating the k eigenvector corresponding to the minimum eigenvalue of W. Specifically, define the matrix where α is a sufficiently large constant, such as α = ‖W k ‖2. Then φ is the eigenvector corresponding to the maximum eigenvalue of. φ can be obtained by iterative solution using a preset algorithm (such as the power method).

[0168] Exemplarily, the process of using the power method to iteratively solve φ includes: 1) Initialize the input φ (0) , 2) Iterate until the iteration stop condition is met (reaching the maximum number of iterations i max or ‖φ (i) - φ (i-1) ‖2 ≤ ∈).

[0169] By performing iterative minimization on the target cost function expression, the RF gain phase estimation value can be obtained.

[0170] Optionally, the base station calibration method disclosed in the present invention can also be implemented as follows:

[0171] Initialization: Air interface measurement and {y k (t), t = 1, 2,..., T}; According to the amplitude estimated by formula (11) Randomly initialize the phase Can get Estimate according to formula (19) Then perform eigenvalue decomposition to obtain the matrix The initial iteration counter i = 0, the maximum number of iterations i max . The threshold constant ∈.

[0172] Iterative phase estimation: Estimate the angle: Search for the L peaks of the spatial spectrum function of, and the estimated value of the angle of arrival k can be obtained; Estimate the phase: Minimize Estimate the phase φ , which can be solved using the power method; The iteration counter i = i + 1, if i < i (i) or ‖φ max or ‖φ(i) -φ (i-1) ‖2≤∈。

[0173] Through the above steps, the RF reception gain β can be estimated, and then the absolute correction of the reception gain can be completed.

[0174] Optionally, measurement signals of multiple terminals or different unknowns of one terminal can be collected, and the average value can be obtained by estimating multiple times, so as to improve the correction performance.

[0175] In summary, the present invention realizes the accurate estimation of the RF gain amplitude by using the first received signal, and at the same time, based on the first received signal, the second received signal and the already estimated RF gain amplitude, realizes the effective estimation of the RF gain phase, ensuring that the channel RF gain is corrected based on the accurate estimated values of the channel RF gain amplitude and the RF gain phase. Since the present invention separates the amplitude correction and the phase correction, it avoids the problem that the correction accuracy cannot be guaranteed due to sensitivity to the initial parameters during the decoupling process, thereby solving the technical problem of how to accurately estimate the channel RF gain in a multipath environment to improve the correction accuracy of the channel RF gain.

[0176] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions for causing a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present invention.

[0177] In an embodiment of the present invention, a base station correction system is further provided for implementing the above embodiments and preferred implementation manners, and those that have been described will not be repeated. As used hereinafter, the term "module" can be a combination of software and / or hardware that can implement a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0178] Figure 3 is a structural block diagram of a base station correction system 300 according to an embodiment of the present invention, as Figure 3As shown in the figure, the system includes: an acquisition module 301, configured to acquire a first received signal and a second received signal received by a base station, where the first received signal does not include a calibration signal sent by a test terminal, and the second received signal includes the calibration signal sent by the test terminal; a first determination module 302, configured to determine an estimated value of the radio frequency gain amplitude according to the first received signal; a second determination module 303, configured to determine an estimated value of the radio frequency gain phase according to the first received signal, the estimated value of the radio frequency gain amplitude, and the second received signal; and a calibration module 304, configured to calibrate the base station according to the estimated value of the radio frequency gain amplitude and the estimated value of the radio frequency gain phase.

[0179] Optionally, the first determination module 302 is further configured to: determine a first covariance matrix corresponding to the first received signal according to the first received signal; determine a first covariance estimation matrix according to a plurality of first received signals; and determine the estimated value of the radio frequency gain amplitude according to the first covariance matrix and the first covariance estimation matrix.

[0180] Optionally, the first determination module 302 is further configured to: determine an expression for estimating the radio frequency gain amplitude according to the first covariance matrix; and determine the estimated value of the radio frequency gain amplitude according to the first covariance estimation matrix and the expression for estimating the radio frequency gain amplitude.

[0181] Optionally, the first determination module 302 is further configured to: sequentially substitute the diagonal element values in the first covariance estimation matrix into the expression for estimating the radio frequency gain amplitude to obtain the estimated value of the radio frequency gain amplitude, where the estimated value of the radio frequency gain amplitude includes a plurality of sub-estimated values of the radio frequency gain amplitude.

[0182] Optionally, the second determination module 303 is further configured to: determine a first covariance matrix corresponding to the first received signal according to the first received signal; determine a second covariance matrix corresponding to the second received signal according to the second received signal; determine a first covariance estimation matrix according to a plurality of first received signals; determine a second covariance estimation matrix according to a plurality of second received signals; determine a third covariance estimation matrix according to the first covariance matrix, the second covariance matrix, the first covariance estimation matrix, and the second covariance estimation matrix; and determine the estimated value of the radio frequency gain phase according to the third covariance estimation matrix and the estimated value of the radio frequency gain amplitude.

[0183] Optionally, the second determination module 303 is further configured to: determine an expression for the third covariance matrix according to the first covariance matrix and the second covariance matrix; determine an expression for the third covariance estimation matrix according to the expression for the third covariance matrix; and substitute the first covariance estimation matrix and the second covariance estimation matrix into the expression for the third covariance estimation matrix to determine the third covariance estimation matrix.

[0184] Optionally, the second determination module 303 is further configured to: perform eigenvalue decomposition on the third covariance estimation matrix to obtain a fourth matrix; perform spectral peak search on the first spectral function to obtain an arrival angle estimation value, where the first spectral function is constructed based on the fourth matrix; determine the radio frequency gain phase estimation value according to the arrival angle estimation value, the radio frequency gain amplitude estimation value, and a preset cost function expression.

[0185] Optionally, the second determination module 303 is further configured to: within a preset range, perform spectral peak search on the first spectral function to determine a preset number of peaks of the first spectral function, so as to obtain an arrival angle estimation value, where the preset number is determined based on the number of multipaths of the channel.

[0186] Optionally, the second determination module 303 is further configured to: substitute the arrival angle estimation value and the radio frequency gain amplitude estimation value into the preset cost function expression to obtain a target cost function expression; use a preset algorithm to perform iterative minimization on the target cost function expression to obtain the radio frequency gain phase estimation value.

[0187] An embodiment of the present invention further provides an electronic device, including: a memory storing an executable program; a processor configured to run the executable program, where when the executable program runs, it executes the base station calibration method described in any of the above embodiments.

[0188] Optionally, in this embodiment, the processor in the above electronic device may be configured to run the executable program to execute the following steps:

[0189] Step S101, obtain a first received signal and a second received signal received by the base station, where the first received signal does not include the calibration signal sent by the test terminal, and the second received signal includes the calibration signal sent by the test terminal.

[0190] Step S102, determine a radio frequency gain amplitude estimation value according to the first received signal.

[0191] Step S103, determine a radio frequency gain phase estimation value according to the first received signal, the radio frequency gain amplitude estimation value, and the second received signal.

[0192] Step S104, calibrate the base station according to the radio frequency gain amplitude estimation value and the radio frequency gain phase estimation value.

[0193] Optionally, the processor in the above electronic device may be configured to run the executable program to execute the following steps: determine a first covariance matrix corresponding to the first received signal according to the first received signal; determine a first covariance estimation matrix according to a plurality of first received signals, where the first test signal set includes a plurality of first received signals; determine the radio frequency gain amplitude estimation value according to the first covariance matrix and the first covariance estimation matrix.

[0194] Optionally, the processor in the above electronic device can be set to run an executable program to perform the following steps: determine a radio frequency gain amplitude estimation expression according to the first covariance matrix; determine a radio frequency gain amplitude estimation value according to the first covariance estimation matrix and the radio frequency gain amplitude estimation expression.

[0195] Optionally, the processor in the above electronic device can be set to run an executable program to perform the following steps: sequentially substitute the diagonal element values in the first covariance estimation matrix into the radio frequency gain amplitude estimation expression to obtain a radio frequency gain amplitude estimation value, where the radio frequency gain amplitude estimation value includes multiple radio frequency gain amplitude estimation sub-values.

[0196] Optionally, the processor in the above electronic device can be set to run an executable program to perform the following steps: determine a first covariance matrix corresponding to the first received signal according to the first received signal; determine a second covariance matrix corresponding to the second received signal according to the second received signal; determine a first covariance estimation matrix according to multiple first received signals; determine a second covariance estimation matrix according to multiple second received signals; determine a third covariance estimation matrix according to the first covariance matrix, the second covariance matrix, the first covariance estimation matrix, and the second covariance estimation matrix; determine a radio frequency gain phase estimation value according to the third covariance estimation matrix and the radio frequency gain amplitude estimation value.

[0197] Optionally, the processor in the above electronic device can be set to run an executable program to perform the following steps: determine a third covariance matrix expression according to the first covariance matrix and the second covariance matrix; determine a third covariance estimation matrix expression according to the third covariance matrix expression; substitute the first covariance estimation matrix and the second covariance estimation matrix into the third covariance estimation matrix expression to determine the third covariance estimation matrix.

[0198] Optionally, the processor in the above electronic device can be set to run an executable program to perform the following steps: perform eigenvalue decomposition on the third covariance estimation matrix to obtain a fourth matrix; perform spectral peak search on the first spectral function to obtain an arrival angle estimation value, where the first spectral function is constructed based on the fourth matrix; determine a radio frequency gain phase estimation value according to the arrival angle estimation value, the radio frequency gain amplitude estimation value, and a preset cost function expression.

[0199] Optionally, the processor in the above electronic device can be set to run an executable program to perform the following steps: perform spectral peak search on the first spectral function within a preset range to determine a preset number of peaks of the first spectral function to obtain an arrival angle estimation value, where the preset number is determined based on the number of multipaths of the channel.

[0200] Optionally, the processor in the above electronic device may be configured to run an executable program to perform the following steps: substituting the angle-of-arrival estimate value and the radio frequency gain amplitude estimate value into a preset cost function expression to obtain a target cost function expression; using a preset algorithm to perform iterative minimization on the target cost function expression to obtain the radio frequency gain phase estimate value.

[0201] An embodiment of the present invention further provides a computer program product, including a computer program, where the computer program, when executed by a processor, implements the base station calibration method described in any one of the above embodiments.

[0202] Optionally, in this embodiment, when the above computer program is executed by a processor, the following steps are implemented:

[0203] Step S101: Obtain a first received signal and a second received signal received by the base station, where the first received signal does not include a calibration signal sent by a test terminal, and the second received signal includes a calibration signal sent by the test terminal.

[0204] Step S102: Determine a radio frequency gain amplitude estimate value according to the first received signal.

[0205] Step S103: Determine a radio frequency gain phase estimate value according to the first received signal, the radio frequency gain amplitude estimate value, and the second received signal.

[0206] Step S104: Calibrate the base station according to the radio frequency gain amplitude estimate value and the radio frequency gain phase estimate value.

[0207] Optionally, when the above computer program is executed by a processor, the following steps are implemented: determining a first covariance matrix corresponding to the first received signal according to the first received signal; determining a first covariance estimation matrix according to a plurality of first received signals; determining a radio frequency gain amplitude estimate value according to the first covariance matrix and the first covariance estimation matrix.

[0208] Optionally, when the above computer program is executed by a processor, the following steps are implemented: determining a radio frequency gain amplitude estimation expression according to the first covariance matrix; determining a radio frequency gain amplitude estimate value according to the first covariance estimation matrix and the radio frequency gain amplitude estimation expression.

[0209] Optionally, when the above computer program is executed by a processor, the following steps are implemented: sequentially substituting the diagonal element values in the first covariance estimation matrix into the radio frequency gain amplitude estimation expression to obtain a radio frequency gain amplitude estimate value, where the radio frequency gain amplitude estimate value includes a plurality of radio frequency gain amplitude estimation sub-values.

[0210] Optionally, when the above computer program is executed by a processor, the following steps are implemented: determining a first covariance matrix corresponding to the first received signal according to the first received signal; determining a second covariance matrix corresponding to the second received signal according to the second received signal; determining a first covariance estimation matrix according to a plurality of first received signals; determining a second covariance estimation matrix according to a plurality of second received signals; determining a third covariance estimation matrix according to the first covariance matrix, the second covariance matrix, the first covariance estimation matrix, and the second covariance estimation matrix; and determining a radio frequency gain phase estimation value according to the third covariance estimation matrix and the radio frequency gain amplitude estimation value.

[0211] Optionally, when the above computer program is executed by a processor, the following steps are implemented: determining an expression of a third covariance matrix according to the first covariance matrix and the second covariance matrix; determining an expression of a third covariance estimation matrix according to the expression of the third covariance matrix; and substituting the first covariance estimation matrix and the second covariance estimation matrix into the expression of the third covariance estimation matrix to determine the third covariance estimation matrix.

[0212] Optionally, when the above computer program is executed by a processor, the following steps are implemented: performing eigenvalue decomposition on the third covariance estimation matrix to obtain a fourth matrix; performing a spectral peak search on a first spectral function to obtain an arrival angle estimation value, where the first spectral function is constructed based on the fourth matrix; and determining a radio frequency gain phase estimation value according to the arrival angle estimation value, the radio frequency gain amplitude estimation value, and a preset cost function expression.

[0213] Optionally, when the above computer program is executed by a processor, the following steps are implemented: performing a spectral peak search on the first spectral function within a preset range to determine a preset number of peaks of the first spectral function, and obtaining an arrival angle estimation value, where the preset number is determined based on the number of multipaths of the channel.

[0214] Optionally, when the above computer program is executed by a processor, the following steps are implemented: substituting the arrival angle estimation value and the radio frequency gain amplitude estimation value into the preset cost function expression to obtain a target cost function expression; and using a preset algorithm to perform iterative minimization on the target cost function expression to obtain a radio frequency gain phase estimation value.

[0215] An embodiment of the present invention further provides a computer-readable storage medium. The computer-readable storage medium includes a stored executable program. When the executable program runs, it controls a device where the computer-readable storage medium is located to execute the base station calibration method described in any one of the above embodiments.

[0216] Optionally, in this embodiment, the above executable program may be set to store an executable program for performing the following steps:

[0217] Step S101: Obtain a first received signal and a second received signal received by the base station. Among them, the first received signal does not include the calibration signal sent by the test terminal, and the second received signal includes the calibration signal sent by the test terminal.

[0218] Step S102: Determine an estimated value of the RF gain amplitude according to the first received signal.

[0219] Step S103: Determine an estimated value of the RF gain phase according to the first received signal, the estimated value of the RF gain amplitude, and the second received signal.

[0220] Step S104: Calibrate the base station according to the estimated value of the RF gain amplitude and the estimated value of the RF gain phase.

[0221] Optionally, the above executable program can be set to store an executable program for performing the following steps: Determine a first covariance matrix corresponding to the first received signal according to the first received signal; Determine a first covariance estimation matrix according to multiple first received signals; Determine an estimated value of the RF gain amplitude according to the first covariance matrix and the first covariance estimation matrix.

[0222] Optionally, the above executable program can be set to store an executable program for performing the following steps: Determine an expression for estimating the RF gain amplitude according to the first covariance matrix; Determine an estimated value of the RF gain amplitude according to the first covariance estimation matrix and the expression for estimating the RF gain amplitude.

[0223] Optionally, the above executable program can be set to store an executable program for performing the following steps: Substitute the diagonal element values in the first covariance estimation matrix into the expression for estimating the RF gain amplitude in turn to obtain an estimated value of the RF gain amplitude, where the estimated value of the RF gain amplitude includes multiple sub-estimated values of the RF gain amplitude.

[0224] Optionally, the above executable program can be set to store an executable program for performing the following steps: Determine a first covariance matrix corresponding to the first received signal according to the first received signal; Determine a second covariance matrix corresponding to the second received signal according to the second received signal; Determine a first covariance estimation matrix according to multiple first received signals; Determine a second covariance estimation matrix according to multiple second received signals; Determine a third covariance estimation matrix according to the first covariance matrix, the second covariance matrix, the first covariance estimation matrix, and the second covariance estimation matrix; Determine an estimated value of the RF gain phase according to the third covariance estimation matrix and the estimated value of the RF gain amplitude.

[0225] Optionally, the above executable program can be set to store an executable program for performing the following steps: determining an expression of a third covariance matrix according to a first covariance matrix and a second covariance matrix; determining an expression of a third covariance estimation matrix according to the expression of the third covariance matrix; substituting the first covariance estimation matrix and the second covariance estimation matrix into the expression of the third covariance estimation matrix to determine the third covariance estimation matrix.

[0226] Optionally, the above executable program can be set to store an executable program for performing the following steps: performing eigenvalue decomposition on the third covariance estimation matrix to obtain a fourth matrix; performing spectral peak search on a first spectral function to obtain an arrival angle estimation value, where the first spectral function is constructed based on the fourth matrix; determining a radio frequency gain phase estimation value according to the arrival angle estimation value, a radio frequency gain amplitude estimation value, and a preset cost function expression.

[0227] Optionally, the above executable program can be set to store an executable program for performing the following steps: performing spectral peak search on the first spectral function within a preset range to determine a preset number of peaks of the first spectral function to obtain an arrival angle estimation value, where the preset number is determined based on the number of multipaths of the channel.

[0228] Optionally, the above executable program can be set to store an executable program for performing the following steps: substituting the arrival angle estimation value and the radio frequency gain amplitude estimation value into the preset cost function expression to obtain a target cost function expression; using a preset algorithm to perform iterative minimization solution on the target cost function expression to obtain a radio frequency gain phase estimation value.

[0229] Optionally, specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and will not be elaborated herein.

[0230] In the above embodiments of the present invention, the descriptions of the respective embodiments have their own emphases. For parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0231] In some embodiments provided by the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the system embodiments described above are merely illustrative. For example, the division of units can be a logical function division. In actual implementation, there may be other division methods. 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 displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of units or modules can be in electrical or other forms.

[0232] The unit described as a separation component may or may not be physically separated, and the component shown as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed over multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0233] In addition, each functional unit in various embodiments of the present invention can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0234] If the integrated unit 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 such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), mobile hard disks, magnetic disks, or optical discs, etc., which can store program codes.

[0235] The above is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A base station calibration method, characterized in that, Including: Obtain a first received signal and a second received signal received by a base station, where the first received signal does not include a calibration signal sent by a test terminal, and the second received signal includes the calibration signal sent by the test terminal; Determine an estimated value of the RF gain amplitude according to the first received signal; Determine an estimated value of the RF gain phase according to the first received signal, the estimated value of the RF gain amplitude, and the second received signal; Calibrate the base station according to the estimated value of the RF gain amplitude and the estimated value of the RF gain phase.

2. The base station calibration method according to claim 1, wherein The determining the estimated value of the RF gain amplitude according to the first received signal includes: Determine a first covariance matrix corresponding to the first received signal according to the first received signal; Determine a first covariance estimation matrix according to multiple first received signals; Determine the estimated value of the RF gain amplitude according to the first covariance matrix and the first covariance estimation matrix.

3. The base station calibration method according to claim 2, wherein The determining the estimated value of the RF gain amplitude according to the first covariance matrix and the first covariance estimation matrix includes: Determine an expression for estimating the RF gain amplitude according to the first covariance matrix; Determine the estimated value of the RF gain amplitude according to the first covariance estimation matrix and the expression for estimating the RF gain amplitude.

4. The base station calibration method according to claim 3, wherein, The determining the estimated value of the RF gain amplitude according to the first covariance estimation matrix and the expression for estimating the RF gain amplitude includes: Substitute the diagonal element values in the first covariance estimation matrix into the expression for estimating the RF gain amplitude in turn to obtain the estimated value of the RF gain amplitude, where the estimated value of the RF gain amplitude includes multiple sub - estimated values of the RF gain amplitude.

5. The base station calibration method according to claim 1, characterized in that The determining the estimated value of the RF gain phase according to the first received signal, the estimated value of the RF gain amplitude, and the second received signal includes: Determine a first covariance matrix corresponding to the first received signal according to the first received signal; Determine a second covariance matrix corresponding to the second received signal according to the second received signal; Determine a first covariance estimation matrix according to multiple first received signals; Determine a second covariance estimation matrix according to multiple second received signals; Determine a third covariance estimation matrix according to the first covariance matrix, the second covariance matrix, the first covariance estimation matrix, and the second covariance estimation matrix; Determine the estimated value of the RF gain phase according to the third covariance estimation matrix and the estimated value of the RF gain amplitude.

6. The base station calibration method according to claim 5, wherein The determining the third covariance estimation matrix according to the first covariance matrix, the second covariance matrix, the first covariance estimation matrix, and the second covariance estimation matrix includes: Determine an expression for the third covariance matrix according to the first covariance matrix and the second covariance matrix; Determine an expression for the third covariance estimation matrix according to the expression for the third covariance matrix; Substitute the first covariance estimation matrix and the second covariance estimation matrix into the expression for the third covariance estimation matrix to determine the third covariance estimation matrix.

7. The base station calibration method according to claim 5, characterized in that Determining the radio frequency gain phase estimation value according to the third covariance estimation matrix and the radio frequency gain amplitude estimation value includes: Performing eigenvalue decomposition on the third covariance estimation matrix to obtain a fourth matrix; Performing a spectral peak search on a first spectral function to obtain an arrival angle estimation value, where the first spectral function is constructed based on the fourth matrix; Determining the radio frequency gain phase estimation value according to the arrival angle estimation value, the radio frequency gain amplitude estimation value, and a preset cost function expression.

8. The base station calibration method according to claim 7, wherein, The performing a spectral peak search on a first spectral function to obtain an arrival angle estimation value includes: Performing a spectral peak search on the first spectral function within a preset range to determine a preset number of peaks of the first spectral function, and obtaining the arrival angle estimation value, where the preset number is determined based on the number of multipaths of the channel.

9. The base station calibration method according to claim 7, wherein The determining the radio frequency gain phase estimation value according to the arrival angle estimation value, the radio frequency gain amplitude estimation value, and a preset cost function expression includes: Substituting the arrival angle estimation value and the radio frequency gain amplitude estimation value into the preset cost function expression to obtain a target cost function expression; Using a preset algorithm to perform iterative minimization on the target cost function expression to obtain the radio frequency gain phase estimation value.

10. An electronic device, characterized in that, including: A memory storing an executable program; A processor for running the executable program, where when the executable program runs, it executes the method according to any one of claims 1 to 9.

11. A computer program product, characterized in that, Including a computer program, where when the computer program is executed by a processor, it implements the method according to any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, where when the executable program runs, it controls the device where the computer-readable storage medium is located to execute the method according to any one of claims 1 to 9.

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