Channel measurement method, device, electronic device and computer-readable storage medium

Abstract

The present application relates to a channel measurement method, device, computer equipment, storage medium and computer program product. The method includes: obtaining initial channel estimation parameters in the current measurement period, determining initial channel characteristic values ​​based on the initial channel estimation parameters; determining the network connection status of the terminal device in the current measurement period; determining a target filtering mode from a set of filtering modes according to the initial channel characteristic values ​​and the network connection status; the set of filtering modes includes at least a first filtering mode and a second filtering mode, and the power consumption required by the second filtering mode is less than the power consumption required by the first filtering mode; filtering the initial channel estimation parameters using the target filtering mode to obtain target channel estimation parameters; determining the target measurement values ​​of each channel measurement indicator in the current measurement period based on the target channel estimation parameters. The use of this method can reduce the system power consumption when the terminal device is measuring.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a channel measurement method, device, electronic device, computer-readable storage medium, and computer program product. Background Art

[0002] With the development of communication technology, wireless communication technology has emerged. In wireless communication technology, the channel environment changes complexly. The quality of the channel directly affects the communication performance. Measuring and reporting the channel through terminal equipment plays a very important role in cell selection and reselection, connection state switching, network planning and optimization. In order to accurately reflect the channel environment, it is necessary to improve the measurement accuracy.

[0003] However, in the process of measuring the channel, the traditional method often has the problem of high power consumption of the terminal device. Summary of the invention

[0004] Embodiments of the present application provide a channel measurement method, apparatus, electronic device, computer-readable storage medium, and computer program product, which can reduce system power consumption of terminal devices.

[0005] On the one hand, the present application provides a channel measurement method. The method includes: obtaining initial channel estimation parameters in the current measurement period, determining initial channel characteristic values ​​based on the initial channel estimation parameters; determining the network connection status of the terminal device in the current measurement period; determining a target filtering mode from a set of filtering modes according to the initial channel characteristic values ​​and the network connection status; the set of filtering modes includes at least a first filtering mode and a second filtering mode, and the power consumption required by the second filtering mode is less than the power consumption required by the first filtering mode; filtering the initial channel estimation parameters using the target filtering mode to obtain target channel estimation parameters; determining the target measurement values ​​of each channel measurement indicator in the current measurement period based on the target channel estimation parameters.

[0006] On the other hand, the present application also provides a channel measurement device. The device includes: a characteristic value determination module, which is used to obtain the initial channel estimation parameters in the current measurement period, and determine the initial channel characteristic values ​​based on the initial channel estimation parameters; a connection status determination module, which is used to determine the network connection status of the terminal device in the current measurement period; a filtering mode determination module, which is used to determine the target filtering mode from the filtering mode set according to the initial channel characteristic value and the network connection status; the filtering mode set includes at least a first filtering mode and a second filtering mode, and the power consumption required by the second filtering mode is less than the power consumption required by the first filtering mode; a filtering processing module, which is used to filter the initial channel estimation parameters using a target filtering mode to obtain target channel estimation parameters; a measurement value determination module, which is used to determine the target measurement value of each channel measurement indicator in the current measurement period based on the target channel estimation parameters.

[0007] On the other hand, the present application further provides an electronic device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above channel measurement method when executing the computer program.

[0008] On the other hand, the present application further provides a computer-readable storage medium, wherein a computer program is stored thereon, and when the computer program is executed by a processor, the steps of the above-mentioned channel measurement method are implemented.

[0009] On the other hand, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned channel measurement method are implemented.

[0010] The above-mentioned channel measurement method, device, electronic device, computer-readable storage medium and computer program product obtain the initial channel estimation parameters in the current measurement period, determine the initial channel characteristic value based on the initial channel estimation parameters, further determine the network connection status of the terminal device in the current measurement period, determine the target filtering mode from the filtering mode set according to the initial channel characteristic value and the network connection status, and use the target filtering mode to filter the initial channel estimation parameters to obtain the target channel estimation parameters. Since the target filtering mode can be adaptively selected from the filtering mode set according to the initial channel characteristic value and the network connection status, and the filtering mode set includes at least the first filtering mode and the second filtering mode, and the power consumption required by the second filtering mode is less than the power consumption required by the first filtering mode, it is avoided to uniformly use a high-power filtering mode for filtering, thereby reducing the system power consumption when the terminal device is measured. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0012] Figure 1 A diagram showing an application environment of a channel measurement method in an embodiment;

[0013] Figure 2 is a flow chart of a channel measurement method in one embodiment;

[0014] Figure 3 is a flow chart of a channel measurement method in a specific embodiment;

[0015] Figure 4 A schematic diagram of a specific flow of a judgment module in an embodiment;

[0016] Figure 5 is a structural block diagram of a channel measurement device in one embodiment;

[0017] Figure 6 FIG. 4 is a diagram showing the internal structure of an electronic device in one embodiment. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0019] At present, for the measurement of terminal equipment (UE), while meeting the basic requirements defined by the protocol, further consideration is generally given to improving the measurement accuracy. However, the improvement of measurement accuracy means the increase of complexity, and the increase of complexity will inevitably bring some negative effects, such as power consumption overhead. For complex channel environments and even real scenarios, the protocol does not have a clear definition. In order to ensure the coverage of the terminal in various scenarios, improving the measurement accuracy becomes the primary goal. However, if the scenarios are not distinguished and only the measurement accuracy is maintained, the power consumption problem will be very prominent in some scenarios, becoming a defect in evaluating a system solution. Therefore, for measurement, it is necessary to systematically consider the problem from the aspects of measurement accuracy and power consumption, and achieve a system balance on the basis of meeting the standards defined by the protocol. Based on this, the present application proposes a channel measurement method that can realize adaptive measurement, while taking into account the measurement accuracy requirements, reducing the system power consumption as much as possible.

[0020] The channel measurement method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. The terminal device 102 communicates with the network device 104 through the network. The terminal device 102 (Terminal Equipment) may also be referred to as User Equipment (UE), and the terminal device may be various mobile devices, such as a mobile phone (or "cellular" phone), a computer with a mobile terminal, etc., or a portable, pocket-sized, handheld, computer-built-in or vehicle-mounted mobile device. The network device may be a device for communicating with the user equipment, such as a base station (Base Transceiver Station, referred to as "BTS") in a GSM system or CDMA, a base station (NodeB, referred to as "NB") in a WCDMA system, or an evolved base station (Evolutional Node B, referred to as "eNB" or "eNodeB") in an LTE system. The present application does not limit the terminal device and the network device.

[0021] Specifically, the terminal device 102 obtains the initial channel estimation parameters in the current measurement period, determines the initial channel characteristic values ​​based on the initial channel estimation parameters, determines the network connection status of the terminal device in the current measurement period, and determines the target filtering mode from the filtering mode set according to the initial channel characteristic values ​​and the network connection status. The filtering mode set includes at least a first filtering mode and a second filtering mode, and the power consumption required by the second filtering mode is less than the power consumption required by the first filtering mode. The initial channel estimation parameters are filtered using the target filtering mode to obtain the target channel estimation parameters. Based on the target channel estimation parameters, the target measurement values ​​of each channel measurement indicator in the current measurement period are determined. The terminal device 102 can further report the target measurement values ​​to the network device 104.

[0022] In one embodiment, Figure 2 As shown, a channel measurement method is provided, which is applied to Figure 1 The terminal device in the example is used to illustrate, including the following steps:

[0023] Step 202: Acquire initial channel estimation parameters in the current measurement period, and determine initial channel characteristic values ​​based on the initial channel estimation parameters.

[0024] The initial channel estimation parameters are obtained based on the reference signal in the received signal in the current measurement period, the received signal may carry a data signal and multiple reference signals, and the reference signal may include DMRS and / or PTRS. The initial channel characteristic value is used to preliminarily characterize the characteristics of the channel, and the initial channel characteristic value may include one or more of the signal-to-noise ratio (SNR), delay spread, Doppler spread, reference signal receiving power (RSRP) and reference signal receiving quality (RSRQ).

[0025] Specifically, the terminal device first performs preprocessing such as removing the cyclic prefix on the time domain signal received in the current measurement period, and then performs Fourier transform to convert the time domain signal into a frequency domain signal to obtain a received signal, and performs channel estimation based on each reference signal in the received signal to obtain the initial channel estimation parameters corresponding to each reference signal, and then the initial channel eigenvalue can be determined based on the initial channel estimation parameters. Here, the Fourier transform can be a discrete Fourier transform (DFT, DFT), a fast Fourier transform (FFT, FFT), etc., and the embodiments of the present application are not limited to this.

[0026] In one embodiment, after obtaining the initial channel estimation parameters corresponding to each reference signal, the terminal device can obtain the SNR value corresponding to each reference signal based on the initial channel estimation parameters corresponding to each reference signal, calculate the average value of each SNR value to obtain the initial SNR value, and then select the filtering method based on the initial SNR value.

[0027] Step 204: Determine the network connection status of the terminal device in the current measurement period.

[0028] Among them, the network connection state includes a connection state (CONNECT STATE), an idle state (Idle State) and a discontinuous reception state (CDRX STATE) under the connection state, wherein the connection state refers to the state in which the terminal device establishes a network connection with the network device, the idle state refers to the state in which the terminal device does not establish a network connection with the network device, and the discontinuous reception state of the connection state refers to the state in which the terminal device establishes a network connection with the network device but does not continuously receive signals.

[0029] Specifically, the terminal may determine its own network connection state in the current measurement period, and further determine the filtering mode according to its own network connection state.

[0030] Step 206, determining a target filtering mode from a set of filtering modes according to the initial channel characteristic value and the network connection status, wherein the set of filtering modes includes at least a first filtering mode and a second filtering mode, and the power consumption required by the second filtering mode is less than the power consumption required by the first filtering mode.

[0031] Among them, the filtering method set includes at least a first filtering method and a second filtering method, the first filtering method and the second filtering method are different filtering methods, and the first filtering method and the second filtering method can both be used to filter the channel estimation parameters to improve the performance of noise estimation. The computational complexity of the first filtering method is greater than that of the second filtering method, so the power consumption required by the second filtering method is less than that required by the first filtering method.

[0032] Specifically, in order to cover complex real channel scenarios, especially the performance at both ends of high and low signal-to-noise ratios, it becomes very necessary to further add channel filtering processing after the initial channel estimation in the frequency domain. This filtering will improve the performance of noise estimation. In the embodiment of the present application, considering that the measurement results have different sensitivities to the channel estimation parameters in different channel scenarios, the terminal device can identify the channel scenario based on the initial channel characteristic value and the network connection status to obtain a scene recognition result, and determine the target filtering method from the filtering method set based on the scene recognition result.

[0033] In one embodiment, the first filtering method may be to perform frequency domain denoising or time domain denoising on the initial channel estimation parameters. In one embodiment, the second filtering method may be to perform average filtering on the initial channel estimation parameters.

[0034] Step 208: filter the initial channel estimation parameters using a target filtering method to obtain target channel estimation parameters.

[0035] Specifically, the terminal device may filter the initial channel estimation parameters using a target filtering method to obtain target channel estimation parameters.

[0036] Step 210: Determine target measurement values ​​of various channel measurement indicators in the current measurement period based on target channel estimation parameters.

[0037] Among them, the channel measurement index can be determined according to the measurement configuration information of the mobile terminal. In one embodiment, the channel measurement index may include one or more of the signal-to-noise ratio SNR, the reference signal received power RSRP and the reference signal received quality RSRQ.

[0038] Specifically, since the target channel estimation parameters are obtained through filtering, the terminal can determine the target measurement values ​​of each channel measurement indicator in the previous measurement period based on the target channel estimation parameters. Further, the terminal device can report the obtained target measurement values ​​to the network device.

[0039] In the above-mentioned channel estimation method, by obtaining the initial channel estimation parameters in the current measurement period, the initial channel characteristic values ​​are determined based on the initial channel estimation parameters, and the network connection status of the terminal device in the current measurement period is further determined. According to the initial channel characteristic values ​​and the network connection status, the target filtering mode is determined from the filtering mode set, and the initial channel estimation parameters are filtered using the target filtering mode to obtain the target channel estimation parameters. Since the target filtering mode can be adaptively selected from the filtering mode set according to the initial channel characteristic values ​​and the network connection status, and the filtering mode set includes at least the first filtering mode and the second filtering mode, and the power consumption required by the second filtering mode is less than the power consumption required by the first filtering mode, it is avoided to uniformly use a high-power filtering mode for filtering, thereby reducing the system power consumption when the terminal device is measured.

[0040] In one embodiment, a target filtering mode is determined from a set of filtering modes according to initial channel characteristic values ​​and network connection status, including: identifying a channel scene according to the initial channel characteristic values ​​and network connection status to obtain a scene recognition result; and determining a target filtering mode from a set of filtering modes based on the scene recognition result.

[0041] The channel scenario refers to a scenario divided according to channel characteristic values. For example, the channel scenario can be divided into a first channel scenario in a high and low signal-to-noise ratio area and a second channel scenario in a medium signal-to-noise ratio area according to the signal-to-noise ratio.

[0042] Specifically, considering that different channel scenarios have different sensitivities to channel estimation parameters, in some channel scenarios, the measurement results are more sensitive to the channel estimation parameters, requiring the channel estimation parameters to be more accurate, while in some channel scenarios, the measurement results are less sensitive to the channel estimation parameters. The mobile terminal can identify the channel scenario based on the initial channel characteristic value and the network connection status to identify the first channel scenario in which the measurement results are more sensitive to the channel estimation parameters and the second channel scenario in which the measurement results are less sensitive to the channel estimation parameters. If the first channel scenario is identified, the first filtering method is selected as the target filtering method. Since the power consumption required by the first filtering method is greater than the power consumption required by the second filtering method, the first filtering method can implement more complex filtering calculations to achieve more accurate filtering, so that better measurement performance can be achieved in the first channel scenario.

[0043] If the second channel scenario is identified, the second filtering method is selected as the target filtering method. Since the measurement results in the second channel scenario are not very sensitive to the channel estimation parameters, a simpler filtering method can be used to implement filtering, and measurement results comparable to the measurement performance of the complex filtering method can be obtained.

[0044] In the above embodiment, the channel scene is identified according to the initial channel characteristic value and the network connection status to obtain a scene identification result, and the target filtering method is determined from the filtering method set based on the scene identification result, so that an adaptive measurement algorithm can be adopted according to the channel scene. Under the premise of ensuring the measurement accuracy, the power consumption problem caused by the additional complexity can be effectively reduced, avoiding the negative effects of simply improving the measurement accuracy or simply reducing the complexity to reduce the power consumption.

[0045] In one embodiment, initial channel estimation parameters within a current measurement cycle are obtained, and initial channel characteristic values ​​are determined based on the initial channel estimation parameters, including: obtaining initial channel estimation parameters within a current measurement cycle, and determining initial signal-to-noise ratio values ​​based on the initial channel estimation parameters; identifying a channel scenario according to the initial channel characteristic values ​​and a network connection state, and obtaining a scenario identification result, including: if the network connection state is a connected state, and the initial signal-to-noise ratio value satisfies a first judgment condition, then identifying the channel scenario as a second channel scenario; determining a target filtering method from a set of filtering methods based on the scenario identification result, including: selecting a second filtering method from the set of filtering methods as the target filtering method.

[0046] The first decision condition is used to indicate that the initial signal-to-noise ratio value is greater than the first signal-to-noise ratio threshold value and less than the second signal-to-noise ratio threshold value. The first signal-to-noise ratio threshold value and the second signal-to-noise ratio threshold value can be set according to actual needs.

[0047] Specifically, in this embodiment, the terminal device is in a connected state. After obtaining the initial channel estimation parameters, the terminal device can determine the initial signal-to-noise ratio value based on the initial channel estimation parameters, and judge whether the initial signal-to-noise ratio value satisfies the first judgment condition. If so, the channel scenario is identified as the second channel scenario. In the second channel scenario, the measurement result is less sensitive to the channel estimation parameters, and a simpler filtering method can be used to reduce the system power consumption of the terminal. Therefore, the terminal device can select the second filtering method from the filtering method set as the target filtering method.

[0048] In one embodiment, the channel scene is identified according to the initial channel characteristic value and the network connection status to obtain a scene identification result, which also includes: if the network connection status is a connected state and the initial signal-to-noise ratio value does not meet the first judgment condition, then the channel scene is identified as a first channel scene; based on the scene identification result, a target filtering method is determined from a set of filtering methods, including: selecting a first filtering method from the set of filtering methods as the target filtering method.

[0049] Specifically, when the initial signal-to-noise ratio value is less than the first signal-to-noise ratio threshold value or greater than the second signal-to-noise ratio threshold value, the terminal device can determine that the initial signal-to-noise ratio value does not meet the first judgment condition. At this time, if the network connection state of the terminal device is connected, it can be identified that the channel scenario is the first channel scenario. In the first channel scenario, the measurement result is more sensitive to the channel estimation parameters. In order to ensure the measurement performance, the terminal device can select the first filtering method from the filtering method set as the target filtering method to filter the initial channel estimation parameters more accurately.

[0050] It is understandable that in other embodiments, in order to better ensure the measurement performance, multiple different initial channel characteristic values ​​may be considered when identifying the channel scene, for example, the channel scene may be further identified in combination with parameters such as the Doppler spread and delay spread of the channel. Based on this, the present application further proposes the following embodiments.

[0051] In one embodiment, initial channel estimation parameters in a current measurement cycle are obtained, and initial channel characteristic values ​​are determined based on the initial channel estimation parameters, including: obtaining initial channel estimation parameters in a current measurement cycle, and determining initial signal-to-noise ratio values ​​and Doppler spread of a channel based on the initial channel estimation parameters; identifying a channel scenario according to the initial channel characteristic values ​​and a network connection state, and obtaining a scenario identification result, including: if the network connection state is a connected state, and the initial signal-to-noise ratio value satisfies a first judgment condition, and the Doppler spread of the channel satisfies a second judgment condition, then the channel scenario is identified as a second channel scenario; based on the scenario identification result, a target filtering method is determined from a set of filtering methods, including: selecting a second filtering method from the set of filtering methods as a target filtering method.

[0052] The second decision condition is used to indicate that the Doppler spread of the channel is less than the Doppler threshold value. The Doppler threshold value can be set according to actual needs.

[0053] Specifically, in this embodiment, the terminal device is in a connected state. After determining the initial signal-to-noise ratio value and the Doppler spread of the channel, the terminal device first determines whether the initial signal-to-noise ratio value satisfies the first judgment condition. If so, it continues to determine whether the Doppler spread of the channel is less than the Doppler threshold value. If the Doppler spread of the channel is less than the Doppler threshold value, it is determined that the Doppler spread of the channel satisfies the second judgment condition. Then, the terminal device can identify that the channel scenario is the second channel scenario. In the second channel scenario, the measurement result is less sensitive to the channel estimation parameters, and a simpler filtering method can be used to reduce the system power consumption of the terminal. Therefore, the terminal device can select the second filtering method from the filtering method set as the target filtering method.

[0054] In one embodiment, initial channel estimation parameters within a current measurement cycle are obtained, and initial channel characteristic values ​​are determined based on the initial channel estimation parameters, including: obtaining initial channel estimation parameters within a current measurement cycle, and determining initial signal-to-noise ratio values ​​and a delay spread of a channel based on the initial channel estimation parameters; identifying a channel scenario according to the initial channel characteristic values ​​and a network connection state, and obtaining a scenario identification result, including: if the network connection state is a non-connected state, and the initial signal-to-noise ratio value satisfies a first judgment condition, and the delay spread satisfies a third judgment condition, then the channel scenario is identified as a second channel scenario; determining a target filtering method from a set of filtering methods based on the scenario identification result, including: selecting a second filtering method from the set of filtering methods as a target filtering method.

[0055] Among them, the non-connected state refers to a network connection state other than the connected state, including the idle state and the discontinuous reception state under the connected state. The third decision condition is used to indicate that the delay spread of the channel is less than the delay threshold value.

[0056] Specifically, in this embodiment, the terminal device is in a non-connected state. After determining the initial signal-to-noise ratio value and the delay spread of the channel, the terminal device first determines whether the delay spread is less than the delay threshold value. If it is less than the delay threshold value, it is determined that the delay spread satisfies the third judgment condition, and continues to determine whether the initial signal-to-noise ratio value satisfies the first judgment condition. If the initial signal-to-noise ratio value satisfies the first judgment condition, the channel scenario is identified as the second channel scenario. In the second channel scenario, the measurement results are less sensitive to the channel estimation parameters, and a simpler filtering method can be used to reduce the system power consumption of the terminal. Therefore, the terminal device can select the second filtering method from the filtering method set as the target filtering method.

[0057] Further, in one embodiment, the channel scenario is identified according to the initial channel characteristic value and the network connection status to obtain a scene identification result, and also includes: if the network connection state is a non-connected state and the delay expansion does not meet the third judgment condition, then the channel scenario is identified as a first channel scenario; based on the scene identification result, a target filtering mode is determined from a set of filtering modes, including: selecting a first filtering mode from the set of filtering modes as the target filtering mode.

[0058] Specifically, when the terminal device is in a non-connected state, if it is determined that the delay spread does not meet the third judgment condition, the measurement result under the current channel scenario must be sensitive to the channel estimation parameters. At this time, there is no need to judge the initial signal-to-noise ratio value, and the channel scenario can be directly identified as the first channel scenario. The initial channel estimation parameters are filtered using the first filtering method corresponding to the first channel scenario to obtain the target channel estimation parameters, so as to obtain the target measurement values ​​of each indicator based on the target channel estimation parameters.

[0059] In this embodiment, since the delay spread of the channel is given priority, only when the delay spread satisfies the third decision condition is it further determined whether the initial signal-to-noise ratio value meets the first decision condition. When the delay spread does not meet the third decision condition, redundant judgments can be avoided, thereby improving measurement efficiency.

[0060] In one embodiment, the channel scenario is identified according to the initial channel characteristic value and the network connection status to obtain a scenario identification result, which also includes: if the network connection status is a non-connected state, and the delay spread satisfies the third judgment condition and the initial signal-to-noise ratio value does not satisfy the first judgment condition, then the channel scenario is identified as a first channel scenario; based on the scenario identification result, a target filtering method is determined from a set of filtering methods, including: selecting a first filtering method from the set of filtering methods as the target filtering method.

[0061] Specifically, when the terminal device is in a non-connected state, if it is determined that the delay spread satisfies the third decision condition, but when judging whether the initial signal-to-noise ratio value satisfies the first decision condition, it is determined that the initial signal-to-noise ratio value does not satisfy the first decision condition, then the channel scenario can be identified as the first channel scenario, and the first filtering method corresponding to the first channel scenario is adopted as the target filtering method to ensure measurement performance.

[0062] In one embodiment, the initial channel estimation parameters include initial channel estimation parameters corresponding to each reference signal, and the initial channel estimation parameters are filtered using a target filtering method to obtain the target channel estimation parameters, including: if the target filtering method is a first filtering method, the first preset method is used to perform frequency domain denoising on the initial channel estimation parameters corresponding to each reference signal; or if the target filtering method is the first filtering method, the second preset method is used to perform time domain denoising on the initial channel estimation parameters corresponding to each reference signal.

[0063] Specifically, if the target filtering method selected by the terminal device from the filtering method set is the first filtering method, the frequency domain denoising of the initial channel estimation parameters can be performed using the first preset method, and the first preset method can be, for example, the MMSE algorithm.

[0064] In other embodiments, if the target filtering method selected by the terminal device from the filtering method set is the first filtering method, the first preset method can also be used to perform time domain denoising on the initial channel estimation parameters. The second preset method can be, for example, a DFT algorithm.

[0065] In the above embodiment, by performing time domain denoising or frequency domain denoising on the initial channel estimation parameters, relatively accurate filtering can be achieved, the performance of noise estimation can be improved, and the obtained measurement result can be highly accurate.

[0066] In one embodiment, the initial channel estimation parameters include initial channel estimation parameters corresponding to each reference signal, and the initial channel estimation parameters are filtered using a target filtering method to obtain the target channel estimation parameters, including: if the target filtering method is the second filtering method, the initial channel estimation parameters corresponding to each reference signal are average filtered to obtain the target channel estimation parameters.

[0067] Specifically, if the target filtering mode selected by the terminal device from the filtering mode set is the second filtering mode, average filtering is performed on the initial channel estimation parameters corresponding to each reference signal to obtain the target channel estimation parameters.

[0068] Assume that the initial channel estimation parameters of the i-th reference signal are as follows: i and the noise part N i P i *.

[0069]

[0070] Among them, H i is the initial channel estimation parameter, Y i To receive the signal, N i For noise, is the reference signal.

[0071] Then the average filter can be further described by the following formula:

[0072]

[0073] Wherein, N is the total number of REs (resource elements), and v is the distance between REs. Specifically, if the current initial channel estimation parameter is Hi, then the initial channel estimation parameter that is v away from the current one is Hi+v.

[0074] It can be understood that after average filtering is performed using the above formula (2), the result obtained can be used as RSRP. Furthermore, SNR and RSRQ can also be obtained based on the result.

[0075] In the above embodiment, the system power consumption of the terminal device can be reduced by performing relatively simple average filtering on the initial channel estimation parameters.

[0076] In one embodiment, the above-mentioned channel measurement method also includes: statistics on the target filtering methods determined within multiple measurement cycles to obtain a first quantity statistical value corresponding to the first filtering method and a second quantity statistical value corresponding to the second filtering method; reporting the first quantity statistical value and the second quantity statistical value to the network device to instruct the network device to filter the target measurement values ​​received within multiple measurement cycles based on the first quantity statistical value and the second quantity statistical value.

[0077] Specifically, in addition to completing the switching between the first filtering mode and the second filtering mode, the terminal device needs to make statistics on the various filtering modes used in the same cell / SSB (Synchronization Signal and PBCH block) in different measurement cycles, and obtain the number of times the first filtering mode is used for filtering in multiple weeks and the number of times the second filtering mode is used for filtering, the first quantity statistical value corresponding to the first filtering mode and the second quantity statistical value corresponding to the second filtering mode. The terminal device can report the obtained statistical value to the network device, and the network device can determine the filtering weight coefficient based on the statistical value, and perform inter-cycle filtering on the reported measurement value according to the filtering weight coefficient. It can be understood that the filtering weight coefficient is positively correlated with the statistical value, that is, the larger the reported statistical value, the larger the corresponding filtering weight coefficient.

[0078] In the above embodiment, by collecting statistics on the target filtering modes determined in multiple measurement cycles and reporting the statistical values ​​to the network device, a basis can be provided for the network device to perform inter-cycle filtering, thereby further improving the measurement accuracy.

[0079] In a specific embodiment, Figure 3As shown, a channel measurement method is provided, which is described by taking the method applied to a terminal device as an example, and includes the following steps:

[0080] Step 302, after the process starts, the terminal device performs pre-measurement processing: obtains the data signal synchronized in the current measurement period from the cache, performs time domain processing, and then removes the cyclic prefix and other processing.

[0081] Step 304: Perform Fourier transform processing on the time domain signal obtained by preprocessing to obtain a frequency domain signal as a received signal.

[0082] Step 306: Perform channel estimation based on each reference signal in the received signal to obtain initial channel estimation parameters corresponding to each reference signal.

[0083] Step 308, performing parameter estimation based on the initial channel estimation parameters to obtain an initial signal-to-noise ratio value, a Doppler spread of the channel, and a time delay spread of the channel. The initial channel estimation parameters estimated in different periods change dynamically, so the initial signal-to-noise ratio value, the Doppler spread of the channel, and the time delay spread of the channel also change dynamically.

[0084] In step 310, the scene recognition module of the terminal device obtains an initial signal-to-noise ratio value, a Doppler spread of a channel, and a delay spread of a channel as dynamic recognition parameters, and obtains a current network connection state of the terminal device as a static recognition parameter.

[0085] Step 312: The decision module of the terminal device makes a decision based on the dynamic recognition parameters and the static recognition parameters obtained by the scene recognition module to select a target filtering mode from the filtering mode set.

[0086] Step 314: When the decision module determines that the channel scenario of the current measurement cycle is the first channel scenario, the initial channel estimation parameters are filtered using the first filtering method; when the decision module determines that the channel scenario of the current measurement cycle is the second channel scenario, the initial channel estimation parameters are filtered using the second filtering method. After filtering, the target channel estimation parameters can be obtained.

[0087] The first filtering method may be to use the MMSE algorithm for frequency domain denoising or to use the DFT algorithm for time domain denoising, and the second filtering method may be average filtering.

[0088] Step 316, post-measurement processing: The terminal device determines target measurement values ​​of measurement indicators such as SNR, RSRP, and RSRQ based on the target channel estimation parameters, and the measurement ends.

[0089] In one embodiment, Figure 4 As shown in the figure, it is a schematic diagram of the specific process of the judgment module. Figure 4, after the judgment starts, the specific process is as follows:

[0090] (1) If the terminal device is in the connected state, then on the basis of the measurement period specified by the protocol, if the obtained dynamic parameters meet the conditions of the intermediate channel ratio region, that is: the first signal-to-noise ratio threshold < the initial signal-to-noise ratio < the second signal-to-noise ratio threshold, continue to judge whether the Doppler spread of the channel is less than the Doppler threshold. If the Doppler spread of the channel is less than the Doppler threshold, it is judged that the channel scenario of the current measurement period is the second channel scenario. If the Doppler spread of the channel is greater than the Doppler threshold, it is judged that the channel scenario of the current measurement period is the first channel scenario; if the obtained dynamic parameters do not meet the conditions of the above intermediate channel ratio region, it is directly judged that the channel scenario of the current measurement period is the first channel scenario.

[0091] (2) If the terminal device is in the non-connected state, then in addition to the above judgment, the delay spread also needs to be considered additionally, and it is preferred to judge whether the delay spread is less than the delay threshold. If the delay spread is less than the delay threshold, then continue to judge whether it meets the conditions of the intermediate channel ratio region (that is, the first signal-to-noise ratio threshold < the initial signal-to-noise ratio < the second signal-to-noise ratio threshold). If it meets, it is judged that the channel scenario of the current measurement period is the second channel scenario. If it does not meet, it is judged that the channel scenario of the current measurement period is the first channel scenario; if it is found at the beginning when judging whether the delay spread is less than the delay threshold that the delay spread is greater than the delay threshold, then even if other conditions are met, it is still judged that the channel scenario of the current measurement period is the first channel scenario.

[0092] In the above embodiments, by using different filtering methods in different channel scenarios for filtering, the adaptive measurement of the channel is realized. On the premise of ensuring the measurement accuracy, the power consumption problem caused by additional complexity can be effectively reduced, and the negative effects caused by simply improving the measurement accuracy or simply reducing the complexity to reduce the power consumption can be avoided.

[0093] In a specific embodiment, the channel measurement method provided by the embodiments of the present application can be applied to measure the AWGN channel. When measuring the AWGN channel, for the medium SNR region (that is, the first signal-to-noise ratio threshold < SNR < the second signal-to-noise ratio threshold), although it will switch to the second filtering method according to the adaptive selection mechanism, in terms of measurement accuracy, the accuracy of the measured SNR and RSRP is basically similar to the measurement performance of the first filtering method, which is a high-precision method. Thus, it can be seen that when measuring the AWGN channel, by using the channel measurement method provided by the embodiments of the present application, by adopting the second filtering method in the medium SNR region, the system power consumption can be significantly reduced on the premise of ensuring the measurement accuracy. It can be understood that for complex fading channel scenarios, basically the same conclusion is followed as that of the AWGN.

[0094] With reference to Table 1, it can be seen that the adaptive measurement method implemented in the present application reduces computational complexity, which means that it will bring about a significant improvement in power consumption performance.

[0095] Table 1

[0096] Filtering method First filtering method Second filtering method Computational complexity 11361 7638

[0097] In summary, the present application improves the robustness of the system solution by introducing an adaptive selection mechanism. And according to different access states, Doppler spread, delay spread, while taking into account the measurement accuracy requirements, the power consumption is effectively reduced. In addition, the adaptive selection mechanism provided by the present application can also be extended to more measurement methods and decision conditions. The measurement method provided by the present application can be used in the measurement mode to reduce power consumption when the measurement requirements are met, thereby improving the robustness of the system solution.

[0098] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0099] Based on the same inventive concept, the embodiment of the present application also provides a channel measurement device for implementing the channel measurement method involved above. The implementation solution provided by the device to solve the problem is similar to the implementation solution recorded in the above method, so the specific limitations in one or more channel measurement device embodiments provided below can refer to the limitations on the channel measurement method above, and will not be repeated here.

[0100] In one embodiment, Figure 5 As shown, a channel measurement device 500 is provided, comprising:

[0101] The characteristic value determination module 502 is used to obtain the initial channel estimation parameters in the current measurement period, and determine the initial channel characteristic value based on the initial channel estimation parameters;

[0102] The connection status determination module 504 is used to determine the network connection status of the terminal device in the current measurement period;

[0103] The filtering mode determination module 506 is used to determine a target filtering mode from a filtering mode set according to the initial channel characteristic value and the network connection state; the filtering mode set includes at least a first filtering mode and a second filtering mode, and the power consumption required by the second filtering mode is less than the power consumption required by the first filtering mode;

[0104] A filtering processing module 508 is used to filter the initial channel estimation parameters using a target filtering method to obtain target channel estimation parameters;

[0105] The measurement value determination module 510 is used to determine the target measurement value of each channel measurement indicator in the current measurement period based on the target channel estimation parameter.

[0106] The above-mentioned channel measurement device obtains the initial channel estimation parameters in the current measurement period, determines the initial channel characteristic values ​​based on the initial channel estimation parameters, further determines the network connection status of the terminal device in the current measurement period, determines the target filtering mode from the filtering mode set according to the initial channel characteristic values ​​and the network connection status, and uses the target filtering mode to filter the initial channel estimation parameters to obtain the target channel estimation parameters. Since the target filtering mode can be adaptively selected from the filtering mode set according to the initial channel characteristic values ​​and the network connection status, and the filtering mode set includes at least the first filtering mode and the second filtering mode, and the power consumption required by the second filtering mode is less than the power consumption required by the first filtering mode, it avoids the unified use of high-power filtering modes for filtering, thereby reducing the system power consumption when the terminal device is measured.

[0107] In one embodiment, the filtering mode determination module is further used to identify the channel scene according to the initial channel characteristic value and the network connection state to obtain a scene recognition result; and determine the target filtering mode from the filtering mode set based on the scene recognition result.

[0108] In one embodiment, the characteristic value determination module is used to obtain the initial channel estimation parameters in the current measurement period, and determine the initial signal-to-noise ratio value based on the initial channel estimation parameters; the filtering mode determination module is also used to identify the channel scenario as the second channel scenario if the network connection state is a connected state and the initial signal-to-noise ratio value satisfies a first judgment condition, and the first judgment condition is used to indicate that the initial signal-to-noise ratio value is greater than a first signal-to-noise ratio threshold value and less than a second signal-to-noise ratio threshold value; select the second filtering mode from the filtering mode set as the target filtering mode.

[0109] In one embodiment, the filtering mode determination module is also used to identify the channel scenario as the first channel scenario if the network connection state is a connected state and the initial signal-to-noise ratio value does not meet the first judgment condition; and select the first filtering mode from the filtering mode set as the target filtering mode.

[0110] In one embodiment, the characteristic value determination module is also used to obtain the initial channel estimation parameters in the current measurement period, and determine the initial signal-to-noise ratio value and the Doppler spread of the channel based on the initial channel estimation parameters; the filtering mode determination module is also used to identify the channel scenario as the second channel scenario if the network connection state is a connected state, and the initial signal-to-noise ratio value satisfies the first judgment condition and the Doppler spread of the channel satisfies the second judgment condition, and the second judgment condition is used to indicate that the Doppler spread of the channel is less than the Doppler threshold value; select the second filtering mode from the filtering mode set as the target filtering mode.

[0111] In one embodiment, the characteristic value determination module is also used to obtain the initial channel estimation parameters in the current measurement period, and determine the initial signal-to-noise ratio value and the delay spread of the channel based on the initial channel estimation parameters; the filtering mode determination module is also used to identify the channel scenario as the second channel scenario if the network connection state is a non-connected state, and the initial signal-to-noise ratio value satisfies the first judgment condition and the delay spread satisfies the third judgment condition, and the third judgment condition is used to indicate that the delay spread of the channel is less than the delay threshold value; select the second filtering mode from the filtering mode set as the target filtering mode.

[0112] In one embodiment, the filtering mode determination module is also used to identify the channel scenario as the first channel scenario if the network connection state is a non-connected state and the delay extension does not meet the third judgment condition; and select the first filtering mode from the filtering mode set as the target filtering mode.

[0113] In one embodiment, the filtering mode determination module is also used to identify the channel scenario as the first channel scenario if the network connection state is a non-connected state, and the delay spread satisfies the third judgment condition and the initial signal-to-noise ratio value does not meet the first judgment condition; and select the first filtering mode from the filtering mode set as the target filtering mode.

[0114] In one embodiment, the filtering processing module is also used to, if the target filtering method is the first filtering method, use the first preset method to perform frequency domain denoising on the initial channel estimation parameters corresponding to each reference signal; or if the target filtering method is the first filtering method, use the second preset method to perform time domain denoising on the initial channel estimation parameters corresponding to each reference signal.

[0115] In one embodiment, the filtering processing module is further configured to, if the target filtering mode is the second filtering mode, perform average filtering on the initial channel estimation parameters corresponding to each reference signal to obtain the target channel estimation parameters.

[0116] In one embodiment, the above-mentioned device also includes: a statistical module, which is used to count the target filtering methods determined within multiple measurement cycles to obtain a first quantity statistical value corresponding to the first filtering method and a second quantity statistical value corresponding to the second filtering method; the first quantity statistical value and the second quantity statistical value are reported to the network device to instruct the network device to filter the target measurement values ​​received within multiple measurement cycles based on the first quantity statistical value and the second quantity statistical value.

[0117] Each module in the above-mentioned channel measurement device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module above.

[0118] In one embodiment, an electronic device is provided. The electronic device may be a terminal device, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. 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 and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a channel measurement method is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0119] 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 application, and does not constitute a limitation on the computer device to which the solution of the present application 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.

[0120] The embodiment of the present application further provides a computer-readable storage medium, which includes one or more non-volatile computer-readable storage media containing computer-executable instructions, and when the computer-executable instructions are executed by one or more processors, the processors execute the steps of the channel measurement method.

[0121] An embodiment of the present application also provides a computer program product including instructions, which, when executed on a computer, enables the computer to execute a channel measurement method.

[0122] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0123] 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 the memory, database or other medium used in the embodiments provided in the present application 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, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. 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). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0124] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0125] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A channel measurement method, It is characterized in that include: Acquire initial channel estimation parameters in a current measurement period, and determine initial channel characteristic values ​​based on the initial channel estimation parameters; Determining a network connection status of a terminal device within the current measurement period; Identify the channel scene according to the initial channel characteristic value and the network connection state to obtain a scene identification result; Determining a target filtering mode from a set of filtering modes based on the scene recognition result; the set of filtering modes includes at least a first filtering mode and a second filtering mode, both of which are used to filter channel estimation parameters, and the power consumption required by the second filtering mode is less than the power consumption required by the first filtering mode; Using a target filtering method to filter the initial channel estimation parameters to obtain target channel estimation parameters; Based on the target channel estimation parameters, target measurement values ​​of each channel measurement indicator in the current measurement period are determined.

2. The method according to claim 1, It is characterized in that The obtaining of initial channel estimation parameters in the current measurement period, and determining initial channel characteristic values ​​based on the initial channel estimation parameters, includes: Acquire initial channel estimation parameters in a current measurement period, and determine an initial signal-to-noise ratio value based on the initial channel estimation parameters; The identifying the channel scene according to the initial channel characteristic value and the network connection state to obtain a scene identification result includes: If the network connection state is a connected state, and the initial signal-to-noise ratio value satisfies a first decision condition, then the channel scenario is identified as a second channel scenario, and the first decision condition is used to indicate that the initial signal-to-noise ratio value is greater than a first signal-to-noise ratio threshold value and less than a second signal-to-noise ratio threshold value; The determining a target filtering mode from the set of filtering modes based on the scene recognition result includes: A second filtering method is selected from the filtering method set as a target filtering method.

3. The method according to claim 2, It is characterized in that The identifying the channel scene according to the initial channel characteristic value and the network connection state to obtain a scene identification result also includes: If the network connection state is a connected state, and the initial signal-to-noise ratio value does not meet the first judgment condition, identifying that the channel scenario is a first channel scenario; The step of determining a target filtering mode from a set of filtering modes based on the scene recognition result includes: A first filtering method is selected from the filtering method set as a target filtering method.

4. The method according to claim 1, It is characterized in that The obtaining of initial channel estimation parameters in the current measurement period, and determining initial channel characteristic values ​​based on the initial channel estimation parameters, includes: Acquire initial channel estimation parameters in a current measurement period, and determine an initial signal-to-noise ratio value and a Doppler spread of a channel based on the initial channel estimation parameters; The identifying the channel scene according to the initial channel characteristic value and the network connection state to obtain a scene identification result includes: If the network connection state is a connected state, and the initial signal-to-noise ratio value satisfies a first decision condition, and the Doppler spread of the channel satisfies a second decision condition, then the channel scenario is identified as a second channel scenario, and the second decision condition is used to indicate that the Doppler spread of the channel is less than a Doppler threshold value; The step of determining a target filtering mode from a set of filtering modes based on the scene recognition result includes: A second filtering method is selected from the filtering method set as a target filtering method.

5. The method according to claim 1, It is characterized in that The obtaining of initial channel estimation parameters in the current measurement period, and determining initial channel characteristic values ​​based on the initial channel estimation parameters, includes: Acquire initial channel estimation parameters in a current measurement period, and determine an initial signal-to-noise ratio value and a delay spread of the channel based on the initial channel estimation parameters; The identifying the channel scene according to the initial channel characteristic value and the network connection state to obtain a scene identification result includes: If the network connection state is a non-connected state, and the initial signal-to-noise ratio value satisfies the first decision condition and the delay spread satisfies the third decision condition, then the channel scenario is identified as the second channel scenario, and the third decision condition is used to indicate that the delay spread of the channel is less than the delay threshold value; The step of determining a target filtering mode from a set of filtering modes based on the scene recognition result includes: A second filtering method is selected from the filtering method set as a target filtering method.

6. The method according to claim 5, It is characterized in that The identifying the channel scene according to the initial channel characteristic value and the network connection state to obtain a scene identification result also includes: If the network connection state is a non-connected state and the delay spread does not satisfy the third decision condition, identifying that the channel scenario is a first channel scenario; The step of determining a target filtering mode from a set of filtering modes based on the scene recognition result includes: A first filtering method is selected from the filtering method set as a target filtering method.

7. The method according to claim 5, It is characterized in that The identifying the channel scene according to the initial channel characteristic value and the network connection state to obtain a scene identification result also includes: If the network connection state is a non-connected state, and the delay spread satisfies the third decision condition, and the initial signal-to-noise ratio value does not satisfy the first decision condition, then identifying that the channel scenario is a first channel scenario; The step of determining a target filtering mode from a set of filtering modes based on the scene recognition result includes: A first filtering method is selected from the filtering method set as a target filtering method.

8. The method according to any one of claims 1 to 7, It is characterized in that The initial channel estimation parameters include initial channel estimation parameters corresponding to each reference signal, and the initial channel estimation parameters are filtered by a target filtering method to obtain target channel estimation parameters, including: If the target filtering mode is the first filtering mode, frequency domain denoising is performed on the initial channel estimation parameters corresponding to each reference signal using a first preset mode; or If the target filtering mode is the first filtering mode, a second preset mode is used to perform time domain denoising on the initial channel estimation parameters corresponding to each reference signal.

9. The method according to any one of claims 1 to 7, It is characterized in that The initial channel estimation parameters include initial channel estimation parameters corresponding to each reference signal, and the initial channel estimation parameters are filtered by a target filtering method to obtain target channel estimation parameters, including: If the target filtering mode is the second filtering mode, average filtering is performed on the initial channel estimation parameters corresponding to each reference signal to obtain the target channel estimation parameters.

10. The method according to any one of claims 1 to 7, It is characterized in that The method further comprises: Counting the target filtering modes determined in multiple measurement cycles to obtain a first quantity statistical value corresponding to the first filtering mode and a second quantity statistical value corresponding to the second filtering mode; The first quantity statistical value and the second quantity statistical value are reported to a network device to instruct the network device to perform filtering processing on the received target measurement values ​​in the multiple measurement cycles based on the first quantity statistical value and the second quantity statistical value.

11. A channel measurement device, It is characterized in that include: A characteristic value determination module, used to obtain initial channel estimation parameters in a current measurement period, and determine initial channel characteristic values ​​based on the initial channel estimation parameters; A connection status determination module, used to determine the network connection status of the terminal device in the current measurement period; A filtering mode determination module is used to identify the channel scene according to the initial channel characteristic value and the network connection state to obtain a scene recognition result; based on the scene recognition result, determine a target filtering mode from a filtering mode set; the filtering mode set includes at least a first filtering mode and a second filtering mode, the first filtering mode and the second filtering mode are both used to filter the channel estimation parameters, and the power consumption required by the second filtering mode is less than the power consumption required by the first filtering mode; A filtering processing module, used for filtering the initial channel estimation parameters by using a target filtering method to obtain target channel estimation parameters; The measurement value determination module is used to determine the target measurement value of each channel measurement indicator in the current measurement cycle based on the target channel estimation parameter.

12. An electronic device comprising a memory and a processor, wherein the memory stores a computer program. It is characterized in that When the computer program is executed by the processor, the processor is caused to perform the steps of the channel measurement method according to any one of claims 1 to 10.

13. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, the steps of the channel measurement method according to any one of claims 1 to 10 are implemented.

14. A computer program product storing a computer program, It is characterized in that When the computer program is executed by a processor, the steps of the channel measurement method according to any one of claims 1 to 10 are implemented.

Images