CN114553336A - Signal filtering method, device, equipment, storage medium and computer program product - Google Patents
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Abstract
The application provides a signal filtering method, a signal filtering device, a signal filtering apparatus, a storage medium and a computer program product. The method comprises the following steps: determining a target filtering type according to the relative size of the current linear measurement value and the last linear measurement value of the measured signal; and filtering the current linear measurement value based on the target filtering type to obtain a measurement filtering value corresponding to the current linear measurement value. According to the method, the change trend of the linear measurement value is determined according to the comparison between the current linear measurement value and the previous linear measurement value, the target filtering type is determined according to the change trend, the current linear measurement value is filtered based on the determined target filtering type, and the error between the measurement filtering value obtained after filtering and the current linear measurement value is reduced through the filtering method, so that the fluctuation condition of the measured signal can be better tracked.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a signal filtering method, apparatus, device, storage medium, and computer program product.
Background
Based on the protocol requirements, the terminal needs to measure and filter some signals after receiving them.
The existing filtering method is to filter the measured signal in the linear domain or filter the measured signal in the logarithmic domain. Whether linear domain filtering or logarithmic domain filtering is selected, the error between the result obtained after filtering and the actually received measured signal is large.
Disclosure of Invention
An object of the embodiments of the present application is to provide a signal filtering method, device, apparatus, storage medium and computer program product, so as to solve the problem in the prior art that an error between a result obtained after filtering and an actually received measurement value is large.
In a first aspect, an embodiment of the present application provides a signal filtering method, including: determining a target filtering type according to the relative size of the current linear measurement value and the last linear measurement value of the measured signal; and filtering the current linear measurement value based on the target filtering type to obtain a measurement filtering value corresponding to the current linear measurement value.
According to the embodiment of the application, the change trend of the linear measurement value is determined according to the comparison between the current linear measurement value and the previous linear measurement value, the target filtering type is determined according to the change trend, and the current linear measurement value is filtered based on the determined target filtering type.
In any embodiment, the determining the target filtering type according to the relative size of the current linear measurement and the last linear measurement of the measured signal includes: if the current linear measurement value is greater than the last linear measurement value, determining that the target filtering type is linear domain filtering; and if the current linear measurement value is less than or equal to the last linear measurement value, determining the target filtering type to be logarithmic domain filtering.
In the embodiment of the application, when the linear measurement value is in an increasing state, linear domain filtering is adopted, and when the linear measurement value is in a decreasing state, logarithmic domain filtering is adopted.
In any embodiment, said filtering said current linearity measurement based on said target filtering type comprises: smooth filtering the current linear measurement based on the target filtering type. The filtering method is used for obtaining a smooth filtering result, and in addition, the filtering method is low in calculation amount, so that the filtering speed is improved.
In any embodiment, said smoothing said current linear measure based on said target filtering type comprises: and performing variable coefficient smoothing filtering on the current linear measurement value based on the target filtering type. According to the embodiment of the application, the variable coefficient smoothing filtering is adopted, and the filter coefficient is variable, so that the time sequence of the current linear filter value can be adapted to select a better filter coefficient to filter the current linear measurement value, and the smoothness of the measurement filter value obtained after filtering is further improved.
In any embodiment, the filtering the current linear measurement value based on the target filtering type to obtain a measured filtered value corresponding to the current linear measurement value includes: when the target filtering type is linear domain filtering, performing linear domain filtering on the current linear measurement value according to the previous linear measurement value to obtain an intermediate filtering value; converting the intermediate filtered value from a linear domain to a logarithmic domain to obtain the measured filtered value.
In the embodiment of the application, after the target filtering type is determined to be linear domain filtering according to the relative size of the current linear measurement value and the last linear measurement value of the measured signal, the current linear measurement value is filtered by adopting a linear domain filtering mode, so that the filtering loss is reduced, and the fluctuation of the measured signal which is actually received can be better tracked by obtaining a result after filtering.
In any embodiment, the filtering the current linear measurement value based on the target filtering type to obtain a measured filtered value corresponding to the current linear measurement value includes: when the target filtering type is logarithmic domain filtering, respectively converting a current linear measurement value and a previous linear measurement value from a linear domain to a logarithmic domain, and obtaining a current logarithmic measurement value corresponding to the current linear measurement value and a previous logarithmic measurement value corresponding to the previous linear measurement value; and carrying out log domain filtering on the current log measurement value according to the last log measurement value to obtain the measurement filtering value.
When the filtering type is determined to be logarithmic domain filtering through comparing the current linear measurement value with the last linear measurement value, the logarithmic domain conversion is firstly carried out, and then filtering is carried out in the logarithmic domain, so that the filtering loss is reduced, and the fluctuation of the measured signal which is actually received can be better tracked by the result obtained after filtering.
In any embodiment, the linear measurement value comprises a reference signal received power, RSRP, or a reference signal received quality, RSRQ.
In a second aspect, the present application provides a signal filtering apparatus comprising: the filter type determining module is used for determining a target filter type according to the relative size of the current linear measurement value and the last linear measurement value of the measured signal; and the filtering module is used for filtering the current linear measurement value based on the target filtering type to obtain a filtering value corresponding to the current linear measurement value.
In a third aspect, an embodiment of the present application provides an electronic device, including: the system comprises a processor, a memory and a bus, wherein the processor and the memory are communicated with each other through the bus; the memory stores program instructions executable by the processor, the processor being capable of performing the method of the first aspect when invoked by the program instructions.
In a fourth aspect, an embodiment of the present application provides a non-transitory computer-readable storage medium, including: the non-transitory computer readable storage medium stores computer instructions that cause the computer to perform the method of the first aspect.
In a fifth aspect, embodiments of the present application provide a computer program product, which includes computer program instructions, when read and executed by a processor, for performing the method of the first aspect.
Additional features and advantages of the present application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the embodiments of the present application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
To more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a schematic flow chart of a signal filtering method according to an embodiment of the present disclosure;
FIG. 2 is a diagram illustrating the results of filtering a measured signal with a plurality of filtering types according to an embodiment of the present disclosure;
FIG. 3 is a diagram illustrating the results of filtering a measured signal according to another filtering type provided by an embodiment of the present application;
fig. 4 is a schematic structural diagram of a signal filtering apparatus according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.
Detailed Description
When filtering linear measured values of received measured signals based on the prior art, filtering is performed in a linear domain or in a logarithmic domain, and the error between the measured filtered values obtained after filtering and actual linear measured values is large due to the filtering mode, so that the measured signals cannot be well tracked. The embodiment of the application provides a signal filtering method, which can select a proper filtering mode according to the fluctuation condition of a linear measurement value of a measured signal, thereby reducing the error between a measurement filtering value obtained after filtering and a real linear measurement value, and further being capable of better tracking the measured signal.
For ease of understanding, before describing the embodiments of the present application, reference is made to some concepts involved in the present application:
reference Signal Receiving Power (RSRP) is one of the key parameters in a network that can represent the wireless Signal strength and the physical layer measurement requirements, and is the average of the received Signal Power over all REs (resource elements) that carry Reference signals within a certain symbol.
Reference Signal Receiving Quality (RSRQ) mainly measures the Receiving Quality of a downlink specific cell Reference Signal. RSRQ is defined as the ratio of the cell reference signal power to the cell overall signal power (RSSI). The calculation formula of the reference signal receiving quality is as follows: RSRQ (RSRP N)PRB/RSSI, wherein RSRP is reference signal received power; n is a radical of hydrogenPRBThe total number of PRBs required in downlink transmission; RSSI is a carrier received signal strength indication.
The purpose of the smoothing filter is to make the signal jitter smaller and the signal smoother.
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
Fig. 1 is a schematic flow chart of a signal filtering method according to an embodiment of the present disclosure, and as shown in fig. 1, the method is applied to a terminal, where the terminal is a terminal capable of communicating with a base station, and may be, for example, a mobile phone, a tablet computer, a smart watch, and the like. The method comprises the following steps:
step 101: determining a target filtering type according to the relative size of the current linear measurement value and the last linear measurement value of the measured signal;
step 102: and filtering the current linear measurement value based on the target filtering type to obtain a measurement filtering value corresponding to the current linear measurement value.
In step 101, the measured signal is a signal that the terminal receives from the base station and needs to perform measurement. Due to the protocol requirement, after the terminal receives the measured signal, the measured signal is measured and filtered, so that the measured signal is smoother. The terminal measures the measured signal based on the measurement module to obtain a measurement value of a linear domain, which is referred to as a linear measurement value in the embodiment of the present application. The linear measurement value corresponding to the current time is called the current linear measurement value. The last linear measurement value refers to a linear measurement value measured at a certain historical time before the current linear measurement value is obtained, for example: the time corresponding to the current linear measurement value is the current time, and the last linear measurement value may be a linear measurement value obtained by receiving the measurement last time or the next last time before the current time.
After the terminal acquires the current linear measurement value, the terminal compares the measurement value with the stored previous linear measurement value, and the target filtering type is determined according to the relative size of the current linear measurement value and the previous linear measurement value. The target filtering type refers to a filtering type used when filtering the current linear measurement value, and may specifically be linear domain filtering or logarithmic domain filtering.
In step 102, after determining the target filtering type, the terminal filters the current linear measurement value by using the target filtering type, so as to obtain a measurement filtering value.
According to the embodiment of the application, the change trend of the linear measurement value is determined according to the comparison between the current linear measurement value and the previous linear measurement value, the target filtering type is determined according to the change trend, and the current linear measurement value is filtered based on the determined target filtering type.
On the basis of the above embodiment, the determining a target filtering type according to the relative sizes of the current linear measurement value and the previous linear measurement value of the received signal includes:
if the current linear measurement value is greater than the last linear measurement value, determining that the target filtering type is linear domain filtering;
and if the current linear measurement value is less than or equal to the last linear measurement value, determining that the target filtering type is logarithmic domain filtering.
In a specific implementation process, fig. 2 is a schematic diagram of a result of filtering a measured signal by using multiple filtering types according to an embodiment of the present application, and as shown in fig. 2, an abscissa is a sampling point, which can also be understood as a sampling time, and the measured signal is sampled at each sampling time to obtain a linear measurement value. The ordinate is the signal energy of the measured signal in various states. Fig. 2 shows a curve of signal energy obtained after logarithmic conversion is performed on a linear measurement value of a measured signal, a curve formed by signal energy (measurement filter value) obtained after filtering the linear measurement value only in a linear domain, a curve formed by signal energy (measurement filter value) obtained after filtering the linear measurement value only in a logarithmic domain, and a curve formed by signal energy (measurement filter value) obtained after filtering the linear measurement value by using the filtering method provided by the embodiment of the present application.
Because the linear measurement value of the measured signal and the value obtained by logarithmically converting the linear measurement value are in a positive correlation relationship, that is, if the linear measurement value a is greater than the linear measurement value B, the logarithm a 'corresponding to the linear measurement value a is still greater than the logarithm B' corresponding to the linear measurement value B. As can be seen from fig. 2, for the case that the current linear measurement value of the measured signal is decreased compared with the previous linear measurement value, if the linear domain filtering is adopted, the error with the actual measurement value is larger, and on the contrary, the logarithmic domain filtering is adopted, the effect is better. For the case that the current linear measurement value of the measured signal is relatively increased from the previous linear measurement value, the effect of the measurement filtering value obtained by adopting the linear domain filtering is better than that obtained by adopting the logarithmic domain filtering.
Based on the above analysis, in the embodiment of the present application, after the current linear measurement value of the measured signal is obtained, by comparing the current linear measurement value with the previous linear measurement value, if the current linear measurement value is greater than the previous linear measurement value, it is indicated that the linear measurement value of the current measured signal is in an ascending trend, and the current linear measurement value is filtered by using linear domain filtering. And if the current linear measurement value is less than or equal to the last linear measurement value, the measured information is in a stable or descending trend, and the current linear measurement value is filtered by adopting log-domain filtering. As can be seen from fig. 2, the measured filtered value obtained by the filtering method provided by the embodiment of the present application is closer to the true linear filtered value.
In the embodiment of the application, when the linear measurement value is in an increasing state, linear domain filtering is adopted, and when the linear measurement value is in a decreasing state, logarithmic domain filtering is adopted.
In another embodiment, the target filtering type may also be determined by:
and comparing the current linear measurement value with the previous linear measurement value, and if the deviation between the current linear measurement value and the previous linear measurement value is within a first preset threshold value, adopting linear domain filtering or adopting logarithmic domain filtering. The first preset threshold is a preset positive number, for example: may be 10, 20 or others.
And if the current linear measurement value is greater than the last linear measurement value and the absolute value of the difference between the current linear measurement value and the last linear measurement value is greater than a first preset threshold, linear domain filtering is adopted.
And if the current linear measurement value is smaller than the last linear measurement value and the absolute value of the difference between the current linear measurement value and the last linear measurement value is larger than a first preset threshold, logarithmic domain filtering is adopted.
According to the embodiment of the application, the filtering type is determined by comparing the current linear measurement value with the previous linear measurement value, and when the linear domain filtering is performed, the filtering is performed in the linear domain and then the linear domain filtering is converted into the measurement value in the logarithmic domain; when the filtering is carried out in the logarithmic domain, the logarithmic domain conversion is firstly carried out, and then the filtering is carried out in the logarithmic domain, so that the filtering loss is reduced, and the fluctuation of the actually received measured signal can be better tracked by the result obtained after the filtering.
On the basis of the foregoing embodiment, the filtering the current linearity measurement value based on the target filtering type includes: smooth filtering the current linear measurement based on the target filtering type.
In a specific implementation, the purpose of smoothing the current linear measurement value is to filter out the noise that is too high and too low in the measured signal, so that the measured information after filtering tends to be smooth.
The following is described for linear domain filtering and logarithmic domain filtering, respectively:
(1) linear domain filtering
Step 01: performing smooth filtering on the current linear measurement value according to the previous linear measurement value, which is specifically shown in formula (1):
y(n)＝α*x(n)+(1-α)x(n-1) (1)
wherein y (n) is the intermediate filtered value; α is a filter coefficient, which may be preset, for example, 1/2, and may also be other values, which is not specifically limited in this embodiment of the present application; x (n) is the current linear measurement; x (n-1) is the last linear measurement; n is used to represent the timing of the linear measurements received by the terminal, which may be an integer number that increments from 0.
Step 02: converting the intermediate filtered value from the linear domain to a logarithmic domain, thereby obtaining a measured filtered value, see in particular equation (2):
y(n)_dB＝10*log10(y(n)) (2)
where y (n) _ dB is the measured filtered value and y (n) is the intermediate filtered value calculated by equation (1).
(2) Logarithmic domain filtering
Step 11: converting the current linear measurement value and the last linear measurement value from the linear domain to the logarithmic domain respectively, wherein the conversion is shown as a formula (3) and a formula (4):
x(n)_dB＝10*log10(x(n)) (3)
x(n-1)_dB＝10*log10(x(n-1)) (4)
wherein x (n) _ dB is the current logarithmic measurement; x (n) is the current linear measurement; x (n-1) _ dB is the last logarithmic measurement value; x (n-1) is the last linear measurement.
Step 12: and carrying out logarithmic domain filtering on the current logarithmic measurement value according to the last logarithmic measurement value to obtain a measurement filtering value. Specifically, the calculation can be obtained by the formula (5):
y(n)_dB＝α*x(n)_dB+(1-α)x(n-1)_dB (5)
wherein, y (n) _ dB is a measurement filtering value; α is a filter coefficient, which may be preset, for example, 1/2, and may also be other values, which is not specifically limited in this embodiment of the present application; x (n) _ dB is the current logarithmic measurement value obtained by the calculation of formula (3); x (n-1) _ dB is the last logarithmic measurement value obtained by the calculation of equation (4).
In the embodiment of the application, the current linear measurement value is filtered by adopting a smooth filtering mode, and the filtering speed is improved because the filtering mode has small calculation amount.
In another embodiment, the current linear measurement may be further filtered by a variable coefficient smoothing filter, which is described below from the linear domain filter and the log domain filter, respectively.
(1) Linear domain filtering
Step 21: and determining a filter coefficient according to a receiving time sequence corresponding to the current linear measurement value, wherein the receiving time sequence refers to the time sequence of the current linear measurement value corresponding to the measured signal received by the terminal. It is understood that the embodiment of the present application records the reception timing of the received linear measurement value from 0, and the reception timing of the linear measurement value is incremented by the unit of the value 1. In practical applications, the receiving time sequence of the linear measurement value can be recorded from other values, and the receiving time sequence can be increased by taking other values as units. For example: the receiving timing of the linear measurement value of the measured signal received by the terminal may be: 2. 4, 6, 8, 10.
When determining the filter coefficient according to the reception timing, the following may be specifically used:
if the receiving time sequence n of the current linear measurement value is 0, the current linear measurement value is a first linear measurement value, and for the first linear measurement value, the filtering is not performed, and the filtering coefficient can be determined to be 1; if the receiving timing n of the current linear measurement value is greater than 0 and less than K, where K is a positive integer, for example, may be 8, and may also be other values. If the receiving timing n of the current linear measurement value is greater than or equal to K, the filter coefficient can be determined to be 1/K.
Step 22: after the filter coefficient is determined in step 21, the current linear measurement value is subjected to smooth filtering according to the previous linear measurement value, which is specifically shown in formula (1):
y(n)'＝α'*x(n)+(1-α')x(n-1) (6)
wherein y (n)' is the intermediate filtered value; α' is the filter coefficient determined by step 21; x (n) is the current linearity measurement; x (n-1) is the last linear measurement; n is used to represent the timing of the linear measurements received by the terminal, which may be an integer number that increments from 0.
Step 23: converting the intermediate filtered value from the linear domain to a logarithmic domain, thereby obtaining a measured filtered value, see in particular equation (7):
y(n)'_dB＝10*log10(y(n)') (7)
where y (n) '_ dB is a measured filtered value, and y (n)' is an intermediate filtered value obtained by calculation of formula (6).
(2) Logarithmic domain filtering
Step 31: and determining a filter coefficient according to a receiving time sequence corresponding to the current linear measurement value, wherein the determination of the filter coefficient is consistent with the determination method of the filter coefficient in the linear domain filtering, and details are not repeated here.
Step 32: the current linear measurement value and the previous linear measurement value are respectively converted from the linear domain to the logarithmic domain, and the specific conversion is shown in formula (3) and formula (4), which is not described herein again.
Step 33: and carrying out logarithmic domain filtering on the current logarithmic measurement value according to the last logarithmic measurement value to obtain a measurement filtering value. Specifically, it can be obtained by calculation according to formula (8):
y(n)'_dB＝α'*x(n)_dB+(1-α')x(n-1)_dB (8)
wherein y (n)' _ dB is a measurement filter value; α' is the filter coefficient determined by step 31; x (n) _ dB is the current logarithmic measurement value obtained by the calculation of formula (3); x (n-1) _ dB is the last logarithmic measurement value obtained by the calculation of equation (4).
According to the embodiment of the application, the variable coefficient smoothing filtering is adopted, and the filter coefficient is variable, so that a better filter coefficient can be selected to filter the current linear measured value, and the accuracy of obtaining the measured filter value after filtering is further improved.
Fig. 3 is a schematic diagram of another result obtained by filtering a measured signal according to multiple filtering types according to an embodiment of the present application, and as shown in fig. 3, an abscissa is a sampling point, which can also be understood as a sampling time, and the measured signal is sampled at each sampling time to obtain a linear measurement value. The ordinate is the deviation between the measured filter value obtained after filtering the measured signal by using different filtering types of filtering methods and the value obtained after logarithmic conversion of the real linear measured value. Fig. 3 shows a deviation of a value obtained by logarithmically converting a measurement filter value obtained by filtering a linear measurement value only in a linear domain and a real linear measurement value, a deviation of a value obtained by logarithmically converting a measurement filter value obtained by filtering a linear measurement value only in a logarithmic domain and a real linear measurement value, and a deviation of a value obtained by logarithmically converting a measurement filter value obtained by filtering a linear measurement value and a real linear measurement value by using the filtering method provided in the embodiment of the present application. As can be seen from fig. 3, the measured filtered value obtained by the filtering method provided by the embodiment of the present application has a smaller deviation from the value obtained by logarithmically converting the true linear measurement value, and therefore, the fluctuation of the true linear measurement value can be better tracked.
Fig. 4 is a schematic structural diagram of a signal filtering apparatus according to an embodiment of the present application, where the apparatus may be a module, a program segment, or a code on an electronic device. It should be understood that the apparatus corresponds to the above-mentioned embodiment of the method of fig. 1, and can perform various steps related to the embodiment of the method of fig. 1, and the specific functions of the apparatus can be referred to the description above, and the detailed description is appropriately omitted here to avoid redundancy. The device comprises: a filtering type determination module 401 and a filtering module 402, wherein:
the filter type determining module 401 is configured to determine a target filter type according to a relative size of a current linear measurement value and a previous linear measurement value of the measured signal;
the filtering module 402 is configured to filter the current linear measurement value based on the target filtering type, and obtain a filtered value corresponding to the current linear measurement value.
On the basis of the foregoing embodiment, the filtering type determining module 401 is specifically configured to:
if the current linear measurement value is greater than the last linear measurement value, determining that the target filtering type is linear domain filtering;
and if the current linear measurement value is less than or equal to the last linear measurement value, determining that the target filtering type is logarithmic domain filtering.
On the basis of the foregoing embodiment, the filtering module 402 is specifically configured to perform smooth filtering on the current linear measurement value based on the target filtering type.
On the basis of the foregoing embodiment, the filtering module 402 is specifically configured to perform coefficient-varying smoothing filtering on the current linear measurement value based on the target filtering type.
On the basis of the foregoing embodiment, the filtering module 402 is specifically configured to:
when the target filtering type is linear domain filtering, performing linear domain filtering on the current linear measurement value according to the previous linear measurement value to obtain an intermediate filtering value;
converting the intermediate filtered value from a linear domain to a logarithmic domain to obtain the measured filtered value;
on the basis of the foregoing embodiment, the filtering module 402 is further specifically configured to:
when the target filtering type is logarithmic domain filtering, respectively converting a current linear measurement value and a previous linear measurement value from a linear domain to a logarithmic domain, and obtaining a current logarithmic measurement value corresponding to the current linear measurement value and a previous logarithmic measurement value corresponding to the previous linear measurement value;
and carrying out log domain filtering on the current log measurement value according to the last log measurement value to obtain the measurement filtering value.
On the basis of the above embodiments, the linear measurement value includes reference signal received power RSRP or reference signal received quality RSRQ.
Fig. 5 is a schematic structural diagram of an entity of an electronic device provided in an embodiment of the present application, and as shown in fig. 5, the electronic device includes: a processor (processor)501, a memory (memory)502, and a bus 503; wherein the content of the first and second substances,
the processor 501 and the memory 502 are communicated with each other through the bus 503;
the processor 501 is configured to call program instructions in the memory 502 to perform the methods provided by the above-mentioned method embodiments, for example, including: determining a target filtering type according to the relative size of the current linear measurement value and the last linear measurement value of the measured signal; and filtering the current linear measurement value based on the target filtering type to obtain a measurement filtering value corresponding to the current linear measurement value.
The processor 501 may be an integrated circuit chip having signal processing capabilities. The Processor 501 may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. Which may implement or perform the various methods, steps, and logic blocks disclosed in the embodiments of the present application. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The Memory 502 may include, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read Only Memory (PROM), Erasable Read Only Memory (EPROM), Electrically Erasable Read Only Memory (EEPROM), and the like.
The present embodiment discloses a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the method provided by the above-mentioned method embodiments, for example, comprising: determining a target filtering type according to the relative size of the current linear measurement value and the last linear measurement value of the measured signal; and filtering the current linear measurement value based on the target filtering type to obtain a measurement filtering value corresponding to the current linear measurement value.
The present embodiments provide a non-transitory computer-readable storage medium storing computer instructions that cause the computer to perform the methods provided by the above method embodiments, for example, including: determining a target filtering type according to the relative size of the current linear measurement value and the last linear measurement value of the measured signal; and filtering the current linear measurement value based on the target filtering type to obtain a measurement filtering value corresponding to the current linear measurement value.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
In addition, units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
Furthermore, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A method of filtering a signal, comprising:
determining a target filtering type according to the relative size of the current linear measurement value and the last linear measurement value of the measured signal;
and filtering the current linear measurement value based on the target filtering type to obtain a measurement filtering value corresponding to the current linear measurement value.
2. The method of claim 1, wherein determining the target filtering type based on the relative magnitudes of the current linear measure and the previous linear measure of the measured signal comprises:
if the current linear measurement value is greater than the last linear measurement value, determining that the target filtering type is linear domain filtering;
and if the current linear measurement value is less than or equal to the last linear measurement value, determining that the target filtering type is logarithmic domain filtering.
3. The method of claim 1, wherein said filtering the current linearity measurement based on the target filtering type comprises:
smooth filtering the current linearity measure based on the target filtering type.
4. The method of claim 3, wherein the smoothly filtering the current linearity measurement based on the target filtering type comprises:
and performing variable coefficient smoothing filtering on the current linear measurement value based on the target filtering type.
5. The method according to any one of claims 1-4, wherein the filtering the current linear measurement value based on the target filtering type to obtain a measured filtered value corresponding to the current linear measurement value comprises:
when the target filtering type is linear domain filtering, performing linear domain filtering on the current linear measurement value according to the previous linear measurement value to obtain an intermediate filtering value;
converting the intermediate filtered value from a linear domain to a logarithmic domain to obtain the measured filtered value;
and/or the presence of a gas in the gas,
when the target filtering type is logarithmic domain filtering, respectively converting a current linear measurement value and a previous linear measurement value from a linear domain to a logarithmic domain, and obtaining a current logarithmic measurement value corresponding to the current linear measurement value and a previous logarithmic measurement value corresponding to the previous linear measurement value;
and carrying out log domain filtering on the current log measurement value according to the last log measurement value to obtain the measurement filtering value.
6. The method of any of claims 1-4, wherein the linear measurement value comprises a reference signal received power, RSRP, or a reference signal received quality, RSRQ.
7. A signal filtering apparatus, comprising:
the filter type determining module is used for determining a target filter type according to the relative size of the current linear measurement value and the last linear measurement value of the measured signal;
and the filtering module is used for filtering the current linear measurement value based on the target filtering type to obtain a filtering value corresponding to the current linear measurement value.
8. An electronic device, comprising: a processor, a memory, and a bus, wherein,
the processor and the memory are communicated with each other through the bus;
the memory stores program instructions executable by the processor, the processor invoking the program instructions to perform the method of any of claims 1-6.
9. A non-transitory computer-readable storage medium storing computer instructions which, when executed by a computer, cause the computer to perform the method of any one of claims 1-6.
10. A computer program product comprising computer program instructions which, when read and executed by a processor, perform the method of any one of claims 1 to 6.
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