CN112702129B - Channel path loss estimation method and device, electronic equipment and storage medium - Google Patents
Channel path loss estimation method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a channel path loss estimation method, which comprises the following steps: acquiring channel impulse response data of a plurality of measuring points, and calculating by using the channel impulse response data to obtain an actual path loss value of each measuring point; calculating to obtain a first elevation angle value and a first distance of the measuring point relative to the signal transmitting end by using the position information corresponding to the measuring point; calculating elevation angle correction data of the channel path loss model by using the first elevation angle value, the first distance and the actual path loss value, and performing elevation angle correction on the channel path loss model by using the elevation angle correction data; calculating a channel path loss estimation value of an estimation point by using the channel path loss model after elevation correction and the parameters of the estimation point; the estimated point parameters include a second elevation value and a second distance of the estimated point relative to the transmit end of the signal. The method improves the estimation precision of the channel path loss model by using elevation correction. The invention also discloses a channel path loss estimation device, electronic equipment and a storage medium, and has the beneficial effects.
Description
Technical Field
The present invention relates to the field of wireless communication channel measurement and modeling, and in particular, to a channel path loss estimation method, apparatus, electronic device, and storage medium.
Background
With the continuous development of the unmanned aerial vehicle technology, the unmanned aerial vehicle is more and more widely applied to various industries, and has more applications in the aspects of air transportation, emergency rescue and relief, public safety and even military use. In order to ensure the safe and reliable working process of the unmanned aerial vehicle, effective and reliable air-ground communication between the sky and the ground should be ensured, so that an accurate air-ground channel model needs to be established. In the process of establishing the air-ground channel model, estimation of the channel path loss is very important.
In the related art, a channel path loss model is mainly used for terrestrial communication, obstacles between a signal sending end and a signal receiving end are randomly distributed in a terrestrial communication scene, and the influence of the obstacles on the channel path loss is random influence. However, in an air-ground communication scenario, the distribution pattern of the obstacles in the propagation path is different from that in a land communication scenario, the distribution pattern is related to the relative position between the signal transmitting end and the signal receiving end, and further, the influence of the obstacles on the channel path loss is also different from that in the land communication scenario, so that the conventional channel path loss model is not suitable for the air-ground communication scenario.
Disclosure of Invention
The invention aims to provide a channel path loss estimation method, a channel path loss estimation device, electronic equipment and a storage medium, which can improve the calculation precision of a channel path loss model by adopting an elevation correction method and effectively improve the effectiveness and reliability of the channel path loss model in an air-ground communication scene between the sky and the ground.
To solve the above technical problem, the present invention provides a channel path loss estimation method, including:
acquiring channel impulse response data of a plurality of measuring points, and calculating by using the channel impulse response data to obtain an actual path loss value of each measuring point;
calculating to obtain a first elevation angle value and a first distance of the measuring point relative to a signal sending end by using the position information corresponding to the measuring point;
calculating elevation angle correction data of the path loss model of the signal path by using the first elevation angle value, the first distance and the actual path loss value, and performing elevation angle correction on the path loss model of the signal path by using the elevation angle correction data;
calculating the channel path loss estimation value of the estimation point by using the channel path loss model after elevation correction and the parameters of the estimation point; the estimated point parameters include a second elevation value and a second distance of the estimated point with respect to the signal transmitting end.
Optionally, after the first elevation value and the first distance of the measurement point with respect to the signal transmission point are calculated by using the position information corresponding to the measurement point, before the elevation correction value of the channel path loss model is calculated by using the first elevation value, the first distance, and the path loss value, the method further includes:
calculating a correlation coefficient value using the first elevation value and the actual path loss value;
judging whether the absolute value of the correlation coefficient value is larger than a preset threshold value or not;
and if so, executing the step of calculating the elevation correction value of the confidence road path loss model by using the first elevation value, the first distance and the actual path loss value.
Optionally, the calculating a correlation coefficient value using the first elevation value and the actual path loss value comprises:
calculating a logarithmic elevation value using the first elevation value;
calculating the correlation coefficient value using the log-elevation value and the actual path loss value.
Optionally, the acquiring channel impulse response data of a plurality of measurement points includes:
acquiring a local sequence signal of the signal transmitting point and a receiving sequence signal received by the measuring point;
and executing sliding correlation processing on the local sequence signal and the received sequence signal to obtain the channel impulse response data.
Optionally, the obtaining, by using the channel impulse response data, an actual path loss value of each measurement point through calculation includes:
performing noise filtering processing on the channel impulse response data to obtain channel receiving power;
and calculating to obtain an actual path loss value by using the channel receiving power and the channel transmitting power data of the signal transmitting end.
Optionally, the performing noise filtering on the channel impulse response data to obtain channel received power includes:
performing noise filtering processing on the channel impulse response data to obtain an effective power time delay spectrum;
and carrying out average calculation on the effective power time delay spectrum to obtain the channel receiving power.
Optionally, the calculating elevation correction data of the confidence road path loss model using the first elevation value, the first distance, and the actual path loss value includes:
correcting the channel path loss model using initial elevation correction data;
and performing linear regression calculation on the corrected channel path loss model by using the first elevation value, the first distance and the actual path loss value to obtain the elevation correction data.
The present invention also provides a channel path loss estimation device, including:
the acquisition module is used for acquiring channel impulse response data of a plurality of measurement points and calculating to obtain an actual path loss value of each measurement point by using the channel impulse response data;
the position relation calculation module is used for calculating a first elevation value and a first distance of the measuring point relative to the signal sending point by using the position information corresponding to the measuring point;
the correction calculation module is used for calculating elevation correction data of the signal path loss model by utilizing the first elevation value, the first distance and the actual path loss value to obtain a channel path loss model after elevation correction;
the estimated value calculation module is used for calculating the estimated value of the channel path loss of the estimation point by utilizing the channel path loss model after the elevation angle correction and the parameters of the estimation point; the estimated point parameters include a second elevation value and a second distance of the estimated point with respect to the signal transmitting end.
The present invention also provides an electronic device comprising:
a memory for storing a computer program;
a processor for implementing the channel path loss estimation method as described above when executing the computer program.
The present invention also provides a storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are loaded and executed by a processor, the method for estimating channel path loss as described above is implemented.
The invention provides a channel path loss estimation method, which comprises the following steps: acquiring channel impulse response data of a plurality of measuring points, and calculating by using the channel impulse response data to obtain an actual path loss value of each measuring point; calculating to obtain a first elevation angle value and a first distance of the measuring point relative to a signal sending point by using the position information corresponding to the measuring point; calculating elevation angle correction data of the road path loss model by using the first elevation angle value, the first distance and the actual path loss value to obtain a channel path loss model after elevation angle correction; calculating the channel path loss estimation value of the estimation point by using the channel path loss model after the elevation angle correction and the estimation point parameter; the estimated point parameters include a second elevation value and a second distance of the estimated point with respect to the signal transmitting end.
Therefore, the elevation angle correction is mainly performed on the first elevation angle value of the signal sending end and the measuring point, besides the actual path loss value of the measuring point, the first distance and the first elevation angle value of the measuring point relative to the signal sending end are collected, the elevation angle correction data are calculated by utilizing the actual path loss value, the first distance and the first elevation angle value, and the channel path loss model after the elevation angle correction is obtained. Since the channel path loss between the signal transmitting end and the receiving end in the terrestrial communication is limited by the height difference, the channel path loss model in the related art does not consider the influence of the first elevation value on the channel path loss. However, in the air-ground communication scene between the sky and the ground, the signal transmitting end and the signal receiving end have larger span in the horizontal direction and the vertical direction, and the elevation angle between the signal transmitting end and the signal receiving end has larger influence on the channel path loss, so that the estimation accuracy of the channel path loss model in the air-ground communication scene can be effectively improved by correcting the channel path loss model by using the first elevation angle value.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flowchart of a channel path loss estimation method according to an embodiment of the present invention;
FIG. 2 is a shadow fading histogram of a free space reference distance model according to an embodiment of the present invention;
FIG. 3 is a path loss fitted curve of a free space reference range model provided by an embodiment of the present invention;
FIG. 4 is a shadow fading histogram of an elevation-corrected logarithmic distance floating intercept model according to an embodiment of the present invention;
FIG. 5 is a path loss fit curve of an elevation-corrected logarithmic distance floating intercept model provided by an embodiment of the present invention;
fig. 6 is a block diagram of a channel path loss estimation apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the related art, a channel path loss model is mainly used for terrestrial communication, obstacles between a signal sending end and a signal receiving end are randomly distributed in a terrestrial communication scene, and the influence of the obstacles on the channel path loss is random influence. However, in an air-ground communication scenario, the distribution mode of the obstacles is different from that in a land scenario and is related to the relative position between the signal transmitting end and the signal receiving end, and further, the influence of the obstacles on the channel path loss is also different from that in the land communication scenario, so that the traditional channel path loss model is not suitable for the air-ground communication scenario. The invention can adopt the elevation angle correction method to improve the calculation precision of the channel path loss model. After research, the influence of the obstacle on the channel path loss is related to the elevation angle between the signal sending end and the signal receiving end, and the influence of the obstacle on the channel path loss is greatly changed along with the change of the elevation angle value, so that the accuracy of the channel path loss model in an air-ground communication scene between the sky and the ground can be effectively improved by correcting the channel path loss model by using the elevation angle. Referring to fig. 1, fig. 1 is a flowchart of a channel path loss estimation method according to an embodiment of the present invention, where the method includes:
s100, obtaining channel impulse response data of a plurality of measuring points, and calculating by using the channel impulse response data to obtain an actual path loss value of each measuring point.
It will be appreciated that in order to modify the channel path loss model with the elevation values, the actual measured actual path loss values used for the calculations need first be collected. Meanwhile, in order to improve the accuracy of correction calculation, the embodiment of the invention collects data of a plurality of measuring points.
It can be understood that, because the channel path loss model in the embodiment of the present invention is used to estimate the loss of a signal in the process of transmitting the signal from a signal transmitting end to a signal receiving end, and meanwhile, in order to acquire the channel impulse response data of a measurement point and calculate an actual path loss value by using the data, the channel transmitting end should be required to transmit the signal to the measurement point, so that the measurement point can receive the signal data and finally acquire the channel impulse response data of a plurality of measurement points. It should be further considered that the channel path loss model in the embodiment of the present invention is applied to an air-ground communication scenario between the sky and the ground, and therefore, either end of the signal transmission and reception in the embodiment of the present invention should be disposed on the ground, and the other end should be disposed in the air.
It should be noted that the embodiments of the present invention do not limit which end of the signal transmitting end and the signal receiving end is located on the ground or in the sky, and the user may select the end according to the application requirement. In the embodiment of the invention, the arrangement mode that the signal transmitting end is arranged on the ground and the signal receiving end is arranged in the sky can be adopted, so that the test points are easy to arrange, and the distance and the elevation angle value between the signal transmitting end and the signal receiving end can be adjusted at will. The embodiment of the invention also does not limit the specific arrangement mode of the signal transmitting end on the ground, for example, the signal transmitting end can be arranged on the open space or the roof. Because the roof can effectively avoid the barrier to disturb, therefore in this application embodiment, signal transmission end can set up in the roof. The embodiment of the present invention also does not limit the specific arrangement manner of the signal receiving end in the sky, and for example, the signal receiving end may be suspended in the air or may be arranged on a flight device. Because the test points are easy to set on the flight equipment and the distance and the elevation angle value between the signal transmitting end and the signal receiving end can be adjusted at will, in the embodiment of the invention, the signal receiving end can be arranged on the flight equipment. The embodiment of the present invention does not limit the hardware devices used by the signal sending end and the signal receiving end, as long as the hardware device used by the signal sending end can send the sequence signal, and the hardware device used by the signal receiving end can receive and analyze the sequence signal.
The embodiment of the invention also does not limit the specific number of the measuring points, as long as the number of the channel impulse response data acquired at the measuring points can meet the precision requirement of the subsequent calculation. The embodiment of the invention also does not limit the distance and the elevation angle value of the measuring point relative to the signal sending end, and a user can set the distance and the elevation angle value of the measuring point relative to the signal sending end according to the actual application requirement. The embodiment of the present invention also does not limit the specific process of acquiring the channel impulse response data of the measurement point, for example, the flight device where the signal receiving end is located may fly according to a designated line, and a plurality of measurement points are set on the execution line, and the acquisition operation of the channel impulse response data is executed when the flight device flies to any measurement point, or the flight device where the signal receiving end is located may fly according to a designated line, and the acquisition operation of the channel impulse response data is executed at preset time intervals.
Further, since the channel impulse response is a basic characteristic reflecting the input and output of the channel system, in the embodiment of the present invention, the channel impulse response is calculated by the local signal sent by the signal sending end and the received signal received by the signal receiving end at the measurement point. The embodiment of the present invention does not limit the type of the local signal, and the user may refer to the related technology of the wireless communication signal and select the local signal according to the actual application requirement, for example, the local signal may be a pseudo-random sequence. It will be appreciated that the type of received signal corresponds to the type of local signal. The embodiment of the present invention also does not limit the specific calculation mode for calculating the channel impulse response by using the local signal and the received signal, and the user may refer to the correlation technique for calculating the impulse response, for example, the correlation technique may be superposition, or may be sliding correlation processing. The embodiment of the invention also does not limit the specific quantity of the channel impulse response data obtained by calculation by using the local signal and the received signal, as long as the quantity of the channel impulse response data can meet the precision requirement of subsequent calculation.
In one possible case, the process of obtaining channel impulse response data of a plurality of measurement points may include:
step 10: acquiring a local sequence signal of a signal transmitting point and a receiving sequence signal received by a measuring point;
step 11: and performing sliding correlation processing on the local sequence signal and the received sequence signal to obtain channel impulse response data.
It should be noted that, the embodiment of the present invention does not limit specific parameter values of the local sequence signal, such as sequence length, chip rate, carrier frequency, and the like, and a user may select the parameter values according to practical application requirements. The embodiment of the invention also does not limit the specific implementation mode of the sliding relevant processing, and a user can refer to the relevant technology of the sliding relevant processing.
Further, the embodiment of the present invention does not limit whether the channel impulse response data needs to be subjected to noise filtering. When effective data in the channel impulse response data can be effectively extracted or the channel impulse response data can meet the requirement of calculation precision, noise filtering processing can not be carried out on the channel impulse response data; when the calculation precision needs to be improved and the noise interference is eliminated, the noise filtering processing can be carried out on the channel impulse response data. Because the channel impulse response data contains noise, and the noise will reduce the calculation precision, the invention can filter the noise of the channel impulse response data. In addition, it is considered that the actual path loss value can be calculated by calculating the channel reception power of the signal receiving end using the channel impulse response and by using the channel transmission power data of the signal transmitting end. Therefore, in a possible case, the calculating the actual path loss value of each measurement point by using the channel impulse response data may include:
step 20: performing noise filtering processing on the channel impulse response data to obtain channel receiving power;
step 21: and calculating to obtain an actual path loss value by using the channel receiving power and the channel transmitting power data of the signal transmitting end.
When the channel receiving power is obtained, the actual path loss value can be calculated by using the existing channel transmitting power data. It should be noted that the embodiment of the present invention does not limit which channel transmission power is used for calculation, and may be, for example, any one or a combination of multiple channel transmission powers of a fixed output transmission power of a power amplifier at a transmitting end, an antenna gain at the transmitting end, an antenna gain at a receiving end, a low noise amplification gain, and a cable loss.
In a possible case, after obtaining the channel receiving power, the actual path loss value may be calculated by using the channel transmitting power formed by combining the fixed output transmitting power of the transmitting-end power amplifier, the antenna gain of the transmitting end, the antenna gain of the receiving end, the low-noise amplifier gain, and the cable loss, and the actual path loss value may be calculated by using the following formula:
L(d)＝PTx-PRx+GTx+GRx+GLNA-LLine
wherein L (d) refers to the path loss at d, PTxFor fixed output of transmitting power, P, of the transmitting terminal power amplifierRxFor receiving power for a channel, GTxFor transmit end antenna gain, GRxFor receiving end antenna gain, GLNAFor low noise amplification gain, LLineIs a cable loss.
It should be noted that, the embodiment of the present invention does not limit the specific way of noise filtering, and the user may refer to the related technology of signal noise filtering, for example, filter processing may be performed by using a filter function, or an initial power delay spectrum may be calculated by using a space alternation generalized expectation-maximization algorithm, and a threshold is set to filter an abnormal power delay spectrum, so as to obtain an effective power delay spectrum. Because the space alternation generalized expectation-maximization algorithm can fit the channel condition, and the calculation by the algorithm can improve the precision, the embodiment of the invention can calculate by adopting the space alternation generalized expectation-maximization algorithm to obtain the initial Power Delay spectrum, and set a threshold to filter the abnormal Power Delay spectrum to obtain the effective Power Delay spectrum, wherein the Power Delay spectrum is Power Delay Profile, which is referred to as PDP for short. The embodiment of the invention also does not limit whether the effective power time delay spectrum needs to be averagely calculated or not. When there is only one effective power delay spectrum, the average calculation is not needed, and when there are a plurality of effective power delay spectrums, the average calculation can be performed. In consideration of the fact that each measurement point may acquire a plurality of channel impulse response data and further may obtain a plurality of effective power delay spectrums, in the embodiment of the present invention, average calculation may be performed on the received power of a plurality of channels to improve the calculation accuracy.
In one possible case, performing noise filtering on the channel impulse response data to obtain channel received power may include:
step 30: performing noise filtering processing on the channel impulse response data to obtain an effective power time delay spectrum;
step 31: and carrying out average calculation on the effective power delay spectrum to obtain the channel receiving power.
S101, calculating to obtain a first elevation angle value and a first distance of the measuring point relative to the signal sending end by using the position information corresponding to the measuring point.
Since the embodiment of the present invention corrects the channel path loss model according to the elevation value, the elevation value and the distance of each measurement point with respect to the signal transmitting end need to be calculated, so as to perform the correction calculation subsequently. It should be noted that the first distance refers to a straight-line distance from the measurement point to the signal sending end.
It should be noted that, the embodiment of the present invention is not limited to a specific form of the location information, and for example, the location information may be GPS data, or may also be location information based on a coordinate system of the signal transmitting end. Because the GPS data is easy to obtain and it is convenient to calculate the elevation value and distance of the measurement point relative to the signal transmitting end, in the embodiment of the present invention, the location information of the measurement point may be GPS data. It is understood that in order to calculate the elevation value and the distance, the height information and the latitude and longitude information of the measurement point need to be acquired, and therefore, the GPS data at least should include the latitude and longitude information and the altitude information. The embodiment of the invention does not limit other contents in the GPS data, and the user can select the contents according to the actual application requirements.
Further, the embodiment of the present invention is not limited to a specific calculation method for calculating the first elevation value and the first distance of the measurement point relative to the signal sending end by using GPS data, for example, the calculation method may be to extract the GPS data of the signal sending end, calculate a vertical distance between the signal sending end and the measurement point in a vertical direction and a horizontal distance between the signal sending end and the measurement point in a horizontal plane, and calculate the first elevation value and the first distance of the measurement point relative to the signal sending end by using the vertical distance and the horizontal distance.
Further, the embodiment of the present invention does not limit whether the correlation between the actual path loss value and the elevation angle value needs to be determined after the actual path loss value and the corresponding elevation angle value are collected. When the collected actual path loss values can be ensured to have strong correlation with the elevation angle values, for example, at the position of the measuring point, the change of the elevation angle values has a large influence on the actual path loss values, and at this time, the correlation between the actual path loss values and the elevation angle values can not be judged; when the elevation angle value corresponding to the actual path loss value is any value and the path loss needs to be determined to be closely related to the elevation angle value, the correlation between the actual path loss value and the elevation angle value can be judged. Considering that the cause of the path loss is more, the correlation between the loss factor corresponding to the actual path loss value and the elevation angle value is possibly lower, and the calculation accuracy will be affected by using such data to perform the elevation angle correction, therefore, in the embodiment of the present invention, after the actual path loss value and the corresponding elevation angle value are collected, the correlation between the actual path loss value and the elevation angle value can be determined, so as to ensure that the loss factor of the example path loss value has a larger relationship with the elevation angle, and finally ensure the accuracy of the elevation angle correction of the channel path loss model. The embodiment of the present invention does not limit the specific process of determining the correlation between the path loss value and the elevation value of the example, and may, for example, calculate the correlation value between the actual path loss value and the elevation value, determine whether the absolute value of the correlation coefficient value is greater than a preset threshold, and determine that the actual path loss value is correlated with the elevation value when the absolute value of the correlation coefficient value is greater than the preset threshold.
In one possible case, after calculating the first elevation value and the first distance of the measurement point relative to the signal transmission point by using the position information corresponding to the measurement point, before calculating the elevation correction value of the channel path loss model by using the first elevation value, the first distance, and the path loss value, the method may further include:
step 40: calculating a correlation coefficient value using the first elevation value and the actual path loss value;
step 41: judging whether the absolute value of the correlation coefficient value is greater than a preset threshold value, if so, entering step 42; if not, go to step 43;
step 42: and calculating an elevation correction value of the channel path loss model by using the first elevation value, the first distance and the actual path loss value.
Step 43: the elevation correction value of the road path loss model is calculated without using the actual path loss value and the first elevation value.
It should be noted that, the embodiment of the present invention does not limit the specific calculation method of the correlation coefficient value, and the user may refer to the correlation technique for calculating the correlation coefficient. The embodiment of the present invention also does not limit what type of elevation value is used for the calculation of the correlation coefficient value, and the calculation may be, for example, an original elevation value or a logarithmic elevation value. Considering that the channel path loss model is mainly calculated in a logarithmic form, in the embodiment of the present invention, the correlation coefficient value may be calculated using a logarithmic elevation value.
In one possible case, calculating the correlation coefficient value using the first elevation value and the actual path loss value may include:
step 50: calculating a logarithmic elevation value using the first elevation value;
step 51: the correlation coefficient value is calculated using the log-elevation value and the actual path loss value.
In one possible case, the correlation value of the log-elevation value and the actual path loss value may be calculated using the following formula:
where ρ is the correlation value and L is the actual pathLoss value log10Theta is a logarithmic elevation value, where theta is tan-1(H/D), H denotes a vertical distance in a vertical direction from the signal transmitting end to the receiving end, and D denotes a horizontal distance in a horizontal plane from the signal transmitting end to the receiving end. Cov (log)10θ, L) is the covariance of the log-elevation value and the actual path loss value, Var [ log ]10θ]And Var [ L ]]The variance of the log-elevation value and the variance of the actual path loss value are respectively.
It should be noted that the embodiment of the present invention does not limit the specific calculation method of the covariance and the variance, and the user may refer to the correlation technique of calculating the covariance and calculating the variance.
S102, elevation angle correction data of the channel path loss model are calculated by utilizing the first elevation angle value, the first distance and the actual path loss value, and elevation angle correction is carried out on the channel path loss model by utilizing the elevation angle correction data.
It should be noted that the embodiment of the present invention does not limit the specific form of the elevation correction data, and may be, for example, an original fitting parameter term of the channel path loss model or a separate elevation correction term. Since the single elevation angle correction term has a better correction effect on the channel path loss model, the single elevation angle correction term can be adopted to correct the channel path loss model in the embodiment of the invention.
The embodiment of the present invention does not limit which kind of channel path loss model is subjected to the elevation correction, and may perform the elevation correction on a free space reference distance model or a logarithmic distance floating intercept model, for example.
In one possible case, the process of calculating elevation correction data for the channel path loss model using the first elevation value, the first distance, and the actual path loss value may include:
step 60: correcting the channel path loss model by using the initial elevation correction data;
step 61: and performing linear regression calculation on the corrected channel path loss model by using the first elevation value, the first distance and the actual path loss value to obtain elevation correction data.
The embodiment of the present invention does not limit the specific implementation manner of the linear regression calculation, and for example, the calculation may be performed by using a least square method or using gradient descent. Since the least square method is fast in calculation, the least square method may be used for linear regression calculation in the embodiment of the present invention.
The above elevation correction process is explained below with reference to specific examples.
The free space reference distance model can be represented using the following formula:
LCI(d)＝L0+10nlog10(d/d0)+Xσ
wherein L isCI(d) Representing the path loss calculated using a free space reference model at d distances, d0As a reference distance, L0Is d0Path loss at distance, L0＝20log10(4πd0λ), where λ is the wavelength.
n is a dimensionless path loss exponent. The dimensionless path loss exponent is calculated in embodiments of the invention using a minimum root mean square error criterion, i.e., n has a value such that E { ∑ L-L0-10nlog10(d/d0)]2The minimum value, where E is the numerical expectation. The embodiment of the invention does not limit the calculation method of the root mean square error, and a user can refer to the related technology for calculating the root mean square error.
XσA zero-mean gaussian random variable representing the standard deviation of shadow fading as σ, where σ can be calculated using the following equation:
wherein K is the number of measuring distances, L (d)i) Is diActual path loss value at distance, Lfit(di) Is diPath loss values from the fit at distance.
The logarithmic distance floating intercept model can be represented by the following formula:
LFI(d)＝α+10βlog10(d)+Xσ
wherein d represents the linear distance from the signal transmitting end to the signal receiving end, LFI(d) And (3) representing the path loss calculated by using a logarithmic distance floating intercept model under the d distance, wherein alpha and beta respectively represent the intercept and the slope of the logarithmic distance floating intercept model, and the linear regression calculation is carried out by using actual measurement data to obtain the linear regression model.
The elevation angle correction term adopted by the embodiment of the invention is gamma log10(θ), wherein log10And (theta) is a logarithmic elevation value, gamma is a correction coefficient of the logarithmic elevation value, and the correction coefficient is obtained by performing linear regression calculation by using actual measurement data.
The free space reference distance model after elevation correction is as follows:
Lf_CI(d,θ)＝L0+10nlog10(d/d0)+γlog10(θ)+Xσ
wherein L isf_CIAnd (d, theta) represents path loss calculated by using the free space reference distance model after elevation correction at the d distance and the theta elevation.
The logarithmic distance floating intercept model after elevation correction is as follows:
Lf_FI(d,θ)＝α+10βlog10(d)+γlog10(θ)+Xσ
wherein L isf_FIAnd (d, theta) represents path loss calculated by using the logarithmic distance floating intercept model after elevation angle correction at d distance and theta elevation angle.
The embodiment of the invention adopts a least square method to carry out linear regression operation. And performing least square calculation on the free space reference distance model after elevation correction and the logarithmic distance floating intercept model after elevation correction by using an actual path loss value and a corresponding elevation value to obtain a fitting parameter, and further obtaining a channel path loss model after elevation correction. It should be noted that, the embodiment of the present invention does not limit the specific implementation process of the least square method, and a user may refer to the related technology of the least square method calculation.
S103, calculating a channel path loss estimation value of an estimation point by using the channel path loss model after elevation correction and the parameters of the estimation point; the estimated point parameters include a second elevation value and a second distance of the estimated point relative to the transmit end of the signal.
After the elevation-corrected channel path loss model is obtained, the channel path loss model can be used for estimating the path loss in an air-ground communication scene between the sky and the ground so as to improve the reliability and the accuracy of the path loss in the air-ground communication scene.
It should be noted that the embodiment of the present invention does not limit whether the second elevation value and the second distance of the estimation point need to be within the elevation range and the distance range covered by the measurement point. Because the elevation correction is calculated by using the data of the measuring points, the fitting accuracy is highest in the elevation range and the distance range covered by the measuring points, and the estimation on the path loss is most accurate, so that in the embodiment of the invention, the second elevation value and the second distance of the estimation point can be in the elevation range and the distance range covered by the measuring points.
Based on the above embodiment, the present invention mainly performs elevation angle correction on a first elevation angle value between a signal transmitting end and a measurement point, collects a first distance and a first elevation angle value of the measurement point relative to the signal transmitting end in addition to collecting an actual path loss value of the measurement point, and calculates elevation angle correction data by using the actual path loss value, the first distance, and the first elevation angle value, to obtain a channel path loss model after elevation angle correction. Since the channel path loss between the signal transmitting end and the receiving end in the terrestrial communication is limited by the height difference, the channel path loss model in the related art does not consider the influence of the first elevation value on the channel path loss. However, in the air-ground communication scene between the sky and the ground, the signal transmitting end and the signal receiving end have larger span in the horizontal direction and the vertical direction, and the elevation angle between the signal transmitting end and the signal receiving end has larger influence on the channel path loss, so that the estimation accuracy of the channel path loss model in the air-ground communication scene can be effectively improved by correcting the channel path loss model by using the first elevation angle value.
Based on the above embodiments, the above channel path loss estimation method is described in detail below with reference to a specific embodiment.
1. Acquiring channel impulse response data of a plurality of measuring points, and calculating to obtain an actual path loss value of each measuring point by using the channel impulse response data.
In this embodiment, the signal transmitting terminal is disposed on the roof of a building, the height of the signal transmitting terminal is about 20m, and the signal receiving terminal is disposed on the helicopter and simultaneously configured to enable the helicopter to fly along a predetermined route. During measurement, a signal generator at a sending end sends a local pseudo-random sequence, a constant-envelope zero autocorrelation sequence with the sequence length of 4096 and the chip rate of 1Mcps is used as a baseband signal to be modulated onto a 150MHz carrier frequency, and the baseband signal is sent through a power amplifier and a columnar omnidirectional antenna, wherein Mcps (million chips per second) is the unit of the chip rate. The receiving end signal analyzer is used for oversampling and storing the receiving signal at the speed of 5 times through a receiving antenna and a low noise amplifier.
The method comprises the steps of carrying out sliding correlation processing on a received signal and a local pseudo-random sequence to obtain channel impulse response containing noise, and extracting effective multipath and instant Power Delay Profile (PDP) in the channel impulse response by utilizing a space alternating generalized expectation-maximization algorithm. And averaging the power of a plurality of PDPs obtained by each measuring point to obtain the received power of the measuring point. According to the formula:
L(d)＝PTx-PRx+GTx+GRx+GLNA-LLine
and calculating the path loss of each measuring point. Wherein L (d) refers to the path loss at d, PTxFor fixed output of transmitting power, P, of the transmitting terminal power amplifierRxFor the channel receiving power, GTxFor transmit end antenna gain, GRxFor receiving end antenna gain, GLNAFor low noise amplification gain, LLineIs a cable loss.
In one possible case, each measurement point obtains about 243 PDPs, and the received power P of the measurement point is obtained by setting a threshold to filter out the PDP with abnormal reception and then averaging the remaining PDP powersRx. Fixed output P of power amplifierTx44dBm, antenna gain G at the transmitting and receiving endsTx＝GRx-4dBi, low noise amplifier gain GLNA52.8dB, cable loss LLineWhere dBi is the unit of power gain referenced to the omni-directional antenna, and dBm represents a power decibel value of 1 milliwatt (mW) relative to the reference power.
2. And calculating to obtain a first elevation angle value and a first distance of the measuring point relative to the signal sending end by using the position information corresponding to the measuring point.
During measurement, the position information of a measuring point is stored through a GPS receiver, and the position information comprises longitude and latitude and altitude. And calculating to obtain a first elevation value and a first distance of the measuring point relative to the signal sending section by utilizing the longitude and latitude and the altitude of the measuring point and the longitude and the altitude of the signal sending point.
After the first elevation value and the actual path loss value are obtained, the correlation coefficient value of the logarithmic elevation value corresponding to the actual path loss value and the first elevation value can be calculated by using the formula:
where ρ is the correlation coefficient value, L is the actual path loss value, log10Theta is a logarithmic elevation value, where theta is tan-1(H/D), H denotes a vertical distance in a vertical direction from the signal transmitting end to the receiving end, and D denotes a horizontal distance in a horizontal plane from the signal transmitting end to the receiving end. Cov (log)10θ, L) is the covariance of the log-elevation value and the actual path loss value, Var [ log ]10θ]And Var [ L ]]The variance of the log-elevation value and the variance of the actual path loss value are respectively.
And performing elevation correction on the actual path loss value and the first elevation value of which the absolute value of the correlation coefficient value is greater than a preset threshold value. In one possible case, the predetermined threshold is 0.8, the correlation coefficient between the logarithmic elevation angle and the actual path loss is-0.8553, and the logarithmic elevation angle and the path loss are highly inversely correlated, so that the elevation angle correction can be performed using the logarithmic elevation angle and the actual path loss value.
3. And calculating elevation angle correction data of the path loss model of the signal path by using the first elevation angle value, the first distance and the actual path loss value, and performing elevation angle correction on the path loss model of the signal path by using the elevation angle correction data.
The invention utilizes an elevation angle correction term gamma log10(theta) performing elevation correction, wherein the free space reference distance model after elevation correction is as follows:
Lf_CI(d,θ)＝L0+10nlog10(d/d0)+γlog10(θ)+Xσ
the logarithmic distance floating intercept model after elevation correction is as follows:
Lf_FI(d,θ)＝α+10βlog10(d)+γlog10(θ)+Xσ
setting a reference distance d01m, L is calculated by the method described in the above example015.96, and 2.276. Obtaining other model parameters through least square fitting, and finally obtaining the expression of each model as shown in table 1:
table 1 model display table after fitting
4. Calculating the channel path loss estimation value of the estimation point by using the channel path loss model after elevation correction and the estimation point parameter; the estimated point parameters include a second elevation value and a second distance of the estimated point with respect to the signal transmitting end.
In a possible case, when the horizontal distance between the signal sending end and the signal receiving end is 800 meters, the height difference is 600 meters, the linear distance is 1000 meters, the elevation angle is about 36.87 degrees, and the logarithmic distance floating intercept model expression of elevation angle correction is substituted, so that the path loss of the position is about 74.20 dB.
To verify the effectiveness of the present invention, please refer to fig. 2, fig. 3, fig. 4 and fig. 5, in which fig. 2 and fig. 3 are a shadow fading histogram and a path loss fitting curve of a free space reference distance model according to an embodiment of the present invention, and fig. 4 and fig. 5 are a shadow fading histogram and a path loss fitting curve of an elevation angle corrected logarithmic distance floating intercept model according to an embodiment of the present invention. Table 2 gives a comparison of the performance of the four models. The elevation angle correction model has obvious performance improvement compared with the traditional model, wherein the elevation angle correction logarithmic distance floating intercept model has the advantages of minimum shadow fading standard deviation, highest fitting goodness and minimum residual square sum, has the best model performance and fully explains the effectiveness of the elevation angle correction model.
Table 2 table for comparing and displaying performance of each model
The following describes a channel path loss estimation device, an electronic device, and a storage medium according to embodiments of the present invention, and the channel path loss estimation device, the electronic device, and the storage medium described below and the channel path loss estimation method described above may be referred to correspondingly.
Referring to fig. 6, fig. 6 is a block diagram of a channel path loss estimation apparatus according to an embodiment of the present invention, where the apparatus may include:
an obtaining module 600, configured to obtain channel impulse response data of multiple measurement points, and calculate an actual path loss value of each measurement point by using the channel impulse response data;
the position relation calculation module 601 is configured to calculate, by using position information corresponding to the measurement point, a first elevation value and a first distance of the measurement point relative to the signal sending point;
a correction calculation module 602, configured to calculate elevation correction data of the channel path loss model by using the first elevation value, the first distance, and the actual path loss value, and obtain a channel path loss model after elevation correction;
an estimated value calculation module 603, configured to calculate a channel path loss estimated value of an estimation point by using the channel path loss model after elevation correction and the estimation point parameter; the estimation point parameters include a second elevation value and a second distance of the estimation point with respect to the signal transmitting end.
The method mainly aims at the first elevation angle value of a signal sending end and a measuring point to carry out elevation angle correction, collects the first distance and the first elevation angle value of the measuring point relative to the signal sending end besides collecting the actual path loss value of the measuring point, and calculates elevation angle correction data by utilizing the actual path loss value, the first distance and the first elevation angle value to obtain a channel path loss model after elevation angle correction. Since the channel path loss between the signal transmitting end and the receiving end in the terrestrial communication is limited by the height difference, the channel path loss model in the related art does not consider the influence of the first elevation value on the channel path loss. However, in the air-ground communication scene between the sky and the ground, the signal transmitting end and the signal receiving end have larger span in the horizontal direction and the vertical direction, and the elevation angle between the signal transmitting end and the signal receiving end has larger influence on the channel path loss, so that the estimation accuracy of the channel path loss model in the air-ground communication scene can be effectively improved by correcting the channel path loss model by using the first elevation angle value.
Optionally, the channel path loss estimation apparatus may further include:
the correlation coefficient calculation module is used for calculating a correlation coefficient value by utilizing the first elevation value and the actual path loss value;
the judging module is used for judging whether the absolute value of the correlation coefficient value is larger than a preset threshold value or not;
optionally, the correlation coefficient calculation module may include:
a logarithmic elevation value operator module for calculating a logarithmic elevation value using the first elevation value;
and the correlation coefficient calculation submodule is used for calculating the correlation coefficient value by utilizing the logarithmic elevation value and the actual path loss value.
Optionally, the obtaining module 600 may include:
the acquisition submodule is used for acquiring a local sequence signal of a signal sending point and a receiving sequence signal received by a measuring point;
and the sliding correlation processing submodule is used for executing sliding correlation processing on the local sequence signal and the received sequence signal to obtain channel impulse response data.
Optionally, the obtaining module 600 may include:
the noise filtering processing submodule is used for performing noise filtering processing on the channel impulse response data to obtain channel receiving power;
and the loss calculation submodule is used for calculating an actual path loss value by utilizing the channel receiving power and the channel transmitting power data of the signal transmitting end.
Optionally, the noise filtering processing sub-module may include:
the noise filtering processing unit is used for performing noise filtering processing on the channel impulse response data to obtain an effective power time delay spectrum;
and the power calculation unit is used for carrying out average calculation on the effective power delay spectrum to obtain the channel receiving power.
Optionally, the modification calculation module 602 may include:
the first correction submodule is used for correcting the channel path loss model by using the initial elevation correction data;
and the linear regression calculation submodule is used for performing linear regression calculation on the corrected channel path loss model by utilizing the first elevation value, the first distance and the actual path loss value to obtain elevation correction data.
And the second correction submodule is used for correcting the channel path loss model by using the elevation correction data to obtain the channel path loss model after elevation correction.
An embodiment of the present invention further provides an electronic device, including:
a memory for storing a computer program;
a processor for implementing the steps of the channel path loss estimation method as described above when executing a computer program.
Since the embodiment of the electronic device portion and the embodiment of the channel path loss estimation method portion correspond to each other, please refer to the description of the embodiment of the channel path loss estimation method portion for the embodiment of the electronic device portion, and details are not repeated here.
An embodiment of the present invention further provides a storage medium, where a computer program is stored on the storage medium, and when the computer program is executed by a processor, the steps of the channel path loss estimation method according to any of the above embodiments are implemented. If the computer program is executed by the processor, the channel impulse response data of a plurality of measuring points are obtained, and the actual path loss value of each measuring point is obtained by utilizing the channel impulse response data; calculating to obtain a first elevation angle value and a first distance of the measuring point relative to the signal transmitting end by using the position information corresponding to the measuring point; calculating elevation angle correction data of the channel path loss model by using the first elevation angle value, the first distance and the actual path loss value, and performing elevation angle correction on the channel path loss model by using the elevation angle correction data; calculating a channel path loss estimation value of an estimation point by using the channel path loss model after elevation correction and the parameters of the estimation point; the estimated point parameters include a second elevation value and a second distance of the estimated point relative to the transmit end of the signal.
Since the embodiment of the storage medium portion and the embodiment of the channel path loss estimation method portion correspond to each other, please refer to the description of the embodiment of the channel path loss estimation method portion for the embodiment of the storage medium portion, which is not repeated here.
The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The detailed description of the channel path loss estimation method, the channel path loss estimation device, the electronic device and the storage medium provided by the invention is provided above. The principles and embodiments of the present invention are explained herein using specific examples, which are presented only to assist in understanding the method and its core concepts. It should be noted that, for those skilled in the art, it is possible to make various improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the scope of the claims of the present invention.
Claims (10)
1. A method for channel path loss estimation, comprising:
acquiring channel impulse response data of a plurality of measuring points, and calculating by using the channel impulse response data to obtain an actual path loss value of each measuring point;
calculating to obtain a first elevation angle value and a first distance of the measuring point relative to a signal sending end by using the position information corresponding to the measuring point;
calculating elevation angle correction data of the path loss model of the signal path by using the first elevation angle value, the first distance and the actual path loss value, and performing elevation angle correction on the path loss model of the signal path by using the elevation angle correction data;
calculating the channel path loss estimation value of the estimation point by using the channel path loss model after elevation correction and the parameters of the estimation point; the estimated point parameters include a second elevation value and a second distance of the estimated point with respect to the signal transmitting end.
2. The channel path loss estimation method according to claim 1, further comprising, after calculating a first elevation value and a first distance of the measurement point with respect to a signal transmission point using the position information corresponding to the measurement point, before calculating an elevation correction value of the channel path loss model using the first elevation value, the first distance, and the path loss value:
calculating a correlation coefficient value using the first elevation value and the actual path loss value;
judging whether the absolute value of the correlation coefficient value is larger than a preset threshold value or not;
and if so, executing the step of calculating the elevation correction value of the confidence road path loss model by using the first elevation value, the first distance and the actual path loss value.
3. The method according to claim 2, wherein said calculating a correlation coefficient value using the first elevation value and the actual path loss value comprises:
calculating a logarithmic elevation value using the first elevation value;
calculating the correlation coefficient value using the log-elevation value and the actual path loss value.
4. The channel path loss estimation method of claim 1, wherein the obtaining channel impulse response data of a plurality of measurement points comprises:
acquiring a local sequence signal of the signal transmitting point and a receiving sequence signal received by the measuring point;
and performing sliding correlation processing on the local sequence signal and the received sequence signal to obtain the channel impulse response data.
5. The method of claim 1, wherein the calculating an actual pathloss value for each of the measurement points using the channel impulse response data comprises:
performing noise filtering processing on the channel impulse response data to obtain channel receiving power;
and calculating to obtain an actual path loss value by using the channel receiving power and the channel transmitting power data of the signal transmitting end.
6. The channel path loss estimation method of claim 5, wherein the performing the noise filtering on the channel impulse response data to obtain the channel received power comprises:
performing noise filtering processing on the channel impulse response data to obtain an effective power time delay spectrum;
and carrying out average calculation on the effective power time delay spectrum to obtain the channel receiving power.
7. The channel path loss estimation method according to any one of claims 1 to 6, wherein the calculating of elevation correction data of the confidence road path loss model using the first elevation value, the first distance, and the actual path loss value includes:
correcting the channel path loss model using initial elevation correction data;
and performing linear regression calculation on the corrected channel path loss model by using the first elevation value, the first distance and the actual path loss value to obtain the elevation correction data.
8. A channel path loss estimation apparatus, comprising:
the acquisition module is used for acquiring channel impulse response data of a plurality of measurement points and calculating to obtain an actual path loss value of each measurement point by using the channel impulse response data;
the position relation calculation module is used for calculating a first elevation value and a first distance of the measuring point relative to the signal sending point by using the position information corresponding to the measuring point;
the correction calculation module is used for calculating elevation correction data of the signal path loss model by utilizing the first elevation value, the first distance and the actual path loss value to obtain a channel path loss model after elevation correction;
the estimated value calculation module is used for calculating the estimated value of the channel path loss of the estimation point by utilizing the channel path loss model after the elevation angle correction and the parameters of the estimation point; the estimated point parameters include a second elevation value and a second distance of the estimated point with respect to the signal transmitting end.
9. An electronic device, comprising:
a memory for storing a computer program;
a processor for implementing the channel path loss estimation method according to any one of claims 1 to 7 when executing the computer program.
10. A storage medium having stored thereon computer-executable instructions which, when loaded and executed by a processor, carry out a channel path loss estimation method according to any one of claims 1 to 7.
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