WO2024001326A1 - 物理信道模拟方法、设备、信道模拟系统及存储介质 - Google Patents

物理信道模拟方法、设备、信道模拟系统及存储介质 Download PDF

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Publication number
WO2024001326A1
WO2024001326A1 PCT/CN2023/082907 CN2023082907W WO2024001326A1 WO 2024001326 A1 WO2024001326 A1 WO 2024001326A1 CN 2023082907 W CN2023082907 W CN 2023082907W WO 2024001326 A1 WO2024001326 A1 WO 2024001326A1
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channel
signal power
target
domain data
tap
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PCT/CN2023/082907
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English (en)
French (fr)
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甄露
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中兴通讯股份有限公司
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Publication of WO2024001326A1 publication Critical patent/WO2024001326A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/391—Modelling the propagation channel
    • H04B17/3912—Simulation models, e.g. distribution of spectral power density or received signal strength indicator [RSSI] for a given geographic region
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/391—Modelling the propagation channel
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/06—Testing, supervising or monitoring using simulated traffic
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • embodiments of the present disclosure provide a physical channel simulation method, which is applied to network equipment.
  • the method includes:
  • the frequency domain data of each terminal device in the target cell Obtain the frequency domain data of each terminal device in the target cell; generate multiple sets of channel feature values according to the frequency domain data, the multiple sets of channel feature values include channel feature values of physical channels corresponding to each of the terminal devices; convert the Multiple sets of channel feature values are sent to the channel simulation device, so that the channel simulation device determines a target channel feature value from the multiple sets of channel feature values, and performs channel simulation based on the target channel feature value.
  • embodiments of the present disclosure provide a physical channel simulation method, which is applied to channel simulation equipment.
  • the method includes:
  • inventions of the present disclosure also provide a network device.
  • the terminal device includes a processor, a memory, a computer program stored on the memory and executable by the processor, and a computer program for implementing the processor and
  • the memory The data bus communicates between the connections, and when the computer program is executed by the processor, the steps of the physical channel simulation method applied to the network device as described in any one of the disclosure descriptions are implemented.
  • embodiments of the present disclosure further provide a storage medium for computer-readable storage.
  • the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors. , to implement the steps of any one of the physical channel simulation methods applied to network equipment or the steps of any one of the physical channel simulation methods applied to channel simulation equipment provided in this disclosure.
  • Figure 2 is a schematic flowchart of a physical channel simulation method applied to a channel simulation device provided by an embodiment of the present disclosure
  • Figure 3 is a schematic structural block diagram of a network device provided by an embodiment of the present disclosure.
  • Figure 4 is a schematic structural block diagram of a channel simulation device provided by an embodiment of the present disclosure.
  • Figure 5 is a schematic structural block diagram of a channel simulation system provided by an embodiment of the present disclosure.
  • Industrial digital twin is a digital transformation methodology centered on the integration of data and models. It builds accurate digital mapping of physical objects in the digital space based on multiple types of modeling tools, and promotes closed-loop optimization of the entire industrial business process. As wireless communication systems become more and more complex, factors such as multiple manufacturer models, a wide number of devices, and dispersed locations have caused a significant increase in operation and maintenance costs, and the labor costs are even more expensive. For cells with abnormal indicators, in order to find out the cause of the abnormality, it is generally necessary to manually collect channel information on site. This is limited by the season, weather or geographical location of outdoor testing. In actual situations, Performing physical channel analysis is very difficult.
  • Embodiments of the present disclosure provide a physical channel simulation method, network equipment, channel simulation equipment, channel simulation system and storage medium. Among them, this construction method can be applied to network equipment, so that channel characteristic values can be accurately collected for channel simulation, which reduces labor costs and improves the efficiency of physical channel analysis.
  • FIG. 1 is a schematic flowchart of a physical channel simulation method provided by an embodiment of the present disclosure.
  • This physical channel simulation method can accurately collect channel characteristic values for channel simulation, which reduces labor costs and improves the efficiency of physical channel analysis.
  • This physical channel simulation method can be specifically applied to network equipment, and the network equipment can include Devices such as base stations that can obtain frequency domain data of each terminal device in the target cell.
  • the physical channel simulation method applied to network equipment includes steps S101 to S103.
  • Step S101 Obtain frequency domain data of each terminal device in the target cell.
  • a cell refers to an area covered by a base station or a part of a base station (sector antenna) in a cellular mobile communication system. In this area, mobile stations can reliably communicate with the base station through wireless channels.
  • the target cell is a cell corresponding to a channel characteristic value that needs to be collected.
  • the terminal device may be a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, etc., but is not limited thereto.
  • the base station issues a frequency domain data capture task to each terminal device under the target cell in the selected area. After receiving the frequency domain data capture task, each terminal device under the target cell , collect the corresponding frequency domain data and upload it to the base station, so that the base station can obtain the frequency domain data of each terminal device in the target cell.
  • Step S102 Generate multiple sets of channel feature values based on the frequency domain data, where the multiple sets of channel feature values include channel feature values of physical channels corresponding to each of the terminal devices.
  • the channel characteristic value is used to indicate the characteristic value of a physical channel, and each group of channel characteristic values respectively corresponds to the channel characteristic value of the physical channel corresponding to each of the terminal devices.
  • the channel characteristic values include multipath propagation parameters
  • the frequency domain data is processed using demodulation reference signals to obtain time domain data of each terminal device; according to the time domain data of the terminal device data, and generate a target channel tap corresponding to the time domain data and a multipath propagation parameter of the target channel tap.
  • the corresponding target channel tap and the multipath propagation parameters of the target channel tap can be accurately generated based on the frequency domain data.
  • the demodulation reference signal (Demodulation Reference Signal, DMRS) can be generated through a specific communication protocol and used to extract the pilot signal.
  • the demodulation reference signal can be generated through a specific communication protocol, and the corresponding communication protocol can be used for physical resource mapping, thereby extracting the pilot signal and processing to obtain each The time domain data of the terminal equipment; according to the time domain data of each terminal equipment, the target channel tap corresponding to the time domain data of each terminal equipment and the multipath propagation parameter of the target channel tap are generated.
  • the demodulation reference signal and the frequency domain data are subjected to conjugate multiplication and time domain transformation processing to obtain time domain data of each of the terminal devices.
  • frequency domain data can be accurately converted into time domain data, thereby facilitating the generation of corresponding target channel taps and multipath propagation parameters of the target channel taps.
  • the demodulation reference signal and the frequency domain data of each terminal device can be conjugated and multiplied first to obtain the target frequency domain data of each terminal device, and then the target frequency domain data of each terminal device can be quickly processed.
  • Fourier transform to obtain the time domain data of each terminal device.
  • the target frequency domain data is obtained by conjugate multiplication of the demodulation reference signal and the frequency domain data.
  • the conjugate multiplication of the demodulation reference signal and the frequency domain data of each terminal device can be expressed as:
  • the time domain transformation processing of the target frequency domain data can be expressed as:
  • t_d is the time domain.
  • the multipath propagation parameters of the channel tap include multipath power, multipath number, and multipath delay.
  • the time domain data of the terminal device is sampled and processed to obtain the time domain data corresponding to the time domain data. Multiple channel taps; calculate the signal power of the channel tap according to the time domain data; filter the signal power of each channel tap according to the signal power of the channel tap to obtain the target channel tap, and add the The signal power corresponding to the target channel tap is used as the multipath power; the number of the target channel taps is counted, and the number of the target channel taps is used as the number of multipaths; according to the position of the target channel tap and the time domain data, Determine the time delay corresponding to the target channel tap, and use the time delay corresponding to the target channel tap as the multipath delay.
  • the multipath power, multipath number and multipath delay can be accurately calculated, thereby extracting the channel characteristic value of the physical channel corresponding to each terminal device.
  • multipath effect is an important feature.
  • the radio wave propagation mechanism there are reflections, scattering, etc., and the signal reaching the receiving end can be understood as the superposition of channel characteristics of different paths.
  • Statistical analysis shows that using the tapped delay line model to simulate actual multipath channels is an important means. Different paths correspond to different average power and delay characteristics, which are then superimposed to form the overall channel characteristics. Therefore, the channel tap is expressed on the basis of the tapped delay line model, that is, the characteristics of each path used for modeling.
  • the target channel tap is obtained by filtering the signal power of each channel tap.
  • the target channel tap The channel characteristic values of the taps are used for channel simulation.
  • the time domain data of one of the terminal devices can be sampled and processed to obtain multiple channel taps; the signal power of the channel tap is calculated based on the time domain data; and the signal power of each channel tap is calculated based on the signal power of the channel tap. Filter the signal power of the channel taps to obtain the target channel tap, and use the signal power corresponding to the target channel tap as the multipath power; count the number of the target channel taps, and use the number of the target channel taps as the multipath power.
  • the number of paths according to the position of the target channel tap and the time domain data, determine the delay corresponding to the target channel tap, and use the delay corresponding to the target channel tap as the multipath delay, and use the terminal
  • the multipath power, multipath number and multipath delay corresponding to the device are used as the channel characteristic value of the physical channel corresponding to the terminal device, that is, a set of channel characteristic values.
  • the physical channel corresponding to each terminal device in the target cell is obtained.
  • channel characteristic values that is, multiple sets of channel characteristic values.
  • the number of antennas and the number of sequences of the demodulation reference signals are obtained; and based on the time domain data, the number of antennas and the number of sequences of the demodulation reference signals, the number of each channel tap is calculated. Signal power.
  • the number of antennas is the number of antennas of the network device.
  • calculating the signal power of the channel tap can be expressed as:
  • Pp is the signal power of the channel tap
  • T is the number of antennas
  • S is the number of sequences of the demodulation reference signal
  • time domain data is time domain data. Therefore, the signal power of each channel tap can be obtained through the above formula.
  • the preset signal power threshold can be determined according to actual conditions, and is not specifically limited here.
  • the number of preset channel taps can be determined according to actual conditions, such as 25, and is not specifically limited here.
  • each channel tap it is determined whether the signal power of each channel tap exceeds a preset signal power threshold; if there is a signal power of the channel tap that exceeds the preset signal power threshold, determine the channel whose signal power exceeds the preset signal power threshold. Number of taps; if the signal power of the channel tap does not exceed the preset signal power threshold, then the channel taps that do not exceed the preset signal power threshold are filtered out.
  • the preset number of channel taps is 25, and if the number of channel taps whose signal power exceeds the preset signal power threshold exceeds 25, then the first 25 channel taps with the largest signal power are retained as the target channel taps; if The number of channel taps whose signal power exceeds the preset signal power threshold does not exceed 25, and the number of channel taps which exceeds the preset signal power threshold is only 20, then these 20 channel taps whose signal power exceeds the preset signal power threshold are regarded as Target channel taps, so that the number of target channel taps can be counted, and the number of target channel taps is used as the number of multipaths.
  • the channel tap after calculating the signal power of each channel tap, determine the channel tap corresponding to the maximum signal power from the signal power of each channel tap; and determine the channel tap corresponding to the maximum signal power according to the maximum signal power. Normalize the signal power of each channel tap to obtain the target signal power of each channel tap; filter the signal power of each channel tap according to the target signal power of each channel tap to obtain the target channel tap. Therefore, by normalizing the signal power of each channel tap, the target channel tap can be screened more accurately.
  • the target signal power is obtained by normalizing the signal power of the channel tap.
  • the channel tap corresponding to the maximum signal power can be determined from the signal power of each channel tap, and the position of the channel tap corresponding to the maximum signal power can be determined. According to the maximum The signal power normalizes the signal power of each channel tap to obtain the target signal power of each channel tap; finally, the target signal power is used to filter the signal power of each channel tap to obtain the target channel tap. Compared with directly using the signal power of each channel tap for screening, the target channel tap can be screened more accurately and conveniently.
  • P p is the signal power of the channel tap
  • t_d is the time domain
  • P max is the maximum signal power
  • L max is the maximum signal The position of the channel tap corresponding to the power.
  • the signal power of each channel tap is normalized according to the maximum signal power, and the target signal power of each channel tap can be obtained by a formula:
  • the target signal power of the channel tap is the target signal power of the channel tap.
  • the target signal power of each channel tap can be calculated using the above formula.
  • the interference noise window positions L low and L up it is necessary to obtain the interference noise window positions L low and L up first, and then determine the channel tap position based on the interference noise window position and the number of channel taps.
  • L S is the position of the channel tap
  • L low and L up are the interference noise window positions
  • L total is the number of channel taps
  • mod is the modulo processing.
  • the preset signal power threshold at this time can be set according to the actual situation or determined by the interference noise power.
  • the interference noise power is determined based on the number of channel taps and the signal power of each channel tap, and then the preset signal power threshold is determined based on the interference noise power.
  • the preset signal power threshold is generally n times the interference noise power, and n can be 2 or 3, etc.
  • the interference noise power can be determined by the number of channel taps and the signal power of each channel tap, which can be expressed as:
  • P N is the interference noise power
  • L total is the number of channel taps.
  • the delay corresponding to the target channel tap is determined, and The delay corresponding to the target channel tap is used as the multipath delay.
  • Determining the delay corresponding to the channel tap can be expressed as:
  • fftsize 1 is the fft size converted from the time domain to the frequency domain
  • fftsize 2 is the number of fft points converted from the pilot to the time domain
  • T is the time corresponding to the channel tap.
  • Step S103 Send the multiple sets of channel characteristic values to a channel simulation device, so that the channel simulation device determines a target channel characteristic value from the multiple sets of channel characteristic values, and performs channel simulation based on the target channel characteristic value.
  • the channel simulation equipment may include network management equipment, cloud computing centers, edge computing centers and other equipment capable of channel simulation.
  • the target channel characteristic value is used to perform channel simulation using channel simulation equipment to establish a digital twin model of the physical channel of the cell in the area, or to perform real-time modeling after channel simulation using the channel simulation equipment to select an uplink channel suitable for the area.
  • SU MIMO Single-User Multiple-InputMultiple-Output
  • the multiple groups of channel feature values may be clustered through a clustering algorithm, and the centroid of the cluster with the largest number of markers after clustering and a proportion exceeding a preset percentage of the total number is selected as the target channel feature value.
  • the clustering algorithm includes SVM (support vector machine) algorithm, KNN (nearest neighbor method) algorithm, Decision Tree (decision tree classification) algorithm, Naive Bayes (naive Bayes classification) algorithm, Neural Networks (neural network) Algorithms etc.
  • SVM support vector machine
  • KNN nearest neighbor method
  • Decision Tree decision tree classification
  • Naive Bayes Naive Bayes classification
  • Neural Networks Neural network Algorithms etc.
  • K-Means Clustering K-means Clustering
  • the preset percentage can be set according to actual conditions and is not specifically limited here.
  • the multiple groups of channel feature values may be clustered using a clustering algorithm, and the centroid of the cluster with the largest number of markers after clustering and accounting for more than 50% of the total number is selected as the target channel feature value.
  • FIG. 2 is a schematic flowchart of a physical channel simulation method provided by an embodiment of the present disclosure.
  • This physical channel simulation method can accurately collect channel characteristic values for channel simulation, which reduces labor costs and improves the efficiency of physical channel analysis.
  • This physical channel simulation method can be specifically applied to channel simulation equipment.
  • the channel simulation equipment It can include network management equipment, cloud computing centers, edge computing centers and other equipment that can be used for channel simulation.
  • the physical channel simulation method applied to channel simulation equipment includes steps S201 to S202.
  • Step S201 Receive multiple sets of channel feature values sent by the network device.
  • the multiple sets of channel feature values are generated by the network device based on frequency domain data of each terminal device in the target cell.
  • the multiple sets of channel feature values include each set of channel feature values.
  • a cell refers to an area covered by a base station or a part of a base station (sector antenna) in a cellular mobile communication system. In this area, mobile stations can reliably communicate with the base station through wireless channels.
  • the target cell is a cell corresponding to a channel characteristic value that needs to be collected.
  • the terminal device may be a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, etc., but is not limited thereto.
  • the channel characteristic value is used to indicate the characteristic value of a physical channel, and each group of channel characteristic values respectively corresponds to the channel characteristic value of the physical channel corresponding to each of the terminal devices.
  • the channel characteristic values include multipath propagation parameters
  • the frequency domain data can be analyzed using demodulation reference signals. Processing is performed to obtain the time domain data of each terminal device; and based on the time domain data of the terminal device, a target channel tap corresponding to the time domain data and a multipath propagation parameter of the target channel tap are generated.
  • Step S202 Determine a target channel characteristic value from the plurality of sets of channel characteristic values, and perform channel simulation based on the target channel characteristic value.
  • the target channel characteristic value is used to use channel simulation equipment to perform channel simulation, thereby establishing a physical channel digital twin model of the community in the area, or to use the channel simulation equipment to perform real-time modeling after channel simulation, and select the one suitable for the area.
  • Uplink single-user multiple-input multiple-output technology Single-User Multiple-InputMultiple-Output, SU MIMO
  • Single-User Multiple-InputMultiple-Output, SU MIMO single and dual stream switching threshold.
  • clustering processing and centroid calculation are performed on the multiple sets of channel feature values, and the channel feature value corresponding to the centroid is used as the target channel feature value, so that the target channel can be determined from the multiple sets of channel feature values.
  • Eigenvalues to improve the accuracy of channel simulation.
  • clustering processing is to classify sample types into a certain category based on certain attributes or certain types of features of the sample (multiple types of features can be integrated).
  • the multiple groups of channel feature values may be clustered through a clustering algorithm, and the centroid of the cluster with the largest number of markers after clustering and a proportion exceeding a preset percentage of the total number is selected as the target channel feature value.
  • the clustering algorithm includes SVM (support vector machine) algorithm, KNN (nearest neighbor method) algorithm, Decision Tree (decision tree classification) algorithm, Naive Bayes (naive Bayes classification) algorithm, Neural Networks (neural network) Algorithms etc.
  • SVM support vector machine
  • KNN nearest neighbor method
  • Decision Tree decision tree classification
  • Naive Bayes Naive Bayes classification
  • Neural Networks Neural network Algorithms etc.
  • K-Means Clustering K-means Clustering
  • the preset percentage can be set according to actual conditions and is not specifically limited here.
  • the multiple groups of channel feature values may be clustered using a clustering algorithm, and the centroid of the cluster with the largest number of markers after clustering and accounting for more than 50% of the total number is selected as the target channel feature value.
  • the preset path and the multi-stream switching threshold can be selected.
  • the path power determines the power difference of each of the paths; the single- and double-flow switching threshold is determined based on the preset path weight and the power difference of each of the paths.
  • the path number 2-4 can be used as the corresponding preset path, and the power difference and the preset path weight of each path can be obtained, and a weighted sum can be performed to calculate the single- and double-stream switching threshold.
  • threshold is the single- and dual - stream switching threshold,
  • the right proportion corresponding to the power difference of the path, ⁇ P i is the power difference of each path.
  • FIG. 3 is a schematic structural block diagram of a network device provided by an embodiment of the present disclosure.
  • the network device 300 may include a processor 301 and a memory 302.
  • the processor 301 and the memory 302 are connected through a bus 303, such as an I2C (Inter-integrated Circuit) bus.
  • I2C Inter-integrated Circuit
  • the processor 301 can be used to provide computing and control capabilities to support the operation of the entire terminal device.
  • the processor 301 can be a central processing unit (Central Processing Unit, CPU).
  • the processor 301 can also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC). ), Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
  • the general processor may be a microprocessor or the processor may be any conventional processor.
  • the memory 302 may be a Flash chip, a read-only memory (ROM, Read-Only Memory) disk, an optical disk, a U disk or a mobile hard disk, etc.
  • ROM Read-Only Memory
  • the memory 302 may be a Flash chip, a read-only memory (ROM, Read-Only Memory) disk, an optical disk, a U disk or a mobile hard disk, etc.
  • FIG. 3 is only a block diagram of a partial structure related to the embodiments of the present disclosure, and does not constitute a limitation on the terminal equipment to which the embodiments of the present disclosure are applied.
  • the terminal device may include more or fewer components than shown in the figures, or combine certain components, or have a different arrangement of components.
  • the processor 301 is configured to run a computer program stored in the memory, and implement any of the physical channel simulation methods provided by the embodiments of the present disclosure when executing the computer program.
  • the processor 301 is used to run a computer program stored in the memory, and implement the following steps when executing the computer program:
  • the frequency domain data of each terminal device in the target cell Obtain the frequency domain data of each terminal device in the target cell; generate multiple sets of channel feature values according to the frequency domain data, the multiple sets of channel feature values include channel feature values of physical channels corresponding to each of the terminal devices; convert the Multiple sets of channel feature values are sent to the channel simulation device, so that the channel simulation device determines a target channel feature value from the multiple sets of channel feature values, and performs channel simulation based on the target channel feature value.
  • the channel characteristic values include multipath propagation parameters.
  • the processor 301 When the processor 301 generates multiple sets of channel characteristic values according to the frequency domain data, the processor 301 is configured to: use a demodulation reference signal to The frequency domain data is processed to obtain the time domain data of each terminal device; and based on the time domain data of the terminal device, a target channel tap corresponding to the time domain data and a multipath propagation parameter of the target channel tap are generated.
  • the processor 301 when the processor 301 uses the demodulation reference signal to process the frequency domain data to obtain the time domain data of each of the terminal devices, the processor 301 is configured to: convert the demodulation reference signal to Perform conjugate multiplication and time domain transformation processing with the frequency domain data to obtain time domain data of each terminal device.
  • the multipath propagation parameters of the channel tap include multipath power, multipath number and multipath delay.
  • the processor 301 generates the time domain data according to the time domain data of the terminal device.
  • the target channel tap corresponding to the domain data and the multipath propagation parameter of the target channel tap are used to implement: perform sampling processing on the time domain data of the terminal device to obtain multiple channel taps corresponding to the time domain data; Calculate the signal power of the channel tap according to the time domain data; filter the signal power of each channel tap according to the signal power of the channel tap to obtain a target channel tap, and obtain the target channel tap corresponding to
  • the signal power is used as multipath power; the number of target channel taps is counted, and the number of target channel taps is used as the number of multipaths; the target channel is determined according to the position of the target channel tap and the time domain data
  • the delay corresponding to the tap, and the delay corresponding to the tap of the target channel is regarded as the multipath delay.
  • the processor 301 implements the filtering of the signal power of each channel tap to obtain the target When the channel tap is marked, it is used to: determine whether the signal power of each channel tap exceeds the preset signal power threshold, and determine the number of channel taps whose signal power exceeds the preset signal power threshold; if the signal power exceeds the preset signal power threshold, Assume that the number of channel taps with the signal power threshold exceeds the preset number of channel taps, then retain the channel taps corresponding to the preset number of channel taps as the target channel taps; if the number of channel taps with the signal power exceeding the preset signal power threshold does not exceed the preset number If the number of channel taps is determined, the channel tap whose signal power exceeds the preset signal power threshold is regarded as the target channel tap.
  • the processor 301 when calculating the signal power of the channel tap based on the time domain data, is configured to: obtain the number of antennas and the number of sequences of the demodulation reference signal; The signal power of each channel tap is calculated based on the time domain data, the number of antennas, and the number of sequences of the demodulation reference signal.
  • the processor 301 is configured to: determine the channel tap corresponding to the maximum signal power from the signal power of each channel tap; according to the The maximum signal power normalizes the signal power of each of the channel taps to obtain the target signal power of each of the channel taps; and filters the signal power of each of the channel taps according to the target signal power of each of the channel taps. , get the target channel tap.
  • FIG. 4 is a schematic structural block diagram of a channel simulation device provided by an embodiment of the present disclosure.
  • the channel simulation device 400 may include a processor 401 and a memory 402.
  • the processor 401 and the memory 402 are connected through a bus 403, such as an I2C (Inter-integrated Circuit) bus.
  • I2C Inter-integrated Circuit
  • the memory 402 may be a Flash chip, a read-only memory (ROM, Read-Only Memory) disk, an optical disk, a U disk or a mobile hard disk, etc.
  • ROM Read-Only Memory
  • the memory 402 may be a Flash chip, a read-only memory (ROM, Read-Only Memory) disk, an optical disk, a U disk or a mobile hard disk, etc.
  • FIG. 3 is only a block diagram of a partial structure related to the embodiments of the present disclosure, and does not constitute a limitation on the terminal equipment to which the embodiments of the present disclosure are applied.
  • the terminal device may include more or fewer components than shown in the figures, or combine certain components, or have a different arrangement of components.
  • the processor 401 is used to run a computer program stored in the memory, and implement any of the physical channel simulation methods provided by the embodiments of the present disclosure when executing the computer program.
  • the processor 401 is used to run a computer program stored in the memory, and implement the following steps when executing the computer program:
  • Receive multiple sets of channel feature values sent by the network device are generated by the network device based on frequency domain data of each terminal device in the target cell.
  • the multiple sets of channel feature values include each of the terminal devices.
  • the channel characteristic value of the corresponding physical channel determine the target channel characteristic value from the plurality of sets of channel characteristic values, and perform channel simulation based on the target channel characteristic value.
  • the processor 401 when determining the target channel feature value from the multiple sets of channel feature values, is configured to: perform clustering processing and centroid calculation on the multiple sets of channel feature values, and The channel characteristics corresponding to the centroid are The eigenvalue is used as the target channel characteristic value.
  • the target channel characteristic value includes multipath power.
  • the processor 401 is configured to: according to the preset path and the multipath power Determine the power difference of each of the paths; determine the single- and double-stream switching threshold according to the preset path weight and the power difference between each of the paths.
  • FIG. 5 is a schematic structural block diagram of a channel simulation system provided by an embodiment of the present disclosure.
  • an embodiment of the present disclosure also provides a channel simulation system 500.
  • the channel simulation system 500 includes the network device 300 provided by the present disclosure and the channel simulation device 400 provided by the present disclosure.
  • Embodiments of the present disclosure also provide a storage medium for computer-readable storage.
  • the storage medium stores one or more programs.
  • the one or more programs can be executed by one or more processors to implement the following:
  • the embodiments of this disclosure describe the steps of any physical channel simulation method provided.
  • the storage medium may be an internal storage unit of the terminal device described in the previous embodiment, such as a hard disk or memory of the terminal device.
  • the storage medium may also be an external storage device of the terminal device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), or a secure digital (Secure Digital, SD) card equipped on the terminal device. Flash Card, etc.

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Abstract

本公开实施例提供一种物理信道模拟方法、网络设备、信道模拟设备、信道模拟系统及存储介质，属于通信技术领域。该方法包括：获取目标小区中各终端设备的频域数据；根据频域数据生成多组信道特征值，多组信道特征值包括各终端设备对应的物理信道的信道特征值；将多组信道特征值发送至信道模拟设备，以使信道模拟设备从多组信道特征值中确定目标信道特征值，并通过目标信道特征值进行信道模拟。

Description

物理信道模拟方法、设备、信道模拟系统及存储介质
相关申请的交叉引用
本公开基于2022年6月28日提交的发明名称为“物理信道模拟方法、设备、信道模拟系统及存储介质”的中国专利申请CN202210742462.5，并且要求该专利申请的优先权，通过引用将其所公开的内容全部并入本公开。
技术领域
本公开涉及通信技术领域，尤其涉及一种物理信道模拟方法、网络设备、信道模拟设备、信道模拟系统及存储介质。
背景技术
对于出现指标异常的小区情况，为了找出异常原因，一般需要人工现场采集信道信息，受限于室外测试的季节、天气或者地理位置等原因，在实际情况下进行物理信道分析是非常困难的。为了节省运维费用，简化人力上站采集数据的流程，推动了真实无线信道采集的自动化，构建物理信道在实时的数字化映射。
现有方法可以利用模拟实际条件的模拟装置来模拟信道。但这种方式在采集信道特征时无法利用现有的基站装置进行采集，仍然需要部署大量设备，且耗费大量成本进行信道特征采集，同时采集到的信道特征一般仅用于评估测试无线通信设备性能，不适宜大规模的应用场景。
发明内容
本公开实施例的主要目的在于提供一种物理信道模拟方法、网络设备、信道模拟设备及存储介质，旨在通过模拟无线信道的方法采集到信道特征值以进行信道模拟，降低了人力成本，提高了物理信道分析的效率。
第一方面，本公开实施例提供一种物理信道模拟方法，应用于网络设备，该方法包括：
获取目标小区中各终端设备的频域数据；根据所述频域数据生成多组信道特征值，所述多组信道特征值包括各所述终端设备对应的物理信道的信道特征值；将所述多组信道特征值发送至信道模拟设备，以使所述信道模拟设备从所述多组信道特征值中确定目标信道特征值，并通过所述目标信道特征值进行信道模拟。
第二方面，本公开实施例提供一种物理信道模拟方法，应用于信道模拟设备，该方法包括：
接收网络设备发送的多组信道特征值，所述多组信道特征值是所述网络设备根据目标小区中各终端设备的频域数据生成的，所述多组信道特征值包括各所述终端设备对应的物理信道的信道特征值；从所述多组信道特征值中确定目标信道特征值，并通过所述目标信道特征值进行信道模拟。
第三方面，本公开实施例还提供一种网络设备，该终端设备包括处理器、存储器、存储在所述存储器上并可被所述处理器执行的计算机程序以及用于实现所述处理器和所述存储器 之间的连接通信的数据总线，其中所述计算机程序被所述处理器执行时，实现如本公开说明书提供的任一项所述应用在网络设备的物理信道模拟方法的步骤。
第四方面，本公开实施例还提供一种信道模拟设备，所述终端设备包括处理器、存储器、存储在所述存储器上并可被所述处理器执行的计算机程序以及用于实现所述处理器和所述存储器之间的连接通信的数据总线，其中所述计算机程序被所述处理器执行时，实现如本公开说明书提供的任一项所述应用在信道模拟设备的物理信道模拟方法的步骤。
第五方面，本公开实施例还提供一种信道模拟系统，所述信道模拟系统包括本公开说明书提供的网络设备和本公开说明书提供的信道模拟设备。
第六方面，本公开实施例还提供一种存储介质，用于计算机可读存储，所述存储介质存储有一个或者多个程序，所述一个或者多个程序可被一个或者多个处理器执行，以实现如本公开说明书提供的任一项所述应用在网络设备的物理信道模拟方法的步骤或任一项所述应用在信道模拟设备的物理信道模拟方法的步骤。
附图说明
为了更清楚地说明本公开实施例技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图是本公开的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本公开实施例提供的一种应用在网络设备的物理信道模拟方法的流程示意图；
图2为本公开实施例提供的一种应用在信道模拟设备的物理信道模拟方法的流程示意图；
图3为本公开实施例提供的一种网络设备的结构示意性框图；
图4为本公开实施例提供的一种信道模拟设备的结构示意性框图；
图5为本公开实施例提供的一种信道模拟系统的结构示意性框图。
具体实施方式
下面将结合本公开实施例中的附图，对本公开实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本公开一部分实施例，而不是全部的实施例。基于本公开中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本公开保护的范围。
附图中所示的流程图仅是示例说明，不是必须包括所有的内容和操作/步骤，也不是必须按所描述的顺序执行。例如，有的操作/步骤还可以分解、组合或部分合并，因此实际执行的顺序有可能根据实际情况改变。
应当理解，在此本公开说明书中所使用的术语仅仅是出于描述特定实施例的目的而并不意在限制本公开。如在本公开说明书和所附权利要求书中所使用的那样，除非上下文清楚地指明其它情况，否则单数形式的“一”、“一个”及“该”意在包括复数形式。
工业数字孪生是一种以数据与模型的集成融合为核心的数字化转型方法论，基于多类建模工具在数字空间构建物理对象的精准数字化映射，推动工业全业务流程的闭环优化。随着无线通信系统越来越复杂，厂商型号多、设备数量广、位置分散等因素造成运维成本大幅增长，人力成本更是花费惊人。对于存在指标异常的小区情况，为了找出异常原因，一般需要人工现场采集信道信息，受限于室外测试的季节、天气或者地理位置等原因，在实际情况下 进行物理信道分析是非常困难的。
本公开实施例提供一种物理信道模拟方法、网络设备、信道模拟设备、信道模拟系统及存储介质。其中，该构建方法可应用于网络设备中，由此可以准确地采集到信道特征值以进行信道模拟，降低了人力成本，提高了物理信道分析的效率。
请参照图1，图1为本公开实施例提供的一种物理信道模拟方法的流程示意图。该物理信道模拟方法可以准确地采集到信道特征值以进行信道模拟，降低了人力成本，提高了物理信道分析的效率，该物理信道模拟方法具体可以应用于网络设备中，所述网络设备可以包括基站等能够获取目标小区中各终端设备的频域数据的设备。
如图1所示，该应用在网络设备的物理信道模拟方法包括步骤S101至步骤S103。
步骤S101、获取目标小区中各终端设备的频域数据。
其中，小区是指在蜂窝移动通信系统中，其中的一个基站或基站的一部分(扇形天线)所覆盖的区域，在这个区域内移动台可以通过无线信道可靠地与基站进行通信。所述目标小区为需要采集信道特征值对应的小区。所述终端设备可以是智能手机、平板电脑、笔记本电脑、台式计算机、智能音箱、智能手表等，但并不局限于此。
具体地，以网络设备为基站为例，基站向所选区域内的目标小区下的各个终端设备下发频域数据抓数任务，目标小区下的各个终端设备接收到频域数据抓数任务后，采集对应的频域数据并上传基站，从而使基站获取到目标小区中各终端设备的频域数据。
步骤S102、根据所述频域数据生成多组信道特征值，所述多组信道特征值包括各所述终端设备对应的物理信道的信道特征值。
其中，所述信道特征值用于指示物理信道的特征值，各组信道特征值分别对应各所述终端设备对应的物理信道的信道特征值。
在一些实施例中，所述信道特征值包括多径传播参数，利用解调参考信号对所述频域数据进行处理，得到各所述终端设备的时域数据；根据所述终端设备的时域数据，生成所述时域数据对应的目标信道抽头以及所述目标信道抽头的多径传播参数。由此可以准确地根据频域数据生成对应的目标信道抽头以及目标信道抽头的多径传播参数。
其中，所述解调参考信号(Demodulation Reference Signal，DMRS)可以通过特定的通信协议生成的，用于对提取导频信号。
具体地，获取目标小区中各终端设备的频域数据后，可以通过特定的通信协议生成解调参考信号，并利用对应的通信协议进行物理资源映射，从而提取导频信号，并进行处理得到各终端设备的时域数据；根据各终端设备的时域数据，生成各终端设备的时域数据对应的目标信道抽头以及所述目标信道抽头的多径传播参数。
在一些实施例中，将所述解调参考信号和所述频域数据进行共轭相乘以及时域变换处理，得到各所述终端设备的时域数据。由此可以准确地将频域数据转换为时域数据，从而便于生成对应的目标信道抽头以及目标信道抽头的多径传播参数。
具体地，可以先将所述解调参考信号和各终端设备的频域数据进行共轭相乘，分别得到各终端设备的目标频域数据，再分别对各终端设备的目标频域数据进行快速傅里叶变换，从而得到各终端设备的时域数据。所述目标频域数据为所述解调参考信号和所述频域数据进行共轭相乘而得到的。
其中，抓取的频域数据的信号模型如下：ya，r，s＝ha，r，ssr，s+nia，r，s；ya，r，s为频域数据，ha，r，s为 信道特征，nia，r，s为干扰及噪声，sr，s为解调参考信号。将所述解调参考信号和各终端设备的频域数据进行共轭相乘可以用公式表示为：
其中，为目标频域数据，对目标频域数据进行时域变换处理可以用公式表示为：
其中，为时域数据，a为天线索引，r为Re索引，s为符号索引，p表示时域抽头索引，t_d为时域。
在一些实施例中，所述信道抽头的多径传播参数包括多径功率、多径数目和多径时延，对所述终端设备的时域数据进行采样处理，得到所述时域数据对应的多个信道抽头；根据所述时域数据，计算所述信道抽头的信号功率；根据所述信道抽头的信号功率对各所述信道抽头的信号功率进行筛选，得到目标信道抽头，并将所述目标信道抽头对应的信号功率作为多径功率；统计所述目标信道抽头的数量，并将所述目标信道抽头的数量作为多径数目；根据所述目标信道抽头的位置和所述时域数据，确定所述目标信道抽头对应的时延，并将所述目标信道抽头对应的时延作为多径时延。由此可以准确地计算得到多径功率、多径数目和多径时延，从而提取到各终端设备对应的物理信道的信道特征值。
其中，在无线信道建模中，多径效应是重要特征，根据无线电波传播机制，存在反射，散射等，到达接收端的信号，可以理解为不同路径的信道特性的叠加。统计分析表明，用抽头延迟线模型，仿真实际多径信道，是一个重要手段。不同路径，对应不同的平均功率和时延表征，然后叠加，形成整体的信道特性。因此所述信道抽头是在抽头延迟线模型的基础上表述，即建模用的每一径的特性，所述目标信道抽头是对各信道抽头的信号功率进行筛选而得到的，所述目标信道抽头的信道特征值用于进行信道模拟。
具体地，可以对其中一个终端设备的时域数据进行采样处理，得到多个信道抽头；根据所述时域数据，计算所述信道抽头的信号功率；根据所述信道抽头的信号功率对各所述信道抽头的信号功率进行筛选，得到目标信道抽头，并将所述目标信道抽头对应的信号功率作为多径功率；统计所述目标信道抽头的数量，并将所述目标信道抽头的数量作为多径数目；根据所述目标信道抽头的位置和所述时域数据，确定所述目标信道抽头对应的时延，并将所述目标信道抽头对应的时延作为多径时延，并将该终端设备对应的多径功率、多径数目和多径时延作为该终端设备对应的物理信道的信道特征值，即一组信道特征值，以此类推，得到目标小区中各终端设备对应的物理信道的信道特征值，即多组信道特征值。
在一些实施例中，获取天线数量以及所述解调参考信号的序列数量；根据所述时域数据、所述天线数量以及所述解调参考信号的序列数量，计算得到各所述信道抽头的信号功率。
其中，所述天线数量为网络设备的天线数量。
具体地，计算信道抽头的信号功率可以用公式表示为：
其中，Pp为信道抽头的信号功率，T为天线数量，S为解调参考信号的序列数量，为时域数据。故可以通过上述公式得到各所述信道抽头的信号功率。
在一些实施例中，确定各所述信道抽头的信号功率是否超过预设信号功率阈值，并确定所述信号功率超过预设信号功率阈值的信道抽头数量；若所述信号功率超过预设信号功率阈值的信道抽头数量超过预设信道抽头数量，则保留预设信道抽头数量对应的信道抽头作为目标信道抽头；若所述信号功率超过预设信号功率阈值的信道抽头数量未超过预设信道抽头数量，则将所述信号功率超过预设信号功率阈值的信道抽头作为目标信道抽头。由此可以筛选得到最适合进行信道模拟的信道抽头的多径传播参数作为信道特征值。
其中，所述预设信号功率阈值可以根据实际情况确定，在此不做具体限定，所述预设信道抽头数量可以根据实际情况确定，比如25个，在此不做具体限定。
具体地，确定各所述信道抽头的信号功率是否超过预设信号功率阈值；若存在所述信道抽头的信号功率超过预设信号功率阈值，则确定所述信号功率超过预设信号功率阈值的信道抽头数量；若所述信道抽头的信号功率未超过预设信号功率阈值，则将未超过预设信号功率阈值的信道抽头筛选掉。
示例性的，若预设信道抽头数量为25个，若所述信号功率超过预设信号功率阈值的信道抽头数量超过25个，则保留信号功率最大的前25个信道抽头作为目标信道抽头；若所述信号功率超过预设信号功率阈值的信道抽头数量未超过25个，超过预设信号功率阈值的信道抽头数量只有20个，则将这20个信号功率超过预设信号功率阈值的信道抽头作为目标信道抽头，从而可以统计目标信道抽头的数量，并将所述目标信道抽头的数量作为多径数目。
在一些实施例中，在计算各所述信道抽头的信号功率之后，从各所述信道抽头的信号功率中，确定最大信号功率对应的信道抽头；根据所述最大信号功率对各所述信道抽头的信号功率进行归一化处理，得到各所述信道抽头的目标信号功率；根据各所述信道抽头的目标信号功率对各所述信道抽头的信号功率进行筛选，得到目标信道抽头。由此可以通过对各信道抽头的信号功率进行归一化处理，能够更准确地筛选得到目标信道抽头。
其中，所述目标信号功率为信道抽头的信号功率进行归一化处理得到的。
具体地，计算各所述信道抽头的信号功率，可以从各所述信道抽头的信号功率中，确定最大信号功率对应的信道抽头，并确定最大信号功率对应的信道抽头的位置，根据所述最大信号功率对各所述信道抽头的信号功率进行归一化处理，得到各所述信道抽头的目标信号功率；最后利用目标信号功率对各所述信道抽头的信号功率进行筛选，得到目标信道抽头。相较于与直接利用各信道抽头的信号功率进行筛选，能够更准确便捷地筛选得到目标信道抽头。
其中，查找最大信号功率对应的信道抽头可以用公式表示为：
其中，Pp为信道抽头的信号功率，t_d为时域，Pmax为最大信号功率，Lmax为最大信号 功率对应的信道抽头的位置。
根据所述最大信号功率对各所述信道抽头的信号功率进行归一化处理，得到各所述信道抽头的目标信号功率可以用公式表示为：
其中，为信道抽头的目标信号功率，具体可以使用上述公式计算得到各信道抽头的目标信号功率。
具体地，在获取各个信道抽头的位置前，需要先获取干扰噪声窗位置为Llow，Lup，再根据干扰噪声窗位置和信道抽头个数确定信道抽头的位置。
确定信道抽头的位置可以用公式表示为：
LS＝mod(Lmax+Lup：Lmax+Llow，Ltotal)
其中，LS为信道抽头的位置，Llow和Lup为干扰噪声窗位置，Ltotal为信道抽头个数，mod为取模处理。
由于此时是利用目标信号功率对各信道抽头的信号功率进行筛选，从而得到目标信道抽头，因此对应的预设信号功率阈值自然也不同。此时的预设信号功率阈值可以根据实际情况设置，也可以通过干扰噪声功率确定。
具体地，通过信道抽头个数和各信道抽头的信号功率确定干扰噪声功率，再根据干扰噪声功率确定预设信号功率阈值。示例性的，预设信号功率阈值一般为干扰噪声功率n倍，n可以为2或3等。
通过信道抽头个数和各信道抽头的信号功率确定干扰噪声功率可以用公式表示为：
其中，PN为干扰噪声功率，Ltotal为信道抽头个数。
具体地，由于所述时域数据是频域数据通过快速傅里叶变换得到的，因此时域数据包括频域数据的fft点数即时域转频域的fft大小以及导频转换到时域的fft点数，再根据所述目标信道抽头的位置确定目标信道抽头的位置与最大信号功率对应的信道抽头的距离。最后根据目标信道抽头的位置与最大信号功率对应的信道抽头的距离、时域转频域的fft大小和导频转换到时域的fft点数，确定所述目标信道抽头对应的时延，并将所述目标信道抽头对应的时延作为多径时延。
确定信道抽头对应的时延可以用公式表示为：
其中，为信道抽头的位置与最大信号功率对应的信道抽头的距离，fftsize1为时域转频域的fft大小，fftsize2为导频转换到时域的fft点数，T为信道抽头对应的时间。
步骤S103、将所述多组信道特征值发送至信道模拟设备，以使所述信道模拟设备从所述多组信道特征值中确定目标信道特征值，并通过所述目标信道特征值进行信道模拟。
其中，所述信道模拟设备可以包括网络管理设备、云计算中心、边缘计算中心等能够用于信道模拟的设备。所述目标信道特征值用于利用信道模拟设备进行信道模拟，从而建立该区域小区的物理信道数字孪生模型，或，利用信道模拟设备信道模拟后进行实时建模，选定适用于该区域的上行单用户多入多出技术(Single-User Multiple-InputMultiple-Output，SU MIMO)单双流切换门限。
在一些实施例中，对所述多组信道特征值进行聚类处理以及质心计算，并将所述质心对应的信道特征值作为目标信道特征值，从而可以从多组信道特征值中确定目标信道特征值，提高信道模拟的准确性。
其中，聚类处理是根据样本某些属性或某类特征(可以融合多类特征)，把样本类型归为已确定的某一类别中。
具体地，可以通过聚类算法对所述多组信道特征值进行聚类处理，选择聚类后标记数量最多且占比超过总数预设百分比的聚类簇质心作为该目标信道特征值。
其中，所述聚类算法包括SVM(支持向量机)算法、KNN(最邻近法)算法、Decision Tree(决策树分类)算法、Naive Bayes(朴素贝叶斯分类)算法、Neural Networks(神经网络)算法等。但当对海量数据进行分类时，为了降低数据满足分类算法要求所需要的预处理代价，往往需要选择非监督学习的聚类算法，如K-Means Clustering(K均值聚类)等。所述预设百分比可以根据实际情况设定，在此不作具体限定。
示例性的，可以通过聚类算法对所述多组信道特征值进行聚类处理，选择聚类后标记数量最多且占比超过总数50％的聚类簇质心作为该目标信道特征值。
请参照图2，图2为本公开实施例提供的一种物理信道模拟方法的流程示意图。该物理信道模拟方法可以准确地采集到信道特征值以进行信道模拟，降低了人力成本，提高了物理信道分析的效率，该物理信道模拟方法具体可以应用于信道模拟设备中，所述信道模拟设备可以包括网络管理设备、云计算中心、边缘计算中心等能够用于信道模拟的设备。
如图2所示，该应用在信道模拟设备的物理信道模拟方法包括步骤S201至步骤S202。
步骤S201、接收网络设备发送的多组信道特征值，所述多组信道特征值是所述网络设备根据目标小区中各终端设备的频域数据生成的，所述多组信道特征值包括各所述终端设备对应的物理信道的信道特征值。
其中，小区是指在蜂窝移动通信系统中，其中的一个基站或基站的一部分(扇形天线)所覆盖的区域，在这个区域内移动台可以通过无线信道可靠地与基站进行通信。所述目标小区为需要采集信道特征值对应的小区。所述终端设备可以是智能手机、平板电脑、笔记本电脑、台式计算机、智能音箱、智能手表等，但并不局限于此。所述信道特征值用于指示物理信道的特征值，各组信道特征值分别对应各所述终端设备对应的物理信道的信道特征值。
示例性的，所述信道特征值包括多径传播参数，可以利用解调参考信号对所述频域数据 进行处理，得到各所述终端设备的时域数据；根据所述终端设备的时域数据，生成所述时域数据对应的目标信道抽头以及所述目标信道抽头的多径传播参数。
生成多组信道特征值的具体过程详见步骤S101-步骤102。
步骤S202、从所述多组信道特征值中确定目标信道特征值，并通过所述目标信道特征值进行信道模拟。
其中，所述目标信道特征值用于利用信道模拟设备进行信道模拟，从而建立该区域小区的物理信道数字孪生模型，或，利用信道模拟设备信道模拟后进行实时建模，选定适用于该区域的上行单用户多入多出技术(Single-User Multiple-InputMultiple-Output，SU MIMO)单双流切换门限。
在一些实施例中，对所述多组信道特征值进行聚类处理以及质心计算，并将所述质心对应的信道特征值作为目标信道特征值，从而可以从多组信道特征值中确定目标信道特征值，提高信道模拟的准确性。
其中，聚类处理是根据样本某些属性或某类特征(可以融合多类特征)，把样本类型归为已确定的某一类别中。
具体地，可以通过聚类算法对所述多组信道特征值进行聚类处理，选择聚类后标记数量最多且占比超过总数预设百分比的聚类簇质心作为该目标信道特征值。
其中，所述聚类算法包括SVM(支持向量机)算法、KNN(最邻近法)算法、Decision Tree(决策树分类)算法、Naive Bayes(朴素贝叶斯分类)算法、Neural Networks(神经网络)算法等。但当对海量数据进行分类时，为了降低数据满足分类算法要求所需要的预处理代价，往往需要选择非监督学习的聚类算法，如K-Means Clustering(K均值聚类)等。所述预设百分比可以根据实际情况设定，在此不作具体限定。
示例性的，可以通过聚类算法对所述多组信道特征值进行聚类处理，选择聚类后标记数量最多且占比超过总数50％的聚类簇质心作为该目标信道特征值。
在一些实施例中，以利用信道模拟设备信道模拟后进行实时建模，选定适用于该区域的上行单用户多入多出技术单双流切换门限为例，可以根据预设路径和所述多径功率确定各所述路径的功率差；根据预设的路径权重和各所述路径的功率差确定单双流切换门限。
其中，所述预设路径可以根据用户需求确定，所述预设的路径权重也可以根据用户需求确定，从而为各路径得功率差分配对应的权重比例。
具体地，可以取径数2-4作为对应的预设路径，并获取各所述路径的功率差以及预设的路径权重，进行加权求和，从而计算得到单双流切换门限。
计算得到单双流切换门限可以用公式表示为：
threshold＝υX
其中，threshold为单双流切换门限，X为总功率差，即各路径的功率差进行加权求和后得到的结果，v为预设的调优参数，具体可以根据实际情况设置，αi为各路径的功率差对应的权利比例，ΔPi为各路径的功率差。从而可以准确地计算得到单双流切换门限。
需要说明的是，此处仅以计算得到单双流切换门限作为示例，还可以利用目标信道特征 值计算得到任何参数。
请参阅图3，图3为本公开实施例提供的一种网络设备的结构示意性框图。
如图3所示，网络设备300可以包括处理器301和存储器302，处理器301和存储器302通过总线303连接，该总线比如为I2C(Inter-integrated Circuit)总线。
在一示例性的实施方式中，处理器301可以用于提供计算和控制能力，支撑整个终端设备的运行。处理器301可以是中央处理单元(Central Processing Unit，CPU)，该处理器301还可以是其他通用处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现场可编程门阵列(Field-Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。其中，通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
具体地，存储器302可以是Flash芯片、只读存储器(ROM，Read-Only Memory)磁盘、光盘、U盘或移动硬盘等。
本领域技术人员可以理解，图3中示出的结构，仅仅是与本公开实施例方案相关的部分结构的框图，并不构成对本公开实施例方案所应用于其上的终端设备的限定，具体的终端设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
其中，处理器301用于运行存储在存储器中的计算机程序，并在执行所述计算机程序时实现本公开实施例提供的任意一种所述的物理信道模拟方法。
在一实施例中，处理器301用于运行存储在存储器中的计算机程序，并在执行所述计算机程序时实现如下步骤：
获取目标小区中各终端设备的频域数据；根据所述频域数据生成多组信道特征值，所述多组信道特征值包括各所述终端设备对应的物理信道的信道特征值；将所述多组信道特征值发送至信道模拟设备，以使所述信道模拟设备从所述多组信道特征值中确定目标信道特征值，并通过所述目标信道特征值进行信道模拟。
在一实施例中，所述信道特征值包括多径传播参数，处理器301在实现所述根据所述频域数据生成多组信道特征值时，用于实现：利用解调参考信号对所述频域数据进行处理，得到各所述终端设备的时域数据；根据所述终端设备的时域数据，生成所述时域数据对应的目标信道抽头以及所述目标信道抽头的多径传播参数。
在一实施例中，处理器301在实现所述利用解调参考信号对所述频域数据进行处理，得到各所述终端设备的时域数据时，用于实现：将所述解调参考信号和所述频域数据进行共轭相乘以及时域变换处理，得到各所述终端设备的时域数据。
在一实施例中，所述信道抽头的多径传播参数包括多径功率、多径数目和多径时延，处理器301在实现所述根据所述终端设备的时域数据，生成所述时域数据对应的目标信道抽头以及所述目标信道抽头的多径传播参数时，用于实现：对所述终端设备的时域数据进行采样处理，得到所述时域数据对应的多个信道抽头；根据所述时域数据，计算所述信道抽头的信号功率；根据所述信道抽头的信号功率对各所述信道抽头的信号功率进行筛选，得到目标信道抽头，并将所述目标信道抽头对应的信号功率作为多径功率；统计所述目标信道抽头的数量，并将所述目标信道抽头的数量作为多径数目；根据所述目标信道抽头的位置和所述时域数据，确定所述目标信道抽头对应的时延，并将所述目标信道抽头对应的时延作为多径时延。
在一实施例中，处理器301在实现所述对各所述信道抽头的信号功率进行筛选，得到目 标信道抽头时，用于实现：确定各所述信道抽头的信号功率是否超过预设信号功率阈值，并确定所述信号功率超过预设信号功率阈值的信道抽头数量；若所述信号功率超过预设信号功率阈值的信道抽头数量超过预设信道抽头数量，则保留预设信道抽头数量对应的信道抽头作为目标信道抽头；若所述信号功率超过预设信号功率阈值的信道抽头数量未超过预设信道抽头数量，则将所述信号功率超过预设信号功率阈值的信道抽头作为目标信道抽头。
在一实施例中，处理器301在实现所述根据所述时域数据，计算所述信道抽头的信号功率时，用于实现：获取天线数量以及所述解调参考信号的序列数量；根据所述时域数据、所述天线数量以及所述解调参考信号的序列数量，计算得到各所述信道抽头的信号功率。
在一实施例中，处理器301在所述计算各所述信道抽头的信号功率之后，用于实现：从各所述信道抽头的信号功率中，确定最大信号功率对应的信道抽头；根据所述最大信号功率对各所述信道抽头的信号功率进行归一化处理，得到各所述信道抽头的目标信号功率；根据各所述信道抽头的目标信号功率对各所述信道抽头的信号功率进行筛选，得到目标信道抽头。
需要说明的是，所属领域的技术人员可以清楚地了解到，为了描述的方便和简洁，上述描述的终端设备的具体工作过程，可以参考前述物理信道模拟方法实施例中的对应过程，在此不再赘述。
请参阅图4，图4为本公开实施例提供的一种信道模拟设备的结构示意性框图。
如图4所示，信道模拟设备400可以包括处理器401和存储器402，处理器401和存储器402通过总线403连接，该总线比如为I2C(Inter-integrated Circuit)总线。
在一示例性的实施方式中，处理器401可以用于提供计算和控制能力，支撑整个终端设备的运行。处理器401可以是中央处理单元(Central Processing Unit，CPU)，该处理器401还可以是其他通用处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现场可编程门阵列(Field-Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。其中，通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
具体地，存储器402可以是Flash芯片、只读存储器(ROM，Read-Only Memory)磁盘、光盘、U盘或移动硬盘等。
本领域技术人员可以理解，图3中示出的结构，仅仅是与本公开实施例方案相关的部分结构的框图，并不构成对本公开实施例方案所应用于其上的终端设备的限定，具体的终端设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
其中，处理器401用于运行存储在存储器中的计算机程序，并在执行所述计算机程序时实现本公开实施例提供的任意一种所述的物理信道模拟方法。
在一实施例中，处理器401用于运行存储在存储器中的计算机程序，并在执行所述计算机程序时实现如下步骤：
接收网络设备发送的多组信道特征值，所述多组信道特征值是所述网络设备根据目标小区中各终端设备的频域数据生成的，所述多组信道特征值包括各所述终端设备对应的物理信道的信道特征值；从所述多组信道特征值中确定目标信道特征值，并通过所述目标信道特征值进行信道模拟。
在一实施例中，处理器401在实现所述从所述多组信道特征值中确定目标信道特征值时，用于实现：对所述多组信道特征值进行聚类处理以及质心计算，并将所述质心对应的信道特 征值作为目标信道特征值。
在一实施例中，所述目标信道特征值包括多径功率，处理器401在实现所述通过所述目标信道特征值进行信道模拟时，用于实现：根据预设路径和所述多径功率确定各所述路径的功率差；根据预设的路径权重和各所述路径间的功率差确定单双流切换门限。
需要说明的是，所属领域的技术人员可以清楚地了解到，为了描述的方便和简洁，上述描述的终端设备的具体工作过程，可以参考前述物理信道模拟方法实施例中的对应过程，在此不再赘述。
请参阅图5，图5为本公开实施例提供的一种信道模拟系统的结构示意性框图。
如图5所示，本公开实施例还提供一种信道模拟系统500，信道模拟系统500包括本公开说明书提供的网络设备300和本公开说明书提供的信道模拟设备400。
在一实施例中，网络设备300用于获取目标小区中各终端设备的频域数据；根据所述频域数据生成多组信道特征值，所述多组信道特征值包括各所述终端设备对应的物理信道的信道特征值；将所述多组信道特征值发送至信道模拟设备，以使所述信道模拟设备从所述多组信道特征值中确定目标信道特征值，并通过所述目标信道特征值进行信道模拟。
在一实施例中，信道模拟设备400用于接收网络设备发送的多组信道特征值，所述多组信道特征值是所述网络设备根据目标小区中各终端设备的频域数据生成的，所述多组信道特征值包括各所述终端设备对应的物理信道的信道特征值；从所述多组信道特征值中确定目标信道特征值，并通过所述目标信道特征值进行信道模拟。
本公开实施例还提供一种存储介质，用于计算机可读存储，所述存储介质存储有一个或者多个程序，所述一个或者多个程序可被一个或者多个处理器执行，以实现如本公开实施例说明书提供的任一项物理信道模拟方法的步骤。
其中，所述存储介质可以是前述实施例所述的终端设备的内部存储单元，例如所述终端设备的硬盘或内存。所述存储介质也可以是所述终端设备的外部存储设备，例如所述终端设备上配备的插接式硬盘，智能存储卡(Smart Media Card，SMC)，安全数字(Secure Digital，SD)卡，闪存卡(Flash Card)等。
本领域普通技术人员可以理解，上文中所公开方法中的全部或某些步骤、系统、装置中的功能模块/单元可以被实施为软件、固件、硬件及其适当的组合。在硬件实施例中，在以上描述中提及的功能模块/单元之间的划分不一定对应于物理组件的划分；例如，一个物理组件可以具有多个功能，或者一个功能或步骤可以由若干物理组件合作执行。某些物理组件或所有物理组件可以被实施为由处理器，如中央处理器、数字信号处理器或微处理器执行的软件，或者被实施为硬件，或者被实施为集成电路，如专用集成电路。这样的软件可以分布在计算机可读介质上，计算机可读介质可以包括计算机存储介质(或非暂时性介质)和通信介质(或暂时性介质)。如本领域普通技术人员公知的，术语计算机存储介质包括在用于存储信息(诸如计算机可读指令、数据结构、程序模块或其他数据)的任何方法或技术中实施的易失性和非易失性、可移除和不可移除介质。计算机存储介质包括但不限于RAM、ROM、EEPROM、闪存或其他存储器技术、CD-ROM、数字多功能盘(DVD)或其他光盘存储、磁盒、磁带、磁盘存储或其他磁存储装置、或者可以用于存储期望的信息并且可以被计算机访问的任何其他的介质。此外，本领域普通技术人员公知的是，通信介质通常包含计算机可读指令、数据结构、程序模块或者诸如载波或其他传输机制之类的调制数据信号中的其他数据，并且可包 括任何信息递送介质。
应当理解，在本公开说明书和所附权利要求书中使用的术语“和/或”是指相关联列出的项中的一个或多个的任何组合以及所有可能组合，并且包括这些组合。需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者系统不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者系统所固有的要素。在没有更多限制的情况下，由语句“包括一个......”限定的要素，并不排除在包括该要素的过程、方法、物品或者系统中还存在另外的相同要素。
上述本公开实施例序号仅仅为了描述，不代表实施例的优劣。以上所述，仅为本公开的具体实施例，但本公开的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本公开揭露的技术范围内，可轻易想到各种等效的修改或替换，这些修改或替换都应涵盖在本公开的保护范围之内。因此，本公开的保护范围应以权利要求的保护范围为准。

Claims (14)

  1. 一种物理信道模拟方法，应用于网络设备，所述方法包括：
    获取目标小区中各终端设备的频域数据；
    根据所述频域数据生成多组信道特征值，所述多组信道特征值包括各所述终端设备对应的物理信道的信道特征值；
    将所述多组信道特征值发送至信道模拟设备，以使所述信道模拟设备从所述多组信道特征值中确定目标信道特征值，并通过所述目标信道特征值进行信道模拟。
  2. 根据权利要求1所述的方法，其中，所述信道特征值包括多径传播参数，所述根据所述频域数据生成多组信道特征值，包括：
    利用解调参考信号对所述频域数据进行处理，得到各所述终端设备的时域数据；
    根据所述终端设备的时域数据，生成所述时域数据对应的目标信道抽头以及所述目标信道抽头的多径传播参数。
  3. 根据权利要求2所述的方法，其中，所述利用解调参考信号对所述频域数据进行处理，得到各所述终端设备的时域数据，包括：
    将所述解调参考信号和所述频域数据进行共轭相乘以及时域变换处理，得到各所述终端设备的时域数据。
  4. 根据权利要求2所述的方法，其中，所述信道抽头的多径传播参数包括多径功率、多径数目和多径时延，所述根据所述终端设备的时域数据，生成所述时域数据对应的目标信道抽头以及所述目标信道抽头的多径传播参数，包括：
    对所述终端设备的时域数据进行采样处理，得到所述时域数据对应的多个信道抽头；
    根据所述时域数据，计算所述信道抽头的信号功率；
    根据所述信道抽头的信号功率对各所述信道抽头的信号功率进行筛选，得到目标信道抽头，并将所述目标信道抽头对应的信号功率作为多径功率；
    统计所述目标信道抽头的数量，并将所述目标信道抽头的数量作为多径数目；
    根据所述目标信道抽头的位置和所述时域数据，确定所述目标信道抽头对应的时延，并将所述目标信道抽头对应的时延作为多径时延。
  5. 根据权利要求4所述的方法，其中，所述对各所述信道抽头的信号功率进行筛选，得到目标信道抽头，包括：
    确定各所述信道抽头的信号功率是否超过预设信号功率阈值，并确定所述信号功率超过预设信号功率阈值的信道抽头数量；
    若所述信号功率超过预设信号功率阈值的信道抽头数量超过预设信道抽头数量，则保留预设信道抽头数量对应的信道抽头作为目标信道抽头；
    若所述信号功率超过预设信号功率阈值的信道抽头数量未超过预设信道抽头数量，则将所述信号功率超过预设信号功率阈值的信道抽头作为目标信道抽头。
  6. 根据权利要求4所述的方法，其中，所述根据所述时域数据，计算所述信道抽头的信号功率，包括：
    获取天线数量以及所述解调参考信号的序列数量；
    根据所述时域数据、所述天线数量以及所述解调参考信号的序列数量，计算得到各所述 信道抽头的信号功率。
  7. 根据权利要求4所述的方法，其中，在所述计算各所述信道抽头的信号功率之后，还包括：
    从各所述信道抽头的信号功率中，确定最大信号功率对应的信道抽头；
    根据所述最大信号功率对各所述信道抽头的信号功率进行归一化处理，得到各所述信道抽头的目标信号功率；
    根据各所述信道抽头的目标信号功率对各所述信道抽头的信号功率进行筛选，得到目标信道抽头。
  8. 一种物理信道模拟方法，应用于信道模拟设备，所述方法包括：
    接收网络设备发送的多组信道特征值，所述多组信道特征值是所述网络设备根据目标小区中各终端设备的频域数据生成的，所述多组信道特征值包括各所述终端设备对应的物理信道的信道特征值；
    从所述多组信道特征值中确定目标信道特征值，并通过所述目标信道特征值进行信道模拟。
  9. 根据权利要求8所述的方法，其中，所述从所述多组信道特征值中确定目标信道特征值，包括：
    对所述多组信道特征值进行聚类处理以及质心计算，并将所述质心对应的信道特征值作为目标信道特征值。
  10. 根据权利要求8所述的方法，其中，所述目标信道特征值包括多径功率，所述通过所述目标信道特征值进行信道模拟，包括：
    根据预设路径和所述多径功率确定各所述路径的功率差；
    根据预设的路径权重和各所述路径间的功率差确定单双流切换门限。
  11. 一种网络设备，所述网络设备包括：
    处理器、存储器、存储在所述存储器上并可被所述处理器执行的计算机程序以及用于实现所述处理器和所述存储器之间的连接通信的数据总线，其中所述计算机程序被所述处理器执行时，实现如权利要求1至7中任一项所述应用在网络设备的物理信道模拟方法的步骤。
  12. 一种信道模拟设备，所述信道模拟设备包括：
    处理器、存储器、存储在所述存储器上并可被所述处理器执行的计算机程序以及用于实现所述处理器和所述存储器之间的连接通信的数据总线，其中所述计算机程序被所述处理器执行时，实现如权利要求8至10中任一项所述应用在信道模拟设备的物理信道模拟方法的步骤。
  13. 一种信道模拟系统，所述信道模拟系统包括如权利要求11所述的网络设备和如权利要求12所述的信道模拟设备。
  14. 一种存储介质，用于计算机可读存储，所述存储介质存储有一个或者多个程序，所述一个或者多个程序可被一个或者多个处理器执行，以实现如权利要求1至7中任一项所述应用在网络设备的物理信道模拟方法或如权利要求8至10中任一项所述应用在信道模拟设备的物理信道模拟方法的步骤。
PCT/CN2023/082907 2022-06-28 2023-03-21 物理信道模拟方法、设备、信道模拟系统及存储介质 WO2024001326A1 (zh)

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