Signal processing method, device and equipment based on directional orbit vector field environment

Abstract

The invention provides a signal processing method, device and equipment based on a directional orbit vector field environment, and the method comprises the steps: obtaining initial signal data in a communication network, and carrying out the preprocessing of the initial signal data, and obtaining target signal data; mapping the target signal data to a directional orbit vector field according to the at least one piece of position information to obtain reference vector context data; determining a target analysis area in the directional orbit vector field, and determining first vector contextual data located in the target analysis area from the reference vector contextual data; determining second vector context data corresponding to each signal source according to the first vector context data, and determining aggregation feature information corresponding to each signal source according to the second vector context data; and displaying the aggregation feature information corresponding to each signal source through the directional orbit vector field. The technical problem that in the prior art, feature information of different signal sources is difficult to effectively distinguish, and consequently the feature information presentation effect of the signal sources is poor is solved.

Description

Technical Field

[0001] This disclosure relates to the field of wireless communication technology, and in particular to a signal processing method, apparatus and device based on a directional orbit vector field environment. Background Technology

[0002] In mobile testing scenarios, a "directional track vector field" can be defined separately based on the constraints of movement. The characteristics of a "directional track vector field" include: extremely low degrees of freedom of motion, limited to the track direction; structured and highly regular vector distribution; frequent use of dedicated network coverage; and applications such as high-speed railways and urban rail transit. In wireless communication networks, the visualization of signal coverage is crucial for network optimization.

[0003] Signal representation methods in related technologies mainly rely on two-dimensional map displays from Geographic Information Systems (GIS), using colors or icons to represent signal strength. However, it is difficult to effectively distinguish the characteristic information of different signal sources, resulting in poor representation of signal source characteristic information. Summary of the Invention

[0004] This disclosure aims to at least partially address one of the technical problems in the related art.

[0005] To this end, this disclosure proposes a signal processing method, apparatus, electronic device, computer-readable storage medium, and computer program product based on a directional orbital vector field environment, which can effectively distinguish the feature information of different signal sources and improve the presentation effect of the feature information of signal sources.

[0006] The first aspect of this disclosure proposes a signal processing method based on a directional orbit vector field environment, comprising: acquiring initial signal data in a communication network and preprocessing the initial signal data to obtain target signal data, wherein the target signal data includes at least one location information; mapping the target signal data to a directional orbit vector field based on the at least one location information to obtain reference vector field data; determining a target analysis region in the directional orbit vector field and determining first vector field data located within the target analysis region from the reference vector field data; determining second vector field data corresponding to each signal source based on the first vector field data and determining aggregated feature information corresponding to each signal source based on the second vector field data; and displaying the aggregated feature information corresponding to each signal source through the directional orbit vector field. A second aspect of this disclosure provides a signal processing apparatus based on a directional orbit vector field environment, comprising: an acquisition module for acquiring initial signal data in a communication network and preprocessing the initial signal data to obtain target signal data, wherein the target signal data includes at least one location information; a mapping module for mapping the target signal data to a directional orbit vector field based on at least one location information to obtain reference vector field data; a first determination module for determining a target analysis region in the directional orbit vector field and determining first vector field data located within the target analysis region from the reference vector field data; a second determination module for determining second vector field data corresponding to each signal source based on the first vector field data and determining aggregated feature information corresponding to each signal source based on the second vector field data; and a processing module for displaying the aggregated feature information corresponding to each signal source through the directional orbit vector field. A third aspect of this disclosure provides an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the signal processing method based on a directional orbit vector field environment as proposed in the first aspect of this disclosure.

[0007] A fourth aspect of this disclosure provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement the signal processing method based on a directional orbit vector field environment as proposed in the first aspect of this disclosure.

[0008] The fifth aspect of this disclosure provides a computer program product, including a computer program that, when executed by a processor, implements the signal processing method based on a directional orbit vector field environment as proposed in the first aspect of this disclosure.

[0009] The signal processing method, apparatus, electronic device, computer-readable storage medium, and computer program product based on a directional orbit vector field environment disclosed herein acquire initial signal data from a communication network and preprocess the initial signal data to obtain target signal data. The target signal data includes at least one location information. Based on the at least one location information, the target signal data is mapped to a directional orbit vector field to obtain reference vector field data. A target analysis region in the directional orbit vector field is determined. First vector field data located within the target analysis region is determined from the reference vector field data. Based on the first vector field data, second vector field data corresponding to each signal source is determined. Aggregated feature information corresponding to each signal source is determined based on the second vector field data. The aggregated feature information corresponding to each signal source is displayed through the directional orbit vector field. This effectively distinguishes the feature information of different signal sources and improves the presentation effect of signal source feature information.

[0010] Additional aspects and advantages of this disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this disclosure. Attached Figure Description

[0011] The above and / or additional aspects and advantages of this disclosure will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, in which: Figure 1 A schematic flowchart illustrating a signal processing method based on a directional orbit vector field environment provided in an embodiment of this disclosure; Figure 2 This is a schematic flowchart illustrating another signal processing method based on a directional orbit vector field environment provided in an embodiment of this disclosure; Figure 3 This is a schematic flowchart illustrating another signal processing method based on a directional orbit vector field environment provided in an embodiment of the present disclosure; Figure 4 This is a schematic diagram of frequency sweep data in an embodiment of this disclosure; Figure 5 This is a schematic diagram of a signal data conversion embodiment of the present disclosure; Figure 6 This is a schematic diagram of another signal data conversion in an embodiment of this disclosure; Figure 7 This is a schematic diagram of an interactive function in one embodiment of this disclosure; Figure 8 This is a schematic diagram illustrating a signal presentation effect in one embodiment of the present disclosure; Figure 9a This is a schematic diagram illustrating another signal presentation effect in an embodiment of this disclosure; Figure 9bThis is a schematic diagram illustrating another signal presentation effect in an embodiment of this disclosure; Figure 9c This is a schematic diagram illustrating another signal presentation effect in an embodiment of this disclosure; Figure 10 This is an optional example of the automatic capture function in the embodiments of this disclosure; Figure 11 This is a schematic diagram of the structure of a signal processing device based on a directional orbit vector field environment provided in an embodiment of the present disclosure; Figure 12 A block diagram of an exemplary electronic device suitable for implementing embodiments of the present disclosure is shown. Detailed Implementation

[0012] Embodiments of this disclosure are described in detail below. Examples of these embodiments are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this disclosure, and should not be construed as limiting this disclosure.

[0013] It should be noted that all information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals involved in this disclosure are authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. The acquisition, transmission, storage, use, and processing of data in the technical solution of this disclosure all comply with the relevant provisions of national laws and regulations.

[0014] It should be noted that in the embodiments disclosed herein, certain software, components, models, and other existing solutions in the industry may be mentioned. These should be considered as exemplary and are intended only to illustrate the feasibility of implementing the technical solutions disclosed herein. However, they do not mean that the applicant has used or necessarily used such solutions.

[0015] Figure 1 This is a schematic flowchart illustrating a signal processing method based on a directional orbit vector field environment provided in an embodiment of this disclosure.

[0016] This embodiment illustrates the example of a signal processing method based on a directional orbit vector field environment being configured within a signal processing device based on a directional orbit vector field environment. In this embodiment, the signal processing method based on a directional orbit vector field environment can be configured within a signal processing device based on a directional orbit vector field environment. This signal processing device can be installed in an electronic device, such as in a client running on an electronic device, or it can be installed in a server; there are no limitations on this.

[0017] like Figure 1 As shown, this signal processing method based on a directional orbit vector field environment includes: S101: Acquire initial signal data in the communication network and preprocess the initial signal data to obtain target signal data, wherein the target signal data includes at least one location information.

[0018] Initial signal data refers to the signal data initially acquired. There can be one or more initial signal data sets, and they can cover one or more physical cells. For example, in a mobile testing scenario, a frequency sweeper module can be used to collect initial signal data from a real-world communication network.

[0019] Optionally, after acquiring the initial signal data in the communication network, the initial signal data can be preprocessed to obtain target signal data, wherein the target signal data includes at least one location information. The location information can be used to describe the location corresponding to the target signal data; for example, the target signal data may be received and / or transmitted based on the location indicated by the corresponding location information, without limitation.

[0020] Optionally, the number of target signal data can be one or more, and each target signal data can have a corresponding location information, such as latitude and longitude, without limitation.

[0021] Optionally, initial signal data from the communication network can be collected, and the collected initial signal data can be preprocessed to obtain target signal data. Preprocessing may include data cleaning, summarization, and padding to ensure the accuracy and consistency of the signal data.

[0022] S102: Map the target signal data to the directional orbit vector field based on at least one position information to obtain reference vector field data.

[0023] Optionally, after determining the target signal data and at least one position information in the target signal data, the target signal data can be mapped to the directional orbital vector field based on the position information to obtain reference vector field data.

[0024] Optionally, a directional orbital vector field assigns a vector with a definite direction and intensity to each point (location point) within a spatial region. This field not only statically describes the directional distribution of vectors in space but also dynamically defines the motion patterns and trends driven by the field, serving as a geometric representation connecting the attributes of spatial points and their dynamic behavior. Optionally, in embodiments of this disclosure, the directional orbital vector field can be used to describe the signal direction and intensity vectors of each location point within a spatial region of scenarios such as "high-speed railways, urban rail transit, etc.", without limitation.

[0025] Optionally, a directional orbital vector field can be displayed on electronic devices (such as computers, mobile phones, and tablets). This usually refers to setting up a two-dimensional or three-dimensional space in an electronic device and displaying a field with directional arrows (vectors) in the two-dimensional or three-dimensional space. These arrows indicate the direction and magnitude of the vector at each point. Streamlines or particle trajectories can also be used to represent the dynamic behavior of the "orbit".

[0026] Optionally, target signal data can be mapped to a directional orbit vector field based on at least one location information to obtain reference vector field data. The data obtained by mapping the target signal data to the directional orbit vector field presented in the electronic device can be referred to as reference vector field data. This reference vector field data can be vector field data containing one or more signal sources.

[0027] Optionally, in the process of mapping target signal data to a directional orbit vector field based on at least one location information to obtain reference vector field data, a corresponding spatial coordinate system can be established based on the location information, and signal attribute vectors (such as direction of arrival, signal strength, and multipath components) at each spatial point can be calculated according to the physical model of signal propagation (such as attenuation model, beamforming vector, or channel impulse response). Then, these signal attribute vectors are constructed into physical vectors with direction and amplitude, and assigned to the corresponding spatial positions in the directional orbit vector field according to a preset mapping rule. Furthermore, through vector field normalization and spatial interpolation processing, continuous and differentiable reference vector field data is generated. This reference vector field data can simultaneously characterize the coverage intensity distribution and directional trend of energy flow of the target signal data in the spatial region.

[0028] Optionally, in the process of mapping target signal data to a directional orbital vector field based on at least one position information to obtain reference vector field data, the target signal data can be mapped to a one-dimensional lattice index in the directional orbital vector field. Each lattice index corresponds to a position information, and the target signal data is expanded according to direction using the lattice index to obtain the reference vector field data. The direction is determined based on at least one position information. Thus, by establishing a spatial mapping mechanism using a one-dimensional lattice index, a dimensionality reduction and structured transformation (converting to reference vector field data) is achieved from high-dimensional target signal data to a vector field structure. Specifically, it discretizes continuous spatial positions into indexed lattice units, ensuring that each lattice index uniquely corresponds to a position information and target signal data. Then, by performing tensor expansion operations on the indexed data along a predetermined direction (derived from the position information), the target signal data is decoupled into field components with separated direction and intensity dimensions. It not only achieves spatial anchoring and orientation alignment of target signal data in the vector field, but also generates reference vector field data with directional separability and parallel computation through indexed expansion, thereby intuitively displaying the changing trend of target signal data in a specific direction.

[0029] S103: Determine the target analysis region in the directional orbit vector field, and determine the first vector field data located within the target analysis region from the reference vector field data.

[0030] Optionally, the target analysis area can be an area selected by the analyst.

[0031] Optionally, in response to a first instruction input by the analyst, all regions presented in the directional orbit vector field may be identified as the target analysis region, or, in response to a second instruction input by the analyst, a portion of the directional orbit vector field indicated by the second instruction may be identified as the target analysis region; there is no limitation on this.

[0032] In other words, the target analysis area is a local or total area dynamically identified from the directional orbital vector field presented in the electronic device based on the analysis requirements, without any restrictions.

[0033] Optionally, the first vector field data located within the target analysis region can be determined from the reference vector field data. That is, the reference vector field data located within the target analysis region can be used as the first vector field data.

[0034] S104: Based on the first vector field data, determine the second vector field data corresponding to each signal source, and based on the second vector field data, determine the aggregated feature information corresponding to each signal source.

[0035] Optionally, in determining the first vector field data, signal stripping can be performed based on the first vector field data.

[0036] Optionally, second vector field data corresponding to each signal source can be determined based on the first vector field data. For example, the first vector field data can be processed by source separation, specifically by extracting the contribution components of each signal source from the mixed first vector field data based on the physical characteristics of the signal sources (such as temporal and / or spatial coding or modulation characteristics) or statistical independence. Subsequently, for each separated signal source component, the vector field distribution formed by the signal source acting alone within the target analysis region is calculated through backpropagation reconstruction or spatial filtering projection, thereby generating purified second vector field data corresponding one-to-one with each independent signal source.

[0037] Optionally, after determining the second vector field data corresponding to each signal source based on the first vector field data, the aggregated feature information corresponding to each signal source can also be determined based on the second vector field data.

[0038] S105: Displays aggregated feature information corresponding to each signal source through a directional orbital vector field.

[0039] Optionally, the aggregated feature information corresponding to each signal source, determined based on the second vector field data, can be displayed using a directional orbital vector field.

[0040] Optionally, the directional orbital vector field can be presented on the display interface of the electronic device, and then the aggregated feature information corresponding to each signal source can be displayed through the directional orbital vector field.

[0041] Optionally, in the process of displaying the aggregated feature information corresponding to each signal source through a directional orbital vector field, the second vector field data corresponding to each signal source can be input into the visualization engine of the electronic device. The second vector field data can then be converted into graphical elements using a field-graph mapping algorithm. This allows the aggregated feature information of each signal source (such as the maximum received level within the aggregated distance) to be mapped to the corresponding spatial region using a layered coloring scheme. Finally, the mapped aggregated feature information is rendered in real time using graphics, generating an interactive directional orbital vector field visualization scene on the electronic device screen that integrates the intensity distribution and spatial flow characteristics of multiple signal sources.

[0042] In this embodiment, initial signal data from the communication network is acquired and preprocessed to obtain target signal data. The target signal data includes at least one location information. Based on this location information, the target signal data is mapped to a directional orbital vector field to obtain reference vector field data. The target analysis region within the directional orbital vector field is determined. First vector field data located within the target analysis region is determined from the reference vector field data. Second vector field data corresponding to each signal source is determined based on the first vector field data. Aggregated feature information corresponding to each signal source is determined based on the second vector field data. The aggregated feature information corresponding to each signal source is then displayed using the directional orbital vector field. This effectively distinguishes the feature information of different signal sources and improves the presentation of signal source feature information.

[0043] Figure 2 This is a schematic flowchart illustrating another signal processing method based on a directional orbit vector field environment provided in an embodiment of this disclosure.

[0044] like Figure 2 As shown, this signal processing method based on a directional orbit vector field environment includes: S201: Acquire initial signal data in the communication network and preprocess the initial signal data to obtain target signal data, wherein the target signal data includes at least one location information.

[0045] S202: Map the target signal data onto a one-dimensional lattice index in the directional orbit vector field, where each lattice index corresponds to a position information.

[0046] S203: The target signal data is expanded according to the direction by the dot matrix index to obtain reference vector field data, wherein the direction is determined based on at least one position information.

[0047] S204: Determine the target analysis region in the directional orbit vector field, and determine the first vector field data located within the target analysis region from the reference vector field data.

[0048] S205: Based on the first vector field data, determine the second vector field data corresponding to each signal source.

[0049] For a detailed description of S201-S205, please refer to the above embodiments, which will not be repeated here.

[0050] S206: Determine at least one signal reception level for each signal source based on the second vector field data.

[0051] S207: Within the target analysis area, using a preset length as the aggregation distance, determine the maximum signal reception level of each signal source within the aggregation distance as the aggregation feature information of each signal source within the aggregation distance.

[0052] Optionally, in determining the aggregated feature information corresponding to each signal source based on the second vector field data, it can be done by determining at least one signal reception level for each signal source based on the second vector field data, and within the target analysis area, using a preset length as the aggregation distance, determining the maximum signal reception level of each signal source within the aggregation distance as the aggregated feature information for each signal source within the aggregation distance. Thus, through a reception level filtering mechanism based on spatial aggregation distance, the continuously distributed second vector field data is transformed into discretized, spatially representative aggregated feature information. Specifically, using the aggregation distance as a spatial unit, the maximum reception level of each signal source is extracted within each spatial unit, achieving spatial quantitative characterization of signal coverage strength and extraction of local peak features. This not only suppresses fluctuation noise caused by small-scale fading in the signal field and highlights the spatial distribution structure of the dominant signal strength, but also generates gridded aggregated feature information that can be directly used for network planning, interference analysis, or handover decisions.

[0053] For example, in a high-speed rail scenario, the preset length could be, for instance, 200 meters.

[0054] S208: Using the center line of the target analysis area as a reference, aggregated feature information corresponding to each signal source is displayed on both sides of the center line in different visual chart formats.

[0055] Optionally, after determining the aggregated feature information corresponding to each signal source, the aggregated feature information corresponding to each signal source can be displayed in different visualization charts on both sides of the track centerline, using the track centerline as a reference. Thus, by using bilateral differentiated visualization encoding with the track centerline as the axis of symmetry, symmetrical comparison and correlation analysis of the aggregated feature information of multiple signal sources in spatial structure are achieved. Specifically, abstract signal feature data is anchored to a specific physical track reference system, and different visualization charts on both sides of the centerline are used to present the intensity, quality, and other indicators of each signal source, thereby intuitively revealing the symmetry of signal coverage distribution along the track axis, intensity balance, or interference differences in a single view. This not only strengthens the correlation between geographical context and data features but also supports rapid spatial pattern recognition and problem segment location of the signal environment along the track.

[0056] Optionally, in the process of displaying the aggregated feature information corresponding to each signal source in different visualization chart formats on both sides of the track centerline, a first visualization chart can be used on one side of the track centerline to display the proportion of signal coverage area of ​​each signal source within the target analysis area, while a second visualization chart can be used on the other side of the track centerline to display the distribution information of signal reception level of each signal source within the target analysis area. Thus, by implementing multi-dimensional collaborative presentation of heterogeneous visualization charts on both sides of the track centerline, spatial partitioning and attribute decoupling correlation analysis of signal source feature information are achieved. This allows analysis users to simultaneously complete the horizontal comparison and correlation interpretation of the two key dimensions of signal "coverage breadth" and "signal strength" within a unified geographic reference framework, thereby efficiently supporting network coverage optimization and interference analysis decisions.

[0057] In this embodiment, initial signal data from the communication network is acquired and preprocessed to obtain target signal data. The target signal data includes at least one location information. Based on this location information, the target signal data is mapped to a directional orbital vector field to obtain reference vector field data. The target analysis region within the directional orbital vector field is determined, and first vector field data located within this region is identified from the reference vector field data. Based on the first vector field data, second vector field data corresponding to each signal source is determined, and aggregated feature information corresponding to each signal source is determined based on the second vector field data. The aggregated feature information corresponding to each signal source is then displayed through the directional orbital vector field. This effectively distinguishes the feature information of different signal sources, improving the presentation of signal source feature information. Furthermore, by using bilateral differential visualization encoding with the orbital centerline as the axis of symmetry, symmetrical comparison and correlation analysis of aggregated feature information from multiple signal sources in the spatial structure are achieved. This allows for a direct and intuitive display of the symmetry, intensity balance, or interference differences in signal coverage along the orbital axis in a single view. It not only strengthens the connection between geographical context and data features, but also supports rapid spatial pattern recognition and problem section location of signal environment along the track.

[0058] Figure 3 This is a schematic flowchart illustrating another signal processing method based on a directional orbit vector field environment provided in an embodiment of the present disclosure.

[0059] like Figure 3 As shown, this signal processing method based on a directional orbit vector field environment includes: S301: Acquire initial signal data in the communication network and preprocess the initial signal data to obtain target signal data, wherein the target signal data includes at least one location information, signal reception level, frequency point, and PCI.

[0060] The Physical Cell Identifier (PCI) is used to identify the physical cell corresponding to one or more target signal data.

[0061] S302: Map the target signal data to the directional orbit vector field based on at least one position information to obtain reference vector field data.

[0062] S303: Determine the target analysis region in the directional orbital vector field, and determine the first vector field data located within the target analysis region from the reference vector field data.

[0063] S304: Based on the first vector field data, determine the second vector field data corresponding to each signal source, and based on the second vector field data, determine the aggregated feature information corresponding to each signal source.

[0064] S305: Displays aggregated feature information corresponding to each signal source through a directional orbital vector field.

[0065] For a detailed description of S301-S305, please refer to the above embodiments, which will not be repeated here.

[0066] S306: Provides a graphical analysis interface.

[0067] Optionally, a graphical analysis interface can be provided in the electronic device. The graphical analysis interface provided in this embodiment can be used to display the signal coverage curve corresponding to each signal source.

[0068] S307: In the graphical analysis interface, a signal coverage curve corresponding to each signal source is generated with a one-dimensional dot matrix index as the horizontal axis and the signal reception level as the vertical axis. The signal coverage curve is used to describe multiple signal coverage data, which are related to frequency points and PCI.

[0069] Optionally, the signal coverage curve corresponding to each signal source can be used to describe multiple signal coverage data for that signal source. The signal coverage data is related to frequency point and PCI. Specifically, the signal coverage data is two-dimensional or multi-dimensional spatial sampling data based on a specific frequency point and physical cell identifier (PCI), used to quantitatively characterize the propagation characteristics of signals emitted by a specific cell (uniquely identified by PCI) at its operating frequency point within a given geographical area of ​​the wireless network.

[0070] Optionally, a signal coverage curve corresponding to each signal source can be generated in the graphical analysis interface, using a one-dimensional dot matrix index as the horizontal axis and the signal received level as the vertical axis. This signal coverage curve describes the coverage data of multiple signals. Thus, by linearly encoding the location information of the target signal data into a one-dimensional dot matrix index and using this index as the horizontal axis, a dimensionality reduction mapping and serialization presentation of multi-dimensional target signal data to a two-dimensional Cartesian coordinate system is achieved. This allows for the generation of a signal coverage curve for each signal source that intuitively reflects the trend of its signal strength along the dot matrix index. This not only compresses complex spatial field information into a standard graphical format, facilitating horizontal comparison and trend analysis of different signal sources, but also...

[0071] Optionally, the graphical analysis interface includes operation controls corresponding to each signal source; the method further includes: responding to user commands to the operation controls, displaying or hiding the signal coverage curve of the signal source corresponding to the operation control in the graphical analysis interface. This enables interactive data layer management in complex graphical environments with multiple signal sources overlaid. Users can selectively display or hide the signal coverage curve of specific signal sources by triggering controls, thereby dynamically controlling visual complexity, focusing on the target signal, and supporting flexible comparative and combined analysis of multiple signal sources, greatly improving the visualization readability and exploration efficiency in multi-source data scenarios.

[0072] Optionally, in response to an automatic capture command, the system determines the starting and ending point indexes and the single-map range based on the command. Then, based on these indexes, at least one signal coverage data point is identified from multiple signal coverage data sets. A signal coverage analysis chart is generated based on this chart, and the target signal data is analyzed according to the chart and signal coverage quality assessment rules to obtain a structured analysis report. Thus, the system accurately extracts at least one signal coverage data point based on the starting and ending point indexes and the single-map range, and processes this data point according to signal coverage quality assessment rules to generate a structured analysis report. This not only standardizes and batches the analysis process but also significantly improves the efficiency and accuracy of large-scale network coverage assessment by transforming spatially continuous data into discretized, computable analysis units.

[0073] In this embodiment, initial signal data from the communication network is acquired and preprocessed to obtain target signal data. The target signal data includes at least one location information. Based on this location information, the target signal data is mapped to a directional orbit vector field to obtain reference vector field data. The target analysis region within the directional orbit vector field is determined. First vector field data located within the target analysis region is determined from the reference vector field data. Second vector field data corresponding to each signal source is determined based on the first vector field data. Aggregated feature information corresponding to each signal source is determined based on the second vector field data. The aggregated feature information corresponding to each signal source is then displayed through the directional orbit vector field. This effectively distinguishes the feature information of different signal sources and improves the presentation of signal source feature information. Furthermore, a signal coverage curve corresponding to each signal source is generated in the graphical analysis interface, using a one-dimensional dot matrix index as the horizontal axis and the signal reception level as the vertical axis. This signal coverage curve describes multiple signal coverage data. Therefore, by linearly encoding the location information of the target signal data into a one-dimensional dot matrix index and using this index as the horizontal axis, a dimensionality reduction mapping and serialization presentation of multi-dimensional target signal data to a two-dimensional Cartesian coordinate system is achieved. This enables the generation of a signal coverage curve for each signal source that intuitively reflects the trend of its signal intensity along the dot matrix index. This not only compresses complex spatial field information into a standard graphical format, facilitating horizontal comparison and trend analysis of different signal sources, but also...

[0074] Examples of the above embodiments are illustrated below: This disclosure proposes a signal stripping and presentation method based on a directional orbital vector field environment, including the following steps: The first step: data acquisition and preprocessing.

[0075] Optionally, initial signal data from the wireless communication network can be collected, including signal strength, frequency, and location information. The collected initial signal data is then preprocessed to obtain the target signal data. Preprocessing includes data cleaning, summarization, and data filling to ensure data accuracy and consistency.

[0076] Optionally, existing sweep frequency generator modules can be used to collect front-end data. The sweep frequency data (an optional example of the initial signal data mentioned above) includes standard test items. For example... Figure 4 As shown, Figure 4 This is a schematic diagram of frequency sweep data in an embodiment of this disclosure.

[0077] Optionally, to avoid signal omissions in the frequency sweep data, the sampling point signals are averaged according to a 1-second dimension.

[0078] The second step: constructing and storing vector field data.

[0079] Optionally, target signal data in geospatial space can be converted into vector field data (an optional example of the aforementioned vector field data). Specifically, the target signal data is mapped onto a one-dimensional dot matrix index, with each dot matrix index corresponding to a specific location point (an optional example of the aforementioned location information). Then, the target signal data is expanded according to direction using the dot matrix index to visually display the changing trends of the target signal data in different directions.

[0080] Optionally, based on the characteristics of the "directional orbital vector field", the two-dimensional plane vector (an optional example of the target signal data mentioned above) can be converted into a one-dimensional dot matrix index, so that subsequent comparisons between different signals or between the same signal in the time dimension can be carried out using the one-dimensional dot matrix index as the dimension.

[0081] Optional, such as Figure 5 As shown, Figure 5 This is a schematic diagram of a signal data conversion in an embodiment of the present disclosure. Figure 5 The "index" in the text is an optional example of the one-dimensional dot matrix index mentioned above. A dot matrix index can also be called an "indexPoint".

[0082] Optional, such as Figure 6 As shown, Figure 6 This is a schematic diagram of another signal data conversion in an embodiment of this disclosure. It shows location information (longitude; latitude; EARFCN, used to uniquely identify the center frequency of the LTE radio carrier; PCI; time information (DTime)).

[0083] The third step: signal stripping and presentation in local areas.

[0084] Optionally, the target signal data can be stripped within a vector field (an optional example of the directional orbit vector field described above). By setting the offset distance and rendering size, signals from different signal sources can be separated and rendered separately.

[0085] Optionally, for each signal source, rendering is performed according to its position and intensity in the vector field (an optional example of the second vector field data mentioned above). For example, the original position shows the strongest state of the selected frequency range in that area, with signals on either side having progressively decreasing overall proportions.

[0086] Optionally, interactive features can be provided, allowing users to zoom in and highlight the cell icon of the current signal by double-clicking it, etc., for more detailed analysis of the coverage of a specific signal source (an optional example of the signal coverage data mentioned above). By selecting the area to be displayed (an optional example of the target analysis area mentioned above), signals within the specified range can be stripped out and presented. For example... Figure 7 As shown, Figure 7 This is a schematic diagram of an interactive function in an embodiment of this disclosure.

[0087] Optionally, during signal stripping, the maximum value of the same signal within the aggregation distance corresponding to the preset length (an optional example of the maximum received level mentioned above) can be used as the feature value of the signal source (an optional example of the aggregation feature information mentioned above). For example, in a high-speed rail scenario, the preset length can be 200 meters, i.e., 200 meters is used as the aggregation distance required for statistics. Subsequently, the aggregated feature values ​​are used for tabular statistics and chart rendering to obtain a result table. The left side of the result table (an optional example of the first visualization chart mentioned above) shows the coverage ratio of each signal within the area, and the right side (an optional example of the second visualization chart mentioned above) shows the level distribution of each signal within the area. Figure 8 As shown, Figure 8 This is a schematic diagram illustrating a signal presentation effect in an embodiment of this disclosure.

[0088] Optionally, the rendering points of one (or more) physical cells (each rendering point is used to render the second vector field data corresponding to a signal source under that physical cell) can be increased, while the rendering of the remaining physical cells still uses smaller points. For example... Figures 9a-9c As shown, Figure 9a This is a schematic diagram illustrating another signal presentation effect in an embodiment of this disclosure. Figure 9b This is a schematic diagram illustrating another signal presentation effect in an embodiment of this disclosure. Figure 9c This is a schematic diagram illustrating another signal presentation effect in an embodiment of this disclosure.

[0089] The fourth step: Visual analysis and automatic capture. Optionally, chart presentation functionality can be added to the vector scene. Users can control the rendering signal in the graphics area by clicking on the legend; the upper options are used to select rendering, and the lower options are used to turn rendering off.

[0090] Optionally, the vertical axis represents signal strength, and the horizontal axis is the dot matrix index value of the location point (i.e., the signal coverage curve), with the unit being meters. The label is "Frequency Point - PCI," which controls the signal display in the graphic area.

[0091] Optionally, an automatic capture function is provided, where users can set the start position, end position, and single map range. The system will automatically capture and present the signal coverage within the specified range (an optional example of the above signal coverage data).

[0092] Optionally, when analyzing a single area, the problem area can be selected to present the aforementioned issues. However, sometimes it's preferable to directly capture the signal status of the entire line and then view it through charts. The start and end points of the capture, as well as the banner size of each image, can be set accordingly. For example... Figure 10 As shown, Figure 10 As an optional example of the automatic capture function in the embodiments of this disclosure, it can be implemented as follows: Figure 10 The interface shown detects and analyzes the user's automatic capture commands.

[0093] Optionally, it can automatically display the corresponding analysis and test file information, setting information, and image capture information for each segment in the form of a Word report.

[0094] The fifth step: Generate a structured analysis report.

[0095] Optionally, based on the analysis results, a detailed report can be generated, presenting the signal status of each graph. Graph interpretation functionality is provided to help users understand signal distribution, such as determining test direction and checking overlapping signal areas. Based on the analysis results, optimization suggestions are proposed to assist network optimization personnel in decision-making. The overall signal can be checked according to preset inspection rules (an optional example of the aforementioned signal coverage quality assessment rules), outputting problematic sections and specific problem points.

[0096] Optionally, the output question types currently include the following categories: Category 1: Weak Coverage in a Specific Area: This indicates that there is no signal within a specific area that meets the requirements. This category includes cases with no coverage at all. The output information includes: Problem ID, dot matrix value, frequency point (can be blank), PCI (can be blank), problem type, and description (a weak signal or no coverage occurs within the range of XX-XX for XXX meters).

[0097] Category 2: Signal Interruption or Weakness: This indicates that the sample range that meets the conditions for a specific signal is XX-XXX, but signal interruption occurs within the dot matrix range. Output information includes: Problem ID, Dot matrix value, frequency point, PCI, Problem Type, and description (Cell coverage distance range XX-XX, signal interruption or weakness occurs within the XX-XX range).

[0098] Category 3: Insufficient signal overlap distance: Cells with coverage distances greater than a specific distance (used to exclude base station cells and public network cells) have signal overlap distances less than a set distance, requiring output. Output information includes: Problem ID, dot matrix value, frequency point, PCI, problem type, and description information (previous overlap distance XX, cell coverage distance, subsequent overlap distance XX).

[0099] The method provided in this disclosure, through the construction of a vector field and signal stripping processing, can clearly display the coverage and intensity differences of different signal sources, solving the signal overlap problem in the prior art. The vector field presentation method can intuitively show the signal's changing trend in a specific direction, helping network optimization personnel more accurately judge the quality of signal coverage and potential problems. It provides rich interactive functions, allowing users to deeply analyze the coverage of specific signal sources through simple operations, improving analysis efficiency and accuracy. Through automatic capture and chart presentation functions, users can quickly obtain signal coverage information within a specified range, reducing manual screening time and improving overall work efficiency.

[0100] Figure 11 This is a schematic diagram of the structure of a signal processing device based on a directional orbital vector field environment provided in an embodiment of this disclosure.

[0101] like Figure 11 As shown, the signal processing device 110 based on the directional orbit vector field environment includes: The acquisition module 1101 is used to acquire initial signal data in the communication network and preprocess the initial signal data to obtain target signal data, wherein the target signal data includes at least one location information.

[0102] The mapping module 1102 is used to map the target signal data to the directional orbit vector field based on at least one position information to obtain reference vector field data.

[0103] The first determining module 1103 is used to determine the target analysis region in the directional orbit vector field and to determine the first vector field data located within the target analysis region from the reference vector field data.

[0104] The second determining module 1104 is used to determine the second vector field data corresponding to each signal source based on the first vector field data, and to determine the aggregated feature information corresponding to each signal source based on the second vector field data.

[0105] The processing module 1105 is used to display aggregated feature information corresponding to each signal source through a directional orbital vector field.

[0106] It should be noted that the foregoing explanation of the signal processing method based on the directional orbit vector field environment also applies to the signal processing device based on the directional orbit vector field environment in this embodiment, and will not be repeated here.

[0107] In this embodiment, initial signal data from the communication network is acquired and preprocessed to obtain target signal data. The target signal data includes at least one location information. Based on this location information, the target signal data is mapped to a directional orbital vector field to obtain reference vector field data. The target analysis region within the directional orbital vector field is determined. First vector field data located within the target analysis region is determined from the reference vector field data. Second vector field data corresponding to each signal source is determined based on the first vector field data. Aggregated feature information corresponding to each signal source is determined based on the second vector field data. The aggregated feature information corresponding to each signal source is then displayed using the directional orbital vector field. This effectively distinguishes the feature information of different signal sources and improves the presentation of signal source feature information.

[0108] To implement the above embodiments, this disclosure also proposes an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided in the foregoing embodiments. To implement the above embodiments, this disclosure also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.

[0109] To implement the above embodiments, this disclosure also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.

[0110] Figure 12 A block diagram of an exemplary electronic device suitable for implementing embodiments of the present disclosure is shown. Figure 12 The electronic device 12 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0111] like Figure 12 As shown, the electronic device 12 is represented in the form of a general-purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, memory 28, and bus 18 connecting different system components (including memory 28 and processing unit 16).

[0112] Bus 18 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. Examples of these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0113] Electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0114] Memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and / or cache 32. Electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write non-removable, non-volatile magnetic media (… Figure 12 Not shown; usually referred to as a "hard drive".

[0115] although Figure 12 As not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disc drive for reading and writing to a removable non-volatile optical disc (e.g., a compact disc read-only memory (CD-ROM), a digital video disc read-only memory (DVD-ROM), or other optical media) may be provided. In these cases, each drive may be connected to bus 18 via one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of this disclosure.

[0116] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 42 typically perform the functions and / or methods described in the embodiments of this disclosure.

[0117] Electronic device 12 can also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), and with one or more devices that enable human interaction with electronic device 12, and / or with any device that enables electronic device 12 to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed via input / output (I / O) interface 22. Furthermore, electronic device 12 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 20. As shown, network adapter 20 communicates with other modules of electronic device 12 via bus 18. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0118] The processing unit 16 executes various functional applications and data processing by running programs stored in the memory 28, such as implementing the signal processing method based on the directional orbit vector field environment mentioned in the foregoing embodiments.

[0119] To implement the above embodiments, this disclosure also proposes an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method provided in the foregoing embodiments. To implement the above embodiments, this disclosure also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.

[0120] To implement the above embodiments, this disclosure also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.

[0121] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in this disclosure all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0122] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0123] This disclosure is intended to provide implementation schemes for users to selectively prevent the use or access to their personal information data. Specifically, this disclosure is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.

[0124] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0125] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0126] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of this disclosure includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of this disclosure pertain.

[0127] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0128] It should be understood that various parts of this disclosure can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0129] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0130] Furthermore, the functional units in the various embodiments of this disclosure can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0131] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present disclosure.

Claims

1. A signal processing method based on a directional orbit vector field environment, characterized in that, include: Acquire initial signal data from a communication network and preprocess the initial signal data to obtain target signal data, wherein the target signal data includes at least one location information. The target signal data is mapped to a directional orbit vector field based on the at least one location information to obtain reference vector field data. Determine the target analysis region in the directional orbit vector field, and determine the first vector field data located within the target analysis region from the reference vector field data; Based on the first vector field data, determine the second vector field data corresponding to each signal source, and based on the second vector field data, determine the aggregated feature information corresponding to each signal source; and The directional orbital vector field displays aggregated feature information corresponding to each signal source.

2. The method according to claim 1, characterized in that, The step of mapping the target signal data to a directional orbital vector field based on the at least one position information to obtain reference vector field data includes: The target signal data is mapped onto a one-dimensional lattice index in the directional orbit vector field, wherein each lattice index corresponds to a position information. The target signal data is expanded according to direction using the dot matrix index to obtain the reference vector field data, wherein the direction is determined based on the at least one position information.

3. The method according to claim 1, characterized in that, The step of determining the aggregated feature information corresponding to each signal source based on the second vector field data includes: Based on the second vector field data, determine at least one signal reception level for each signal source; Within the target analysis area, with a preset length as the aggregation distance, the maximum signal reception level of each signal source within the aggregation distance is determined as the aggregation feature information of each signal source within the aggregation distance.

4. The method according to claim 1, characterized in that, The process of displaying aggregated feature information corresponding to each signal source through the directional orbit vector field includes: Using the orbital centerline of the target analysis area as a reference, aggregated feature information corresponding to each signal source is displayed on both sides of the orbital centerline in different visual chart formats.

5. The method according to claim 4, characterized in that, The aggregated feature information corresponding to each signal source is displayed in different visual chart formats on both sides of the orbit centerline, including: On one side of the centerline of the track, the percentage of signal coverage area of ​​each signal source within the target analysis area is displayed in the form of a first visual chart; On the other side of the centerline of the track, the distribution information of the signal reception level of each signal source in the target analysis area is displayed in the form of a second visualization chart.

6. The method according to claim 2, characterized in that, The target signal data also includes signal reception level, frequency point, and Physical Cell Identifier (PCI); wherein, the method further includes: Provides a graphical analysis interface; In the graphical analysis interface, a signal coverage curve corresponding to each signal source is generated with the one-dimensional dot matrix index as the horizontal axis and the signal reception level as the vertical axis. The signal coverage curve is used to describe multiple signal coverage data, which are related to the frequency point and PCI.

7. The method according to claim 6, characterized in that, The graphical analysis interface includes operation controls corresponding to each signal source; wherein, the method further includes: In response to the user's operation command on the operation control, the signal coverage curve of the signal source corresponding to the operation control is displayed or hidden in the graphical analysis interface.

8. The method according to claim 6, characterized in that, The method further includes: In response to an automatic capture command, a starting dot matrix index, an ending dot matrix index, and a single map range are determined according to the automatic capture command, and at least one signal coverage data is determined from the plurality of signal coverage data based on the starting dot matrix index, the ending dot matrix index, and the single map range. Generate a signal coverage analysis chart based on the at least one signal coverage data; Based on the signal coverage analysis chart and signal coverage quality assessment rules, the target signal data is analyzed to obtain a structured analysis report.

9. A signal processing device based on a directional orbit vector field environment, characterized in that, include: An acquisition module is used to acquire initial signal data in a communication network and preprocess the initial signal data to obtain target signal data, wherein the target signal data includes at least one location information. The mapping module is used to map the target signal data to a directional orbit vector field based on the at least one position information to obtain reference vector field data; The first determining module is used to determine the target analysis region in the directional orbit vector field, and to determine the first vector field data located within the target analysis region from the reference vector field data; The second determining module is used to determine, based on the first vector field data, second vector field data corresponding to each signal source, and to determine, based on the second vector field data, aggregated feature information corresponding to each signal source. The processing module is used to display aggregated feature information corresponding to each signal source through the directional orbit vector field.

10. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-8.

12. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1-8.

Images