A 5G base station indoor coverage control method and system

Abstract

The application discloses a 5G base station indoor coverage control method and system, relates to the field of 5G base station indoor coverage control, and is used for effectively controlling system energy consumption while ensuring key service communication performance, and comprises the following steps: acquiring a wireless signal measurement report of a user terminal in a base station coverage area and a probe signal echo characteristic of a base station itself; the probe signal echo characteristic comprises an echo time delay and strength; fusing the wireless signal measurement report and the probe signal echo characteristic, constructing and updating a real-time radio frequency environment map; comparing the real-time radio frequency environment map with a benchmark map, identifying physical environment changes and inferring obstacle characteristics; adjusting a beamforming direction and transmission power according to the physical environment changes and the obstacle characteristics; identifying key services, improving the priority of the communication quality of the key services when the beamforming direction and the transmission power are adjusted, and simultaneously coordinating and suppressing interference to adjacent areas.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of 5G base station indoor coverage control, and in particular to a 5G base station indoor coverage control method and system. BACKGROUND

[0002] An intelligent office building usually has an advanced 5G indoor coverage system deployed inside. At the initial stage of system planning, engineers will design the installation location of wireless access points (e.g., small base stations or distributed antenna units), the type of antenna, the initial transmission power, and the frequency resource allocation for each floor and area.

[0003] However, the demand for 5G networks by building tenants shows high diversity and dynamics. Some require extremely low latency and extremely high reliability. Some require extremely high uplink and downlink bandwidths for the network. Some require high bandwidth and stable low-latency connection.

[0004] In addition, tenants make internal modifications and rearrangements to their office spaces, which can have a significant and unpredictable impact on the propagation characteristics of 5G signals. For example, metal partitions or server cabinets can reflect and absorb millimeter wave signals, resulting in unexpected signal blind areas or weak coverage areas in certain areas; while some composite materials or soundproof panels can directly absorb wireless energy, causing a sharp decline in signal strength.

[0005] Due to the dynamic changes in the above-mentioned physical environment, the original wireless propagation path is completely disrupted, resulting in a sharp decline in signal quality in local areas and a serious imbalance in capacity allocation. In those signal shadow areas formed by new partitions, user equipment may not be able to connect normally to the nearest access point and be forced to connect to a more distant and weaker signal access point, resulting in a decline in communication quality. At the same time, due to the obstruction of physical obstacles, adjacent access points that could have shared the load may not be able to provide effective service due to signal obstruction, further exacerbating congestion in local areas. In order to compensate for these weak coverage areas, the system may automatically or manually increase the transmission power of certain access points, but this in turn raises new problems: the increase in signal power can cause signal overflow to adjacent floors or adjacent areas, causing serious same-frequency or adjacent-frequency interference with access points there, further deteriorating the wireless environment of the entire building and reducing overall network performance.

[0006] In the face of the above problems, the traditional 5G indoor coverage system tends to adopt a "conservative" strategy, i.e., maintaining all access points at a high transmission power and allocating more wireless resources to ensure that basic service quality is provided even in the worst case. If the system still maintains high power consumption during the low traffic period, it will result in a large amount of energy waste.

[0007] Therefore, how to dynamically adjust the operating status and resource configuration of each access point while ensuring high performance, so as to find a dynamic balance between performance and energy efficiency, is a technical problem that urgently needs to be solved. Summary of the Invention

[0008] This invention provides a 5G base station indoor coverage control method, which effectively controls system energy consumption while ensuring the communication performance of critical services.

[0009] In a first aspect, to address the aforementioned technical problems, this invention provides a 5G base station indoor coverage control method, comprising: acquiring wireless signal measurement reports from user terminals within the base station coverage area and echo characteristics of probe signals emitted by the base station itself, wherein the echo characteristics of the probe signals include echo delay and intensity; fusing the wireless signal measurement reports and echo characteristics of the probe signals to construct and update a real-time radio frequency environment map; comparing the real-time radio frequency environment map with a reference map to identify changes in the physical environment and infer obstacle characteristics; adjusting the beamforming direction and transmission power according to changes in the physical environment and obstacle characteristics; identifying key services, and, when adjusting the beamforming direction and transmission power, prioritizing the communication quality of key services while coordinating and suppressing interference to adjacent areas.

[0010] Optionally, the real-time radio frequency environment map is constructed and updated by integrating wireless signal measurement reports and probe signal echo characteristics, including: dividing the base station coverage area into multiple grid cells; for each grid cell, the RSRP values ​​reported by multiple user terminals within the cell are weighted averaged or interpolated, and combined with the propagation characteristics analysis of the probe signal in the grid cell, the real-time signal strength and channel quality of the grid cell are determined, thus obtaining the real-time signal strength and channel quality of multiple grid cells;

[0011] Based on the real-time signal strength and channel quality of multiple grid cells, a real-time radio frequency environment map is constructed and updated.

[0012] Optionally, the physical environment changes can be identified by comparing the real-time radio frequency environment map and the reference map, including: comparing the difference in signal strength and channel quality at each grid cell at the same location in the real-time radio frequency environment map and the reference map; if the difference in signal strength at each grid cell at the same location is greater than or equal to a preset signal strength difference and the difference in channel quality at each grid cell at the same location is greater than or equal to a preset channel quality difference, then the physical environment changes.

[0013] Optionally, inferring obstacle characteristics includes: extracting multipath propagation features from wireless signal measurement reports; multipath propagation features include the signal's angle of arrival, time of arrival, and multipath component intensity; inferring the obstacle material type based on the multipath propagation features and the echo characteristics of the probed signal; monitoring and inferring the real-time state and impact attributes of the variable partition wall, wherein monitoring and inferring the real-time state and impact attributes of the variable partition wall includes: monitoring the fluctuation patterns generated by the variable partition wall on the echo characteristics of the probed signal and the wireless signal measurement reports, and inferring the real-time state of the variable partition wall and its specific impact attributes on the signal by monitoring the signal characteristics during the transition period; estimating the obstacle's position and geometry by combining the real-time location information of the user terminal and the echo delay and angle of arrival information of the probed signal; and inferring obstacle characteristics based on the obstacle material type, the real-time state and impact attributes of the variable partition wall, and the obstacle's position and geometry.

[0014] Optionally, key services are identified, and when adjusting beamforming direction and transmit power, the priority of improving the communication quality of key services is increased, while coordinating the suppression of interference to adjacent areas. This includes: identifying the communication requirements of key services, including requirements for latency, bandwidth, and packet loss rate; analyzing channel state information reports from user terminals and echoes of probe signals emitted by the base station itself to identify multiple signal paths with different propagation characteristics, and evaluating the stability of each signal path under variable barrier state switching or instantaneous high-power interference; dynamically selecting and activating at least two signal paths with relatively independent propagation characteristics and expected to be less affected by environmental changes for key service users based on communication requirements and signal path stability, thus constructing resilient channels; allocating redundant radio resources to resilient channels and continuously monitoring the signal quality and performance indicators of key services for each resilient channel; when a significant degradation in the performance of a resilient channel is detected, seamlessly switching the data stream of key services to another resilient channel with good performance, and adjusting beamsidelobe suppression and null-point beamforming strategies according to environmental interference conditions.

[0015] Optionally, key services are identified, and when adjusting beamforming direction and transmit power, the priority of improving the communication quality of key services is increased, while coordinating the suppression of interference to adjacent areas. This includes: acquiring the communication requirements of multiple key services; analyzing the channel state information reports of each key service user terminal and the echo of the probe signal transmitted by the base station itself, identifying multiple signal paths between each key service user terminal and the base station, and evaluating the propagation characteristics and stability of each signal path; dynamically selecting and activating at least one primary path and one backup path for each key service based on communication requirements and signal path stability, where the primary and backup paths have relatively independent propagation characteristics; identifying key... The system monitors the spatial proximity and signal path overlap between services. Based on these factors and the priority of each critical service, it dynamically adjusts the beamforming direction and transmit power of the base station antenna array to align the main lobe with the user terminals of each critical service. It also coordinates and optimizes the sidelobe suppression and nulling of each critical service beam, creating nulls or reducing sidelobe energy in the interference directions between critical services and between critical and non-critical services. The system continuously monitors the performance indicators of each critical service and the signal quality of each signal path. When a performance degradation of any critical service or a deterioration in the signal quality of the main path is detected, the system seamlessly switches to a backup path and re-optimizes the beamforming and transmit power.

[0016] Optionally, coordinate and optimize the sidelobe suppression and null shaping of each key service beam to form nulls or reduce sidelobe energy in the interference directions between key services and between key services and non-key services, including: determining the positions where nulls are formed in the interference directions between key services and between key services and non-key services.

[0017] The amplitude and phase weighting of the base station antenna array are adjusted in a coordinated manner to form nulls or reduce sidelobe energy in the direction of interference, while ensuring that the signal strength in non-critical service areas is not lower than a preset threshold; the signal quality of each critical and non-critical service is continuously monitored; when the signal quality of a non-critical service is detected to be lower than a preset threshold, the beam null position or sidelobe suppression intensity is finely adjusted without affecting the communication quality of critical services, so as to improve the signal coverage of non-critical services.

[0018] Optionally, the steps for continuously monitoring the performance indicators and signal quality of each critical and non-critical service include: the base station sending a probe request to the user terminal and obtaining the user terminal's response; adjusting the frequency and power of the probe request based on the response to the probe request to obtain signal data in sparse or interrupted areas; combining the known obstacle locations, obstacle material types, and variable partition wall status in the real-time radio frequency environment map to perform attribute-enhanced interpolation and extrapolation on the signal data in sparse or interrupted areas to complete the missing performance indicators and signal quality data; using the user terminal's movement trajectory information and historical communication patterns to predict the user terminal's future location and communication needs; and estimating signal quality and predicting performance indicators based on the predicted future location and communication needs of the user terminal, thereby achieving continuous monitoring of each critical and non-critical service.

[0019] Optionally, based on the predicted future location and communication needs of the user terminal, the signal quality and prediction performance indicators are estimated, including: adjusting the prediction time window based on the user terminal's moving speed and direction, combined with known physical layout information inside the building where the user terminal is located, and correcting the path of the predicted future location of the user terminal; monitoring changes in the user terminal's service type and data traffic, identifying bursty communication patterns, and adjusting the prediction weights of communication needs based on the identification results; and estimating the signal quality and prediction performance indicators based on the corrected future location of the user terminal and the adjusted prediction weights of communication needs.

[0020] Secondly, the present invention provides a 5G base station indoor coverage control system, the system comprising:

[0021] The acquisition module is used to acquire wireless signal measurement reports from user terminals within the base station coverage area and echo characteristics of the probe signals emitted by the base station itself. The echo characteristics of the probe signals include echo delay and intensity.

[0022] The fusion module is used to fuse wireless signal measurement reports and probe signal echo characteristics to build and update a real-time radio frequency environment map.

[0023] The comparison module is used to compare real-time radio frequency environment maps with baseline maps to identify changes in the physical environment and infer obstacle characteristics;

[0024] The adjustment module is used to adjust the beamforming direction and transmission power according to changes in the physical environment and the characteristics of obstacles;

[0025] The protection module is used to identify critical services and prioritize the communication quality of critical services when adjusting beamforming direction and transmit power, while coordinating the suppression of interference to adjacent areas.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] This application discloses a 5G base station indoor coverage control method. By acquiring wireless signal measurement reports from user terminals and echo characteristics of probe signals emitted by the base station itself, and fusing these data to construct and update a real-time radio frequency environment map, the system can accurately and in real-time perceive dynamic changes in the indoor physical environment. Based on this, by comparing the real-time radio frequency environment map with a reference map, the system can identify physical environment changes and infer obstacle characteristics, thus providing a precise basis for subsequent beamforming and transmit power adjustments. Addressing the signal blind spots and weak coverage issues caused by frequent physical layout changes in smart office buildings (such as the construction of partition walls and the introduction of metal cabinets), this application can dynamically adjust the beamforming direction and transmit power, effectively compensating for insufficient signal coverage and avoiding the failure of traditional static planning. Furthermore, this application can identify key services and, when adjusting the beamforming direction and transmit power, prioritize the communication quality of these key services while simultaneously coordinating and suppressing interference to adjacent areas. This effectively solves the problem of co-channel or adjacent-channel interference caused by increasing transmission power to compensate for weak coverage areas in existing technologies, ensuring the low latency and high bandwidth requirements of critical services (such as financial transactions and software development), while maintaining the wireless environment quality throughout the building. In summary, this application overcomes the challenges faced by existing 5G indoor coverage systems in complex and ever-changing intelligent office environments through real-time environmental awareness, dynamic coverage adjustment, and intelligent service assurance, significantly improving the stability, reliability, and user experience of network services. Attached Figure Description

[0028] Figure 1 This is a schematic flowchart of a 5G base station indoor coverage control method provided in an embodiment of the present invention;

[0029] Figure 2 This is a schematic diagram of another 5G base station indoor coverage control method provided in an embodiment of the present invention;

[0030] Figure 3 This is a schematic diagram of a 5G base station indoor coverage control system provided in an embodiment of the present invention. Detailed Implementation

[0031] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0032] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0033] The following specific embodiments will provide a detailed description and explanation of a 5G base station indoor coverage control method provided in this application.

[0034] Reference Figure 1 This invention provides a method for controlling indoor coverage of a 5G base station, comprising the following steps:

[0035] S1, acquire the wireless signal measurement report of user terminals within the base station coverage area and the echo characteristics of the detection signal emitted by the base station itself.

[0036] The echo characteristics of the detected signal include echo delay and intensity.

[0037] The wireless signal measurement report may include reference signal received power (RSRP), reference signal received quality (RSRQ), signal-to-noise ratio (SNR), etc. The echo characteristics of the probed signal may include echo delay and intensity, etc.

[0038] As one possible implementation, user terminal wireless signal measurement reports can be obtained in various ways. For example, user terminals can periodically report information such as the received reference signal received power (RSRP), reference signal received quality (RSRQ), and signal-to-noise ratio (SNR) to the base station. These reports can be triggered by the user terminal in idle or connected states.

[0039] As another possible implementation, the base station can proactively request user terminals to report measurement data based on network load or specific events (such as user terminal movement or signal quality degradation). The echo characteristics of the probe signal are obtained by the base station itself transmitting probe signals and receiving echoes. For example, the base station can periodically transmit short pulses or frequency sweep signals and obtain the echo delay and intensity by analyzing the delay and intensity of the received echo signals. The echo delay can be obtained by calculating the time difference between the transmitted signal and the received echo signal, while the echo intensity can be obtained by measuring the power of the received echo signal.

[0040] S2. Integrate wireless signal measurement reports and probe signal echo characteristics to construct and update a real-time radio frequency environment map.

[0041] As another possible implementation, the base station can divide its coverage area into multiple grid cells. For each grid cell, a simple arithmetic average of the RSRP values ​​reported by multiple user terminals within that grid cell can be calculated, and combined with the analysis of the propagation characteristics of the probe signal within that grid cell, the real-time signal strength and channel quality of that grid cell can be determined. Then, based on the real-time signal strength and channel quality of all grid cells, a real-time radio frequency environment map is constructed and updated.

[0042] For example, this data can be mapped onto a two-dimensional or three-dimensional spatial grid to form a dynamic distribution map of signal strength and channel quality.

[0043] S3. Compare the real-time radio frequency environment map with the baseline map to identify changes in the physical environment and infer obstacle characteristics.

[0044] Among them, changes in the physical environment refer to changes in the wireless propagation path and characteristics caused by the movement of objects or the addition or removal of obstacles (such as partition walls, furniture, equipment, etc.) within the base station coverage area. "Obstacle characteristics" include the location, geometry, material type of the obstacle, and its impact on wireless signal propagation (such as reflection, absorption, scattering, etc.).

[0045] As one possible implementation, base stations can identify changes in the physical environment by directly comparing the absolute difference in signal strength and channel quality at each grid cell in the same location in a real-time radio frequency environment map and a reference map.

[0046] For example, if the signal strength difference of a certain grid cell is greater than a preset threshold, it is considered that a change in the physical environment may have occurred at that location. Obstacle characteristics can be inferred by extracting multipath propagation features from wireless signal measurement reports, such as the signal's angle of arrival, time of arrival, and multipath component strength.

[0047] Then, based on these multipath propagation characteristics and the echo characteristics of the probed signal, the material type of the obstacle can be inferred. For example, by analyzing the attenuation and reflection characteristics of the echo signal, it is possible to preliminarily determine whether the obstacle is metal, concrete, or wood. Combining the real-time location information of the user terminal with the echo delay and angle of arrival information of the probed signal, the location and geometry of the obstacle can be estimated. For example, using triangulation or multi-point positioning techniques, combined with echo delay and angle of arrival, the precise coordinates and approximate outline of the obstacle can be calculated.

[0048] As one possible implementation, the base station can compare the difference in signal strength and channel quality at each grid cell in the same location in the real-time radio frequency environment map and the reference map; if the difference in signal strength at each grid cell in the same location is greater than or equal to a preset signal strength difference and the difference in channel quality at each grid cell in the same location is greater than or equal to a preset channel quality difference, the physical environment is identified as having changed.

[0049] Specifically, the comparison operation involves comparing the real-time radio frequency environment map with the corresponding grid cells in the reference map one by one. For each grid cell, the difference between its signal strength in the real-time map and its signal strength in the reference map, as well as the difference between its channel quality in the real-time map and its channel quality in the reference map, are calculated.

[0050] Among them, the preset signal strength difference and the preset channel quality difference are preset thresholds.

[0051] Understandably, by comparing the difference in signal strength and channel quality between the real-time RF environment map and the baseline map for each grid cell at the same location, and combining this with a preset threshold, random noise and minor fluctuations in the environment can be effectively eliminated, accurately capturing significant physical environment changes caused by the introduction or removal of obstacles, structural adjustments, etc. This refined identification mechanism provides reliable input for subsequent obstacle characteristic inference and beamforming adjustment, thereby improving the adaptability and robustness of 5G base station indoor coverage control and ensuring the communication quality of user terminals in dynamically changing indoor environments.

[0052] S4. Adjust the beamforming direction and transmission power according to changes in the physical environment and the characteristics of obstacles.

[0053] Among them, beamforming direction refers to the process by which the base station antenna array adjusts the amplitude weighting and phase weighting of each antenna element to concentrate the wireless signal energy in a specific direction, forming a directional beam to enhance the target user signal and suppress interference.

[0054] As one possible implementation, when a significant decrease in signal strength is detected in a certain area due to the addition of new obstacles, the base station can adjust the beamforming direction to align the main lobe with the weak coverage area, thereby enhancing signal coverage. Simultaneously, the transmit power in that direction can be appropriately increased to compensate for signal attenuation.

[0055] As another possible implementation, if obstacles in a certain area are identified as having high reflectivity, which may lead to multipath interference, the base station can adjust the beamforming direction to form null or sidelobe suppression in order to reduce the interference of reflected signals to other areas.

[0056] S5. Identify key services and prioritize the communication quality of key services when adjusting beamforming direction and transmit power, while coordinating the suppression of interference to adjacent areas.

[0057] Among them, critical business refers to business that has high requirements for communication quality (such as latency, bandwidth, and packet loss rate), such as real-time video conferencing, telemedicine, and industrial automation control.

[0058] As one possible implementation, the base station can identify critical services based on the service type reported by the user terminal or network-side configuration information. For the identified critical services, their communication quality can be prioritized when adjusting beamforming direction and transmit power.

[0059] For example, narrower, more focused beams can be allocated to critical services, ensuring that the received signal strength and signal-to-noise ratio reach a preset high-quality threshold.

[0060] Meanwhile, in order to suppress interference to adjacent areas, base stations can use null-shaping or sidelobe suppression techniques to create signal nulls or reduce sidelobe energy in non-critical service areas or in the direction of adjacent base station coverage areas, thereby reducing interference.

[0061] In summary, this application establishes a closed-loop adaptive control mechanism through real-time environmental perception, intelligent identification of changes, precise parameter adjustment, and prioritization of critical services. This mechanism enables 5G base stations to dynamically adapt to complex indoor environmental changes and diverse service demands, effectively solving problems such as coverage blind spots, signal interference, and service quality degradation in traditional systems under dynamic physical environments and diverse service requirements. This significantly improves the adaptability, reliability, and user experience of indoor 5G networks.

[0062] In one possible design, such as Figure 2 As shown, in order to construct and update the real-time radio frequency environment map, this application may further include the following steps:

[0063] S101. Divide the base station coverage area into multiple grid units.

[0064] Dividing the base station coverage area into multiple grid units refers to logically or physically subdividing the indoor space served by the base station into a series of discrete areas with specific sizes and shapes.

[0065] As one possible implementation, these grid cells can be divided according to the actual indoor layout, signal propagation characteristics, or required coverage accuracy; for example, they can be divided into square, rectangular, or irregularly shaped areas. The aim is to provide fine spatial granularity for independent and accurate assessment of the RF environment at different locations.

[0066] S102. For each grid cell, the RSRP values ​​reported by multiple user terminals within the grid cell are weighted averaged or interpolated, and combined with the propagation characteristics analysis of the probe signal in the grid cell, the real-time signal strength and channel quality of the grid cell are determined, thus obtaining the real-time signal strength and channel quality of multiple grid cells.

[0067] As one possible implementation, after receiving the Reference Signal Received Power (RSRP) values ​​reported by multiple user terminals located within the grid cell, the base station synthesizes these RSRP data using statistical methods (such as weighted averaging) or spatial estimation algorithms (such as interpolation). Weighted averaging can assign different weights based on factors such as the distance of the user terminals and the reporting time; interpolation can use the RSRP values ​​of known points to estimate the RSRP values ​​of unknown points.

[0068] Simultaneously, analyzing the propagation characteristics of the probe signal within the grid cell reveals that the echo delay and intensity of the probe signal emitted by the base station are affected by the environment within the grid cell during penetration, reflection, and diffraction. By analyzing the echo characteristics of these probe signals, the impact of the physical environment of the grid cell on signal propagation can be understood more accurately. This allows for the determination of the real-time signal strength and channel quality of the grid cell, yielding real-time signal strength and channel quality for multiple grid cells. Real-time signal strength reflects the signal coverage level of the area, while channel quality comprehensively considers factors such as signal strength, interference, and noise, reflecting the reliability of data transmission.

[0069] S103. Based on the real-time signal strength and channel quality of multiple grid cells, construct and update the real-time radio frequency environment map.

[0070] Through the above technical solution, this application can obtain a more refined, accurate, and dynamically updated real-time radio frequency environment map. Compared with methods that rely solely on a single data source or coarse-grained area division, this solution significantly improves the modeling accuracy and real-time response capability for complex indoor radio frequency environments by combining the actual sensed data (RSRP) from user terminals and the physical environment information (echo characteristics) actively detected by the base station. This high-precision map enables the base station to more accurately identify subtle changes in the indoor physical environment, such as personnel movement, furniture adjustments, or switching of variable partition walls. This allows for more effective fine-tuning of beamforming and transmit power, thereby optimizing indoor coverage performance and improving user experience.

[0071] In one possible design, in order to infer obstacle characteristics, this application further includes the following steps:

[0072] S201. Extract multipath propagation features from wireless signal measurement reports.

[0073] Multipath propagation characteristics include the signal's angle of arrival, time of arrival, and multipath component intensity.

[0074] The multipath component intensity represents the energy level of the signal along each path. By analyzing these characteristics, we can make a preliminary judgment on whether there are obstacles in the signal propagation path and the mode of influence of the obstacles on the signal.

[0075] S202. Based on the multipath propagation characteristics and the echo characteristics of the detection signal, infer the material type of the obstacle.

[0076] For example, different materials (such as concrete, glass, wood, and metal) have different absorption, reflection, and transmission characteristics for wireless signals, resulting in different patterns in multipath propagation characteristics and echo characteristics of the detected signal (such as echo delay and intensity). By establishing a mapping relationship between these patterns and material types, machine learning algorithms or pre-set rule bases can be used to infer the specific material type of an obstacle based on observed multipath propagation characteristics and echo characteristics. The aim is to obtain the physical properties of the obstacle and provide more accurate parameters for subsequent signal propagation models.

[0077] S203. Monitor and infer the real-time status and impact properties of variable partition walls.

[0078] The monitoring and inference of the real-time status and impact attributes of the variable partition wall includes: monitoring the fluctuation patterns generated by the variable partition wall on the echo characteristics of the probe signal and the wireless signal measurement report; and inferring the real-time status of the variable partition wall and its specific impact attributes on the signal by monitoring the signal characteristics during the transition period.

[0079] For example, when a variable partition wall moves or changes its state, its signal blocking, reflection, or transmission characteristics change instantaneously, resulting in specific fluctuation patterns in the delay and intensity of the detected signal echo, as well as in the wireless signal measurement reports (such as RSRP and RSRQ) received by the user terminal. By monitoring these fluctuation patterns and combining them with the analysis of signal characteristics during the transition period, the real-time state of the variable partition wall (e.g., whether it is open, closed, partially open, or changed from one material to another) and its specific impact on the signal (e.g., attenuation coefficient, reflection coefficient, etc.) can be inferred. The aim is to dynamically adapt to changes in indoor layout and ensure the real-time accuracy of the radio frequency environment map.

[0080] S204. Combine the real-time location information of the user terminal with the echo delay and angle of arrival information of the detection signal to estimate the position and geometry of the obstacle.

[0081] The real-time location information of the user terminal can be obtained through various positioning technologies (such as Wi-Fi positioning, Bluetooth positioning, UWB positioning, or base station-assisted positioning). The echo delay of the detection signal can be used to calculate the distance from the obstacle to the base station, while the angle of arrival information can determine the direction of the obstacle. By comprehensively utilizing this information through algorithms such as triangulation, multi-point positioning, or ray tracing, the position coordinates of the obstacle in the indoor space can be accurately estimated, and its approximate geometric shape can be inferred (e.g., whether it is planar, cylindrical, or irregular).

[0082] S205. Based on the obstacle material type, the real-time status and influence attributes of the variable partition wall, the obstacle location and geometry, infer the obstacle characteristics.

[0083] The final obstacle characteristics are a comprehensive description that includes all the inferred attributes mentioned above.

[0084] For example, an obstacle might be inferred as "a concrete wall at coordinates (X, Y, Z) with a thickness of D, a signal attenuation coefficient of A, and a reflection coefficient of R", or "a variable glass partition currently in a half-open state with a signal transmittance of T".

[0085] Through the above technical solutions, this application can significantly improve the accuracy and comprehensiveness of inferring the characteristics of indoor obstacles. Specifically, by extracting multipath propagation characteristics and combining them with the echo characteristics of the probed signal, the material type of the obstacle can be identified more accurately, which is crucial for assessing signal penetration loss and reflection intensity. Simultaneously, dynamic monitoring of the real-time status and impact attributes of variable partition walls enables the system to respond promptly to changes in indoor layout, avoiding coverage blind spots or increased interference caused by environmental dynamics. Furthermore, by combining the user terminal location and probed signal echo information to estimate the obstacle's location and geometry, a more accurate spatial reference is provided for subsequent beamforming. These refined obstacle characteristic inference results lay a solid foundation for constructing a high-precision real-time radio frequency environment map, enabling base stations to more intelligently and accurately adjust beamforming direction and transmit power, effectively optimizing indoor coverage, reducing interference, and improving user experience, especially in dynamically changing indoor scenarios where its advantages are more pronounced.

[0086] In some preferred embodiments, a specific example is given below. Assume a large open-plan office area containing fixed concrete walls, glass partitions, and movable office screens (variable partition walls). When the base station needs to infer the characteristics of these obstacles, the system first extracts multipath propagation features from the wireless signal measurement reports submitted by user terminals. For example, when a signal passes through a glass partition, it may observe smaller angle-of-arrival dispersion and lower attenuation, while passing through a concrete wall may result in greater attenuation and more complex multipath components. Simultaneously, the base station transmits a probe signal and analyzes its echo delay and intensity. For example, the echo intensity of a concrete wall may be higher and the delay longer, while the echo intensity of a glass partition may be lower. By inputting these multipath propagation features and probe signal echo characteristics into a pre-trained classification model, the material types of the concrete walls and glass partitions can be inferred.

[0087] Furthermore, for movable office partitions, the system continuously monitors the fluctuation patterns generated by their impact on the echo characteristics of probed signals and the wireless signal measurement reports from user terminals. For example, when an office partition is moved or folded, its signal blocking or reflection characteristics change instantaneously, causing identifiable fluctuations in signal strength and multipath characteristics in specific areas. By analyzing the signal characteristics during these transition periods, the system can infer the real-time state of the office partition (e.g., whether it is fully unfolded, partially folded, or fully retracted) and its specific impact on the signal (e.g., the equivalent attenuation value in the current state).

[0088] Simultaneously, by combining real-time location information from user terminals (e.g., obtained through an indoor positioning system) and echo delay and angle of arrival information of the probe signals, the system can accurately estimate the location coordinates and approximate geometry of concrete walls, glass partitions, and office screens. For example, by using measurement reports from multiple user terminals at different locations and echo information from base station probe signals, triangulation or ray tracing algorithms can be used to determine the precise boundaries and shapes of obstacles. Ultimately, based on the inferred obstacle material type, the real-time state and influence attributes of the variable partition wall, and the obstacle location and geometry, the system can construct a comprehensive and dynamically updated obstacle characteristic model. For example, it can identify "a concrete wall located at (X1, Y1) with an attenuation coefficient of A1," "a glass partition located at (X2, Y2) with a transmittance of T1," and "a movable office screen located at (X3, Y3), currently in a semi-folded state, with an attenuation coefficient of A2 for the signal." These detailed obstacle characteristics will serve as a precise basis for subsequent beamforming and power adjustment.

[0089] In one possible design, in order to identify critical services and prioritize improving the communication quality of critical services when adjusting beamforming direction and transmit power, while coordinating the suppression of interference to adjacent areas, this application further includes the following steps:

[0090] S301. Identify the communication requirements of key services, including requirements for latency, bandwidth, and packet loss rate.

[0091] The communication requirements of critical services refer to the specific network performance requirements of those services. For example, services such as real-time video conferencing or remote surgery may require extremely low latency and high bandwidth, while certain IoT sensor data transmissions may have strict limitations on packet loss rates. These requirements can be identified through methods such as service type identification, user subscription information, or application layer protocol analysis.

[0092] S302. Analyze the channel state information report of the user terminal and the echo of the probe signal emitted by the base station itself, identify multiple signal paths with different propagation characteristics, and evaluate the stability of each signal path under the switching of variable partition wall state or instantaneous high power interference.

[0093] The Channel State Information (CSI) report from the user terminal provides detailed information on channel quality, multipath effects, and interference levels. The echo of the probe signal emitted by the base station itself provides physical information about environmental reflection, scattering, and diffraction, particularly the real-time location and material properties of dynamic obstacles such as variable partition walls. By fusing this information, multiple independent signal propagation paths between the base station and the user terminal can be accurately identified. The stability of each signal path can be evaluated by analyzing historical data, real-time fluctuation patterns, and predictive models.

[0094] S303. Based on communication requirements and signal path stability, dynamically select and activate at least two signal paths with relatively independent propagation characteristics and expected to be less affected by environmental changes for critical business users, and build resilient channels.

[0095] The construction of resilient channels is intended to ensure the continuity and reliability of critical services. This means that the system will intelligently select and activate at least two physically or logically independent signal paths for critical service users, based on the requirements of critical services for latency, bandwidth, packet loss rate, etc., and in conjunction with the evaluation results of the stability of each signal path.

[0096] It should be noted that these paths should have different propagation characteristics, such as passing through different reflective surfaces, diffraction paths, or penetrating obstacles of different materials, thereby reducing the probability that they will be simultaneously affected by the same environmental changes. Paths expected to be less affected by environmental changes refer to those whose signal quality and transmission performance fluctuate less under common indoor dynamics such as the movement of variable partition walls, personnel flow, or local interference.

[0097] S304. Allocate redundant radio resources to resilient channels and continuously monitor the signal quality and performance indicators of key services for each resilient channel.

[0098] For example, base stations can allocate more time-frequency resource blocks, higher modulation and coding scheme (MCS) redundancy, or lower retransmission thresholds to resilient channels, thus allocating redundant radio resources to resilient channels.

[0099] Meanwhile, the base station will continuously monitor the signal quality (such as RSRP, RSRQ, SINR) of each activated resilient channel and the performance indicators of key services (such as actual latency, throughput, and packet loss rate) in order to detect potential performance degradation in a timely manner.

[0100] S305. When a significant performance degradation of the resilient channel is detected, the data flow of critical services is seamlessly switched to another resilient channel with good performance, and the beam sidelobe suppression and null-point shaping strategies are adjusted according to the environmental interference.

[0101] For example, once a base station detects that the signal quality of the currently used resilient channel is lower than a preset threshold or that the performance indicators of critical services have deteriorated, and determines that the performance of the resilient channel has significantly declined, the system will immediately initiate a seamless handover mechanism to quickly and smoothly migrate the data flow of critical services to another resilient channel with good current performance in order to avoid service interruption.

[0102] Meanwhile, in order to cope with environmental interference, the base station will dynamically adjust the beamforming strategy according to the real-time interference situation, including enhancing beam sidelobe suppression to reduce interference to adjacent areas, and performing null beamforming in specific interference directions to minimize the impact of interference sources on critical business communications.

[0103] In some preferred embodiments, a specific example is given below. Suppose there is a large open-plan office area with multiple movable partitions, and multiple user terminals are conducting critical business activities, such as remote video conferencing and AR / VR collaboration.

[0104] First, the base station will identify the stringent requirements of these critical services for latency, bandwidth, and packet loss rate.

[0105] Next, the base station continuously analyzes the channel state information reports from these user terminals and the echoes of its own transmitted probe signals. For example, for a user terminal conducting a video conference, the base station might identify three main signal paths: a direct path, a path reflected through a glass partition, and a path reflected through the ceiling. By analyzing historical data and real-time fluctuations of these paths under transient interference such as movement of the partition wall or operation of a nearby microwave oven, the base station assesses that the direct path may be blocked when the partition wall moves, while the reflected path remains relatively stable.

[0106] Based on this, the system dynamically selects and activates two relatively independent paths for the video conferencing user, such as the path reflected through the glass partition and the path reflected through the ceiling, to construct a resilient channel. Simultaneously, additional wireless resources are allocated to this resilient channel, such as more PRBs and stronger error correction coding.

[0107] During the video conference, the base station continuously monitors the signal quality of both paths and the real-time performance metrics of the video conference (such as video smoothness and audio latency). If a significant decrease in the signal quality of one path is detected due to the movement of the partition wall, the system immediately and seamlessly switches the video data stream to the other, high-performance reflection path, ensuring uninterrupted video conferencing. Simultaneously, the base station adjusts beamforming based on the detected direction of the interference source, for example, by creating null points in the direction of the interference source, to minimize the impact on video conference communication and suppress interference to adjacent office areas.

[0108] Through the above technical solutions, this application can significantly improve the communication reliability and resilience of critical services in indoor coverage control of 5G base stations. Compared with solutions that only perform priority enhancement and general interference suppression, this application effectively addresses the challenges posed by dynamic obstacles and transient interference in indoor environments by constructing resilient channels with multi-path redundancy, ensuring the service continuity of critical services in complex and ever-changing environments. Furthermore, the introduction of seamless handover mechanisms and dynamic beamforming adjustment strategies further ensures that critical services can recover rapidly when link performance degrades, and effectively suppresses interference to adjacent areas, thereby optimizing overall spectrum efficiency and user experience while ensuring high-quality communication for critical services.

[0109] In one possible design, in order to identify critical services and prioritize improving the communication quality of critical services when adjusting beamforming direction and transmit power, while coordinating the suppression of interference to adjacent areas, this application further includes:

[0110] S401: Obtain the communication requirements of multiple key services.

[0111] Communication requirements can include specific requirements for latency, bandwidth, packet loss rate, and reliability. These requirements are usually determined by the type of service. For example, video conferencing services have high requirements for latency and bandwidth, while industrial control services may have extremely high requirements for latency and packet loss rate. These requirements can be obtained through user terminal reporting, network policy configuration, or requests to the service server.

[0112] S402. Analyze the channel state information reports of each key service user terminal and the echo of the probe signal emitted by the base station itself, identify multiple signal paths between each key service user terminal and the base station, and evaluate the propagation characteristics and stability of each signal path.

[0113] The channel state information report provides detailed information on channel quality, multipath effects, and interference levels. The sounding signal echo provides information on the reflection, scattering, and diffraction characteristics of environmental obstacles (such as walls, furniture, and people), including echo delay and intensity. By fusing this information, multiple signal propagation paths between the base station and each key service user terminal can be identified, such as direct paths, reflected paths, and diffracted paths. Simultaneously, the propagation characteristics (such as path loss, delay spread, and Doppler shift) and stability (such as the degree of susceptibility to environmental changes and the frequency of instantaneous fading) of each path are evaluated to provide a basis for subsequent path selection and beam optimization.

[0114] S403. Based on communication requirements and signal path stability, dynamically select and activate at least one primary path and one backup path for each critical service.

[0115] The primary path and the backup path have relatively independent propagation characteristics.

[0116] In practical applications, based on the assessment of communication requirements and signal path stability, the system dynamically selects the best-performing or most stable path as the primary path for each critical service user terminal, and selects at least one path with relatively independent propagation characteristics (i.e., its propagation path differs significantly from the primary path and is not easily affected by the same environmental changes simultaneously) as a backup path. This primary and backup path mechanism aims to improve the communication resilience of critical services.

[0117] S404. Identify the spatial proximity and signal path overlap between key business operations.

[0118] As one possible approach, by analyzing the real-time location information, signal angle of arrival, multipath propagation characteristics, and real-time radio frequency environment map of user terminals, the spatial distance relationship between different key service user terminals and whether their respective signal paths overlap can be identified.

[0119] S405. Based on spatial proximity, signal path overlap, and the priority of each key service, dynamically adjust the beamforming direction and transmit power of the base station antenna array to align the main lobe with the user terminals of each key service, and coordinate and optimize the sidelobe suppression and nulling of each key service beam to form nulls or reduce sidelobe energy in the interference directions between key services and between key services and non-key services.

[0120] Specifically, the beamforming direction and transmit power of the base station antenna array are dynamically adjusted based on identified spatial proximity relationships, signal path overlap, and the pre-defined priorities of each critical service. The main lobe is precisely aligned with each critical service user terminal to maximize its received signal strength. Simultaneously, to effectively suppress interference, the sidelobe suppression and null-point shaping strategies for each critical service beam are coordinated and optimized. This means that in directions where critical services may interfere with each other, and in directions where critical services interfere with non-critical service areas, the amplitude and phase weighting of the antenna array are adjusted to create signal nulls or significantly reduce sidelobe energy, thereby minimizing unnecessary interference, ensuring the communication quality of critical services, and maintaining a minimum service level in non-critical service areas.

[0121] S406: Continuously monitor the performance indicators of each key service and the signal quality of each signal path; when a performance degradation of any key service or a deterioration in the signal quality of the main path is detected, seamlessly switch to the backup path and re-optimize beamforming and transmit power.

[0122] Performance metrics can include throughput, latency, and packet loss rate, while signal quality can include RSRP and SINR. The system continuously monitors these metrics. Once a performance metric for a critical service is detected to be below a preset threshold, or if the signal quality of its main path deteriorates significantly (e.g., due to path congestion or increased interference caused by environmental changes), the system immediately initiates a seamless handover mechanism to switch the data stream of that critical service to a pre-selected backup path to maintain service continuity and quality. After the handover, beamforming and transmit power are re-optimized based on new channel conditions and environmental changes to adapt to the new propagation environment and ensure the continued high-performance operation of critical services.

[0123] In some preferred embodiments, a specific example is given below. Assume a large, intelligent office floor containing multiple critical business user terminals, such as user terminal A conducting a high-bandwidth video conference, a low-latency robot terminal B connected to an industrial control system, and a VoIP terminal C for emergency communication. These terminals may be distributed across different offices or areas, and the floor contains movable partitions and personnel movement.

[0124] First, the system will obtain the communication requirements of user terminals A, B, and C. For example, A needs high bandwidth and low latency, B needs extremely low latency and high reliability, and C needs extremely high reliability and low packet loss rate.

[0125] Next, the base station analyzes the channel state information reports submitted by these terminals and, in conjunction with the echoes of its own transmitted probe signals, identifies multiple signal paths between the base station and each terminal. For example, for terminal A, it might identify a direct path and a path reflected through a glass partition; for terminal B, it might identify a direct path and a path diffracted through a metal shelf. Simultaneously, it assesses the propagation characteristics and stability of these paths; for instance, a direct path might be stable but easily blocked by people, while a reflected path might be less stable but offers more diversity.

[0126] Based on this, the system dynamically selects a primary and backup path for each terminal. For example, for terminal A, the direct path is selected as the primary path and the reflected path as the backup path; for terminal B, the direct path is selected as the primary path and the diffracted path as the backup path. At the same time, the system will identify that terminal A and terminal B may be in spatial proximity at some time, and some of their signal paths may overlap.

[0127] Then, based on this information and the priorities of each terminal (e.g., emergency communication terminal C has the highest priority, followed by industrial control terminal B, and then video conferencing terminal A), the base station antenna array dynamically adjusts the beamforming direction and transmit power. Specifically, the base station precisely aligns the main lobe with terminals A, B, and C to maximize their received signal strength. Simultaneously, to prevent terminal A from interfering with terminal B, or terminal B from interfering with nearby non-critical service user terminals, the system coordinates and optimizes sidelobe suppression and nulling. For example, in directions where terminals A and B may interfere with each other, or in directions where terminal B may interfere with nearby non-critical service areas, signal nulls are formed or sidelobe energy is significantly reduced.

[0128] Finally, the system continuously monitors the performance metrics of terminals A, B, and C, such as throughput, latency, and packet loss rate, as well as the signal quality of their primary and backup paths. If it detects that the primary path (direct path) of terminal A is blocked due to someone passing by, resulting in a significant decrease in signal quality, the system will immediately and seamlessly switch the data stream of terminal A to the backup path (reflection path) and re-optimize beamforming and transmit power to adapt to the new propagation environment, ensuring the continuity and quality of the video conference.

[0129] Through the above technical solution, this application effectively addresses the limitations of traditional solutions in simultaneously ensuring the communication quality of critical services and suppressing interference in scenarios involving multiple critical services coexisting, dynamic environmental changes, and complex interference. Specifically, by dynamically selecting primary and backup paths for each critical service and identifying spatial proximity relationships, the communication resilience of critical services is significantly improved, enabling them to maintain service continuity even in the face of environmental changes or path degradation. Simultaneously, by finely coordinating and optimizing beamforming, null points are formed or sidelobe energy is reduced in the interference directions between critical services and between critical and non-critical services, greatly reducing unnecessary interference. This effectively maintains the overall spectrum efficiency of the system and the service level of non-critical services while ensuring the high-priority communication quality of multiple critical services. This solution not only improves the reliability of individual critical services but, more importantly, enables efficient collaborative work of multiple critical services in complex indoor environments, significantly enhancing the intelligence and robustness of 5G indoor coverage.

[0130] However, if the interference suppression strategy is too aggressive or lacks dynamic adaptability, it may inadvertently lead to a significant decrease in signal strength in non-critical business areas while ensuring the quality of communication for critical business, thereby affecting the experience of non-critical business users and the balanced utilization of overall network resources.

[0131] In response, this application further proposes a method for controlling indoor coverage of 5G base stations, the method further including:

[0132] S501. Determine the location where zero points are formed in the interference directions between critical business operations and between critical and non-critical business operations.

[0133] Determining the locations where null points form in the interference directions between critical services and between critical and non-critical services refers to the base station accurately calculating the directions of interference that need to be suppressed based on real-time radio frequency environment maps, real-time location information of user terminals, channel state information reports, and echo characteristics of probe signals. These directions typically correspond to the geographical locations of non-critical service user terminals or the directions of potential interference sources. The aim is to minimize signal energy in these specific directions, thereby reducing interference to other services.

[0134] S502, coordinately adjust the amplitude weighting and phase weighting of the base station antenna array to form nulls or reduce sidelobe energy in the direction of interference, while ensuring that the signal strength in non-critical business areas is not lower than the preset threshold.

[0135] As one possible implementation, base stations can use intelligent algorithms to finely control the amplitude (power) and phase of the transmitted signal of each antenna element in the antenna array. This control not only aims to concentrate main lobe energy on critical service user terminals and create signal nulls or significantly reduce sidelobe energy in the direction of interference, but more importantly, during this adjustment, the system will assess the signal strength in non-critical service areas in real time and maintain it above a preset minimum threshold. This preset threshold can be set according to the minimum service quality requirements or user experience standards for non-critical services to avoid coverage blind spots or service interruptions in non-critical services due to excessive interference suppression.

[0136] S503. Continuously monitor the signal quality of each critical and non-critical business.

[0137] As one possible implementation, the base station can periodically receive wireless signal measurement reports (such as RSRP, RSRQ, SINR, etc.) reported by user terminals and combine this with its own detection signal echo analysis to monitor the radio frequency environment of user terminals for both critical and non-critical services in real time.

[0138] As another possible implementation, the base station can send probe requests to user terminals to obtain their response status. Based on the response status, it can adjust the frequency and power of the probe requests to acquire signal data from sparse or interrupted areas. Furthermore, by combining the known obstacle locations, obstacle material types, and variable partition wall states in the real-time radio frequency environment map, it can perform attribute-enhanced interpolation and extrapolation on the signal data in sparse or interrupted areas to fill in missing performance indicators and signal quality data. Using the user terminal's movement trajectory information and historical communication patterns, it can predict the user terminal's future location and communication needs. Furthermore, based on the predicted future location and communication needs of the user terminal, it can estimate signal quality and predict performance indicators, thereby achieving continuous monitoring of various critical and non-critical services.

[0139] In this context, a probe request can be understood as a short-term signal or data packet initiated by the base station to assess the signal quality of a specific area or a specific user terminal.

[0140] Specifically, when the response from user terminals received by the base station is unsatisfactory, such as delayed response, low response rate, or no response, it can be determined that the area may be a sparsely signaled or interrupted area. In this case, the base station can adaptively adjust the transmission strategy of subsequent detection requests, such as increasing the transmission frequency of detection requests to increase data sampling density, or increasing the transmission power of detection requests to penetrate obstacles or cover a greater distance, thereby actively acquiring signal data in these challenging areas and ensuring comprehensive monitoring.

[0141] In practical applications, attribute-enhanced interpolation and extrapolation refer to data completion that, instead of relying solely on simple linear or nonlinear interpolation based on signal data from adjacent areas, fully utilizes existing environmental information from real-time RF environmental maps. For example, known obstacle locations, obstacle material types, and the status of variable partition walls can guide the interpolation and extrapolation process, making the completed signal quality data more consistent with actual physical propagation laws. For instance, behind a wall known to contain high-attenuation material, even without direct measurement data, a more accurate signal strength estimate can be made based on the attenuation characteristics of that material. Furthermore, user terminal movement trajectory information can be obtained through various methods, such as base station positioning, GPS information reported by the user terminal, or Wi-Fi / Bluetooth positioning information. Historical communication patterns can be learned from past user terminal data usage habits and service type preferences (e.g., video conferencing, file downloads, voice calls). Analysis of this historical data allows for the creation of predictive models to anticipate the user terminal's likely location and its demand for communication resources such as bandwidth and latency in the future. The solution proposed in this application combines the predicted future location of the user terminal with a real-time radio frequency environment map, enabling advance estimation of the signal quality conditions the user terminal may face at its future location. Simultaneously, by incorporating predicted communication demands, it can further predict whether the user terminal's service performance indicators (such as throughput, latency, and packet loss rate) can meet the requirements under this signal quality condition. This forward-looking estimation allows the base station to shift from passive response to proactive planning, providing a basis for subsequent beamforming direction and transmit power adjustments.

[0142] S504. When the signal quality of non-critical services is detected to be lower than a preset threshold, the beam null position or sidelobe suppression intensity is finely adjusted to improve the signal coverage of non-critical services without affecting the communication quality of critical services.

[0143] This means the system possesses adaptive adjustment capabilities. Once the signal quality of non-critical services is found to be below acceptable levels, the system will initiate a fine-tuning process. The core of this process is that any adjustments must be made without compromising the communication quality of critical services. Fine-tuning may include slightly shifting the null point so that it is no longer perfectly aligned with non-critical service users, or moderately relaxing the sidelobe suppression strength, thereby allowing more signal energy to reach non-critical service areas to improve their signal coverage and quality.

[0144] Through the above technical solution, this application enables refined and intelligent control of 5G base station indoor coverage, especially in complex indoor environments where multiple services coexist. This solution not only effectively guarantees the communication quality and priority of critical services, but more importantly, by introducing a dynamic monitoring and adaptive adjustment mechanism for the signal quality of non-critical services, it avoids the problem of degraded coverage of non-critical services due to excessive pursuit of critical service performance. This significantly improves the uniformity of user experience across the entire indoor coverage area, optimizes the utilization efficiency of spectrum resources, and enhances the network's adaptability and robustness to dynamic environmental changes. This ability to balance the performance of critical and non-critical services allows base stations to provide more stable, reliable, and user-satisfying indoor communication services.

[0145] In one possible design, in order to estimate signal quality and predict performance metrics based on the predicted future location and communication needs of user terminals, this application further includes:

[0146] S601. Based on the user terminal's moving speed and direction, and combined with the known physical layout information inside the building where the user terminal is located, adjust the prediction time window and correct the path of the predicted future location of the user terminal.

[0147] For example, faster-moving users might require shorter, more frequently updated prediction time windows, while stationary users could benefit from longer windows. Path correction involves optimizing the predicted trajectory of the user terminal by incorporating known physical constraints of the indoor environment, such as walls, corridors, and room layout. This helps avoid predicting unrealistic paths for the user terminal to traverse physical obstacles, thereby improving the accuracy of location prediction.

[0148] S602. Monitor changes in the service type and data traffic of user terminals, identify sudden communication patterns, and adjust the prediction weights of communication demand based on the identification results.

[0149] Monitoring these changes can identify bursty communication patterns, such as users initiating high-bandwidth video conferences or downloading large files. Once such patterns are identified, the predictive weights for communication demands will be adjusted. For example, if a user starts a video call, the weights for low-latency and high-bandwidth requirements in the predictive model will be increased to prioritize such services.

[0150] S603. Based on the predicted weights of the corrected future location of the user terminal and the adjusted communication demand, estimate the signal quality and predict performance indicators.

[0151] In this way, by dynamically adjusting the prediction time window and combining it with physical layout for path correction, the future location of user terminals can be estimated more accurately, avoiding unrealistic propagation path assumptions. Furthermore, by monitoring changes in service types and data traffic and identifying sudden communication patterns, the system can more accurately predict future communication needs and adjust prediction weights accordingly, effectively responding to dynamically changing service loads. Moreover, periodic prediction result verification and adaptive model parameter adjustment mechanisms enable the prediction model to continuously learn and optimize, ensuring high accuracy and robustness in complex and ever-changing indoor environments. As a result, base stations can perform more accurate and forward-looking beamforming and transmit power adjustments based on more reliable prediction information, significantly improving the communication quality assurance capabilities of critical services and effectively suppressing interference to adjacent areas, thus enhancing the overall intelligence and efficiency of indoor coverage control.

[0152] like Figure 3 As shown in the figure, this embodiment of the invention also provides a 5G base station indoor coverage control system. The system includes:

[0153] The acquisition module is used to acquire wireless signal measurement reports from user terminals within the base station coverage area and echo characteristics of the probe signals emitted by the base station itself. The echo characteristics of the probe signals include echo delay and intensity.

[0154] The fusion module is used to fuse wireless signal measurement reports and probe signal echo characteristics to build and update a real-time radio frequency environment map.

[0155] The comparison module is used to compare real-time radio frequency environment maps with baseline maps to identify changes in the physical environment and infer obstacle characteristics;

[0156] The adjustment module is used to adjust the beamforming direction and transmission power according to changes in the physical environment and the characteristics of obstacles;

[0157] The protection module is used to identify critical services and prioritize the communication quality of critical services when adjusting beamforming direction and transmit power, while coordinating the suppression of interference to adjacent areas.

[0158] This application also provides a computer-readable storage medium. All or part of the processes in the above method embodiments can be executed by a computer program instructing related hardware. This program can be stored in the computer-readable storage medium, and when executed, it can include the processes of the above method embodiments. The computer-readable storage medium can be an internal storage unit of the task execution device (including a data sending end and / or a data receiving end) of any of the foregoing embodiments, such as the hard disk or memory of the task execution device. The computer-readable storage medium can also be an external storage device of the terminal device, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device. Further, the computer-readable storage medium can include both the internal storage unit of the task execution device and an external storage device. The computer-readable storage medium is used to store the computer program and other programs and data required by the task execution device. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0159] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0160] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, essentially, or the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0161] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be covered within the scope of protection of this application.

Claims

1. A method for controlling indoor coverage of a 5G base station, characterized in that, include: The system acquires wireless signal measurement reports from user terminals within the base station's coverage area and echo characteristics of the detection signals emitted by the base station itself, wherein the echo characteristics of the detection signals include echo delay and intensity. By integrating the wireless signal measurement report and the echo characteristics of the probed signal, a real-time radio frequency environment map is constructed and updated; By comparing the real-time radio frequency environment map with the baseline map, changes in the physical environment can be identified and obstacle characteristics can be inferred. Adjust the beamforming direction and transmission power according to the changes in the physical environment and the characteristics of the obstacles; Key services are identified, and when adjusting the beamforming direction and the transmit power, the communication quality of the key services is prioritized, while simultaneously coordinating the suppression of interference to adjacent areas.

2. The 5G base station indoor coverage control method according to claim 1, characterized in that, The process of fusing the wireless signal measurement report and the echo characteristics of the detected signal to construct and update the real-time radio frequency environment map includes: The base station coverage area is divided into multiple grid units; For each grid cell, the RSRP values ​​reported by multiple user terminals within the grid cell are weighted averaged or interpolated, and combined with the propagation characteristics analysis of the probe signal in the grid cell, the real-time signal strength and channel quality of the grid cell are determined, thus obtaining the real-time signal strength and channel quality of the multiple grid cells. The real-time radio frequency environment map is constructed and updated based on the real-time signal strength and channel quality of the multiple grid cells.

3. The 5G base station indoor coverage control method according to claim 1, characterized in that, The comparison of the real-time radio frequency environment map and the reference map to identify changes in the physical environment includes: Compare the difference in signal strength and channel quality at each grid cell at the same location in the real-time radio frequency environment map and the reference map; If the difference in signal strength at each grid cell at the same location is greater than or equal to a preset signal strength difference, and the difference in channel quality at each grid cell at the same location is greater than or equal to a preset channel quality difference, then a change in the physical environment is identified.

4. The 5G base station indoor coverage control method according to claim 1, characterized in that, The inferred obstacle characteristics include: Multipath propagation features are extracted from the wireless signal measurement report; the multipath propagation features include the signal's angle of arrival, time of arrival, and multipath component strength. Based on the multipath propagation characteristics and the echo characteristics of the detection signal, the type of obstacle material is inferred; The real-time status and impact attributes of a variable partition wall are monitored and inferred, wherein the monitoring and inference of the real-time status and impact attributes of the variable partition wall includes: monitoring the fluctuation pattern generated by the variable partition wall in response to the echo characteristics of the probe signal and the wireless signal measurement report, and inferring the real-time status of the variable partition wall and its specific impact attributes on the signal by monitoring the signal characteristics during the transition period. By combining the real-time location information of the user terminal with the echo delay and angle of arrival information of the detection signal, the position and geometry of the obstacle are estimated. Based on the obstacle material type, the real-time status and influence attributes of the variable partition wall, the obstacle location and geometry, the obstacle characteristics are inferred.

5. The indoor coverage control method for a 5G base station according to claim 1, characterized in that, The process of identifying key services and prioritizing the improvement of communication quality for those key services when adjusting the beamforming direction and transmit power, while simultaneously coordinating the suppression of interference to adjacent areas, includes: Identify the communication requirements of key services, including requirements for latency, bandwidth, and packet loss rate; Analyze the channel state information reports from user terminals and the echoes of probe signals emitted by the base station itself to identify multiple signal paths with different propagation characteristics, and evaluate the stability of each signal path under the switching of variable partition wall states or instantaneous high-power interference. Based on the communication requirements and the stability of the signal paths, at least two signal paths with relatively independent propagation characteristics and expected to be less affected by environmental changes are dynamically selected and activated for key business users to build resilient channels. Redundant radio resources are allocated to the resilient channels, and the signal quality and performance indicators of the key services of each resilient channel are continuously monitored. When a significant performance degradation of the resilient channel is detected, the data stream of the critical service is seamlessly switched to another resilient channel with good performance, and the beam sidelobe suppression and null-point shaping strategies are adjusted according to environmental interference.

6. The indoor coverage control method for a 5G base station according to claim 1, characterized in that, The process of identifying key services and prioritizing the improvement of communication quality for those key services when adjusting the beamforming direction and transmit power, while simultaneously coordinating the suppression of interference to adjacent areas, includes: Obtain the communication requirements of multiple key business operations; Analyze the channel state information reports of each key service user terminal and the echo of the probe signal emitted by the base station itself to identify multiple signal paths between each key service user terminal and the base station, and evaluate the propagation characteristics and stability of each signal path. Based on the communication requirements and the stability of the signal path, at least one primary path and one backup path are dynamically selected and activated for each critical service, wherein the primary path and the backup path have relatively independent propagation characteristics. Identify spatial proximity and signal path overlap between key business operations; Based on the spatial proximity, signal path overlap, and priority of each key service, the beamforming direction and transmit power of the base station antenna array are dynamically adjusted to align the main lobe with the user terminals of each key service, and the sidelobe suppression and nulling of each key service beam are coordinated and optimized to form nulls or reduce sidelobe energy in the interference directions between key services and between key services and non-key services. Continuously monitor the performance indicators of each key service and the signal quality of each signal path; when a performance degradation of any key service or a deterioration in the signal quality of the main path is detected, seamlessly switch to the backup path and re-optimize beamforming and transmit power.

7. A method for controlling indoor coverage of a 5G base station according to claim 6, characterized in that, The coordinated optimization of sidelobe suppression and null shaping for each key service beam, forming nulls or reducing sidelobe energy in interference directions between key services and between key and non-key services, includes: Determine the locations where zero points are formed in the interference directions between the critical services and between the critical services and the non-critical services; The amplitude weighting and phase weighting of the base station antenna array are adjusted in a coordinated manner to form a null point or reduce sidelobe energy in the interference direction, while ensuring that the signal strength in non-critical service areas is not lower than a preset threshold. Continuously monitor the signal quality of each critical service and the non-critical service; When the signal quality of the non-critical service is detected to be lower than a preset threshold, the beam null position or sidelobe suppression intensity is finely adjusted to improve the signal coverage of the non-critical service without affecting the communication quality of the critical service.

8. A method for controlling indoor coverage of a 5G base station according to claim 7, characterized in that, The continuous monitoring of signal quality for each critical service and the non-critical service includes: The base station sends a probe request to the user terminal to obtain the user terminal's response. Based on the response to the detection request, adjust the frequency and power of the detection request to obtain signal data from sparse or interrupted regions. By combining the known obstacle locations, obstacle material types, and variable partition wall states in the real-time radio frequency environment map, attribute-enhanced interpolation and extrapolation are performed on the signal data of the sparse or interrupted regions to complete the missing performance indicators and signal quality data. By utilizing the user terminal's movement trajectory information and historical communication patterns, the future location and communication needs of the user terminal can be predicted. Based on the predicted future location and communication needs of user terminals, signal quality and performance indicators are estimated, thereby enabling continuous monitoring of the key and non-key services.

9. A 5G base station indoor coverage control method according to claim 8, characterized in that, The process of estimating signal quality and predicting performance metrics based on the predicted future location and communication needs of user terminals includes: Based on the user terminal's moving speed and direction, combined with the known physical layout information inside the building where the user terminal is located, the prediction time window is adjusted, and the predicted future location of the user terminal is path corrected. Monitor changes in the service type and data traffic of the user terminal, identify sudden communication patterns, and adjust the prediction weight of the communication demand based on the identification results; Based on the revised prediction weights of the user terminal's future location and adjusted communication requirements, signal quality and predictive performance metrics are estimated.

10. A 5G base station indoor coverage control system, characterized in that, The system includes: The acquisition module is used to acquire wireless signal measurement reports of user terminals within the base station coverage area and echo characteristics of the detection signal emitted by the base station itself, wherein the echo characteristics of the detection signal include echo delay and intensity; The fusion module is used to fuse the wireless signal measurement report and the echo characteristics of the probe signal to construct and update the real-time radio frequency environment map; The comparison module is used to compare the real-time radio frequency environment map and the reference map to identify changes in the physical environment and infer obstacle characteristics; An adjustment module is used to adjust the beamforming direction and transmission power according to the changes in the physical environment and the characteristics of the obstacles; The protection module is used to identify critical services and, when adjusting the beamforming direction and the transmit power, prioritize the communication quality of the critical services while coordinating the suppression of interference to adjacent areas.

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