Wireless network coverage optimization method based on spatial positioning and transmitting power regulation and control

Abstract

The invention discloses a wireless network coverage optimization method based on spatial positioning and transmitting power regulation and control. The method comprises the following steps: S1, collecting real-time signal quality and link state data of a base station and user equipment; s2, dynamically adjusting the transmitting power of the base station according to the collected signal quality and link state data; s3, constructing an interference sensing matrix, further calculating a conflict weight according to the interference sensing matrix, and optimizing frequency and time slot resources based on the conflict weight; s4, adjusting a frequency subset, a time slot subset and a power upper limit according to an optimization result; s5, dynamically adjusting the transmitting power and the interference coordination strategy by receiving interference information from other base stations in real time and the feedback of the user; and S6, adjusting power distribution, spectrum resources and channel selection of the network according to the real-time feedback of the network environment. According to the method, an efficient and scientific optimization scheme can be provided in wireless network coverage optimization, and remarkable technical values and economic benefits are brought to practical application.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless network coverage, and particularly to an optimization method for wireless network coverage based on spatial positioning and transmission power regulation. Background Art

[0002] The rapid development of wireless networks has brought higher requirements for network coverage and quality. In the current wireless communication system, especially in high-density urban environments, complex network environments, or high-speed mobile scenarios, traditional network optimization methods have become difficult to meet the growing user needs and increasingly complex interference problems. To improve the coverage effect and transmission quality of wireless networks, researchers have introduced technologies such as adaptive power control and interference coordination in wireless network optimization. Adaptive power control can dynamically adjust the transmission power according to the actual load, link quality, and interference information of the network to achieve more balanced coverage and optimize network resource utilization. The interference coordination technology reduces co-channel interference and adjacent-channel interference by coordinating the resource usage between base stations, thereby improving network stability and communication quality.

[0003] Currently, many existing technologies mainly focus on a single aspect of power control or interference management in wireless network optimization. Traditional power control technologies usually rely on simple algorithms and depend on the initial configuration of base stations and user equipment in the network and the static network environment. When the network environment changes dynamically, these technologies cannot quickly respond to changes in interference and load, resulting in uneven network coverage or excessive interference problems. In addition, although existing interference coordination technologies can coordinate resource allocation between base stations, most of them fail to effectively combine dynamic interference information and power control strategies, resulting in frequent resource conflicts between base stations or failure to fully utilize spectrum resources.

[0004] There are still some limitations in the existing technologies, mainly reflected in their inability to flexibly adjust power control and interference coordination strategies according to real-time environmental changes. For example, when traditional power control methods adjust the transmission power, they usually rely on static signal quality and link state data, while ignoring the dynamic changes of interference feedback and network load. In addition, existing interference coordination algorithms are often too simplified and fail to reflect the interference effects between different base stations and user equipment in real time. Therefore, the existing technologies cannot fully optimize the overall coverage effect of wireless networks, resulting in unbalanced resource utilization and even network congestion or insufficient signal coverage in high-density user scenarios.

[0005] To overcome the above deficiencies, the present invention proposes a method for optimizing wireless network coverage based on adaptive power control and interference coordination. This method collects real-time network environment data, including key indicators such as base station transmit power, received signal strength indication, signal-to-interference-plus-noise ratio, and network load. By combining adaptive power control and interference coordination technologies, it dynamically adjusts network resource allocation, thereby achieving optimized network coverage and communication quality. During this process, the base station can flexibly adjust transmit power, frequency resources, and time slot resources according to the real-time feedback of interference information and network load, avoiding resource conflicts and reducing interference, and enhancing the overall network stability and throughput. The innovation of this method lies in combining power control and interference coordination technologies, and through dynamic response to environmental changes, it realizes more efficient network resource management, especially effectively improving the service quality and user experience of wireless networks in complex environments. Summary of the Invention

[0006] An object of the present invention is to propose a method for optimizing wireless network coverage based on spatial positioning and transmit power regulation. The present invention can provide an efficient and scientific optimization scheme in wireless network coverage optimization, bringing significant technical value and economic benefits to practical applications.

[0007] The method for optimizing wireless network coverage based on spatial positioning and transmit power regulation according to an embodiment of the present invention includes the following steps:

[0008] S1. Collect real-time signal quality and link state data of base stations and user equipment;

[0009] S2. The base station, according to the collected signal quality and link state data, adopts an adaptive power control algorithm to dynamically adjust the transmit power of the base station for the actual link conditions between each base station and user equipment.

[0010] S3. The base station constructs an interference awareness matrix based on the frequency subsets, time slot subsets, and transmit powers of all base stations in the neighboring cell set, and further calculates the conflict weight according to the interference awareness matrix, and jointly coordinates and allocates and optimizes frequency and time slot resources based on the conflict weight.

[0011] S4. The base station adjusts its own frequency subset, time slot subset, and power upper limit according to the optimization result.

[0012] S5. The base station dynamically adjusts the transmit power and interference coordination strategy by receiving interference information from other base stations and feedback from user equipment in real time.

[0013] S6. The base station dynamically adjusts the power allocation, spectrum resources, and channel selection of the network according to the real-time feedback and load changes of the network environment and in combination with adaptive power control and interference coordination technologies.

[0014] Optionally, S1 includes the following steps:

[0015] S11. Collect data on the base station's transmit power, received signal strength indication, signal-to-interference-plus-noise ratio, changes in the link state between the base station and the user equipment, connection quality data between the base station and the user equipment, and geographical location data of the base station and the user equipment.

[0016] Optionally, S2 includes the following steps:

[0017] S21. The base station calculates the signal quality of the current link based on the received signal strength indication and the signal-to-interference-plus-noise ratio, and sets the target signal strength and the target signal-to-interference-plus-noise ratio;

[0018] S22. Calculate the difference between the actual transmit power P actual and the target transmit power P target , and adjust the actual transmit power according to the power increment ΔP:

[0019]

[0020] where P' actual is the adjusted actual transmit power, γ and δ are constants that control the signal quality and power adjustment sensitivity, SINR actual is the actual signal-to-interference-plus-noise ratio of the current link, SINR target is the target signal-to-interference-plus-noise ratio of the current link, and the adjustment formula takes into account the impact of the deviation of the signal-to-interference-plus-noise ratio on power adjustment;

[0021] S23. The base station dynamically adjusts the transmit power according to the geographical location and movement state of the user equipment:

[0022] P base = P′ actual + ΔP state ;

[0023] where P base is the adjusted transmit power, and ΔP state is the power allocated according to the geographical location and movement state of the user equipment;

[0024] S24. The base station further adjusts the transmit power to P final according to the service requirements and load conditions of different users, and the load balancing optimization formula is:

[0025]

[0026] where U i is the service requirement of the i-th user equipment, σ i is the bandwidth requirement of the i-th user equipment, N is the number of users in the network, and ΔPload Allocate power according to user load and requirements to optimize network coverage and throughput.

[0027] Optionally, S23 includes the following steps:

[0028] S231. The power ΔP allocated according to the geographical location and movement status of the user equipment state is:

[0029]

[0030] where η is an adjustment factor, d is the distance between the user equipment and the base station, d0 is the reference distance, RSSI target is the target signal strength, RSSI actual is the actual signal strength, and κ and λ are constants calculated according to the propagation model to ensure the optimization of the transmission power at different positions and distances.

[0031] Optionally, S3 includes the following steps:

[0032] S31. The base station periodically broadcasts the frequency subset F i ={f1,f2,…,f m}, time slot subset T i ={t1,t2,…,t n} and the current transmission power P i to adjacent base stations;

[0033] S32. Each base station receives the frequency and power configuration data from all base stations in the neighboring cell set and constructs an interference awareness matrix I ij :

[0034]

[0035] where P j is the transmission power of the neighboring base station j, G ji is the channel gain from base station j to base station i, and N0 is the noise power density;

[0036] S33. The base station calculates the conflict weight W ij in the interference awareness matrix I ij :

[0037] W ij =φ(I ij )=log2(1 + I ij );

[0038] where φ is a conflict weight mapping function for nonlinearly amplifying interference awareness, reflecting the conflict degree of resource usage between neighboring cells;

[0039] S34. The base station utilizes the conflict weight W ij to jointly coordinate and optimize the allocation of frequency and time slot resources.

[0040] Optionally, S34 includes the following steps:

[0041] S341. The base station jointly coordinates the allocation of frequency and time slot resources by optimizing the following objective function:

[0042]

[0043] where represents the set of neighboring cells of base station i, W ij is the conflict weight, 1(·) is an indicator function used to determine whether there is a resource conflict between base stations, F i is the frequency subset of base station i, F i is the frequency subset of base station i, T i is the time slot subset of base station i, T j is the time slot subset of base station j, η is a regulation factor that controls the trade-off between interference suppression and resource allocation, P k is the transmit power of base station k, G ki is the channel gain from base station k to base station i. This objective function aims to minimize the conflict of frequency and time slot resources while considering the impact of power and channel interference between base stations on resource allocation.

[0044] Optionally, S4 includes the following steps:

[0045] S41. The base station adjusts its own frequency subset, time slot subset, and power ceiling according to the optimization result. The power ceiling is calculated as:

[0046]

[0047] where P target is the target transmit power, P i is the transmit power of base station i, represents the set of neighboring cells of base station i, W ij is the conflict weight. This power constraint expression is used to suppress the co-channel interference caused by excessive power while maintaining the communication quality.

[0048] Optionally, S5 includes the following steps:

[0049] S51. The base station constructs an updated interference matrix by receiving interference information from other base stations and feedback from user equipment in real time, and calculates a new transmit power adjustment amount according to the updated interference matrix;

[0050] S52. The base station adjusts the current transmission power according to the new transmission power adjustment amount;

[0051] S53. The base station dynamically adjusts the interference coordination strategy according to the network load and user requirements.

[0052] Optionally, the S6 includes the following steps:

[0053] S61. The base station re-evaluates the current transmission power and interference awareness matrix according to the real-time feedback of the network environment and load changes;

[0054] S62. The base station dynamically adjusts the allocation of power and spectrum resources according to the interference situation of the network and user requirements;

[0055] S63. The base station calculates the target quality of service indicators and adjusts power control and resource allocation according to the bandwidth requirements of user equipment;

[0056] S64. The base station dynamically adjusts the power allocation, spectrum resources and channel selection of the network according to the optimization results to ensure stability and reliability in high-density or complex environments, and further improve the throughput and coverage of the network. The resource update is carried out through the following optimization constraint formula:

[0057] ∑ i∈I P i (t) ≤ P max ,∑ i∈I σ u (t) ≤ σ total ;

[0058] Where, P i (t) represents the transmission power of base station i at time t, P max is the maximum available power of the network, σ u (t) is the bandwidth requirement of the user equipment at time t, σ total is the total network bandwidth limit.

[0059] Optionally, the S63 includes the following steps:

[0060] S631. The base station adjusts power control and resource allocation by optimizing the following objective function:

[0061]

[0062] Where, P i (t) represents the transmission power of base station i at time t, C i (t) represents the channel selected by base station i at time t, U i is the set of user equipment of base station i, σ u (t) the bandwidth requirement of the user equipment, Let \(B(t)\) be the target bandwidth requirement of the user equipment at time \(t\), \(\lambda\) be the coefficient for balancing bandwidth requirements and interference, and \(I(t)\) be the re-evaluated interference matrix. ij is the re-evaluated interference matrix.

[0063] The beneficial effects of the present invention are as follows:

[0064] (1) The method for optimizing wireless network coverage based on adaptive power control and interference coordination proposed by the present invention can effectively solve the limitations in the prior art, and provides a more flexible and efficient wireless network resource management method. By combining adaptive power control and interference coordination technologies, this method can automatically adjust network resources according to the real-time changes in the network environment. Especially in the case of dynamic load and interference changes, it can achieve dynamic optimization of the network.

[0065] (2) After adopting the adaptive power control technology in the present invention, the base station can intelligently adjust the transmission power according to the signal quality and link status data collected in real time to ensure that the signal strength between each base station and the user equipment always remains within the ideal range. This not only avoids the problems of insufficient coverage or over-coverage caused by too strong or too weak signals, but also can significantly improve the coverage uniformity and stability of the network. Especially in complex or high-density environments, it can effectively solve the deficiencies in traditional power control methods.

[0066] (3) Through the interference coordination mechanism in the present invention, the base stations can share frequency, time slot, and power usage information in real time and make coordinated adjustments according to the interference situation in the network. This mechanism can effectively reduce co-channel interference and adjacent-channel interference, thereby improving the stability of the wireless network, ensuring that there are no resource conflicts between multiple base stations, and avoiding the defects in traditional interference management methods that do not fully consider interference and resource conflicts. At the same time, the dynamic coordinated adjustment between base stations can make more reasonable use of spectrum resources and improve spectrum efficiency. Description of the Drawings

[0067] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0068] Figure 1 is the flowchart of the method for optimizing wireless network coverage based on spatial positioning and transmission power regulation proposed by the present invention;

[0069] Figure 2 is the flowchart of dynamically adjusting the transmission power of the base station in the method for optimizing wireless network coverage based on spatial positioning and transmission power regulation proposed by the present invention;

[0070] Figure 3It is the flow chart of the joint optimization of frequency and time slot resources in the wireless network coverage optimization method based on spatial positioning and transmission power regulation proposed by the present invention. Detailed implementation manners

[0071] Now, the present invention will be further described in detail with reference to the accompanying drawings. These drawings are all simplified schematic diagrams, only illustrating the basic structure of the present invention in a schematic manner, so they only show the components related to the present invention.

[0072] Refer to Figures 1 - 3 , the wireless network coverage optimization method based on spatial positioning and transmission power regulation includes the following steps:

[0073] S1. Collect the real-time signal quality and link state data of the base station and the user equipment;

[0074] S2. According to the collected signal quality and link state data, the base station adopts an adaptive power control algorithm to dynamically adjust the transmission power of the base station according to the actual link conditions between each base station and the user equipment;

[0075] S3. The base station constructs an interference awareness matrix based on the frequency subset, time slot subset, and transmission power of all base stations in the neighboring cell set, and further calculates the conflict weight according to the interference awareness matrix, and jointly coordinates and allocates and optimizes the frequency and time slot resources based on the conflict weight;

[0076] S4. The base station adjusts its own frequency subset, time slot subset, and power upper limit according to the optimization result;

[0077] S5. The base station dynamically adjusts the transmission power and interference coordination strategy by receiving the interference information from other base stations and the feedback of the user equipment in real time;

[0078] S6. The base station dynamically adjusts the power distribution, spectrum resources, and channel selection of the network according to the real-time feedback and load changes of the network environment, and combines the adaptive power control and interference coordination technologies.

[0079] By collecting the real-time signal quality and link state data of the base station and the user equipment in the wireless network, the present invention can provide accurate basic data support for subsequent power control and interference coordination. Through the real-time monitoring of key indicators such as received signal strength indication, signal-to-interference-plus-noise ratio, link quality, and base station transmission power, the network management system can obtain comprehensive and detailed network environment information. This process effectively avoids the problem that the traditional static configuration method is insensitive to environmental changes, ensures that the network can adjust resources in real time in a dynamically changing environment, and provides a more accurate and efficient optimization solution.

[0080] In this embodiment, S1 includes the following steps:

[0081] S11. Collect the base station transmission power, received signal strength indication, signal-to-interference plus noise ratio, data on the change in the link state between the base station and the user equipment, connection quality data between the base station and the user equipment, and geographical location data of the base station and the user equipment.

[0082] Through the application of the adaptive power control algorithm in the present invention, the base station can dynamically adjust the transmission power according to the real-time collected signal quality and link state data. This mechanism ensures that the signal strength between each base station and the user equipment in the network always remains within the ideal range, avoiding problems such as insufficient coverage or over-coverage caused by too strong or too weak signals. Compared with the traditional fixed power control method, this step enables quick response and adaptive adjustment when the network load and environmental conditions change, thereby improving the coverage uniformity and stability of the wireless network.

[0083] In this embodiment, S2 includes the following steps:

[0084] S21. The base station calculates the signal quality of the current link according to the received signal strength indication and the signal-to-interference plus noise ratio, and sets the target signal strength and the target signal-to-interference plus noise ratio.

[0085] S22. Calculate the difference between the actual transmission power P actual and the target transmission power P target , and adjust the actual transmission power according to the power increment ΔP:

[0086]

[0087] where P' actual is the adjusted actual transmission power, γ and δ are constants controlling the sensitivity of signal quality and power adjustment, SINR actual is the actual signal-to-interference plus noise ratio of the current link, SINR target is the target signal-to-interference plus noise ratio of the current link, and the adjustment formula takes into account the impact of the deviation of the signal-to-interference plus noise ratio on power adjustment;

[0088] S23. The base station dynamically adjusts the transmission power according to the geographical location and movement state of the user equipment:

[0089] P base = P′ actual + ΔP state ;

[0090] where P base is the adjusted transmission power, and ΔP state is the power allocated according to the geographical location and movement state of the user equipment;

[0091] S24. The base station further adjusts the transmission power to P according to the service requirements and load conditions of different users.final , the load balancing optimization formula is:

[0092]

[0093] where U i is the service demand of the i-th user equipment, σ i is the bandwidth demand of the i-th user equipment, N is the number of users in the network, and ΔP load allocates power according to user load and demand to optimize network coverage and throughput.

[0094] In this embodiment, S23 includes the following steps:

[0095] S231. The power ΔP allocated according to the geographical location and movement state of the user equipment state is:

[0096]

[0097] where η is an adjustment factor, d is the distance between the user equipment and the base station, d0 is the reference distance, RSSI target is the target signal strength, RSSI actual is the actual signal strength, and κ and λ are constants calculated according to the propagation model to ensure the optimization of the transmission power at different positions and distances.

[0098] The interference coordination mechanism of the present invention effectively reduces the co-channel interference and adjacent-channel interference problems by sharing the frequency, time slot, and power usage conditions among base stations. The resource sharing and collaborative adjustment among base stations can not only reduce the risk of spectrum usage conflicts but also improve the utilization efficiency of spectrum resources, thereby optimizing the overall network performance. Compared with the traditional single-base-station interference management method, this mechanism can more effectively avoid the interference caused by the frequency and time slot conflicts of neighboring base stations, improving the stability and reliability of the network, especially in high-density and complex wireless environments.

[0099] In this embodiment, S3 includes the following steps:

[0100] S31. The base station periodically broadcasts the frequency subset F i ={f1, f2, …, f m}, time slot subset T i ={t1, t2, …, t n}, and the current transmission power P i to adjacent base stations;

[0101] S32. Each base station receives the frequency and power configuration data of all base stations from the neighboring cell set and constructs an interference awareness matrix I ij :

[0102]

[0103] Among them, P j is the transmission power of the neighboring base station j, G ji is the channel gain from base station j to base station i, and N0 is the noise power density;

[0104] S33. The base station calculates the conflict weight W ij according to the interference intensity value in the interference perception matrix I ij :

[0105] W ij = φ(I ij ) = log2(1 + I ij );

[0106] Among them, φ is a conflict weight mapping function for non-linearly amplifying interference perception, reflecting the conflict degree of resource usage between neighboring cells;

[0107] S34. The base station jointly coordinates and allocates and optimizes frequency and time slot resources by using the conflict weight W ij .

[0108] In this embodiment, S34 includes the following steps:

[0109] S341. The base station jointly coordinates and allocates frequency and time slot resources by optimizing the following objective function:

[0110]

[0111] Among them, represents the set of neighboring cells of base station i, W ij is the conflict weight, 1(·) is an indicator function used to judge whether there is a resource conflict between base stations, F i is the frequency subset of base station i, F i is the frequency subset of base station i, T i is the time slot subset of base station i, T j is the time slot subset of base station j, η is a regulation factor that controls the trade-off between interference suppression and resource allocation, P k is the transmission power of base station k, G ki is the channel gain from base station k to base station i. This objective function aims to minimize the frequency and time slot resource conflicts while considering the influence of power and channel interference between base stations on resource allocation.

[0112] The present invention adjusts the transmission power according to interference information, selects appropriate channels, and optimizes the time-domain and frequency-domain resource allocation, which can significantly reduce interference and improve the signal transmission quality. Different from traditional interference management technologies, the present invention calculates the interference matrix in real time and dynamically adjusts the resource allocation to ensure the minimization of interference between each base station and other base stations in the network, thereby improving the stability and communication quality of the entire network. In addition, through real-time optimization of power and channel selection, this step can more flexibly respond to environmental changes, improve the spectrum utilization efficiency, and effectively avoid network congestion problems caused by unreasonable resource allocation.

[0113] In this embodiment, S4 includes the following steps:

[0114] S41. The base station adjusts its own frequency subset, time slot subset, and power ceiling according to the optimization result. The calculation method of the power ceiling is:

[0115]

[0116] where P target is the target transmission power, P i is the transmission power of base station i, represents the set of neighboring cells of base station i, and W ij is the conflict weight. This power constraint expression is used to suppress the co-channel interference caused by excessive power while maintaining the communication quality.

[0117] The present invention continuously monitors the changes in the network environment and dynamically adjusts the power control and interference coordination strategies according to real-time interference feedback and network load. This continuous dynamic adjustment can ensure the stability and reliability of the network in a complex environment. Especially in high-density scenarios or complex network conditions, it can automatically respond to load changes and interference fluctuations, avoiding performance bottlenecks caused by fixed configuration strategies. At the same time, the base station dynamically optimizes the resource allocation according to the load and interference feedback, thereby effectively improving the network throughput and user experience, and maximizing the utilization efficiency of network resources on the premise of ensuring the quality of service.

[0118] In this embodiment, S5 includes the following steps:

[0119] S51. The base station constructs an updated interference matrix by receiving real-time interference information from other base stations and feedback from user equipment, and calculates a new transmission power adjustment amount according to the updated interference matrix;

[0120] S52. The base station adjusts the current transmission power according to the new transmission power adjustment amount;

[0121] S53. The base station dynamically adjusts the interference coordination strategy according to the network load and user requirements. ​

[0122] Through the combination of adaptive power control and interference coordination, the present invention optimizes the interaction between the base station and the user equipment. By adjusting the transmission power, spectrum resources, and channel allocation in real time, the present invention can achieve the optimal resource allocation in different network environments, improve the coverage effect and throughput of the wireless network. Compared with the traditional optimization methods, this step can not only achieve the coordinated optimization of power control and interference coordination, but also dynamically adapt to the changes of user requirements and network load, ensuring that the network always maintains an efficient and stable operating state in high-load, high-density, or dynamically changing environments, thus significantly improving the service quality of the user equipment.

[0123] In this embodiment, S6 includes the following steps:

[0124] S61. The base station re-evaluates the current transmission power and interference perception matrix according to the real-time feedback of the network environment and the load change.

[0125] S62. The base station dynamically adjusts the allocation of power and spectrum resources according to the interference situation of the network and the user requirements.

[0126] S63. The base station adjusts the power control and resource allocation by calculating the target service quality index and according to the bandwidth requirements of the user equipment.

[0127] S64. The base station dynamically adjusts the power allocation, spectrum resources, and channel selection of the network according to the optimization results, ensuring the stability and reliability in high-density or complex environments, and further improving the throughput and coverage of the network. The resource update is performed through the following optimization constraint formula:

[0128] ∑ i∈I P i (t) ≤ P max ,∑ i∈I σ u (t) ≤ σ total ;

[0129] Wherein, P i (t) represents the transmission power of base station i at time t, P max is the maximum available power of the network, σ u (t) is the bandwidth requirement of the user equipment at time t, and σ total is the total network bandwidth limit.

[0130] In this embodiment, S63 includes the following steps:

[0131] S631. The base station adjusts the power control and resource allocation by optimizing the following objective function:

[0132]

[0133] Among them, P i (t) represents the transmission power of base station i at time t, C i (t) represents the channel selected by base station i at time t, U i is the set of user equipment of base station i, σ u (t) is the bandwidth requirement of the user equipment, is the target bandwidth requirement of the user equipment at time t, λ is the coefficient for balancing bandwidth requirements and interference, I ij (t) is the re-evaluated interference matrix.

[0134] Embodiment:

[0135] In this embodiment, a typical urban high-density area is selected as the application scenario, located in the commercial core area of a certain city. This area is densely populated, with dense buildings, and a large number of user equipments are simultaneously connected to the wireless network. Due to the large mobility of users, diverse device types, and complex usage requirements in the commercial core area, traditional wireless network optimization methods cannot effectively meet the requirements of this area for network coverage quality, signal stability, and throughput, and problems such as uneven signals, frequent disconnections, and network congestion often occur.

[0136] In such an environment, traditional wireless network optimization technologies usually use fixed transmission power and interference management methods for coverage optimization. However, as the network load increases, these methods often cannot respond in real time to the dynamic changes in the network environment, resulting in uneven signal strength, waste of spectrum resources, and frequent network lags. This situation is particularly serious in high-density areas, leading to a decline in user experience and the inability to effectively guarantee network reliability and service quality.

[0137] The present invention effectively solves the above problems by combining adaptive power control and interference coordination technologies. In this scenario, the implementer applies a wireless network coverage optimization method based on adaptive power control and interference coordination to optimize the communication quality between base stations and user equipments in this area.

[0138] First, the implementer deploys a series of base stations in this area. All base stations are equipped with wireless communication devices that support dynamic power adjustment and interference coordination. At each base station, the implementer collects signal quality data in real time, including received signal strength indication, signal-to-interference-plus-noise ratio, etc., and simultaneously monitors information such as the transmission power and link status of each base station. Whenever the network environment changes, the system automatically adjusts the transmission power according to the collected data to ensure that the signal strength between each base station and the user equipment remains within the ideal range.

[0139] In addition, all base stations share frequency, time slot, and power usage in real time through an interference coordination mechanism, and cooperate to adjust resource allocation to reduce interference. For example, the base station will select different frequencies and time slots for communication according to the channel interference matrix and resource conflict situation to avoid interference and improve the utilization efficiency of spectrum resources. The power adjustment and channel allocation strategies of each base station will be dynamically optimized according to real-time load and interference feedback, thus effectively improving the throughput and stability of the network.

[0140] To verify the effectiveness of the method of the present invention, the implementer conducted a two-week on-site test in the commercial core area and collected a large amount of actual data. During the test period, a total of 5 base stations were deployed in the area, and the average number of connected user devices per day was about 5,000 (reaching 7,000 during peak hours). By comparing the network performance under the traditional fixed power and spectrum resource management methods with the network performance after adopting the method of the present invention, the specific data is shown in Table 1 below:

[0141] Table 1 Comparison of network performance in the test of the present invention and traditional methods

[0142]

[0143]

[0144] As can be seen from the above data, when using the traditional fixed power method, there are obvious fluctuations in the signal strength of the base station, and the signal strength is weak in different time periods, resulting in insufficient coverage in some areas. After adopting the method of the present invention, the signal strength is effectively improved, and the fluctuation is small, remaining within an ideal range, ensuring uniform network coverage.

[0145] Through actual tests and data comparison in the high-density area of this city, the remarkable effects of the method of the present invention in improving signal strength, network throughput, and stability are verified. The combination of adaptive power control and interference coordination technology enables the base station to flexibly cope with interference and optimize power allocation in complex environments, improving network coverage uniformity and service quality, and solving problems such as insufficient coverage, excessive interference, and low throughput existing in traditional technologies. This optimization method is not only applicable to high-density environments such as commercial core areas, but also can provide effective solutions for other high-load network environments.

[0146] The above is only the preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. A method for optimizing wireless network coverage based on spatial positioning and transmission power regulation, characterized in that, It includes the following steps: S1. Collect the real-time signal quality and link status data of the base station and the user equipment; S2. According to the collected signal quality and link status data, the base station adopts an adaptive power control algorithm to dynamically adjust the transmission power of the base station for the actual link conditions between each base station and the user equipment; S3. The base station constructs an interference awareness matrix based on the frequency subset, time slot subset, and transmission power of all base stations in the neighboring cell set, and further calculates the conflict weight according to the interference awareness matrix, and jointly coordinates and allocates and optimizes the frequency and time slot resources based on the conflict weight; S4. The base station adjusts its own frequency subset, time slot subset, and power ceiling according to the optimization result; S5. The base station dynamically adjusts the transmission power and interference coordination strategy by receiving the interference information from other base stations and the feedback of the user equipment in real time; S6. The base station dynamically adjusts the power allocation, spectrum resources, and channel selection of the network according to the real-time feedback and load change of the network environment and in combination with the adaptive power control and interference coordination technologies.

2. The method for optimizing wireless network coverage based on spatial positioning and transmission power regulation according to claim 1, wherein The S1 includes the following steps: S11. Collect the transmission power of the base station, received signal strength indication, signal-to-interference-plus-noise ratio, link status change data between the base station and the user equipment, connection quality data between the base station and the user equipment, and geographical location data of the base station and the user equipment.

3. The method for optimizing wireless network coverage based on spatial positioning and transmission power regulation according to claim 1, wherein, The S2 includes the following steps: S21. The base station calculates the signal quality of the current link according to the received signal strength indication and the signal-to-interference-plus-noise ratio, and sets the target signal strength and target signal-to-interference-plus-noise ratio; S22. Calculate the actual transmission power P actual and the difference from the target transmission power P target , and adjust the actual transmission power according to the power increment ΔP: where P' actual is the adjusted actual transmission power, γ and δ are constants for controlling signal quality and power adjustment sensitivity, and SINR actual is the actual signal-to-interference-plus-noise ratio of the current link, and SINR target is the target signal-to-interference-plus-noise ratio of the current link. The adjustment formula takes into account the impact of the deviation of the signal-to-interference-plus-noise ratio on power adjustment; S23. The base station dynamically adjusts the transmission power according to the geographical location and moving state of the user equipment: P base = P' actual + ΔP state ; Among them, P base is the adjusted transmission power, and ΔP state is the power allocated according to the geographical location and movement status of the user equipment; S24. The base station further adjusts the transmission power to P according to the service requirements and load conditions of different users final , and the load balancing optimization formula is: Among them, U i is the service requirement of the i-th user equipment, and σ i is the bandwidth requirement of the i-th user equipment. N is the number of users in the network, and ΔP load allocates power according to user load and requirements to optimize network coverage and throughput.

4. The method for optimizing wireless network coverage based on spatial positioning and transmission power regulation according to claim 3, characterized in that The S23 includes the following steps: S231, the power ΔP allocated according to the geographical location and movement state of the user device state is as follows: Among them, η is the adjustment factor, d is the distance between the user equipment and the base station, d0 is the reference distance, RSSI target is the target signal strength, RSSI actual is the actual signal strength, and κ and λ are constants calculated according to the propagation model.

5. The method for optimizing wireless network coverage based on spatial positioning and transmission power regulation according to claim 1, wherein The S3 includes the following steps: S31. The base station periodically broadcasts the frequency subset F of the current base station i = {f1, f2, …, f m}, the time slot subset T i = {t1, t2, …, t n} and the current transmission power P i to adjacent base stations; S32. Each base station receives the frequency and power configuration data from all base stations in the neighboring cell set and constructs an interference awareness matrix I ij : Among them, P j is the transmission power of the neighboring base station j, G ji is the channel gain from base station j to base station i, and N0 is the noise power density; S33. The base station calculates the conflict weight W ij according to the interference intensity values in the interference perception matrix I ij : W ij = φ(I ij ) = log2(1 + I ij ); Wherein, φ is a conflict weight mapping function for non-linearly amplifying interference awareness; S34. The base station uses the conflict weight W ij to jointly coordinate the allocation and optimization of frequency and time slot resources.

6. The method for optimizing wireless network coverage based on spatial positioning and transmission power regulation according to claim 5, wherein The S34 includes the following steps: S341. The base station jointly coordinates and allocates the frequency and time slot resources by optimizing the following objective function: Among them, represents the neighbor cell set of base station i, W ij is the conflict weight, 1(·) is the indicator function, F i is the frequency subset of base station i, F i is the frequency subset of base station i, T i is the time slot subset of base station i, T j is the time slot subset of base station j, η is the adjustment factor that controls the trade-off between interference suppression and resource allocation, P k is the transmit power of base station k, G ki is the channel gain from base station k to base station i.

7. The method for optimizing wireless network coverage based on spatial positioning and transmission power regulation according to claim 1, wherein The S4 includes the following steps: S41. The base station adjusts its own frequency subset, time slot subset, and power ceiling according to the optimization result. The calculation method of the power ceiling is as follows: The calculation method is: Among them, P target is the target transmit power, and P i is the transmit power of base station i. represents the set of neighboring cells of base station i, and W ij is the conflict weight.

8. The method for optimizing wireless network coverage based on spatial positioning and transmission power regulation according to claim 1, wherein The S5 includes the following steps: S51. The base station constructs an updated interference matrix by receiving the interference information from other base stations and the feedback of the user equipment in real time, and calculates a new transmission power adjustment amount according to the updated interference matrix; S52. The base station adjusts the current transmission power according to the new transmission power adjustment amount; S53. The base station dynamically adjusts the interference coordination strategy according to the network load and user requirements.

9. The method for optimizing wireless network coverage based on spatial positioning and transmission power regulation according to claim 1, wherein The S6 includes the following steps: S61. The base station re-evaluates the current transmission power and interference awareness matrix according to the real-time feedback and load change of the network environment; S62. The base station dynamically adjusts the allocation of power and spectrum resources according to the interference situation of the network and user requirements; S63. The base station adjusts the power control and resource allocation by calculating the target quality of service index and according to the bandwidth requirement of the user equipment; S64. The base station dynamically adjusts the power allocation, spectrum resources, and channel selection of the network according to the optimization result, and updates the resources through the following optimization constraint formula: ∑ i∈I P i (t) ≤ P max ,∑ i∈I σ u (t) ≤ σ total ; Among them, P i (t) represents the transmission power of base station i at time t, P max is the maximum available power of the network, σ u (t) is the bandwidth requirement of the user equipment at time t, σ total is the total network bandwidth limit.

10. The method for optimizing wireless network coverage based on spatial positioning and transmission power regulation according to claim 9, wherein, The S63 includes the following steps: S631. The base station adjusts the power control and resource allocation by optimizing the following objective function: Among them, P i (t) represents the transmission power of base station i at time t, C i (t) represents the channel selected by base station i at time t, U i is the set of user equipments of base station i, σ u (t) is the bandwidth requirement of the user equipment, is the target bandwidth requirement of the user equipment at time t, λ is the coefficient for balancing bandwidth requirement and interference, I ij (t) is the re-evaluated interference matrix.

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