Network deployment method and device, computer equipment, storage medium and program product

Abstract

The invention relates to a network deployment method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: acquiring at least one service equipment combination scheme, acquiring an optimal equipment deployment scheme of the service equipment combination scheme under a current equipment quantity level for any service equipment combination scheme, and acquiring communication performance of the optimal equipment deployment scheme, and under the condition that the communication performance does not meet the preset communication performance standard, taking the next equipment quantity level as a new current equipment quantity level, and returning to execute the step of obtaining the optimal equipment deployment scheme of the service equipment combination scheme under the current equipment quantity level until the communication performance meets the communication performance standard. And obtaining candidate device deployment schemes corresponding to the service device combination scheme, and finally determining a target device deployment scheme from the corresponding candidate device deployment schemes based on service requirements so as to execute network deployment for the target area. By adopting the scheme, the resource utilization rate is improved.

Description

Technical Field

[0001] This application relates to the field of wireless communication technology, and in particular to a network deployment method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Technology

[0002] With the rapid development of emerging technologies such as 5G, IoT, and edge computing, the complexity and diversity of network deployments have significantly increased. In practical applications, different business types and user groups have different requirements for network performance. For example, high-definition video conferencing and AR (Augmented Reality) / VR (Virtual Reality) applications focus more on high transmission rates and low latency performance, while smart manufacturing and industrial IoT scenarios emphasize coverage stability and access reliability, and ordinary mobile terminal users may place more emphasis on a balance between signal coverage and average transmission rate.

[0003] In recent years, some studies have attempted to introduce intelligent methods to assist network deployment decisions. For example, some methods use particle swarm optimization (PSO) to evaluate and optimize multiple layout schemes, improving deployment efficiency. However, their evaluation models rely only on a single quality coefficient and do not consider users' comprehensive needs for various communication performance characteristics. Other methods construct building-wide or hierarchical models for base station deployment planning, but without setting clear minimum communication performance standards, it is difficult to ensure that deployment schemes meet basic service quality requirements in practical applications. Furthermore, some methods use grid-based strategies for deployment location selection, focusing only on optimizing areas with weak signal coverage. They lack comprehensive consideration of other key communication performance indicators and do not perform global search and multi-objective optimization of deployment schemes, limiting the potential for overall network performance optimization.

[0004] In summary, existing network deployment methods suffer from low resource utilization. Summary of the Invention

[0005] Therefore, it is necessary to provide a network deployment method, apparatus, computer equipment, computer-readable storage medium, and computer program product that can improve resource utilization in response to the above-mentioned technical problems.

[0006] Firstly, this application provides a network deployment method, including:

[0007] Obtain at least one service device combination scheme; the service device combination scheme is used to characterize the matching relationship between network services and access devices;

[0008] For any service device combination scheme, obtain the optimal device deployment scheme under the current number of devices, and obtain the communication performance of the optimal device deployment scheme;

[0009] If the communication performance does not meet the pre-set communication performance standard, the next device quantity level is taken as the new current device quantity level, and the process returns to the step of obtaining the optimal device deployment scheme of the service device combination scheme under the current device quantity level, until the communication performance meets the communication performance standard. The optimal device deployment scheme is then taken as the candidate device deployment scheme corresponding to the service device combination scheme. The next device quantity level is the next level below the current device quantity level.

[0010] Based on business needs, the target device deployment scheme is determined from the candidate device deployment schemes corresponding to each service device combination scheme, and network deployment for the target deployment area is executed through the target device deployment scheme.

[0011] In conjunction with the first aspect, in one embodiment, obtaining the optimal device deployment scheme for the service device combination scheme at the current device quantity level includes:

[0012] Obtain the initial device deployment plan at the current device quantity level;

[0013] Based on the initial equipment deployment plan and the pre-built communication performance prediction model, obtain the optimal equipment deployment plan for the current number of equipment combinations.

[0014] In conjunction with the first aspect, in one embodiment, based on the initial device deployment plan and a pre-built communication performance prediction model, the optimal device deployment plan for the service device combination scheme at the current device quantity level is obtained, including:

[0015] The initial equipment deployment plan is input into the communication performance prediction model, and the communication performance prediction model outputs the predicted evaluation index data of the initial equipment deployment plan. The predicted evaluation index data includes at least one of the following: predicted signal poor coverage, predicted average signal strength, predicted average signal-to-noise ratio, predicted average downlink rate, and predicted connection success rate.

[0016] Based on the predicted evaluation index data of the initial equipment deployment plan, the performance evaluation data corresponding to the initial equipment deployment plan is obtained;

[0017] The device deployment locations in the initial device deployment plan are changed to obtain a new initial device deployment plan. Then, the process returns to the step of inputting the initial device deployment plan into the communication performance prediction model to obtain the performance evaluation data corresponding to the initial device deployment plan. This process continues until the performance evaluation data corresponding to the new initial device deployment plan meets the preset convergence conditions. The new initial device deployment plan is then taken as the optimal device deployment plan for the service device combination plan at the current device quantity level.

[0018] In conjunction with the first aspect, in one embodiment, a target device deployment scheme is determined from candidate device deployment schemes corresponding to various service device combination schemes based on business requirements, including:

[0019] Analyze business requirements to obtain target evaluation metrics;

[0020] Based on the target evaluation indicators, the target equipment deployment scheme is determined from the candidate equipment deployment schemes corresponding to each service equipment combination scheme.

[0021] In conjunction with the first aspect, in one embodiment, when the target evaluation indicator is a single evaluation indicator, the target device deployment scheme is determined from the candidate device deployment schemes corresponding to each service device combination scheme based on the target evaluation indicator, including:

[0022] Obtain target evaluation index data corresponding to the target evaluation index from the candidate equipment deployment schemes corresponding to each service equipment combination scheme;

[0023] Based on the evaluation index data of each target, the target equipment deployment scheme is determined from the candidate equipment deployment schemes corresponding to each service equipment combination scheme.

[0024] In conjunction with the first aspect, in one embodiment, when there are multiple target evaluation indicators, the target device deployment scheme is determined from the candidate device deployment schemes corresponding to each service device combination scheme based on the target evaluation indicators, including:

[0025] Obtain the indicator weights corresponding to the target evaluation indicators, and obtain the target evaluation indicator data corresponding to the target evaluation indicators from the candidate equipment deployment schemes corresponding to each service equipment combination scheme;

[0026] By using the weights of each indicator, the data of each target evaluation indicator are weighted and summed to obtain the comprehensive evaluation data of the candidate equipment deployment schemes corresponding to each service equipment combination scheme;

[0027] Based on the comprehensive evaluation data, the target equipment deployment scheme is determined from the candidate equipment deployment schemes corresponding to each service equipment combination scheme.

[0028] Secondly, this application also provides a network deployment apparatus, comprising:

[0029] The first acquisition module is used to acquire at least one service device combination scheme; the service device combination scheme is used to characterize the matching relationship between network services and access devices;

[0030] The second acquisition module is used to acquire the optimal device deployment scheme of any service device combination scheme under the current number of devices, and to acquire the communication performance of the optimal device deployment scheme.

[0031] The loop module is used to, when the communication performance does not meet the pre-set communication performance standard, take the next device quantity level as the new current device quantity level, return to execute the step of obtaining the optimal device deployment scheme of the service device combination scheme under the current device quantity level, until the communication performance meets the communication performance standard, and take the optimal device deployment scheme as the candidate device deployment scheme corresponding to the service device combination scheme; the next device quantity level is the next level below the current device quantity level;

[0032] The deployment module is used to determine the target device deployment scheme from the candidate device deployment schemes corresponding to each service device combination scheme based on business needs, and to execute network deployment for the target deployment area through the target device deployment scheme.

[0033] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0034] Obtain at least one service device combination scheme; the service device combination scheme is used to characterize the matching relationship between network services and access devices;

[0035] For any service device combination scheme, obtain the optimal device deployment scheme under the current number of devices, and obtain the communication performance of the optimal device deployment scheme;

[0036] If the communication performance does not meet the pre-set communication performance standard, the next device quantity level is taken as the new current device quantity level, and the process returns to the step of obtaining the optimal device deployment scheme of the service device combination scheme under the current device quantity level, until the communication performance meets the communication performance standard. The optimal device deployment scheme is then taken as the candidate device deployment scheme corresponding to the service device combination scheme. The next device quantity level is the next level below the current device quantity level.

[0037] Based on business needs, the target device deployment scheme is determined from the candidate device deployment schemes corresponding to each service device combination scheme, and network deployment for the target deployment area is executed through the target device deployment scheme.

[0038] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0039] Obtain at least one service device combination scheme; the service device combination scheme is used to characterize the matching relationship between network services and access devices;

[0040] For any service device combination scheme, obtain the optimal device deployment scheme under the current number of devices, and obtain the communication performance of the optimal device deployment scheme;

[0041] If the communication performance does not meet the pre-set communication performance standard, the next device quantity level is taken as the new current device quantity level, and the process returns to the step of obtaining the optimal device deployment scheme of the service device combination scheme under the current device quantity level, until the communication performance meets the communication performance standard. The optimal device deployment scheme is then taken as the candidate device deployment scheme corresponding to the service device combination scheme. The next device quantity level is the next level below the current device quantity level.

[0042] Based on business needs, the target device deployment scheme is determined from the candidate device deployment schemes corresponding to each service device combination scheme, and network deployment for the target deployment area is executed through the target device deployment scheme.

[0043] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0044] Obtain at least one service device combination scheme; the service device combination scheme is used to characterize the matching relationship between network services and access devices;

[0045] For any service device combination scheme, obtain the optimal device deployment scheme under the current number of devices, and obtain the communication performance of the optimal device deployment scheme;

[0046] If the communication performance does not meet the pre-set communication performance standard, the next device quantity level is taken as the new current device quantity level, and the process returns to the step of obtaining the optimal device deployment scheme of the service device combination scheme under the current device quantity level, until the communication performance meets the communication performance standard. The optimal device deployment scheme is then taken as the candidate device deployment scheme corresponding to the service device combination scheme. The next device quantity level is the next level below the current device quantity level.

[0047] Based on business needs, the target device deployment scheme is determined from the candidate device deployment schemes corresponding to each service device combination scheme, and network deployment for the target deployment area is executed through the target device deployment scheme.

[0048] The aforementioned network deployment method, apparatus, computer equipment, computer-readable storage medium, and computer program product acquire at least one service device combination scheme to characterize the matching relationship between network services and access devices. For any service device combination scheme, they acquire the optimal device deployment scheme at the current device quantity level and obtain the communication performance of the optimal device deployment scheme. If the communication performance does not meet a pre-set communication performance standard, they take the next device quantity level as the new current device quantity level and return to the step of acquiring the optimal device deployment scheme at the current device quantity level until the communication performance meets the communication performance standard. The optimal device deployment scheme is then taken as the candidate device deployment scheme corresponding to the service device combination scheme. Here, the next device quantity level is the level below the current device quantity level. Finally, based on business requirements, a target device deployment scheme is determined from the candidate device deployment schemes corresponding to each service device combination scheme, and network deployment for the target deployment area is performed using the target device deployment scheme. By adopting an incremental device deployment optimization strategy, starting from the minimum device scale and gradually increasing the device deployment scale, and using the corresponding communication performance as the judgment condition for the solution, the optimal device deployment solution can be obtained in a timely manner, reducing device redundancy, avoiding over-configuration of resources and unnecessary computing overhead, and thus improving resource utilization. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is an application environment diagram of a network deployment method in one embodiment;

[0051] Figure 2 This is a flowchart illustrating a network deployment method in one embodiment;

[0052] Figure 3 This is a flowchart illustrating the network deployment steps in another embodiment;

[0053] Figure 4 This is a schematic diagram of a service device combination scheme in one embodiment;

[0054] Figure 5 This is a schematic diagram illustrating the incremental device number deployment optimization search in one embodiment;

[0055] Figure 6This is a schematic diagram illustrating the performance compliance determination and submission termination in another embodiment;

[0056] Figure 7 This is a schematic diagram illustrating the construction of a candidate solution library for achieving the target in one embodiment;

[0057] Figure 8 This is a structural block diagram of a network deployment device in one embodiment;

[0058] Figure 9 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0060] The network deployment method provided in this application embodiment can be applied to, for example, Figure 1In the application environment shown, terminal 102 communicates with server 104 via a network, and server 104 communicates with multiple wireless access devices via a network. These wireless access devices can provide wireless networks to the terminal. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or located in the cloud or on other network servers. Server 104 retrieves at least one service device combination scheme from the data storage system to characterize the matching relationship between network services and access devices. For any service device combination scheme, it obtains the optimal device deployment scheme under the current device quantity level and its communication performance. If the communication performance does not meet the pre-set communication performance standard, the next device quantity level is taken as the new current device quantity level, and the process of obtaining the optimal device deployment scheme under the current device quantity level is repeated until the communication performance meets the standard. The optimal device deployment scheme is then taken as the candidate device deployment scheme corresponding to the service device combination scheme, and the next device quantity level is the next level below the current device quantity level. Finally, based on business requirements, the target device deployment scheme is determined from the candidate device deployment schemes corresponding to each service device combination scheme, and network deployment for the target deployment area is executed using the target device deployment scheme. The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, projection devices, etc. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted displays. Head-mounted displays can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. Server 104 can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server providing cloud computing services.

[0061] In one exemplary embodiment, such as Figure 2 As shown, a network deployment method is provided, which is applied to Figure 1 Taking server 104 as an example, the explanation includes the following steps S201 to S204. Wherein:

[0062] Step S201: Obtain at least one service device combination scheme; the service device combination scheme is used to characterize the matching relationship between network services and access devices.

[0063] Among them, the service equipment combination scheme can be understood as the basic evaluation unit and candidate deployment configuration set in the deployment optimization process. Each scheme represents a matching relationship between a network service and an access device that has practical deployment significance.

[0064] For example, server 104 generates multiple service device combination schemes based on network service configuration information provided by the service provider, including but not limited to parameters such as uplink bandwidth, downlink bandwidth, and maximum concurrent connections, as well as candidate wireless access device models, and obtains at least one service device combination scheme from them.

[0065] Step S202: For any service device combination scheme, obtain the optimal device deployment scheme of the service device combination scheme under the current number of devices level, and obtain the communication performance of the optimal device deployment scheme.

[0066] Among them, the current number of devices level can be understood as the level of the device deployment scale, and the communication performance can be understood as the relevant index data of the smoothness of communication of various evaluation nodes, which may include index data such as average signal strength, average signal-to-noise ratio, average downlink rate, connection success rate and signal strength poor coverage rate.

[0067] Optionally, for any service device combination scheme, server 104 obtains the optimal device deployment scheme of the service device combination scheme under the current number of devices level—that is, obtains the optimal device deployment scheme of the service device combination scheme under the corresponding data scale, and combines communication propagation modeling and prediction technology, including ray tracing model, path loss model, and communication quality prediction artificial intelligence model, to predict the communication performance of each device deployment location in the optimal device deployment scheme, and then obtains the communication performance of the optimal device deployment scheme based on the predicted communication performance of each device deployment location.

[0068] Step S203: If the communication performance does not meet the preset communication performance standard, the next device quantity level is taken as the new current device quantity level, and the process returns to the step of obtaining the optimal device deployment scheme of the service device combination scheme under the current device quantity level, until the communication performance meets the communication performance standard, and the optimal device deployment scheme is taken as the candidate device deployment scheme corresponding to the service device combination scheme; the next device quantity level is the next level below the current device quantity level.

[0069] Among them, the communication performance standard can be understood as the minimum overall communication performance standard that the user-defined deployment plan must meet. The minimum standard includes, but is not limited to, the threshold requirements of key communication quality parameters such as average signal strength, average signal-to-noise ratio, average downlink transmission rate, and poor signal strength coverage. The next device quantity level can be understood as the next level with a device deployment scale that is one more than the current device quantity level. The candidate device deployment plan can be understood as a device deployment plan that meets the performance standard. Each candidate plan includes: network service configuration information, device model, device quantity, deployment coordinates, and various overall communication performance indicators.

[0070] For example, if the communication performance does not meet the pre-set communication performance standards (i.e., the average signal strength, average signal-to-noise ratio, average downlink transmission rate, and signal strength poor coverage do not meet the corresponding threshold requirements), the server 104 will take the next device number level with a device deployment scale that is one more than the current device number level as the new current device number level, and return to the step of obtaining the optimal device deployment scheme of the service device combination scheme under the current device number level, until the communication performance meets the communication performance standards, and the optimal deployment scheme is taken as the candidate device deployment scheme corresponding to the service device combination scheme.

[0071] Step S204: Based on business requirements, determine the target device deployment scheme from the candidate device deployment schemes corresponding to each service device combination scheme, and execute network deployment for the target deployment area through the target device deployment scheme.

[0072] Network deployment can be understood as deploying wireless access devices according to the device deployment locations in the target device deployment plan.

[0073] Optionally, the server 104 may specify sorting dimensions (such as average signal strength, coverage, throughput, number of devices, etc.) according to business requirements, or adopt a comprehensive evaluation method (such as multi-index weighting, etc.) to sort and screen candidate deployment schemes that meet performance standards, determine the target device deployment scheme from the candidate device deployment schemes, and deploy wireless access devices in the target deployment area according to the device deployment locations in the target device deployment scheme.

[0074] In the aforementioned network deployment method, at least one service device combination scheme is obtained to characterize the matching relationship between network services and access devices. For any service device combination scheme, the optimal device deployment scheme under the current device quantity level is obtained, and the communication performance of the optimal device deployment scheme is acquired. If the communication performance does not meet the pre-set communication performance standard, the next device quantity level is taken as the new current device quantity level, and the step of obtaining the optimal device deployment scheme under the current device quantity level is repeated until the communication performance meets the communication performance standard. The optimal device deployment scheme is then taken as the candidate device deployment scheme corresponding to the service device combination scheme. Here, the next device quantity level is the level below the current device quantity level. Finally, based on business requirements, the target device deployment scheme is determined from the candidate device deployment schemes corresponding to each service device combination scheme, and network deployment for the target deployment area is executed using the target device deployment scheme. By adopting an incremental device deployment optimization strategy, starting from the minimum device scale and gradually increasing the device deployment scale, using the communication performance corresponding to the scheme as the scheme judgment condition, the corresponding optimal device deployment scheme is obtained in a timely manner, reducing device redundancy, avoiding over-configuration of resources and unnecessary computing overhead, thereby improving resource utilization.

[0075] In one embodiment, obtaining the optimal device deployment scheme for the service device combination scheme under the current number of devices includes: obtaining the initial device deployment scheme under the current number of devices; and obtaining the optimal device deployment scheme for the service device combination scheme under the current number of devices based on the initial device deployment scheme and a pre-built communication performance prediction model.

[0076] The initial equipment deployment scheme can be understood as a scheme formed by randomly combining various deployment locations within the target deployment area according to the corresponding equipment deployment scale. The communication performance prediction model can be a deterministic model based on physical principles or a data-driven model with learning capabilities, such as ray tracing model, path loss model, and artificial intelligence model for communication quality prediction.

[0077] For example, within the target deployment area, server 104 randomly combines the deployment locations of each device according to the deployment scale corresponding to the current device quantity level, thereby obtaining an initial device deployment scheme for the service device combination scheme under the current device quantity level. The initial device deployment scheme is input into a pre-built communication performance prediction model to obtain the prediction evaluation index data of the initial device deployment scheme. Based on the prediction evaluation index data, the performance evaluation data corresponding to the initial device deployment scheme is obtained. The device deployment locations in the initial device deployment scheme are changed to obtain a new initial device deployment scheme, and the performance evaluation data corresponding to the new initial device deployment scheme is obtained. This process continues until the performance evaluation data corresponding to the new initial device deployment scheme meets the pre-set convergence conditions. The new initial device deployment scheme is then taken as the optimal device deployment scheme for the service device combination scheme under the current device quantity level.

[0078] Based on the aforementioned implementation methods, a communication performance prediction model is introduced to predict the communication performance of the equipment deployment scheme, ensuring the full automation of the prediction and improving the accuracy of the communication performance prediction. By using multiple evaluation index data obtained from the prediction to construct corresponding performance evaluation data, the equipment deployment scheme is iteratively optimized, thereby ensuring the traceability of the optimal equipment deployment scheme obtained at the current scale.

[0079] In one embodiment, based on the initial device deployment scheme and a pre-built communication performance prediction model, the optimal device deployment scheme for the service device combination scheme at the current device quantity level is obtained. This includes: inputting the initial device deployment scheme into the communication performance prediction model, and outputting the prediction evaluation index data of the initial device deployment scheme through the communication performance prediction model; the prediction evaluation index data includes at least one of predicted signal inferiority coverage, predicted average signal strength, predicted average signal-to-noise ratio, predicted average downlink rate, and predicted connection success rate; obtaining the performance evaluation data corresponding to the initial device deployment scheme based on the prediction evaluation index data of the initial device deployment scheme; changing the device deployment positions in the initial device deployment scheme to obtain a new initial device deployment scheme, and returning to the step of inputting the initial device deployment scheme into the communication performance prediction model to obtain the performance evaluation data corresponding to the initial device deployment scheme, until the performance evaluation data corresponding to the new initial device deployment scheme meets the preset convergence condition, and using the new initial device deployment scheme as the optimal device deployment scheme for the service device combination scheme at the current device quantity level.

[0080] Among them, performance evaluation data can be understood as the evaluation data obtained after unifying the optimization direction of the prediction index data. Therefore, after performing a negative value transformation on the evaluation index data that needs to be maximized, the convergence condition is that the performance evaluation data reaches the minimum value, or after performing a positive value transformation on the evaluation index data that needs to be minimized, the convergence condition is that the performance evaluation data reaches the maximum value.

[0081] Optionally, server 104 inputs the initial device deployment plan into the communication performance prediction model, outputs the prediction evaluation index data of each device deployment location in the initial device deployment plan through the communication performance prediction model, and integrates the prediction evaluation index data of each device deployment location to obtain the prediction evaluation index data of the initial device deployment plan. The prediction evaluation index data includes at least one of the following: predicted signal poor coverage rate, predicted average signal strength, predicted average signal-to-noise ratio, predicted average downlink rate, and predicted connection success rate.

[0082] Subsequently, for the performance indicators that need to be maximized (such as average signal strength, average signal-to-noise ratio, average downlink rate, and connection success rate), negative value transformation is performed accordingly. Then, based on the transformed predicted evaluation indicator data, performance evaluation data corresponding to the initial equipment deployment scheme is constructed. Next, the equipment deployment positions in the initial equipment deployment scheme are changed to obtain a new initial equipment deployment scheme. Then, the process returns to the step of inputting the initial equipment deployment scheme into the communication performance prediction model to obtain the performance evaluation data corresponding to the initial equipment deployment scheme. This process continues until the performance evaluation data corresponding to the new initial equipment deployment scheme reaches the minimum value. The new initial equipment deployment scheme is then taken as the optimal equipment deployment scheme for the service equipment combination scheme at the current equipment quantity level.

[0083] Alternatively, for performance metrics that need to be minimized (such as signal degradation coverage), a positive value transformation is performed accordingly. Then, based on the transformed predicted evaluation metrics data, performance evaluation data corresponding to the initial equipment deployment scheme is constructed. The equipment deployment locations in the initial equipment deployment scheme are then changed to obtain a new initial equipment deployment scheme. The process then returns to the step of inputting the initial equipment deployment scheme into the communication performance prediction model to obtain the performance evaluation data corresponding to the initial equipment deployment scheme. This process continues until the performance evaluation data corresponding to the new initial equipment deployment scheme reaches its maximum value. The new initial equipment deployment scheme is then used as the optimal equipment deployment scheme for the service equipment combination scheme at the current equipment quantity level.

[0084] According to the above implementation method, by unifying the optimization direction of each evaluation index in the multi-prediction evaluation index data, it is convenient to achieve unified optimization of multiple objectives, thereby ensuring the overall optimality of the communication performance of the optimal equipment deployment scheme. The unification of the optimization direction also speeds up the acquisition of the optimal equipment deployment scheme.

[0085] In one embodiment, determining the target device deployment scheme from the candidate device deployment schemes corresponding to each service device combination scheme based on business requirements includes: parsing the business requirements to obtain target evaluation indicators; and determining the target device deployment scheme from the candidate device deployment schemes corresponding to each service device combination scheme based on the target evaluation indicators.

[0086] Among them, the target evaluation index can be understood as the index dimension for ranking and evaluating the candidate equipment deployment schemes corresponding to each service equipment combination scheme.

[0087] For example, server 104 obtains the service requirements initiated by the user from terminal 102, parses the service requirements, obtains the target evaluation index ranking dimension for each candidate device deployment scheme, sorts the candidate device deployment schemes corresponding to each service device combination scheme according to the target evaluation index ranking dimension, and determines the target device deployment scheme from the candidate device deployment schemes corresponding to each service device combination scheme after sorting.

[0088] Based on the aforementioned implementation method, by parsing the business requirements, the sorting dimensions specified by the user are obtained, thereby sorting the candidate device deployment schemes. This allows for the rapid selection of the target device deployment scheme from the sorted candidate schemes, ensuring the adaptability of the target device deployment scheme to the user's needs and thus improving the user's business interaction experience.

[0089] In one embodiment, when the target evaluation index is a single evaluation index, the target device deployment scheme is determined from the candidate device deployment schemes corresponding to each service device combination scheme based on the target evaluation index. This includes: obtaining target evaluation index data corresponding to the target evaluation index from the candidate device deployment schemes corresponding to each service device combination scheme; and determining the target device deployment scheme from the candidate device deployment schemes corresponding to each service device combination scheme based on the target evaluation index data.

[0090] Optionally, when the target evaluation indicator is a single evaluation indicator (such as average signal strength, slack rate, throughput, number of devices, etc.), the server 104 obtains the target evaluation indicator data corresponding to the target evaluation indicator from the subsequent per-device deployment schemes corresponding to each service device combination scheme, sorts the candidate device deployment schemes from best to worst performance according to the target evaluation indicator data, and determines the target device deployment scheme from the sorted candidate device deployment schemes.

[0091] According to the above implementation method, user needs are given priority, and the deployment scheme that best fits the business scenario and service quality requirements is determined from the candidate equipment deployment schemes, so as to provide customer-oriented and quantitative decision-making basis for network construction and optimization.

[0092] In one embodiment, when there are multiple target evaluation indicators, the target device deployment scheme is determined from the candidate device deployment schemes corresponding to each service device combination scheme based on the target evaluation indicators. This includes: obtaining the indicator weights corresponding to the target evaluation indicators; obtaining target evaluation indicator data corresponding to the target evaluation indicators from the candidate device deployment schemes corresponding to each service device combination scheme; using the indicator weights, performing a weighted summation of the target evaluation indicator data to obtain comprehensive evaluation data of the candidate device deployment schemes corresponding to each service device combination scheme; and determining the target device deployment scheme from the candidate device deployment schemes corresponding to each service device combination scheme based on the comprehensive evaluation data.

[0093] For example, when there are multiple target evaluation indicators, the server 104 obtains the indicator weights corresponding to the target evaluation indicators, and obtains the target evaluation indicator data corresponding to the target evaluation indicators from the candidate device deployment schemes corresponding to each service device combination scheme. Using the indicator weights, the server performs a weighted summation on the target evaluation indicator data to obtain the comprehensive evaluation data of the candidate device deployment schemes corresponding to each service device combination scheme. The server sorts the candidate device deployment schemes from best to worst performance according to the comprehensive evaluation data to obtain the sorted candidate device deployment schemes. The server then determines the target device deployment scheme from the sorted candidate device deployment schemes.

[0094] Based on the aforementioned implementation methods, while ensuring that all communication performance targets are met, personalized user needs are taken into account, and the deployment scheme that best suits the business scenario and service quality requirements is selected, providing a scientific and quantitative basis for network construction and optimization.

[0095] In one exemplary embodiment, such as Figure 3 As shown, a specific implementation of a network deployment method is provided, wherein:

[0096] 1. Obtain deployment space resource information: Obtain physical space resource information of the target deployment area provided by the user, including environmental factors such as the geometric boundaries of the deployment area, obstacle distribution characteristics, and building material types that affect the attenuation of wireless signal propagation.

[0097] 2. Set minimum communication performance standards: Users set minimum overall communication performance standards that the deployment plan must meet. These minimum standards include, but are not limited to, threshold requirements for key communication quality parameters such as average RSSI (Received Signal Strength Indicator), average SNR (Signal-to-Noise Ratio), average downlink transmission rate, and RSSI poor coverage rate. These standards serve as conditions for subsequent deployment optimization and plan selection, thereby ensuring that the final deployment plan can meet the user's actual application needs for network coverage quality.

[0098] 3. For example Figure 4 As shown, a service-device combination set is constructed: based on network service configuration information provided by the operator, including but not limited to parameters such as uplink bandwidth, downlink bandwidth, and maximum concurrent connections, as well as candidate wireless access device models, multiple service-device combination schemes are generated. Each combination scheme represents a matching relationship between a network service and an access device with practical deployment significance. It serves as the basic evaluation unit and candidate deployment configuration set in the subsequent deployment optimization process, supporting multi-dimensional performance evaluation and scheme selection.

[0099] 4. Define a multi-objective communication performance evaluation function: For each service-device combination and candidate deployment scheme (specific deployment location of each device), combine communication propagation modeling and prediction techniques, including ray tracing models, path loss models, and communication quality prediction AI models, to predict the communication performance at each location within the target deployment area, and further calculate the overall communication performance mentioned in step 2. Considering that most optimization algorithm frameworks are based on minimization problems, for performance indicators that need to be maximized (such as average RSSI, average SNR, average downlink rate, connection success rate, etc.), negative value conversion should be performed to ensure the consistency and comparability of the multi-objective optimization process. Based on this, a corresponding multi-dimensional performance evaluation function is constructed, with the output result being a vector, used to characterize the comprehensive performance of the deployment scheme in different performance dimensions. For example, the evaluation function of the network deployment multi-objective optimization problem can be formally expressed as:

[0100] min F(p)=[f1(p),f2(p),f3(p),f4(p)]

[0101] Where p=[(x1,y1,z1),(x2,y2,z2),(x3,y3,z3),(x4,y4,z4)] represents the set of decision variables for the deployment scheme, specifically consisting of a set of device deployment location coordinates. f1(p)=-RSSI_avg(p), f2(p)=-SNR_avg(p), and f3(p)=-Rate_avg(p) represent the negative values ​​of the average RSSI, average SNR, and average downlink transmission rate within the target deployment area corresponding to deployment scheme p, respectively. f4(p)=Coverage_weak(p) is the proportion of areas within the target deployment area where the signal quality is lower than the set value, which is a minimization target and does not need to be negative.

[0102] 5. For example Figure 5 As shown, the incremental device quantity deployment optimization search is as follows: For each service-device combination, an incremental deployment optimization strategy is adopted, starting from an initial configuration with 1 device and gradually increasing the deployment scale to build multiple device quantity levels. Within each quantity level, based on the multi-objective communication performance evaluation function defined in step 4, multi-objective heuristic optimization algorithms (such as SPEA (Strength Pareto Evolutionary Algorithm) and IBEA (Indicator-Based Evolutionary Algorithm)) are used to iteratively optimize and search for candidate deployment locations. Through the multi-objective optimization process, the optimal deployment location for the service-device combination at a specific device quantity level, as well as the corresponding overall communication performance indicators, are obtained. These results provide comprehensive data support and technical basis for subsequent performance target assessment and deployment optimization.

[0103] 6. For example Figure 6 As shown, the performance compliance determination and incremental termination are as follows: For each service-device combination, after optimization at each device quantity level, the generated deployment scheme is judged to meet performance standards. The judgment is based on the user-preset minimum communication performance standard in step 2. If the deployment scheme at the current device quantity level meets all minimum performance standards, the service-device combination is determined to have achieved performance compliance, and the scheme is recorded. Optimization at higher device quantity levels for this combination is terminated to avoid resource redundancy and unnecessary computational overhead. If the performance standards are not met, the device quantity continues to increase, entering the deployment optimization at the next device quantity level until a compliant scheme is found.

[0104] 7. For example Figure 7As shown, the candidate solution library for achieving performance standards is constructed by saving solutions that meet the performance standards for each service-device combination into the candidate solution library. Each record contains the following key information: network service configuration information, device model, number of devices, deployment coordinates, and overall communication performance indicators. This candidate deployment solution library provides a unified and structured data foundation for subsequent solution selection, multi-dimensional ranking, and user decision-making, and supports rapid retrieval and accurate performance comparison.

[0105] 8. User Preference Deployment Scheme Decision: Users can specify ranking dimensions (such as average RSSI, coverage, throughput, number of devices, etc.) based on business needs, or adopt comprehensive evaluation methods (TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), multi-index weighting, etc.) to rank and filter candidate deployment schemes that meet performance standards. During the comprehensive evaluation process, users can flexibly configure the weights of various indicators to reflect the relative importance of each evaluation dimension in a specific scenario. While ensuring that various communication performance targets are met, personalized user needs are also considered, and the deployment scheme that best suits the business scenario and service quality requirements is selected, providing a scientific and quantitative basis for network construction and optimization.

[0106] Example 1: Intelligent Deployment of Indoor Routers

[0107] 1. Obtain deployment space resource information: For wireless network planning within an office floor, the user provides the geometric boundaries, wall structure, and obstacle distribution of the deployment area. Based on the electromagnetic attenuation characteristics of building materials (such as glass partitions and concrete walls), a database of environmental elements required for signal propagation modeling is constructed.

[0108] 2. Set minimum communication performance standards: Users set the following minimum overall communication performance standards: average RSSI ≥ -65dBm and average downlink transmission rate ≥ 150Mbps, as conditions for judging whether the deployment plan meets the standards.

[0109] 3. Construct service and device combination sets: Based on the two service packages provided by the operator (such as 1000M enterprise broadband and 2000M enterprise broadband) and the three candidate Wi-Fi 6 router models (A, B, C), generate six service-device combination configuration schemes as the basis for subsequent optimization calculations.

[0110] 4. Define a multi-objective communication performance evaluation function: Using a ray tracing model and an AI prediction model, obtain the RSSI and downlink transmission rate of each candidate location within the deployment area. Calculate the overall average RSSI and the minimum overall communication performance standard: average RSSI and average downlink transmission rate. Perform negative value conversion to form a two-dimensional vector, which serves as the performance evaluation function. The evaluation function for the multi-objective optimization problem of indoor router network deployment can be formally expressed as:

[0111] minF(p)=[f1(p),f2(p)]

[0112] Where p represents the set of decision variables for the deployment scheme, which consists of router deployment coordinates, and f1(p)=-RSSI_avg(p) and f2(p)=-Rate_avg(p) represent the negative values ​​of the average RSSI and average downlink transmission rate in the target deployment area corresponding to deployment scheme p, respectively.

[0113] 5. Incremental Device Deployment Optimization Search: For all 6 service-device combinations, the deployment scale is gradually increased starting from the deployment of 1 router. The multi-objective communication performance evaluation function and SPEA algorithm are used to optimize the deployment location search, so as to obtain the best deployment location of the service-device combination at a specific number of routers, as well as 2 overall communication performance indicators.

[0114] 6. Performance Compliance Determination and Incremental Termination: For each service-device combination, after optimization at each device quantity level, the generated router deployment scheme is subjected to performance compliance determination. When the scheme reaches the minimum standard set by the user, the subsequent incremental search is terminated to reduce computational redundancy and resource overhead.

[0115] 7. Construction of the candidate solution library for compliance: Record the compliance solutions of 6 service-device combinations into the candidate solution library. The recorded content includes: service configuration bandwidth, router model, quantity, coordinates, and 2 overall performance indicators.

[0116] 8. User Preference Deployment Scheme Decision: Based on the "rate priority" strategy, users sort the candidate schemes by average downlink transmission rate to obtain the final deployment scheme of 2000M enterprise broadband and 5 B-type routers. The actual construction and deployment are guided according to the specific deployment location of the routers in this scheme, ensuring that the communication performance meets the preset goals while taking into account the user's personalized needs.

[0117] Example 2: Intelligent Deployment of Campus Base Stations:

[0118] 1. Obtain deployment space resource information: To carry out smart base station deployment planning within a campus, the school provides physical space information of the target campus area, including the geometric boundaries of buildings such as teaching buildings, dormitories, libraries, and laboratories, as well as wall materials (such as concrete, glass, and brick walls) and other factors that affect the propagation of wireless signals.

[0119] 2. Setting minimum communication performance standards: To ensure the communication experience of teachers and students, the school has set minimum overall communication performance standards that the deployment plan must meet: average SNR ≥ 20dB, average downlink speed ≥ 80Mbps, and weak coverage (RSRP ≤ -105dBm) area percentage ≤ 5%.

[0120] 3. Construct a service-equipment combination set: The network service configuration provided by the operator includes two options: 1Gbps fiber optic backhaul and 10Gbps fiber optic backhaul, with a maximum of 1024 access users for each option. Combined with the candidate base station models (D, E), four service-equipment combination configuration schemes are formed.

[0121] 4. Define a multi-objective communication performance evaluation function: Based on path loss models, deep learning models, and ray tracing models, predict the SNR, downlink rate, and RSRP at various locations within the target campus area, and further calculate the average SNR, average downlink rate, and proportion of weak coverage areas. After negative conversion of the average SNR and average downlink rate, the evaluation function for the multi-objective optimization problem of campus base station network deployment can be formally expressed as:

[0122] minF(p)=[f1(p),f2(p),f3(p)]

[0123] Where p represents the set of decision variables for the deployment scheme, which consists of the base station deployment coordinates. f1(p)=-SNR_avg(p), f2(p)=-Rate_avg(p), and f3(p)=Coverage_weak(p) represent the negative values ​​of the average SNR, the negative values ​​of the average downlink transmission rate, and the proportion of weak coverage areas within the target deployment area corresponding to deployment scheme p, respectively.

[0124] 5. Incremental Deployment Optimization Search for All 4 Service-Equipment Combinations: An incremental deployment optimization strategy is adopted, starting with the deployment of 1 base station and gradually increasing the number of deployments. Based on the multi-objective communication performance evaluation function and the IBEA algorithm, the deployment location optimization search is performed to obtain the optimal deployment location of the service-equipment combination at a specific base station number level, as well as 3 overall communication performance indicators.

[0125] 6. Performance Compliance Assessment and Termination of Incremental Deployment: For each service-device combination, after optimization at each device quantity level, the generated base station deployment plan is assessed for performance compliance. If the plan meets the minimum standard set by the university, subsequent searches are terminated.

[0126] 7. Construction of the candidate solution library for compliance: Record the compliance solutions of the four service-equipment combinations into the candidate solution library. The recorded content includes: service configuration, base station model, quantity, coordinates, and three overall performance indicators.

[0127] 8. User Preference Deployment Scheme Decision: TOPSIS is used to evaluate three overall performance metrics in the candidate deployment scheme library. By calculating the relative proximity of each scheme to the positive ideal solution (optimal performance combination) and the negative ideal solution (worst performance combination), the comprehensive performance ranking of each deployment scheme is obtained. This method effectively identifies deployment schemes with optimal trade-offs, thus providing strong support for the scientific planning and quantitative decision-making of campus networks.

[0128] Compared with the prior art, this application has the following technical advantages:

[0129] 1. Construction of multi-objective communication performance evaluation function: This invention unifies the key indicators that users care about (such as average RSSI, coverage, etc.) into the form of evaluation function, realizes the comprehensive evaluation of candidate deployment schemes in multiple performance dimensions, and ensures that the optimization process fully adapts to the communication needs under diverse business scenarios.

[0130] 2. Incremental Deployment Optimization Strategy: This invention adopts an incremental device deployment optimization strategy, starting from the minimum device scale and gradually increasing the number of deployments. It also combines a multi-objective heuristic optimization algorithm to perform global search and performance optimization at each quantity level, thereby reducing device redundancy, avoiding over-configuration of resources, reducing network construction costs, and improving resource utilization efficiency.

[0131] 3. Communication performance compliance-driven judgment mechanism: Based on the minimum communication performance standard set by the user, this invention introduces a communication performance compliance judgment mechanism. After the deployment scheme optimization is completed at each device quantity level, a judgment is made. If a compliant scheme is found, the subsequent search is terminated. While meeting the user's network service quality requirements, unnecessary computational overhead is avoided, and the overall optimization efficiency is improved.

[0132] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0133] Based on the same inventive concept, this application also provides a network deployment apparatus for implementing the network deployment method described above. The solution provided by this apparatus is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more network deployment apparatus embodiments provided below can be found in the limitations of the network deployment method described above, and will not be repeated here.

[0134] In one exemplary embodiment, such as Figure 8 As shown, a network deployment device is provided, including: a first acquisition module 801, a second acquisition module 802, a loop module 803, and a deployment module 804, wherein:

[0135] The first acquisition module 801 is used to acquire at least one service device combination scheme; the service device combination scheme is used to characterize the matching relationship between network services and access devices.

[0136] The second acquisition module 802 is used to acquire the optimal device deployment scheme of any service device combination scheme under the current number of devices level, and to acquire the communication performance of the optimal device deployment scheme.

[0137] The loop module 803 is used to, when the communication performance does not meet the preset communication performance standard, take the next device quantity level as the new current device quantity level, return to execute the step of obtaining the optimal device deployment scheme of the service device combination scheme under the current device quantity level, until the communication performance meets the communication performance standard, and take the optimal device deployment scheme as the candidate device deployment scheme corresponding to the service device combination scheme; the next device quantity level is the next level below the current device quantity level.

[0138] The deployment module 804 is used to determine the target device deployment scheme from the candidate device deployment schemes corresponding to each service device combination scheme based on business needs, and to execute network deployment for the target deployment area through the target device deployment scheme.

[0139] In one embodiment, based on the aforementioned network deployment device, a first acquisition module acquires at least one service device combination scheme representing the matching relationship between network services and access devices. Then, the at least one service device combination scheme is passed to a second acquisition module. For any service device combination scheme, the second acquisition module acquires the optimal device deployment scheme at the current device quantity level and obtains the communication performance of the optimal device deployment scheme. This communication performance is then transmitted to a loop module. If the communication performance does not meet a pre-set communication performance standard, the loop module takes the next device quantity level as the new current device quantity level and returns to the step of acquiring the optimal device deployment scheme at the current device quantity level. This process continues until the communication performance meets the communication performance standard. The optimal device deployment scheme is then used as a candidate device deployment scheme corresponding to the service device combination scheme. The next device quantity level is the level below the current device quantity level. The candidate device deployment schemes corresponding to each service device combination scheme are passed to a deployment module. Based on business requirements, the deployment module determines the target device deployment scheme from the candidate device deployment schemes corresponding to each service device combination scheme and executes network deployment for the target deployment area using the target device deployment scheme. By adopting an incremental device deployment optimization strategy, starting from the minimum device scale and gradually increasing the device deployment scale, and using the corresponding communication performance as the judgment condition for the solution, the optimal device deployment solution can be obtained in a timely manner, reducing device redundancy, avoiding over-configuration of resources and unnecessary computing overhead, and thus improving resource utilization.

[0140] In one embodiment, the second acquisition module 802 is further configured to acquire an initial device deployment scheme under the current device quantity level; and based on the initial device deployment scheme and a pre-built communication performance prediction model, acquire the optimal device deployment scheme of the service device combination scheme under the current device quantity level.

[0141] In one embodiment, the second acquisition module 802 is further configured to input the initial device deployment scheme into the communication performance prediction model, and output the predicted evaluation index data of the initial device deployment scheme through the communication performance prediction model; the predicted evaluation index data includes at least one of predicted signal poor coverage, predicted average signal strength, predicted average signal-to-noise ratio, predicted average downlink rate, and predicted connection success rate; based on the predicted evaluation index data of the initial device deployment scheme, the performance evaluation data corresponding to the initial device deployment scheme is obtained; the device deployment location in the initial device deployment scheme is changed to obtain a new initial device deployment scheme, and the process of inputting the initial device deployment scheme into the communication performance prediction model to obtain the performance evaluation data corresponding to the initial device deployment scheme is returned to be executed until the performance evaluation data corresponding to the new initial device deployment scheme meets the preset convergence condition, and the new initial device deployment scheme is taken as the optimal device deployment scheme of the service device combination scheme under the current number of devices.

[0142] In one embodiment, the deployment module 804 is further configured to parse business requirements and obtain target evaluation indicators; and based on the target evaluation indicators, determine the target device deployment scheme from the candidate device deployment schemes corresponding to each service device combination scheme.

[0143] In one embodiment, the deployment module 804 is further configured to obtain target evaluation index data corresponding to the target evaluation index from the candidate device deployment schemes corresponding to each service device combination scheme; and determine the target device deployment scheme from the candidate device deployment schemes corresponding to each service device combination scheme based on the target evaluation index data.

[0144] In one embodiment, when the target evaluation indicator is a single evaluation indicator, the deployment module 804 is further configured to obtain target evaluation indicator data corresponding to the target evaluation indicator from the candidate device deployment schemes corresponding to each service device combination scheme; and determine the target device deployment scheme from the candidate device deployment schemes corresponding to each service device combination scheme based on the target evaluation indicator data.

[0145] In one embodiment, when there are multiple target evaluation indicators, the deployment module is further configured to obtain the indicator weights corresponding to the target evaluation indicators, obtain target evaluation indicator data corresponding to the target evaluation indicators from the candidate device deployment schemes corresponding to each service device combination scheme, use the indicator weights to perform weighted summation on each target evaluation indicator data to obtain comprehensive evaluation data of the candidate device deployment schemes corresponding to each service device combination scheme, and determine the target device deployment scheme based on the comprehensive evaluation data from the candidate device deployment schemes corresponding to each service device combination scheme.

[0146] Each module in the aforementioned network deployment device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0147] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 9 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores service device combination schemes, optimal device deployment schemes, the communication performance of the optimal device deployment schemes, candidate device deployment schemes corresponding to the service device combination schemes, and target device deployment schemes. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a network deployment method.

[0148] Those skilled in the art will understand that Figure 9 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0149] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the network deployment scheme of the above embodiment.

[0150] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the network deployment scheme of the above embodiment.

[0151] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the network deployment scheme of the above embodiments.

[0152] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0153] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0154] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0155] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A network deployment method, characterized in that, The method includes: Obtain at least one service device combination scheme; the service device combination scheme is used to characterize the matching relationship between network services and access devices; For any of the service device combination schemes, obtain the optimal device deployment scheme of the service device combination scheme under the current number of devices level, and obtain the communication performance of the optimal device deployment scheme; If the communication performance does not meet the preset communication performance standard, the next device quantity level is taken as the new current device quantity level, and the process returns to the step of obtaining the optimal device deployment scheme of the service device combination scheme under the current device quantity level, until the communication performance meets the communication performance standard, and the optimal device deployment scheme is taken as the candidate device deployment scheme corresponding to the service device combination scheme; the next device quantity level is the level below the current device quantity level; Based on business requirements, a target device deployment scheme is determined from the candidate device deployment schemes corresponding to each of the service device combination schemes, and network deployment for the target deployment area is executed through the target device deployment scheme.

2. The method according to claim 1, characterized in that, The step of obtaining the optimal device deployment scheme for the service device combination scheme at the current device quantity level includes: Obtain the initial device deployment plan at the current device quantity level; Based on the initial device deployment scheme and the pre-built communication performance prediction model, the optimal device deployment scheme of the service device combination scheme under the current number of devices is obtained.

3. The method according to claim 2, characterized in that, The step of obtaining the optimal device deployment scheme for the service device combination scheme at the current device quantity level based on the initial device deployment scheme and the pre-built communication performance prediction model includes: The initial equipment deployment plan is input into the communication performance prediction model, and the communication performance prediction model outputs the prediction evaluation index data of the initial equipment deployment plan; the prediction evaluation index data includes at least one of the following: predicted signal poor coverage rate, predicted average signal strength, predicted average signal-to-noise ratio, predicted average downlink rate, and predicted connection success rate. Based on the predicted evaluation index data of the initial equipment deployment scheme, the performance evaluation data corresponding to the initial equipment deployment scheme is obtained; The device deployment locations in the initial device deployment scheme are changed to obtain a new initial device deployment scheme. Then, the process returns to the step of inputting the initial device deployment scheme into the communication performance prediction model to obtain the performance evaluation data corresponding to the initial device deployment scheme. This process continues until the performance evaluation data corresponding to the new initial device deployment scheme meets the preset convergence conditions. The new initial device deployment scheme is then used as the optimal device deployment scheme for the service device combination scheme at the current device quantity level.

4. The method according to claim 1, characterized in that, The step of determining the target device deployment scheme from the candidate device deployment schemes corresponding to each of the service device combination schemes based on business requirements includes: Analyze the business requirements to obtain the target evaluation indicators; Based on the target evaluation indicators, the target device deployment scheme is determined from the candidate device deployment schemes corresponding to each of the service device combination schemes.

5. The method according to claim 4, characterized in that, When the target evaluation indicator is a single evaluation indicator, determining the target device deployment scheme from the candidate device deployment schemes corresponding to each of the service device combination schemes based on the target evaluation indicator includes: Obtain target evaluation index data corresponding to the target evaluation index from the candidate device deployment schemes corresponding to each of the service device combination schemes; Based on the target evaluation index data, the target device deployment scheme is determined from the candidate device deployment schemes corresponding to each of the service device combination schemes.

6. The method according to claim 4, characterized in that, When there are multiple target evaluation indicators, determining the target device deployment scheme from the candidate device deployment schemes corresponding to each service device combination scheme based on the target evaluation indicators includes: Obtain the indicator weights corresponding to the target evaluation indicators, and obtain the target evaluation indicator data corresponding to the target evaluation indicators from the candidate device deployment schemes corresponding to each of the service device combination schemes; By using the weights of each indicator, the data of each target evaluation indicator are weighted and summed to obtain the comprehensive evaluation data of the candidate equipment deployment schemes corresponding to each service equipment combination scheme; Based on the comprehensive evaluation data, the target equipment deployment scheme is determined from the candidate equipment deployment schemes corresponding to each service equipment combination scheme.

7. A network deployment device, characterized in that, The device includes: The first acquisition module is used to acquire at least one service device combination scheme; the service device combination scheme is used to characterize the matching relationship between network services and access devices; The second acquisition module is used to acquire, for any of the service device combination schemes, the optimal device deployment scheme of the service device combination scheme under the current number of devices, and acquire the communication performance of the optimal device deployment scheme; The loop module is used to, when the communication performance does not meet the preset communication performance standard, take the next device quantity level as the new current device quantity level, return to execute the step of obtaining the optimal device deployment scheme of the service device combination scheme under the current device quantity level, until the communication performance meets the communication performance standard, and take the optimal device deployment scheme as the candidate device deployment scheme corresponding to the service device combination scheme; the next device quantity level is the level below the current device quantity level; The deployment module is used to determine the target device deployment scheme from the candidate device deployment schemes corresponding to each of the service device combination schemes based on business needs, and to perform network deployment for the target deployment area through the target device deployment scheme.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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