TWI816074B - System and method for integrated access and backhaul management - Google Patents

Abstract

A system and a method for integrated access and backhaul (IAB) management are provided. In the method, geographic environment data and user statistic data are obtained. The geographic environment data is related to geographic information related to multiple areas where the IAB node would be deployed. The user statistic data is related to the traffic statistic of multiple user equipments (UEs) in the areas. The UEs are grouped, to determine multiple traffic area representatives. The traffic area representatives are related to the deploying places of the IAB nodes. The wireless channel situation is simulated according to the traffic area representatives and the geographic environment data, to determine the power values of the IAB nodes. Accordingly, a suitable deploying place can be determined.

Description

Integrated access and backhaul network management systems and methods

The present invention relates to a network management technology, and in particular to a management system and method for planning and optimizing an Integrated Access and Backhaul (IAB) network.

As users' demand for mobile network data gradually increases, how to effectively and cost-effectively deploy mobile communication networks has become a major challenge faced by telecom operators. It is worth noting that the deployment costs for base stations to deploy fiber optic fronthaul or backhaul network and other wired network resources are considerable. Therefore, how to select deployment sites and the network deployment methods they use based on the characteristics of the deployment site are also issues that telecom operators need to consider.

Integrated Access and Backhaul (IAB) began to be discussed as a Study Item in the 3rd Generation Partnership Project (3GPP) Release 16, and its features can be provided through IAB The access network of the donor serves as the wireless backhaul network of the IAB node, and is used as a signal extension or capacity supplement for the network. The advantage of IAB is that it can reduce the fiber cost of deploying base stations. In addition, for some locations where optical fiber networks are not suitable to be extended, wireless transmission methods can be used to directly deploy them at these locations. In addition, when the original site where IAB nodes are deployed needs to be removed, thanks to the advantages of the wireless network as a backhaul network, the manpower resources and time required for removal can be reduced.

However, the disadvantage of using wireless signals as the backhaul network is that there will be interference problems between the backhaul network and the access network between IAB nodes. Therefore, how to appropriately and quickly adjust wireless parameters to reduce interference is also an issue that telecom operators need to consider.

In view of this, embodiments of the present invention provide an integrated access and backhaul network (IAB) management system and method that can determine appropriate deployment locations and configurations, and adaptively optimize parameters.

The IAB management method in the embodiment of the present invention includes (but is not limited to) the following steps: obtaining geographical environment data and user statistical data. The geographical environment data is related to the geographical information of several areas where several IAB nodes are to be deployed, and the user statistical data is related to the traffic statistics of several user devices in those areas. Group those user devices based on user statistics to determine several traffic area representative points. Those traffic area representative points are related to the deployment locations of those IAB nodes. Simulate wireless channel conditions based on those traffic area representative points and geographical environment data to determine the power values of those IAB nodes.

The IAB management system in the embodiment of the present invention includes (but is not limited to) a data management module and a node planning module. The data management module is used to obtain geographical environment data and user statistical data. The geographical environment data is related to the relevant geographical information of several areas where several IAB nodes are to be deployed, and the user statistical data is related to several user devices in those areas. traffic statistics. The node planning module is used to group those user equipments based on user statistics to determine several traffic area representative points, and simulate wireless channel conditions based on those traffic area representative points and geographical environment data to determine the power values of those IAB nodes. Those traffic area representative points are related to the deployment locations of those IAB nodes.

Based on the above, the IAB management system and method according to the embodiment of the present invention use the concept of Utility Signal-to-Interference-plus-Noise Ratio (SINR) based on a combination of planning and optimization to reduce The complexity of wireless network parameter optimization and completion of IAB node deployment planning. In addition, embodiments of the present invention can adjust and optimize network parameters according to the actual conditions of the mobile network, so as to reduce the operator's maintenance costs and improve the performance of the mobile network system.

In order to make the above-mentioned features and advantages of the present invention more obvious and easy to understand, embodiments are given below and described in detail with reference to the accompanying drawings.

Figure 1 is a system architecture diagram according to an embodiment of the present invention. Please refer to Figure 1. This system includes a mobile network system 50 and a management system 100 for IAB.

The mobile network system 50 may include (but is not limited to) user equipment, base stations, core networks, network management systems and other related mobile network equipment. In one embodiment, the base station includes an IAB provider (Donor) and an IAB node (Node). In addition, according to different mobile network standards, the types of network devices may be different, and the embodiments of the present invention are not limited thereto.

The management system 100 may be one or more servers or related computer systems. The management system 100 includes (but is not limited to) a data management module 110, a node planning module 130, and a network parameter optimization module 150. These software modules can be loaded by the processor and perform their functions, and their functions will be described in detail in subsequent embodiments. In some embodiments, the management system 100 further includes a network interface (for example, supporting Ethernet, optical fiber network, or Wi-Fi) to communicate with network devices in the mobile network system 50 .

In the following, the method described in the embodiment of the present invention will be described with reference to various devices in the system architecture of FIG. 1 . Each process of this method can be adjusted according to the implementation situation, and is not limited to this.

Figure 2 is a flow chart of an IAB management method according to an embodiment of the present invention. Referring to Figure 2, the data management module 110 obtains geographical environment data and user statistical data (step S210). Specifically, the geographical environment data is related to the relevant geographical information of several areas where several IAB nodes are to be deployed. For example, building height, building material, terrain height, allowed deployment location of IAB nodes and/or distance between buildings. User statistics relate to the traffic statistics of several user devices in those areas. The user equipment may be a mobile phone, a tablet computer, an on-board unit (OBU), a smart watch, or other equipment that uses network services provided by the mobile network system 50 . User statistics include information such as mobile network traffic distribution and the number of users in each region.

The node planning module 130 can perform deployment planning of IAB nodes based on geographical environment data and user statistical data (step S230). Specifically, the deployment planning of the embodiment of the present invention is mainly divided into two parts. One is the location planning of the IAB node, and the other is the power setting of the IAB node.

Figure 3 is a flow chart of node planning according to an embodiment of the present invention. Referring to FIG. 3 , the node planning module 130 can group those user equipments according to user statistical data to determine several traffic area representative points (step S310 ). Specifically, the service area representative point is related to the deployment location of those IAB nodes. The node planning module 130 mainly groups user traffic areas according to user traffic distribution conditions. In one embodiment, the node planning module 130 may use k-means clustering to determine several traffic groups. As shown in the following formula (1), U is a vector of representative points of each traffic area, its elements are representative points u _i of each traffic group, and its meaning is all data points x _k in each traffic group (i.e., user The sum of the distances from the device) to the center point u _i of its corresponding traffic group (that is, as the representative point of the traffic area) is the smallest: …(1) where m is the number of traffic groups, is the i-th information service group.

In other embodiments, the node planning module 130 may also use k-nearest neighbors algorithm (k-NN), DBSCAN (Density-based spatial clustering of applications with noise) or other clustering algorithms. Grouping of user devices.

The node planning module 130 may select at least one of several allowed deployment locations based on those traffic area representative points, and the selected allowed deployment location is related to the deployment locations of those IAB nodes (step S330). In other words, the node planning module 130 can find the closest allowed deployment location obtained in step S210 based on the traffic area representative point determined in step S310, so as to obtain the closest possible deployment location that can support user traffic usage and is practical. The location of the deployment. In one embodiment, the node planning module 130 uses the minimum square difference method to find the deployment position vector B of the IAB node: …(2)

In other embodiments, the node planning module 130 may also select all allowed deployment locations within a specific range (for example, within a radius of 50, 100 or 150 meters) from the representative points of the traffic area.

In addition, the node planning module 130 further considers the building characteristics of the deployment area (for example, the distance between buildings, height, surface material, terrain height, etc.). The above-mentioned building characteristics will have an impact on wireless signal attenuation. If these impacts are considered during the planning stage, the deployment location of IAB nodes that is more suitable for actual use can be planned.

The node planning module 130 can simulate wireless channel conditions based on some traffic area representative points and geographical environment data (step S350). Specifically, the node planning module 130 can deploy the IAB node determined in step S330 based on the geographical environment information of the buildings in the area where the IAB node is to be deployed in step S210, according to the distance between buildings, building height, building material, terrain height, and Location and other information is used to draw a three-dimensional model of the field. Then, the node planning module 130 can be built based on this model and simulate wireless signal strength and wireless channel conditions through wireless signal simulation software (eg, Wireless Insite).

The node planning module 130 can form a power configuration problem based on the simulated signal strength and wireless channel conditions, and use geometric programming (Geometric Programming, GP) to linearize the power configuration problem to obtain a linearized rate formula (step S370 ). Specifically, this power configuration issue is related to the rate values and power values assigned by the IAB provider to those IAB nodes. For example, the power configuration issue is related to Shannon's theorem regarding transmission rate limitations. Among them, the rate value of the IAB node to be set can be obtained from user statistics. As shown in the following formula (3), through GP, the IAB node rate formula can be linearized, and the optimal solution can be found through methods such as Lagrange multiplier and particle swarm algorithm. That is, the power values of those IAB nodes can be obtained by solving the linearized rate formula obtained by simulating wireless channel conditions (step S390). In the following formula (3), is the rate of the b-th IAB node in the Resource Block (RB) (i.e., radio resource); is the wireless channel attenuation value between the dth IAB provider and the bth IAB node calculated by simulation software; Configure the power value on the b -th IAB node for the d -th IAB supplier: …(3) Among them, is the bandwidth, , is a constant, For noise.

also, is the amount of other backhaul network interference experienced by the b-th IAB node in the n-th resource block. These interference amounts are caused by the power transmitted by the d-th IAB provider to other IAB nodes, and can be calculated by the following formula (4): …(4)

Node planning module 130 goals enable each rate Maximize and make the total rate It complies with the rate value to be set, and the total power allocated by the IAB provider to each IAB node must be less than the maximum allowed power limit. If there are N resource blocks available in the system, the total rate It can be calculated according to the following formula (5): …(5)

Although the network planning stage does not have immediate needs, it can use more computer hardware and other computing resources to find suitable planning configurations in a time-consuming manner. However, non-linear optimization problems such as network parameter configurations of IAB providers are more difficult. It is complex, so it is not easy to find parameter configurations that can support user traffic usage. Embodiments of the present invention linearly transform the original non-linear optimization problems such as the network parameter configuration of the IAB provider to reduce the complexity of finding solutions and thereby reduce the cost of hardware resources required during the planning period.

Then, the network parameter optimization module 150 can implement the deployment locations of those IAB nodes and the power values of those IAB nodes in the mobile network system 50, and perform parameter optimization accordingly (step S250). That is, telecom operators can actually build IAB nodes at the determined deployment locations and set the power configuration based on the aforementioned power values.

Specifically, FIG. 4 is a flow chart of parameter optimization according to an embodiment of the present invention. Referring to FIG. 4 , the network parameter optimization module 150 measures and reports actual wireless channel conditions via the user equipment through the base station (step S410 ).

Then, the network parameter optimization module 150 can determine the interference amount of those user equipments based on the deployment locations of those IAB nodes, the power values of those IAB nodes and actual wireless channel conditions (step S430). In one embodiment, the network parameter optimization module 150 can calculate the interference amount of the user equipment according to the following formula (6) . Among them, the power P transmitted by other IAB nodes takes into account the distributed radio resource management adopted among IAB nodes, so the transmission power of other IAB nodes is the maximum transmission power when estimating interference. In this way, the transmit power that meets the minimum user service quality requirements can be found. …(6)

The network parameter optimization module 150 can transmit the aforementioned estimated interference amount and the execution network parameter optimization strategy to each IAB node, and determine radio resources and power configuration that meet the user's service quality requirements based on the interference amount of those user equipments ( Step S450). In one embodiment, the operation of the network parameter optimization strategy is as shown in the following formula (7). First, the network parameter optimization module 150 determines that each user equipment reaches (Utility) signal-to-noise ratio (Signal) in the nth resource block. -to-Interference-plus-Noise Ratio, SINR) required power vector, and sort this power vector from small to large . …(7)

Then, the network parameter optimization module 150 can adjust the speed corresponding to the user's service quality requirements. and power vector , calculate the vector M such that . Among them, the elements of the vector M that are not 0 represent that the resource block corresponding to the element can be allocated to the user equipment. On the contrary, if the element of vector M is 0, it means that the resource block corresponding to the element is not allocated to this user equipment. From this, the configuration of radio resources can be derived. The power on each resource block will be adjusted to , where i is the vector M and the power vector The corresponding index. That is, the power configuration of each radio resource is obtained.

The network parameter optimization module 150 can determine whether the radio resources and power configuration meet the user's service quality requirements (step S270). If it is not satisfied, the network parameter optimization module 150 can perform parameter optimization again (step S250).

Each IAB node can execute a network parameter optimization algorithm based on the estimated interference amount and the network parameter optimization strategy required by the upper layer to find the appropriate radio resource and power configuration. Through the interference estimation calculated by the upper layer, the optimization problem of radio resources and power configuration can be reduced in dimension, and each IAB node does not need to exchange the wireless resource allocation situation with each other, and only needs to report the actual measurement results from the user equipment. For wireless channel conditions, Utility SINR can be used to find radio resources and power configurations that ensure user service quality requirements in a decentralized management manner.

It can be seen from this that the embodiments of the present invention can be applied to situations where different user equipments have different resource priorities, mobile network quality requirements, mobile network application scenarios, etc., and configure mobile network parameters. In addition, when mobile network resources are limited, embodiments of the present invention can prioritize user resources with high priority to meet actual network usage scenarios.

FIG. 5 is a schematic diagram of an Open-Radio Access Network (O-RAN) architecture 51 according to an embodiment of the present invention. Please refer to Figure 5. Assume that the embodiment of the present invention is applied to the O-RAN architecture 51. The architecture proposed by the O-RAN Alliance includes the following functional blocks and the functions they support: Service Management and Orchestration (Service Management and Orchestration) SMO, non- Non-real-time Radio Access Network Intelligent Controller (non-RT RIC) RIC1, Near-real-time Radio Access Network Intelligent Controller (near-RT RIC) )RIC2, O-RAN Central Unit (O-RAN Central Unit) O-CU, O-RAN Distributed Unit (O-RAN Distributed Unit) O-DU, O-RAN Radio Unit (O-RAN Radio Unit) O-RU , and O-RAN cloud platform (O-RAN Cloud) O-Cloud.

Service management and orchestration SMO provides O1 interface I1 and O2 interface I2. O1 interface I1 is the interface used to connect various managed components, and is used for error (fault), configuration, accounting, performance, and security management (Fault, Configuration, Accounting, Performance, Fault Management, FCAPS Management), and can collect performance data access network and user performance data; O2 interface I2 is an interface used to connect to the O-RAN cloud platform O-Cloud and is used to orchestrate the cloud platform resources.

The non-instant access network intelligent controller RIC1 provides the A1 interface I3, where the A1 interface I3 is the interface used to connect the near-instant access network intelligent controller RIC2. The non-instant access network intelligent controller RIC1 uses the A1 policy. The A1 policy is used to set policies and is passed to the near-real-time access network intelligent controller RIC2 through the A1 interface I3, and the policies include quality of service (QoS), user experience (Quality of Experience, QoE) and traffic guidance ( Traffic Steering).

The near-instant access network intelligent controller RIC2 provides E2 interface (E2 interface) I4. The E2 interface I4 is an interface used to connect the O-RAN centralized unit O-CU and the O-RAN decentralized unit O-DU, and is used to collect, analyze, and monitor data from the O-RAN centralized unit O-CU and the O-RAN decentralized unit O. -DU's network information and user information, and controls the behavior or parameters of the O-RAN centralized unit O-CU and the O-RAN decentralized unit O-DU.

O-RAN centralized unit O-CU, O-RAN decentralized unit O-DU, and O-RAN radio frequency unit O-RU support the centralized unit, decentralized unit and radio frequency unit functions defined by 3GPP, and support O1 interface I1. The O-RAN centralized unit O-CU can be further divided into the O-RAN control unit control plane (O-RAN Central Unit Control Plane, O-CU-CP) and the user plane (O-RAN Central Unit User Plane, O-CU- UP). The O-RAN centralized unit O-CU and the O-RAN decentralized unit O-DU support F1 interface I5. The O-RAN distributed unit O-DU and the O-RAN radio unit O-RU support the open-fronthaul interface (OFH interface) I6 defined by O-RAN.

In one embodiment, the node planning module 130 can be applied in service management and orchestration SMO to perform IAB node deployment location planning and initial configuration parameter determination of the IAB provider. One or more xAPPs on the near-real-time access network intelligent controller RIC2 can collect base stations (i.e., O-RAN centralized unit O-CU and O-RAN decentralized unit O-DU) through the front-end E2 interface I4. ) to optimize the Radio Resource Management (RRM) function, and send the parameters and optimization execution strategies required for O-RAN distributed unit O-DU scheduling to the O through the E2 interface I4 -RAN distributed unit O-DU enables the O-RAN distributed unit O-DU to execute the network parameter optimization algorithm under the instruction of xAPP. Therefore, the network parameter optimization module 150 is an application of xAPP.

Figure 6 is a flow chart illustrating an IAB management method under the O-RAN architecture 51 according to an embodiment of the present invention. Referring to Figure 6, the data management module 110 external to the service management and orchestration SMO obtains geographical environment data and user statistical data (step S610). The node planning module 130 used in service management and orchestration SMO can determine the network parameter configuration of the IAB provider and the location planning of the IAB node (step S630). Among them, the service management and orchestration SMO can set the power value to the O-RAN radio unit O-RU of the IAB provider through the O1 interface I1.

Then, the IAB node is deployed in the actual mobile network system 50 . These IAB nodes or IAB providers (or E2 nodes) report the wireless channel conditions measured by the user equipment through the E2 interface I4 (step S650).

FIG. 7 is a flow chart illustrating reporting of wireless communication status under the O-RAN architecture 51 according to an embodiment of the present invention. Referring to Figure 7, the near-instant access network intelligent controller RIC2 requests the wireless channel information of the base station measured by each user equipment (as an assessment of the wireless channel status) through the RIC Service Query (step S710), E2 The node N _E2 reports the wireless channel information through the RIC service update (Service Update) (step S730), and the near-real-time access network intelligent controller RIC2 confirms to the E2 node N _E2 whether to receive the wireless channel information through the RIC service update acknowledgment (Service Update Acknowledge). Channel information (step S750).

The near-real-time access network intelligent controller RIC2 estimates the interference amount and transmits the interference amount and the network optimization decision to be executed by the scheduler of the O-RAN distributed unit O-DU to the O of each IAB node through the E2 interface I4. - RAN distributed unit O-DU (step S670).

FIG. 8 is a flow chart illustrating the implementation of a network parameter optimization strategy under the O-RAN architecture 51 according to an embodiment of the present invention. Please refer to Figure 8. The near-real-time access network intelligent controller RIC2 transmits the estimated interference amount and the execution network parameter optimization strategy to the O- of each IAB node through the RIC Subscription Request of the E2 interface I4. RAN distributed unit O-DU (step S810). The O-RAN decentralized unit O-DU confirms whether this network parameter optimization strategy has been implemented through the RIC Subscription Response.

The O-RAN distributed unit O-DU of each IAB node can execute the network parameter optimization algorithm based on the estimation of interference received from the E2 interface I4 and the network parameter optimization strategy required to be executed by the scheduler. Then find appropriate radio resources and power configuration (step S690).

It should be noted that the embodiment of the present invention is not limited to the O-RAN architecture 51.

To sum up, in the IAB management system and method according to the embodiment of the present invention, the grouping method is used to find out the locations that support user network requirements and operators can deploy, and the linearization characteristics of geometric planning are used to reduce the mobile network The complexity of the parameter configuration problem is reduced and the search time for network parameter configuration is reduced. In addition, due to the characteristics of distributed management among IAB nodes and the need for real-time network parameter configuration, the present invention can further configure network parameters that support the needs of mobile network users through interference estimation and Utility SINR calculation. , to achieve the goal of improving network performance.

Embodiments of the present invention further include the following features and effects:

The embodiment of the present invention addresses the problem of IAB node location planning. By grouping user traffic areas and combining the operator's actual deployable location considerations with the mechanism, it is possible to find a location that simultaneously supports the user's network needs and the operator's deployable location. .

Embodiments of the present invention solve issues such as network parameter configuration of IAB providers and IAB nodes based on the deployment location of IAB nodes. However, due to the correlation between mobile network deployment locations and parameters, the joint optimization problem is very complex. Therefore, embodiments of the present invention use the concepts of linearization and Utility SINR to simplify the joint optimization problem.

The embodiments of the present invention are also suitable for users with different priorities and mobile network requirements. Therefore, when configuring the network parameters of the IAB node, the algorithm of the embodiment of the present invention can be used to adjust the network parameters to meet actual network operation requirements.

Embodiments of the present invention also take into account the decentralized nature of IAB node network resource management and the need to set mobile network parameters in real time in response to rapid changes in wireless signals. Centralized management can only be applied to advance planning in the planning stage. After the IAB node is deployed, the network resource configuration of the IAB node cannot meet the actual network characteristics. Therefore, a decentralized network parameter setting mechanism is proposed at the IAB node to meet the needs of real-time adjustment of the actual network. In addition, the concept of Utility SINR proposed by the embodiment of the present invention combined with the consideration of user needs can also be applied to centralized management to respond to users' mobile network needs.

Although the present invention has been disclosed above through embodiments, they are not intended to limit the present invention. Anyone with ordinary knowledge in the technical field may make some modifications and modifications without departing from the spirit and scope of the present invention. Therefore, The protection scope of the present invention shall be determined by the appended patent application scope.

50: Mobile network system 100: Management system 110: Data management module 130: Node planning module 150: Network parameter optimization module S210~S270, S310~S390, S410~S450, S610~S690, S710~S750, S810~S830: Step 51: O-RAN architecture SMO: Service management and orchestration RIC1: Non-instant access network intelligent controller RIC2: Near-instant access network intelligent controller I1: O1 interface I2: O2 interface I3: A1 interface I4 :E2 interface I5: F1 interface I6: Open front-end interface O-Cloud: O-RAN cloud platform O-CU: O-RAN centralized unit O-DU: O-RAN decentralized unit O-RU: O-RAN radio unit xAPP: xAPP N _E2 :E2 node

Figure 1 is a system architecture diagram according to an embodiment of the present invention. Figure 2 is a flow chart of an IAB management method according to an embodiment of the present invention. Figure 3 is a flow chart of node planning according to an embodiment of the present invention. Figure 4 is a flow chart of parameter optimization according to an embodiment of the present invention. FIG. 5 is a schematic diagram of an Open-Radio Access Network (O-RAN) architecture according to an embodiment of the present invention. Figure 6 is a flow chart illustrating an IAB management method under the O-RAN architecture according to an embodiment of the present invention. Figure 7 is a flow chart illustrating reporting of wireless communication status under the O-RAN architecture according to an embodiment of the present invention. Figure 8 is a flow chart illustrating the implementation of a network parameter optimization strategy under the O-RAN architecture according to an embodiment of the present invention.

S210~S270: steps

Claims (10)

An integrated access and backhaul (IAB) network (Integrated Access and Backhaul, IAB) management method includes: obtaining a geographical environment information and a user statistical information, wherein the geographical environment information is related to multiple IAB nodes to be deployed Relevant geographical information of multiple areas, and the user statistics are related to the traffic statistics of multiple user equipment in these areas; group these user equipment based on the user statistics to determine representative points of multiple traffic areas , wherein the communication area representative points are related to the deployment locations of the IAB nodes; and a three-dimensional model of the areas is drawn based on the communication area representative points and the geographical environment data, and a wireless signal simulation software is used to draw a three-dimensional model of the areas To simulate a wireless channel condition based on the three-dimensional model to determine the power value of the IAB nodes, where the three-dimensional model is based on the distance between buildings, building height, building material or terrain height included in the geographical environment data that affects the wireless Signal attenuation conditions are plotted against building characteristics. The IAB management method as described in request 1, wherein the user statistics include the number of users and traffic distribution in each area, and the step of determining the representative points of the traffic areas includes: using k-mean grouping (k -means clustering) determines multiple traffic groups, where the center point of the traffic groups serves as the representative point of the traffic areas, and the user equipment of each traffic group corresponds to a representative point of the traffic area The total distance of Or, the selected allowed deployment location is related to the deployment location of these IAB nodes. The IAB management method according to claim 1, wherein the step of determining the power values of the IAB nodes includes: forming a power configuration configuration problem according to the wireless channel condition, wherein the power configuration configuration problem is related to an IAB provider (Donor) assign the rate value and power value to the IAB nodes; use geometric programming (Geometric Programming, GP) to linearize the power configuration configuration problem to obtain a linearized rate formula; and determine the linearized rate formula solution to obtain the power values of these IAB nodes. The IAB management method described in claim 1 further includes: implementing the deployment locations of the IAB nodes and the power values of the IAB nodes in a mobile network system; based on the deployment locations of the IAB nodes, the The power values of some IAB nodes and an actual wireless channel condition determine the interference amount of the user equipment, where the actual wireless channel condition is reported by the user equipment after measurement; and the interference amount of the user equipment is determined based on the interference amount of the user equipment. A radio resource and power configuration for a user's service quality requirements. The IAB management method as described in claim 4, wherein the radio resource includes a plurality of resource blocks (RB), and the step of determining the radio resource and power configuration that meets the user's service quality requirements includes: determining each The user equipment performs the functions required to achieve the Utility Signal-to-Interference-plus-Noise Ratio (SINR) in each resource block. rate vector; and determine the radio resource and power configuration based on the rate corresponding to the user's service quality requirements and the power vector. A management system for IAB, including: a data management module that obtains a geographical environment data and a user statistical data, wherein the geographical environment data is related to the relevant geographical information of multiple areas where multiple IAB nodes are to be deployed , and the user statistical data is related to the traffic statistics of multiple user equipment in these areas; and a node planning module is used to group the user equipment according to the user statistical data to determine multiple traffic area representative points, and A wireless signal simulation software is used to draw a three-dimensional model of the areas based on the representative points of the communication areas and the geographical environment data, and a wireless channel condition is simulated based on the three-dimensional model to determine the power values of the IAB nodes, where The representative points of the communication area are related to the deployment locations of the IAB nodes, and the three-dimensional model is based on the distance between buildings, building height, building material or terrain height included in the geographical environment data, which affects the attenuation of wireless signals. The characteristics of the building are mapped. The IAB management system as described in request 6, wherein the user statistics include the number of users and traffic distribution in each area, the node planning module uses k-average grouping to determine multiple traffic groups, and the node The planning module selects at least one of multiple allowed deployment locations based on the traffic area representative points, wherein the center points of the traffic groups serve as the traffic area representative points, and the traffic area representative points of each traffic group some user settings The total distance from the equipment to the representative point corresponding to the traffic area is the smallest, and the selected allowed deployment location is related to the deployment location of these IAB nodes. The IAB management system as described in claim 6, wherein the node planning module forms a power configuration problem based on the wireless channel condition, and the node planning module uses geometric programming to linearize the power configuration problem to obtain a first-line linearized rate formula, and the node planning module determines the solution of the linearized rate formula to obtain the power values of the IAB nodes, wherein the power configuration configuration problem is related to an IAB provider allocating to the IAB nodes Speed value and power value. The IAB management system as described in claim 6 further includes: a network parameter optimization module that implements the deployment positions of the IAB nodes and the power values of the IAB nodes in a mobile network system. According to these The deployment location of the IAB nodes, the power values of the IAB nodes and an actual wireless channel condition determine the interference amount of the user equipment, and determine a radio resource that meets a user's service quality requirements based on the interference amount of the user equipment. Power configuration, where the actual wireless channel conditions are reported by the user equipment after measurements. The IAB management system as described in claim 9, wherein the radio resource includes a plurality of resource blocks, and the network parameter optimization module determines that each user equipment achieves an effective signal-to-noise ratio in each resource block. The required power vector is determined, and the radio resource and power configuration are determined based on the rate corresponding to the user's service quality requirements and the power vector.

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