CN114125896B - Wireless resource load assessment method, device and computer-readable storage medium - Google Patents

Abstract

The application provides a wireless resource load assessment method, a wireless resource load assessment device and a computer readable storage medium, relates to the technical field of communication, and can reflect the actual load condition of cell wireless resources in a MIMO scene. The method comprises the following steps: acquiring sampling data of a target cell in a sampling period; determining the airspace available layer number of the target cell in the sampling period according to the sampling data; determining the wireless resource utilization rate of the target cell in the sampling period according to the sampling data and the airspace available layer number of the target cell in the sampling period; wherein the radio resource utilization of the target cell is used to evaluate the radio resource load of the target cell.

Description

Wireless resource load evaluation method, device and computer-readable storage medium

Technical Field

The present application relates to the field of communication technology, and in particular to a method, device and computer-readable storage medium for evaluating wireless resource load.

Background Art

With the development of communication technology, massive multiple-input multiple-output (massive MIMO) (also known as massive multi-antenna) technology has been widely used in wireless networks as a key technology of the fifth generation mobile communication technology (5G) communication. In MIMO scenarios, wireless resources can be divided into different spatial layers (layers) from the spatial dimension, or spatial layers. At present, the wireless resource load of a cell is usually evaluated based on the calculated cell wireless resource utilization rate. Therefore, in the MIMO scenario, when evaluating the wireless resource load of a cell by calculating the cell wireless resource utilization rate, the number of available layers in the cell airspace should be considered.

The existing solution introduces the space division factor (spatial factor) Alpha to characterize the number of available layers in the cell's airspace when calculating the utilization rate of the cell's wireless resources in the MIMO scenario. At present, the space division factor is only specified as a configured constant, and the constant must make the cell's wireless resource utilization rate less than 1. However, in actual applications, the conditions of different cells are different, so the number of available layers in the airspace of different cells may not be the same, and the number of available layers in the airspace of the cell may also change over time. Therefore, if a fixed constant is used as the space division factor to calculate the wireless resource utilization rate of the cell in the MIMO scenario, the space division factor will not be able to faithfully reflect the actual space (space division) capabilities of different cells, and the calculated wireless resource utilization rate of the cell will not be able to reflect the actual load of the cell's wireless resources in the MIMO scenario. Therefore, how to propose a wireless resource load evaluation method that can reflect the actual load of the cell's wireless resources in the MIMO scenario is a problem that needs to be solved urgently.

Summary of the invention

The present application provides a wireless resource load assessment method, device and computer-readable storage medium, which are used to solve the problem that the current wireless resource load assessment method cannot accurately reflect the actual load situation of the cell wireless resources in the MIMO scenario.

In order to achieve the above purpose, this application adopts the following technical solutions:

In a first aspect, a wireless resource load assessment method is provided, which can be executed by a wireless resource load assessment device, and the method includes: acquiring sampling data of a target cell within a sampling period; determining the number of available airspace layers of the target cell within the sampling period based on the sampling data; determining the wireless resource utilization rate of the target cell within the sampling period based on the sampling data and the number of available airspace layers of the target cell within the sampling period; wherein the wireless resource utilization rate of the target cell is used to assess the wireless resource load of the target cell.

The wireless resource load evaluation method provided in the present application is based on the number of available airspace layers of the target cell within the sampling period when determining the wireless resource utilization rate of the target cell. Because the number of available airspace layers of the target cell within the sampling period is determined based on the sampling data within the sampling period, if the cell situation changes, the number of available airspace layers of the target cell within the sampling period will also automatically change with the change of the cell's spatial capacity. In other words, in this solution, the number of available airspace layers of the target cell determined based on the sampling data can represent the actual spatial capacity of the target cell in real time. Furthermore, the wireless resource utilization rate of the cell determined based on the number of available airspace layers of the target cell within the sampling period can reflect the actual load of the cell's wireless resources in different cells or different user distribution scenarios in real time. In summary, compared with the existing solution in which the space division factor Alpha used to characterize the number of available layers in the cell airspace is configured as a fixed constant, this solution, on the one hand, solves the problem that the existing solution is prone to unreasonable setting of the space division factor Alpha value, which leads to the inability of wireless resource utilization to reflect the actual resource occupancy, and can more accurately and reasonably reflect the wireless resource load of the cell in the MIMO scenario. On the other hand, it solves the problem that the existing solution needs to frequently adjust the space division factor Alpha with changes in time, scenarios, and user distribution, and can reduce artificial errors introduced by external interference.

In combination with the first aspect, in certain embodiments of the first aspect, determining the number of available spatial layers of the target cell within the sampling period according to the sampling data includes: determining the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T according to the sampling data; determining the number of available spatial layers of the target cell within the sampling period according to the average scheduling layers of the service channel of the target cell corresponding to the sampling time j and a first calculation rule, and the first calculation rule satisfies the following relationship: LM(T)=MAX _j (L _avg,j ); wherein LM(T) represents the number of available spatial layers of the target cell within the sampling period T; L _avg,j represents the average scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T; MAX _j (L _avg,j ) represents taking the L _avg,j with the largest value from the L _avg, j corresponding to each sampling time j.

In combination with the first aspect, in certain embodiments of the first aspect, the sampling data includes: M1 _i,j (T), L _i,j (T) and PRB _j , M1 _i,j (T) represents the number of physical resource blocks PRBs occupied by the terminal device i accessing the target cell corresponding to the sampling time j within the sampling period T; L _i,j (T) represents the number of spatial layers occupied by the PRBs scheduled by the terminal device i corresponding to the sampling time j within the sampling period T; PRB _j represents the number of PRBs occupied by the service channel of the target cell corresponding to the sampling time j within the sampling period T; according to the sampling data, determining the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T, including: determining the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T according to the sampling data and the second calculation rule, and the second calculation rule satisfies the following relationship: Wherein, L _avg,j represents the average scheduling layer number of the service channel of the target cell corresponding to the sampling time j within the sampling period T, and ∑ _i represents the sum of all i.

In combination with the first aspect, in certain embodiments of the first aspect, the sampling data includes: M1 _i,j (T), L _i,j (T), N(T) and P(T), M1 _i,j (T) represents the number of physical resource blocks PRBs occupied by the terminal device i accessing the target cell corresponding to the sampling time j within the sampling period T; L _i,j (T) represents the number of spatial layers occupied by the PRBs scheduled by the terminal device i corresponding to the sampling time j within the sampling period T; N(T) represents the number of sampling moments within the sampling period T; P(T) represents the number of available PRBs for each layer of the service channel of the target cell at each sampling moment within the sampling period T; determining the wireless resource utilization of the target cell within the sampling period according to the sampling data and the number of available spatial layers of the target cell within the sampling period, including: determining the wireless resource utilization of the target cell within the sampling period according to the sampling data and the number of available spatial layers of the target cell within the sampling period and the third calculation rule, and the third calculation rule satisfies the following relationship: Where _ME (T) represents the wireless resource utilization rate of the target cell within the sampling period T. represents the sum of all i; represents the sum over all j.

In combination with the first aspect, in certain embodiments of the first aspect, the wireless resource utilization of the target cell is the uplink wireless resource utilization of the target cell or the downlink wireless resource utilization of the target cell; when the wireless resource utilization of the target cell is the uplink wireless resource utilization of the target cell, the service channel is the physical uplink shared channel PUSCH channel; when the wireless resource utilization of the target cell is the downlink wireless resource utilization of the target cell, the service channel is the physical downlink shared channel PDSCH channel.

In a second aspect, a wireless resource load assessment device is provided for implementing the wireless resource load assessment method. The wireless resource load assessment device includes a module, unit, or means corresponding to the method, which can be implemented by hardware, software, or hardware executing corresponding software. The hardware or software includes one or more modules or units corresponding to the above functions.

In combination with the second aspect, in certain embodiments of the second aspect, the wireless resource load evaluation device includes: a communication module and a processing module; the communication module is used to obtain sampling data of the target cell within a sampling period; the processing module is used to determine the number of available airspace layers of the target cell within the sampling period based on the sampling data; the processing module is also used to determine the wireless resource utilization of the target cell within the sampling period based on the sampling data and the number of available airspace layers of the target cell within the sampling period; wherein the wireless resource utilization of the target cell is used to evaluate the wireless resource load of the target cell.

In combination with the second aspect, in certain embodiments of the second aspect, a processing module is used to determine the number of available spatial layers of the target cell within the sampling period according to the sampling data, including: a processing module is used to determine the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T according to the sampling data; determine the number of available spatial layers of the target cell within the sampling period according to the average scheduling layers of the service channel of the target cell corresponding to the sampling time j and the first calculation rule, and the first calculation rule satisfies the following relationship: LM(T) = MAX _j (L _avg,j ); wherein LM(T) represents the number of available spatial layers of the target cell within the sampling period T; L _avg,j represents the average scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T; MAX _j (L _avg,j ) represents taking the L _avg,j with the largest value from the L _avg,j corresponding to each sampling time j.

In combination with the second aspect, in certain embodiments of the second aspect, the sampling data includes: M1 _i,j (T), L _i,j (T) and PRB _j , M1 _i,j (T) represents the number of physical resource blocks PRBs occupied by the terminal device i accessing the target cell corresponding to the sampling time j within the sampling period T; L _i,j (T) represents the number of spatial layers occupied by the PRBs scheduled by the terminal device i corresponding to the sampling time j within the sampling period T; PRB _j represents the number of PRBs occupied by the service channel of the target cell corresponding to the sampling time j within the sampling period T; a processing module is used to determine the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T according to the sampling data, including: a processing module is used to determine the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T according to the sampling data and the second calculation rule, and the second calculation rule satisfies the following relationship: Wherein, L _avg,j represents the average scheduling layer number of the service channel of the cell corresponding to the sampling time j within the sampling period T, and ∑ _i represents the sum of all i.

In combination with the second aspect, in certain embodiments of the second aspect, the sampling data includes: M1 _i,j (T), L _i,j (T), N(T) and P(T), M1 _i,j (T) represents the number of physical resource blocks PRBs occupied by the terminal device i accessing the target cell corresponding to the sampling time j within the sampling period T; L _i,j (T) represents the number of spatial layers occupied by the PRBs scheduled by the terminal device i corresponding to the sampling time j within the sampling period T; N(T) represents the number of sampling moments within the sampling period T; P(T) represents the number of available PRBs for each layer of the service channel of the target cell at each sampling moment within the sampling period T; a processing module is used to determine the wireless resource utilization of the target cell within the sampling period according to the sampling data and the number of available spatial layers of the target cell within the sampling period, including: a processing module is used to determine the wireless resource utilization of the target cell within the sampling period according to the sampling data and the number of available spatial layers of the target cell within the sampling period and a third calculation rule, and the third calculation rule satisfies the following relationship: Wherein, _ME (T) represents the wireless resource utilization rate of the target cell within the sampling period T, represents the sum of all i; represents the sum over all j.

In combination with the second aspect, in certain embodiments of the second aspect, the wireless resource utilization of the target cell is the uplink wireless resource utilization of the target cell or the downlink wireless resource utilization of the target cell; when the wireless resource utilization of the target cell is the uplink wireless resource utilization of the target cell, the service channel is the physical uplink shared channel PUSCH channel; when the wireless resource utilization of the target cell is the downlink wireless resource utilization of the target cell, the service channel is the physical downlink shared channel PDSCH channel.

In a third aspect, a wireless resource load assessment device is provided, comprising: at least one processor; the processor is used to execute a computer program or instruction so that the wireless resource load assessment device performs the method of the first aspect above.

In conjunction with the third aspect, in certain implementations of the third aspect, the wireless resource load evaluation device further includes a memory, which is used to store necessary program instructions and data. The memory may be coupled to the processor, or may be independent of the processor.

In some possible designs, the wireless resource load evaluation device may be a chip or a chip system. When the wireless resource load evaluation device is a chip system, it may be composed of a chip, or may include a chip and other discrete devices.

In a fourth aspect, a computer-readable storage medium is provided, wherein computer instructions are stored in the computer-readable storage medium, and when the computer-readable storage medium is executed, the computer can execute the method of the first aspect.

In a fifth aspect, a computer program product comprising instructions is provided, which, when executed on a computer, enables the computer to execute the method of the first aspect.

Among them, the technical effects brought about by any design method in the second to fifth aspects can refer to the technical effects brought about by different design methods in the above-mentioned first aspect, and will not be repeated here.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic diagram of an application scenario of a wireless resource load evaluation method provided in an embodiment of the present application;

FIG2 is a schematic diagram of a flow chart of a method for evaluating a wireless resource load according to an embodiment of the present application;

FIG3 is a schematic diagram of resource occupancy of a PDSCH channel of a cell A corresponding to a first sampling time provided in an embodiment of the present application;

FIG4 is a schematic diagram of resource occupancy of a PDSCH channel of a cell A corresponding to a second sampling time provided in an embodiment of the present application;

FIG5 is a schematic diagram of resource occupancy of a PDSCH channel of a cell A corresponding to a third sampling time provided in an embodiment of the present application;

FIG6 is a schematic diagram of the structure of a wireless resource load evaluation device provided by the present application;

FIG. 7 is a schematic diagram of the structure of another wireless resource load evaluation device provided in the present application.

DETAILED DESCRIPTION

In order to facilitate understanding of the technical solutions of the embodiments of the present application, a brief introduction to the relevant technologies or terms of the present application is first given as follows.

1. MIMO:

As a key technology of 5G communication, massive MIMO has been widely used in wireless networks. In MIMO scenarios, in addition to the time domain and frequency domain dimensions, wireless resources can also be divided into different spatial layers, or spatial layers, from the spatial domain dimension.

Based on the number of users scheduled on the same time-frequency resources, MIMO technology can be divided into single-user MIMO (SU-MIMO) and multi-user MIMO (MU-MIMO).

SU-MIMO, or "Single User Multiple Input Multiple Output", means that multiple spatial layers of the same time-frequency resources are occupied by the same terminal device.

MU-MIMO, which stands for "Multi-User Multiple Input Multiple Output", adds a multi-user simultaneous communication mechanism based on SU-MIMO. Multiple terminal devices can share the same time-frequency resources through spatial division. Network equipment can use the same time-frequency resources with multiple terminal devices for uplink and downlink data transmission at the same time, thereby obtaining additional multi-user diversity gain and improving wireless resource utilization.

2. Radio resource load assessment method in 5G system:

At present, the wireless resource load is usually evaluated by calculating the utilization of the physical resource block (PRB) resources on the wireless side. Considering that PRB can be spatially divided in 5G, the wireless side PRB resource utilization defined in the 3rd Generation Partnership Project (3GPP) protocol 38.314 adds the evaluation of PRB spatial resources. For the wireless resource utilization of the target cell, the calculation formula is as follows:

Among them, M(T) represents the wireless resource utilization rate of the target cell within the sampling period T (it can also be called the wireless resource utilization rate of the service channel of the target cell within the sampling period); M1 _i,j (T) represents the number of PRBs occupied by terminal device i corresponding to sampling time j within the sampling period T (terminal device i is a terminal device accessing the target cell); _Lij (T) represents the number of spatial layers occupied by PRBs occupied by terminal device i corresponding to sampling time j within the sampling period T (or the number of spatial layers of PRBs scheduled by terminal device i corresponding to sampling time j); Alpha represents the spatial division factor; N(T) represents the number of sampling moments within the sampling period T; P(T) represents the number of available PRBs for each layer (spatial layer) of the service channel of the target cell at each sampling moment within the sampling period T. At present, P(T) is a pre-configured constant related to the frequency domain bandwidth. For example, P(T) can be configured as 273.

To avoid ambiguity, the meanings of some operation symbols in formula (1) are explained below: For all, for example represents all i; ∑ represents the sum, for example represents the sum of all i; Indicates rounding down, for example I will explain this uniformly here and will not repeat it in the future.

According to the meaning of the above parameters, it can be understood that in formula (1), It represents the multiplication of the number of PRBs actually occupied by all terminal devices accessing the target cell during the sampling period and the number of layers of the actually scheduled PRBs. In other words, it represents the wireless resources jointly occupied by the cell in the three dimensions of time, frequency and space during the sampling period. N(T)*P(T) represents the number of available PRBs for each layer of the service channel of the target cell during the sampling period. Therefore, in order to calculate the wireless resource utilization rate of the cell during the sampling period T by formula (1), the spatial division factor Alpha should represent the number of available layers in the spatial domain of the cell, so that N(T)*P(T)*Alpha can be used to represent the available wireless resources jointly occupied by the cell in the three dimensions of time, frequency and space during the sampling period.

The current protocol specifies Alpha as a configuration constant with a value range of 1-100, and specifies that the value of Alpha should make the value of PRB utilization within a reasonable range (ie, the value of M(T) is not greater than 1).

However, in actual applications, factors such as the different geographical environments of each cell, different user location distributions, different types of services carried and different traffic volumes will result in different numbers of spatial layers that can be scheduled by the cell. In other words, the number of available layers in the cell's airspace will change over time and space. Therefore, if the actual conditions of the cell are ignored and the Alpha of each cell is unified as a fixed constant, the PRB utilization data will be abnormal and will not be able to truly reflect the actual spatial capacity of different cells. For the same cell, it will also be impossible to reflect the changes in the actual spatial capacity of the cell in different scenarios.

For example, when Alpha is configured to a larger value, some cells use an unattainable limit capacity (spatial capacity) as the denominator, which will cause the PRB utilization calculated according to formula (1) to remain low, but the actual PRB utilization is already very high, resulting in an unreasonable assessment of the cell's wireless resource load, affecting user services and poor user experience. When Alpha is configured to a smaller value, some cells will have an unreasonable PRB utilization of over 100. Therefore, in order to meet the requirement that the value of Alpha should not exceed 100 for the PRB utilization, it is usually necessary to set the spatial factor Alpha to a larger value, resulting in abnormal data on the wireless resource utilization calculated by some cells, which cannot reflect the actual load of the cell's wireless resources. Therefore, how to propose a wireless resource load assessment method that can reflect the actual load of the cell's wireless resources in a MIMO scenario is a problem that needs to be solved urgently.

The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

In the description of this application, unless otherwise specified, "/" indicates that the objects associated with each other are in an "or" relationship, for example, A/B can represent A or B; "and/or" in this application is merely a description of the association relationship between associated objects, indicating that three relationships may exist, for example, A and/or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural.

In the description of this application, unless otherwise specified, "plurality" means two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, and c can be single or multiple.

In addition, in order to facilitate the clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, the words "first", "second" and the like are used to distinguish the same items or similar items with substantially the same functions and effects. Those skilled in the art will understand that the words "first", "second" and the like do not limit the quantity and execution order, and the words "first", "second" and the like do not necessarily limit the differences. At the same time, in the embodiments of the present application, the words "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or design solutions. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete manner for easy understanding.

It is understood that the "embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, the various embodiments in the entire specification do not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It is understood that in various embodiments of the present application, the size of the sequence number of each process does not mean the order of execution, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

It can be understood that in this application, "when", "if" and "if" all mean that corresponding processing will be carried out under certain objective circumstances, but do not limit the time, nor do they require judgment actions when implementing them, nor do they mean the existence of other limitations.

The term “simultaneously” in the present application may be understood as at the same time point, within a period of time, or within the same cycle.

It can be understood that some optional features in the embodiments of the present application may be implemented independently in certain scenarios without relying on other features, such as the solution on which they are currently based, to solve corresponding technical problems and achieve corresponding effects, or may be combined with other features according to needs in certain scenarios. Accordingly, the devices provided in the embodiments of the present application may also realize these features or functions accordingly, which will not be elaborated here.

In this application, unless otherwise specified, the same or similar parts between the various embodiments can refer to each other. In the various embodiments in this application, and the various implementation methods/implementation methods/implementation methods in each embodiment, if there is no special explanation and logical conflict, the terms and/or descriptions between different embodiments and the various implementation methods/implementation methods/implementation methods in each embodiment are consistent and can be referenced to each other. The technical features in different embodiments and the various implementation methods/implementation methods/implementation methods in each embodiment can be combined to form new embodiments, implementation methods, implementation methods, or implementation methods according to their inherent logical relationships. The following implementation methods of this application do not constitute a limitation on the scope of protection of this application.

The technical solution of the embodiments of the present application can be used in various communication systems, which may be a third generation partnership project (3GPP) communication system, such as a long term evolution (LTE) system, or a 5G mobile communication system, an NR system, a vehicle to everything (NR V2X) system, or a system with a hybrid LTE and 5G network, or a device-to-device (D2D) communication system, a machine-to-machine (M2M) communication system, an Internet of Things (IoT), and other next generation communication systems, or a non-3GPP communication system without limitation.

The technical solutions of the embodiments of the present application can be applied to various communication scenarios, for example, one or more of the following communication scenarios: enhanced mobile broadband (eMBB), ultra-reliable low latency communication (URLLC), machine type communication (MTC), massive machine type communications (mMTC), D2D, V2X, and IoT and other communication scenarios.

Among them, the above-mentioned communication systems and communication scenarios applicable to the present application are only examples, and the communication systems and communication scenarios applicable to the present application are not limited to these. They are uniformly described here and will not be repeated below.

As shown in Figure 1, it is a schematic diagram of an application scenario of the wireless resource load evaluation method provided in an embodiment of the present application. The application scenario includes a wireless resource load evaluation device 10 and multiple terminal devices 20. Among them, the multiple terminal devices 20 access the target cell, and there are terminal devices 20 among the multiple terminal devices 20 participating in MU-MIMO.

In this application scenario, after the wireless resource load evaluation device 10 obtains the sampled data of the target cell within the sampling period, the number of available airspace layers of the target cell within the sampling period can be determined based on the sampled data. Then, the wireless resource load evaluation device 10 determines the wireless resource utilization rate of the target cell within the sampling period based on the sampled data and the number of available airspace layers of the target cell within the sampling period; wherein the wireless resource utilization rate of the target cell is used to evaluate the wireless resource load of the target cell. The specific implementation and technical effects of this solution will be described in detail in the subsequent method embodiments and will not be repeated here.

Optionally, as shown in FIG1 , the application scenario may further include a collection device 30. The collection device 30 is used to collect sampled data of the target cell according to a sampling period. In an embodiment of the present application, the wireless resource load evaluation device 10 may be a device independent of the collection device 30. In this case, the wireless resource load evaluation device 10 may obtain sampled data from the collection device 30 (FIG. 1 shows this case as an example). Alternatively, the wireless resource load evaluation device 10 may be a module/chip in the collection device 30. Alternatively, the wireless resource load evaluation device 10 may be integrated with the collection device 30 in the same device. FIG1 merely exemplarily shows a case where the wireless resource load evaluation device 10 is a device independent of the collection device 30.

Optionally, the collection device 30 in the embodiment of the present application may be a wireless network element device.

Optionally, the terminal device 20 in the embodiment of the present application may be a device for realizing a wireless communication function, such as a terminal or a chip that can be used in a terminal. The terminal may also be referred to as user equipment (UE), a mobile station, a mobile terminal, etc. The terminal may be a mobile phone, a tablet computer, a computer with a wireless transceiver function, a virtual reality terminal device, an augmented reality terminal device, a wireless terminal in industrial control, a wireless terminal in unmanned driving, a wireless terminal in remote surgery, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, a wireless terminal in a smart home, etc. The embodiment of the present application does not limit the specific technology and specific device form adopted by the terminal device.

Optionally, the relevant functions of the wireless resource load evaluation device 10 in the embodiment of the present application can be implemented by one device, or by multiple devices together, or by one or more functional modules in one device, and the embodiment of the present application does not specifically limit this. It can be understood that the above functions can be network elements in hardware devices, or software functions running on dedicated hardware, or a combination of hardware and software, or virtualization functions instantiated on a platform (e.g., a cloud platform).

The following will be combined with Figure 1 to expand the description of the wireless resource load evaluation method provided in the embodiment of the present application. As shown in Figure 2, it is a flow chart of a wireless resource load evaluation method provided in the embodiment of the present application, and the wireless resource load evaluation method can be applied to the application scenario shown in Figure 1. Specifically, the wireless resource load evaluation method includes the following steps:

S201. A wireless resource load evaluation device obtains sampling data of a target cell within a sampling period.

S202. The wireless resource load evaluation device determines the number of available layers in the airspace of the target cell within a sampling period according to the sampling data.

S203. The wireless resource load evaluation device determines the wireless resource utilization rate of the target cell within the sampling period according to the sampling data and the number of available airspace layers of the target cell within the sampling period; wherein the wireless resource utilization rate of the target cell is used to evaluate the wireless resource load of the target cell.

For S201, in an embodiment of the present application, the wireless resource load evaluation device can use a fixed time period as a sampling period, obtain sampling data of the target cell corresponding to each sampling moment within the sampling period, and evaluate the wireless resource load of the cell based on the obtained sampling data.

Exemplarily, the sampling period in the embodiment of the present application may be 15 minutes. Of course, the embodiment of the present application does not specifically limit this.

Optionally, in the embodiment of the present application, the sampled data may be performance management (PM) data collected by the collection device for the target cell according to the sampling period and stored in the operation support system (OSS), and may also be referred to as the O-domain PM data obtained by the collection device for the target cell according to the sampling period. In other words, the wireless resource load evaluation device obtains the PM data of the target cell within the sampling period from the OSS as the sampled data.

Exemplarily, in an embodiment of the present application, the collection device may be an operations and maintenance center (OMC) network element.

For S202, in a possible implementation, the wireless resource load evaluation device may determine the number of available layers in the airspace of the target cell according to a preconfigured first calculation rule and the acquired sampling data.

In order to facilitate understanding of how to determine the number of available spatial layers of the target cell in the solution of the present application, the following describes the method of determining the number of available spatial layers of the target cell (or determining the number of the maximum number of scheduling layers in the frequency domain average time domain) by characterizing the number of available spatial layers of the target cell by the maximum number of scheduling layers in the frequency domain average time domain. It should be noted that in the embodiment of the present application, the maximum number of scheduling layers in the frequency domain average time domain is only an example name of a parameter used to characterize the number of available spatial layers of the target cell, and may be other names in the specific implementation, and the embodiment of the present application does not specifically limit this.

In the embodiment of the present application, the first calculation rule may satisfy the following formula (2):

LM(T)＝MAX _j (L _avg,j ) Formula (2)

In the above formula (2), LM(T) represents the average maximum number of scheduling layers in the frequency domain and time domain of the target cell within the sampling period T (the number of available layers in the spatial domain of the target cell); L _avg,j represents the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T. Among them, L _avg,j can be determined by the wireless resource load evaluation device according to the sampling data.

To avoid ambiguity, the meanings of some operation symbols in formula (2) are explained below: MAX means taking the maximum value. For example, MAX _j (L _avg,j ) means taking the L _avg,j with the largest value from the L _avg,j corresponding to each sampling time j. This is explained uniformly here and will not be repeated in the future.

It can be understood that the meaning of the above formula (2) is: determine the average number of service channel scheduling layers of the target cell corresponding to each sampling moment within the sampling period T, and take the average number of service channel scheduling layers of the target cell corresponding to all sampling moments, and the average number of service channel scheduling layers of the target cell with the largest value as the frequency domain average time domain maximum scheduling layer number of the target cell, so that the determined frequency domain average time domain maximum scheduling layer number represents the number of available spatial layers of the target cell.

In a possible implementation, the wireless resource load evaluation device may determine the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T according to the acquired sampling data and a preconfigured second calculation rule.

The second calculation rule satisfies the following formula (3):

In the above formula (3), L _avg,j represents the average number of scheduling layers of the service channel of the target cell corresponding to sampling time j within the sampling period T; M1 _i,j (T) represents the number of PRBs occupied by terminal device i (terminal device i is a terminal device accessing the target cell) corresponding to sampling time j within the sampling period T; L _i,j (T) represents the number of spatial layers occupied by the PRBs scheduled by terminal device i corresponding to sampling time j within the sampling period T (or the number of empty layers of the PRBs scheduled by terminal device i corresponding to sampling time j); PRB _j represents the number of PRBs occupied by the service channel of the target cell corresponding to sampling time j within the sampling period T. Among them, PRB _j can also be understood as the number of PRBs actually occupied in the frequency domain by all terminal devices accessing the target cell corresponding to sampling time j within the sampling period T.

Among the parameters in the above formula (3), M1 _i,j (T), L _i,j (T) and PRB _j can be determined by the acquired sampling data. In other words, the target cell can be sampled within the sampling period T to determine the values of M1 _i,j (T), L _i,j (T) and PRB _j .

The operation symbols in the above formula (4) can refer to the introduction of formula (1) above, which will not be repeated here. It should be noted that ∑ _i in the above formula (3) can also be replaced by Both represent the sum over all i.

As can be seen from the above introduction, in the embodiment of the present application, the frequency domain average time domain maximum scheduling layer number of the target cell within the sampling period is the maximum value of the average scheduling layer number of the service channel of the target cell within the sampling period. It can be understood that the maximum value can represent the maximum number of spatial layers that the target cell can schedule within the sampling period. Therefore, the frequency domain average time domain maximum scheduling layer number of the target cell can be used to characterize the actual number of available airspace (space) layers of the target cell within the sampling period, or the actual spatial capacity of the target cell. In addition, because the frequency domain average time domain maximum scheduling layer number of the target cell is determined based on the sampling data corresponding to the sampling period and the predefined calculation rules, if the situation of the target cell changes, the frequency domain average time domain maximum scheduling layer number of the target cell will also automatically change with the change of the cell space capacity. Therefore, in this scheme, the frequency domain average time domain maximum scheduling layer number of the target cell can represent the actual number of available airspace layers of the target cell in real time, so that it can be used as a dynamic space division factor to calculate the wireless resource utilization of the target cell, without the need to frequently configure the Alpha value like the existing scheme. On the other hand, using the frequency domain average maximum time domain scheduling layer number as the space division factor to determine the wireless resource utilization of the cell can avoid the situation where the wireless resource utilization exceeds 100. The specific reasons are introduced below.

For S203, in a possible implementation, after the wireless resource load evaluation device determines the maximum number of scheduling layers in the frequency domain average time domain of the target cell in the sampling period, the wireless resource utilization rate of the target cell in the sampling period can be determined according to the preconfigured third calculation rule, the sampling data, and the maximum number of scheduling layers in the frequency domain average time domain of the target cell in the sampling period. The wireless resource load evaluation device can evaluate the wireless resource load of the target cell according to the wireless resource utilization rate of the target cell.

In the embodiment of the present application, the third calculation rule may satisfy the following formula (4):

In the above formula (4), M(T) represents the wireless resource utilization rate of the target cell (or the service channel of the cell) within the sampling period T; M1 _i,j (T) represents the number of PRBs occupied by the terminal device i corresponding to the sampling time j within the sampling period T (the terminal device i is the terminal device accessing the target cell); L _ij (T) represents the number of spatial layers occupied by the PRBs scheduled by the terminal device i corresponding to the sampling time j within the sampling period T (or the number of empty layers of the PRBs scheduled by the terminal device i at the sampling time j); N(T) represents the number of sampling times within the sampling period T; P(T) represents the number of available PRBs of each layer (spatial layer) of the service channel of the target cell at each sampling time within the sampling period T; LM(T) represents the frequency domain average maximum number of time domain scheduling layers of the cell within the sampling period T.

In the parameters of the above formula (4), M1 _i,j (T), L _i,j (T), and N(T) can be determined by the acquired sampled data. In other words, the target cell can be sampled within the sampling period T to determine the values of M1 _i,j (T), L _i,j (T), and N(T). P(T) is a preconfigured constant related to the frequency domain bandwidth. Exemplarily, P(T) is configured to be 273.

The operation symbols in the above formula (4) can refer to the introduction of formula (1) above, and will not be repeated here.

Referring to the above introduction, we can know It can be understood as the wireless resources occupied by the cell in the three dimensions of time domain, frequency domain and space domain within the sampling period T. N(T)*P(T)*LM(T) can be understood as the actual available wireless resources of the cell in the three dimensions of time domain, frequency domain and space domain within the sampling period T. Therefore, the wireless resource utilization rate of the target cell within the sampling period can be determined by the above formula (4), thereby evaluating the wireless resource load of the target cell.

Moreover, in the embodiment of the present application, the maximum number of scheduling layers LM(T) averaged in the frequency domain is used as the space division factor, which can avoid the situation where the calculated wireless resource utilization exceeds 100.

The specific derivation process is as follows:

According to LM(T)=MAX _j (L _avg,j ), we can get the following equation (4):

according to We can get:

observe According to the meanings of PRB _j , j, N(T) and P(T) introduced above, we can know that therefore Then get

Because in the above formula (4) The above derivation process leads to Therefore, it can be deduced that M(T) calculated according to the above formula (4) is ≤1.

Therefore, by using the frequency domain average maximum scheduling layer number in the time domain as the space division factor to calculate the wireless resource utilization of the target cell, it is also possible to avoid the unreasonable situation that the calculated wireless resource utilization of the target cell exceeds 100.

The wireless resource load evaluation method provided in the present application is based on the number of available airspace layers of the target cell within the sampling period when determining the wireless resource utilization rate of the target cell. Because the number of available airspace layers of the target cell within the sampling period is determined based on the sampling data within the sampling period, if the cell situation changes, the number of available airspace layers of the target cell within the sampling period will also automatically change with the change of the cell's spatial capacity. In other words, in this solution, the number of available airspace layers of the target cell determined based on the sampling data can represent the actual spatial capacity of the target cell in real time. Furthermore, the wireless resource utilization rate of the cell determined based on the number of available airspace layers of the target cell within the sampling period can reflect the actual load of the cell's wireless resources in different cells or different user distribution scenarios in real time. In summary, compared with the existing solution in which the space division factor Alpha used to characterize the number of available layers in the cell airspace is configured as a fixed constant, this solution, on the one hand, solves the problem that the existing solution is prone to unreasonable setting of the space division factor Alpha value, which leads to the inability of wireless resource utilization to reflect the actual resource occupancy, and can more accurately and reasonably reflect the wireless resource load of the cell in the MIMO scenario. On the other hand, it solves the problem that the existing solution needs to frequently adjust the space division factor Alpha with changes in time, scenarios, and user distribution, and can reduce artificial errors introduced by external interference.

The solution provided in the embodiment of the present application can be applied to calculate the uplink wireless resource utilization rate of the target cell or the downlink wireless resource utilization rate of the target cell, and can also be simultaneously applied to calculate the uplink wireless resource utilization rate of the target cell and the downlink wireless resource utilization rate of the target cell.

It should be noted that, in the embodiment of the present application, among the parameters related to the service channel included in the second calculation rule and the third calculation rule, for the case of calculating the uplink wireless resource utilization of the target cell, the service channel refers to the physical uplink shared channel (PUSCH) channel. For the case of calculating the downlink wireless resource utilization of the cell, the service channel refers to the physical downlink shared channel (PDSCH) channel. For example, for the case of calculating the uplink wireless resource utilization of the target cell, PRB _j represents the number of PRBs occupied by the PUSCH channel of the target cell corresponding to the sampling time j within the sampling period T.

To facilitate understanding, the wireless resource load evaluation method provided in an embodiment of the present application is introduced below with a specific example.

Assuming that the target cell is cell A, the sampling period T includes 3 sampling moments. After the wireless resource load evaluation device obtains the sampling data of cell A within the sampling period T, the resource occupancy of the PDSCH channel of cell A corresponding to each sampling moment can be determined as follows:

At the first sampling moment, there are five terminal devices: UE1, UE2, UE3, UE4 and UE5 accessing cell A. The resource occupancy of the PDSCH channel of cell A is shown in Figure 3. UE1 occupies 10 PRBs in the frequency domain and spatially schedules PRB1 layer. UE2 occupies 30 PRBs in the frequency domain and spatially schedules PRB2 layer. UE3 occupies 30 PRBs in the frequency domain and spatially schedules PRB3 layer. UE4 occupies 100 PRBs in the frequency domain and spatially schedules PRB3 layer. UE5 occupies 100 PRBs in the frequency domain and spatially schedules PRB2 layer. Among them, UE1, UE2 and UE3 are all SU-MIMO, and they schedule different PRBs belonging to themselves in the frequency domain. As shown in Figure 3, the PRB spatial layers scheduled by UE1, UE2 and UE3 are separated in the frequency domain and belong to different PRBs. UE4 and UE5 participate in MU-MIMO and jointly schedule 100 PRBs in the frequency domain. As shown in Figure 3, the PRBs scheduled by UE4 and UE5 overlap in the frequency domain and belong to the same PRB. Therefore, the number of PRBs actually occupied by all UEs in the frequency domain is: 10+30+30+100=170, that is, PRB _j corresponding to the first sampling time = 170.

At the second sampling time, there are four terminal devices: UE1, UE2, UE3 and UE4 accessing cell A. The resource occupancy of the PDSCH channel of cell A is shown in Figure 4. UE1 occupies 60 PRBs in the frequency domain and spatially schedules PRB1 layer. UE2 occupies 70 PRBs in the frequency domain and spatially schedules PRB3 layer. UE3 occupies 90 PRBs in the frequency domain and spatially schedules PRB4 layer. UE4 occupies 90 PRBs in the frequency domain and spatially schedules PRB2 layer. Among them, UE1 and UE2 are both SU-MIMO, and they schedule different PRBs belonging to themselves in the frequency domain. As shown in Figure 4, the PRB spatial layers scheduled by UE1 and UE2 are separated in the frequency domain and belong to different PRBs. UE3 and UE4 participate in MU-MIMO and jointly schedule 90 PRBs in the frequency domain. As shown in Figure 4, the PRBs scheduled by UE3 and UE4 overlap in the frequency domain and belong to the same PRB. Therefore, the number of PRBs actually occupied by all UEs in the frequency domain is: 60+70+90=220, that is, PRB _j corresponding to the second sampling time is 220.

At the third sampling time, there are five terminal devices: UE1, UE2, UE3, UE4 and UE5 accessing cell A. The resource occupancy of the PDSCH channel of cell A is shown in Figure 5. UE1 occupies 20 PRBs in the frequency domain and spatially schedules PRB1 layer. UE2 occupies 30 PRBs in the frequency domain and spatially schedules PRB2 layer. UE3 occupies 100 PRBs in the frequency domain and spatially schedules PRB2 layer. UE4 occupies 100 PRBs in the frequency domain and spatially schedules PRB2 layer. UE5 occupies 100 PRBs in the frequency domain and spatially schedules PRB4 layer. Among them, UE1 and UE2 are both SU-MIMO, and they schedule different PRBs belonging to themselves in the frequency domain. As shown in Figure 5, the PRB spatial layers scheduled by UE1 and UE2 are separated in the frequency domain and belong to different PRBs. UE3, UE4 and UE5 participate in MU-MIMO and jointly schedule 100 PRBs in the frequency domain. As shown in Figure 5, the PRBs scheduled by UE3, UE4 and UE5 overlap in the frequency domain and belong to the same PRB. Therefore, the number of PRBs actually occupied by all UEs in the frequency domain is: 20+30+100=150, that is, PRB _j corresponding to the third sampling time = 150.

After the wireless resource load evaluation device obtains the sampling data corresponding to each sampling time, it can determine the wireless resource utilization rate of cell A according to the sampling data, the first calculation rule and the second calculation rule. The specific process is as follows:

According to the above formula (3), the wireless resources occupied by cell A in the three dimensions of time domain, frequency domain and space domain corresponding to the first sampling time can be obtained as follows: 10×1+30×2+30×3+100×3+100×2=660. That is, ∑ _i M1 _i,j (T)*L _i,j (T) corresponding to the first sampling time is 660.

According to the above formula (3), the wireless resources occupied by cell A in the three dimensions of time, frequency and space corresponding to the second sampling time are obtained as follows: 60×1+70×3+90×4+90×2=810. That is, ∑ _i M1 _i,j (T)*L _i,j (T)=810 corresponding to the second sampling time.

According to the above formula (3), the wireless resources occupied by cell A in the three dimensions of time domain, frequency domain and space domain corresponding to the third sampling time can be obtained as follows = 20×1+30×2+100×2+100×2+100×4=880. That is, ∑ _i M1 _i,j (T)*L _i,j (T) corresponding to the third sampling time is 880.

Therefore, according to the above formula (4), it can be obtained that within the sampling period T, the wireless resources occupied by cell A in the three dimensions of time domain, frequency domain and space domain = 660 + 810 + 880 = 2350. That is, the sampling period T corresponds to

According to the above formula (3), the average scheduling layer number of the service channel of cell A corresponding to the first sampling time is obtained as follows: 660/170=3.88, that is, _Lavg,j corresponding to the first sampling time is 3.88.

According to the above formula (3), the average scheduling layer number of the service channel of cell A corresponding to the second sampling time is obtained as follows: 810/220 = 3.68, that is, _Lavg,j corresponding to the second sampling time is 3.68.

According to the above formula (3), the average scheduling layer number of the service channel of cell A corresponding to the third sampling time is obtained as follows: 880/150=5.87, that is, _Lavg,j corresponding to the third sampling time is 5.87.

After obtaining the average scheduling layer number of the service channel of cell A corresponding to each sampling time, the wireless resource load evaluation device determines the frequency domain average time domain maximum scheduling layer number of cell A = MAX(3.88, 3.68, 5.87) = 5.87 according to the above formula (2). That is, LM(T) = 5.87.

Assuming that the configured P(T)=273, according to the above formula (4), it can be obtained that within the sampling period T, the available wireless resources of cell A in the three dimensions of time domain, frequency domain and space domain are 273×5.87×3=4807.53, that is, N(T)*P(T)*LM(T)=4807.53.

The wireless resource load assessment device obtains the wireless resources occupied by cell A in the three dimensions of time domain, frequency domain and space domain within the sampling period T, as well as the available wireless resources of cell A in the three dimensions of time domain, frequency domain and space domain within the sampling period T. According to the above formula (4), it can be obtained that the wireless resource utilization rate of cell A within the sampling period T = 2350/4807.53 × 100% = 48.88%.

The above mainly introduces the scheme provided by the embodiment of the present application from the perspective of the wireless resource load assessment device executing the wireless resource load assessment method. In order to realize the above functions, the wireless resource load assessment device includes a hardware structure and/or software module corresponding to each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed in this article, the embodiments of the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

The embodiment of the present application can divide the functional modules of the wireless resource load assessment device according to the above method example. For example, each functional module can be divided corresponding to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of software functional modules. Optionally, the division of modules in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, the "module" here may refer to a specific application-specific integrated circuit (ASIC), a circuit, a processor and a memory that executes one or more software or firmware programs, an integrated logic circuit, and/or other devices that can provide the above functions.

In the case of adopting functional module division, FIG6 shows a schematic diagram of the structure of a wireless resource load evaluation device 60. As shown in FIG6, the wireless resource load evaluation device 60 includes a communication module 601 and a processing module 602.

In some embodiments, the wireless resource load evaluation device 60 may further include a storage module (not shown in FIG. 6 ) for storing program instructions and data.

Among them, the communication module 601 is used to obtain the sampling data of the target cell within the sampling period; the processing module 602 is used to determine the number of available airspace layers of the target cell within the sampling period based on the sampling data; the processing module 602 is also used to determine the wireless resource utilization rate of the target cell within the sampling period based on the sampling data and the number of available airspace layers of the target cell within the sampling period; wherein the wireless resource utilization rate of the target cell is used to evaluate the wireless resource load of the target cell.

As a possible implementation, the processing module 602 is used to determine the number of available airspace layers of the target cell within the sampling period according to the sampling data, including: a processing module, used to determine the average number of scheduled layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T according to the sampling data; determine the number of available airspace layers of the target cell within the sampling period according to the average number of scheduled layers of the service channel of the target cell corresponding to the sampling time j and a first calculation rule, wherein the first calculation rule satisfies the following relationship: LM(T)=MAX _j (L _avg,j ); wherein LM(T) represents the number of available airspace layers of the target cell within the sampling period T; L _avg,j represents the average number of scheduled layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T;

MAX _j (L _avg,j ) means taking the L _avg,j with the largest value from the L _avg, j corresponding to each sampling time j.

As a possible implementation, the sampling data includes: M1 _i,j (T), L _i,j (T) and PRB _j , M1 _i,j (T) represents the number of physical resource blocks PRBs occupied by the terminal device i accessing the target cell corresponding to the sampling time j within the sampling period T; L _i,j (T) represents the number of spatial layers occupied by the PRBs scheduled by the terminal device i corresponding to the sampling time j within the sampling period T; PRB _j represents the number of PRBs occupied by the service channel of the target cell corresponding to the sampling time j within the sampling period T; the processing module 602 is used to determine the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T according to the sampling data, including: the processing module 602 is used to determine the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T according to the sampling data and the second calculation rule, and the second calculation rule satisfies the following relationship: Wherein, L _avg,j represents the average scheduling layer number of the service channel of the cell corresponding to the sampling time j within the sampling period T, and ∑ _i represents the sum of all i.

As a possible implementation, the sampling data includes: M1 _i,j (T), L _i,j (T), N(T) and P(T), M1 _i,j (T) represents the number of physical resource blocks PRBs occupied by the terminal device i accessing the target cell corresponding to the sampling time j within the sampling period T; L _i,j (T) represents the number of spatial layers occupied by the PRBs scheduled by the terminal device i corresponding to the sampling time j within the sampling period T; N(T) represents the number of sampling moments within the sampling period T; P(T) represents the number of available PRBs for each layer of the service channel of the target cell at each sampling moment within the sampling period T; a processing module 602 is used to determine the wireless resource utilization of the target cell within the sampling period according to the sampling data and the number of available spatial layers of the target cell within the sampling period, including: a processing module 602 is used to determine the wireless resource utilization of the target cell within the sampling period according to the sampling data and the number of available spatial layers of the target cell within the sampling period and a third calculation rule, and the third calculation rule satisfies the following relationship: Wherein, _ME (T) represents the wireless resource utilization rate of the target cell within the sampling period T, represents the sum of all i; represents the sum over all j.

As a possible implementation, the wireless resource utilization rate of the target cell is the uplink wireless resource utilization rate of the target cell or the downlink wireless resource utilization rate of the target cell; when the wireless resource utilization rate of the target cell is the uplink wireless resource utilization rate of the target cell, the service channel is the physical uplink shared channel PUSCH channel; when the wireless resource utilization rate of the target cell is the downlink wireless resource utilization rate of the target cell, the service channel is the physical downlink shared channel PDSCH channel.

All relevant contents of each step involved in the above method embodiment can be referred to the functional description of the corresponding functional module, and will not be repeated here.

In the case of implementing the functions of the above functional modules in the form of hardware, FIG7 shows a schematic diagram of the structure of another wireless resource load evaluation device 70. As shown in FIG7, the wireless resource load evaluation device includes a processor 701, a memory 702 and a bus 703. The processor 701 and the memory 702 can be connected via a bus 703.

The processor 701 is the control center of the wireless resource load evaluation device 70, which can be a processor or a general term for multiple processing elements. For example, the processor 701 can be a general-purpose central processing unit (CPU) or other general-purpose processors. The general-purpose processor can be a microprocessor or any conventional processor.

As an embodiment, the processor 701 may include one or more CPUs, such as CPU 0 and CPU 1 shown in FIG. 7 .

The memory 702 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

As a possible implementation, the memory 702 may exist independently of the processor 701, and the memory 702 may be connected to the processor 701 via a bus 703 to store instructions or program codes. When the processor 701 calls and executes the instructions or program codes stored in the memory 702, the one-time identity identification method provided in the embodiment of the present invention can be implemented.

In another possible implementation, the memory 702 may also be integrated with the processor 701 .

The bus 703 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, FIG7 only uses one thick line, but does not mean that there is only one bus or one type of bus.

It should be noted that the structure shown in Fig. 7 does not constitute a limitation on the wireless resource load evaluation device 70. In addition to the components shown in Fig. 7, the wireless resource load evaluation device 70 may include more or fewer components than shown, or combine certain components, or arrange the components differently.

As an example, in combination with FIG. 6 , the functions implemented by the communication module 601 and the processing module 602 in the wireless resource load evaluation device 60 are the same as the functions of the processor 701 in FIG. 7 .

Optionally, as shown in FIG. 7 , the wireless resource load assessment device 70 provided in the embodiment of the present application may further include a communication interface 704 .

The communication interface 704 is used to connect with other devices through a communication network. The communication network may be Ethernet, wireless access network, wireless local area network (WLAN), etc. The communication interface 704 may include a receiving unit for receiving data and a sending unit for sending data.

In a possible implementation, in the wireless resource load evaluation device 70 provided in the embodiment of the present application, the communication interface 704 may also be integrated in the processor 701, and the embodiment of the present application does not specifically limit this.

As a possible product form, the wireless resource load assessment device of the embodiment of the present application can also be implemented using the following: one or more field programmable gate arrays (FPGA), programmable logic devices (PLD), controllers, state machines, gate logic, discrete hardware components, any other suitable circuits, or any combination of circuits capable of performing the various functions described throughout the present application.

Through the description of the above implementation methods, those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above functional units is used as an example. In practical applications, the above functions can be assigned to different functional units as needed, that is, the internal structure of the device can be divided into different functional units to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

An embodiment of the present invention further provides a computer-readable storage medium, in which instructions are stored. When a computer executes the instructions, the computer executes each step in the method flow shown in the above method embodiment.

An embodiment of the present invention provides a computer program product including instructions. When the instructions are executed on a computer, the computer is enabled to execute each step in the method flow shown in the above method embodiment.

Among them, the computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, and a hard disk. Random Access Memory (RAM), Read-Only Memory (ROM), Erasable Programmable Read Only Memory (EPROM), registers, hard disks, optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any other form of computer-readable storage medium in a suitable combination of the above, or numerical values in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in a specific-purpose ASIC. In the embodiments of the present application, a computer-readable storage medium may be any tangible medium that contains or stores a program, which may be used by or in conjunction with an instruction execution system, apparatus, or device.

Since the wireless resource load assessment device, computer-readable storage medium, and computer program product provided in this embodiment can be applied to the wireless resource load assessment method provided in this embodiment, the technical effects that can be obtained can also refer to the above-mentioned method embodiments, and the embodiments of the present invention will not be repeated here.

Although the present application is described herein in conjunction with various embodiments, in the process of implementing the claimed application, those skilled in the art may understand and implement other variations of the disclosed embodiments by viewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "one" or "an" does not exclude multiple situations. A single processor or other unit may implement several functions listed in a claim. Certain measures are recorded in different dependent claims, but this does not mean that these measures cannot be combined to produce good results.

Although the present application has been described in conjunction with specific features and embodiments thereof, it is obvious that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and the drawings are merely exemplary illustrations of the present application as defined by the appended claims, and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art may make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims (10)

1. A method for evaluating a wireless resource load, characterized in that the method comprises: Obtain sampling data of the target cell within the sampling period; Determine, according to the sampling data, an average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T; The number of available spatial layers of the target cell within the sampling period is determined according to the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j and a first calculation rule, wherein the first calculation rule satisfies the following relationship: LM(T) = MAX _j (l _{avg, j} ); Wherein, LM(T) represents the number of available layers in the spatial domain of the target cell within the sampling period T; L _avg,j represents the average number of scheduled layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T; MAX _j (l _avg,j ) represents taking the l _avg,j with the largest value from the l _avg, j corresponding to each sampling time j; The wireless resource utilization rate of the target cell within the sampling period is determined according to the sampling data and the number of available airspace layers of the target cell within the sampling period; wherein the wireless resource utilization rate of the target cell is used to evaluate the wireless resource load of the target cell. 2. The method according to claim 1, characterized in that the sampling data includes: M1 _i,j (T), Li _,j (T) and PRB _j , M1 _i,j (T) represents the number of physical resource blocks (PRBs) occupied by the terminal device i accessing the target cell corresponding to the sampling time j within the sampling period T; Li _,j (T) represents the number of spatial layers occupied by the PRBs scheduled by the terminal device i corresponding to the sampling time j within the sampling period T; PRB _j represents the number of PRBs occupied by the service channel of the target cell corresponding to the sampling time j within the sampling period T; the determining, according to the sampling data, the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T comprises: According to the sampling data and the second calculation rule, the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T is determined, and the second calculation rule satisfies the following relationship: Wherein, _Lavg,j represents the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T, _{and ∑i} represents the sum of all i. 3. The method according to claim 1 or 2, characterized in that the sampling data includes: M1 _{i, j} (T), Li _{, j} (T), N (T) and P (T), M1 _{i, j} (T) represents the number of physical resource blocks (PRBs) occupied by the terminal device i accessing the target cell corresponding to the sampling time j within the sampling period T; Li _{, j} (T) represents the number of spatial layers occupied by the PRBs scheduled by the terminal device i corresponding to the sampling time j within the sampling period T; N (T) represents the number of sampling moments within the sampling period T; P (T) represents the number of available PRBs for each layer of the service channel of the target cell at each sampling moment within the sampling period T; the method of determining the wireless resource utilization rate of the target cell within the sampling period according to the sampling data and the number of available layers in the spatial domain of the target cell within the sampling period comprises: Determine the radio resource utilization rate of the target cell within the sampling period according to the sampling data, the number of available airspace layers of the target cell within the sampling period, and a third calculation rule, wherein the third calculation rule satisfies the following relationship: Wherein, _ME (T) represents the radio resource utilization rate of the target cell within the sampling period T, represents the sum of all i; represents the sum over all j. 4. The method according to claim 1 or 2, characterized in that the wireless resource utilization rate of the target cell is the uplink wireless resource utilization rate of the target cell or the downlink wireless resource utilization rate of the target cell; In a case where the radio resource utilization rate of the target cell is the uplink radio resource utilization rate of the target cell, the service channel is a physical uplink shared channel PUSCH channel; When the radio resource utilization rate of the target cell is the downlink radio resource utilization rate of the target cell, the service channel is a physical downlink shared channel PDSCH channel. 5. A wireless resource load assessment device, characterized in that the wireless resource load assessment device comprises: a communication module and a processing module; The communication module is used to obtain sampling data of the target cell within a sampling period; The processing module is used to determine, according to the sampled data, an average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T, and determine the number of available spatial layers of the target cell within the sampling period according to the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j and a first calculation rule, wherein the first calculation rule satisfies the following relationship: LM(T)＝ _MAXj ( _Lavg,j ); Wherein, LM(T) represents the number of available layers in the spatial domain of the target cell within the sampling period T; _Lavg,j represents the average number of scheduled layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T; _MAXj ( _Lavg,j ) represents taking the largest value Lavg,j from the Lavg _{, j} corresponding to each sampling time j; The processing module is also used to determine the wireless resource utilization of the target cell within the sampling period based on the sampling data and the number of available airspace layers of the target cell within the sampling period; wherein the wireless resource utilization of the target cell is used to evaluate the wireless resource load of the target cell. 6. The wireless resource load assessment device according to claim 5 is characterized in that the sampling data includes: M1 _i,j (T), Li _,j (T) and PRB _j , M1 _i,j (T) represents the number of physical resource blocks (PRBs) occupied by the terminal device i accessing the target cell corresponding to the sampling time j within the sampling period T; Li _,j (T) represents the number of spatial layers occupied by the PRBs scheduled by the terminal device i corresponding to the sampling time j within the sampling period T; PRB _j represents the number of PRBs occupied by the service channel of the target cell corresponding to the sampling time j within the sampling period T; the processing module is used to determine the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T according to the sampling data, including: The processing module is used to determine the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T according to the sampling data and the second calculation rule, and the second calculation rule satisfies the following relationship: Wherein, L _avg,j represents the average number of scheduling layers of the service channel of the target cell corresponding to the sampling time j within the sampling period T, and ∑ _i represents the sum of all i. 7. The wireless resource load evaluation device according to claim 5 or 6 is characterized in that the sampling data includes: M1 _{i, j} (T), Li _{, j} (T), N (T) and P (T), M1 _{i, j} (T) represents the number of physical resource blocks (PRBs) occupied by the terminal device i accessing the target cell corresponding to the sampling time j within the sampling period T; Li _{, j} (T) represents the number of spatial layers occupied by the PRBs scheduled by the terminal device i corresponding to the sampling time j within the sampling period T; N (T) represents the number of sampling moments within the sampling period T; P (T) represents the number of available PRBs for each layer of the service channel of the target cell at each sampling moment within the sampling period T; the processing module is used to determine the wireless resource utilization rate of the target cell within the sampling period according to the sampling data and the number of available layers in the spatial domain of the target cell within the sampling period, including: The processing module is used to determine the radio resource utilization rate of the target cell within the sampling period according to the sampling data, the number of available airspace layers of the target cell within the sampling period, and a third calculation rule, wherein the third calculation rule satisfies the following relationship: Wherein, _ME (T) represents the radio resource utilization rate of the target cell within the sampling period T, represents the sum of all i; represents the sum over all j. 8. The wireless resource load evaluation device according to claim 5 or 6, characterized in that the wireless resource utilization rate of the target cell is the uplink wireless resource utilization rate of the target cell or the downlink wireless resource utilization rate of the target cell; In a case where the radio resource utilization rate of the target cell is the uplink radio resource utilization rate of the target cell, the service channel is a physical uplink shared channel PUSCH channel; When the radio resource utilization rate of the target cell is the downlink radio resource utilization rate of the target cell, the service channel is a physical downlink shared channel PDSCH channel. 9. A wireless resource load evaluation device, characterized in that the wireless resource load evaluation device comprises: a processor; The processor is used to read the computer execution instructions in the memory and execute the computer execution instructions so that the wireless resource load evaluation device performs the method as described in any one of claims 1-4. 10. A computer-readable storage medium, characterized in that a computer program or instruction is stored in the computer-readable storage medium, and when the computer program or instruction is executed by a wireless resource load evaluation device, the method according to any one of claims 1 to 4 is implemented.