Resource utilization rate statistical method, device and related equipment

Abstract

Embodiments of the present application provide a resource utilization rate statistical method, device and related equipment, wherein the method comprises: calculating the resource utilization rate by using a total number of physical resource blocks (PRBs) corrected by a layer number factor, wherein the layer number factor is determined according to PRB usage information at at least one sampling time, and the PRB usage information at the at least one sampling time at least comprises a multiple-input multiple-output (MIMO) layer number used by the PRBs during data transmission. The present application can improve the accuracy of resource utilization rate statistics in a spatial division multiplexing scenario.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method, apparatus and related equipment for calculating resource utilization. Background Technology

[0002] Statistics on Physical Resource Block (PRB) utilization are typically used to help operators and network providers understand the PRB utilization of each cell, providing a more intuitive understanding of cell workload and load conditions. For example, if PRB utilization data reveals that certain cells are consistently under high load, it may be necessary to consider expanding the capacity of these cells or adjusting network planning.

[0003] Currently, PRB utilization is typically described as the quotient of the number of PRBs used and the total number of PRBs. Spatial division multiplexing (SDM) technology, which can improve transmission speed, is now widely used. SDM refers to antenna signals for different data streams having identical carrier frequencies and completely overlapping spectral bandwidths. In other words, SDM allows the same frequency band to be reused in different spaces. Therefore, SDM multiplies the amount of data that can be transmitted with the same bandwidth, and thus multiplies spectral utilization. However, current resource utilization statistics do not consider the case of SDM, resulting in lower accuracy of resource utilization figures in SDM scenarios. Summary of the Invention

[0004] This application provides a resource utilization statistics method, apparatus, and related equipment to solve the problem of inaccurate resource utilization statistics in space division multiplexing scenarios.

[0005] To solve the above problems, this application is implemented as follows:

[0006] In a first aspect, embodiments of this application provide a resource utilization statistics method for network-side devices, the resource utilization statistics method comprising:

[0007] Resource utilization is calculated using the total number of Physical Resource Blocks (PRBs) corrected by a layer factor, wherein the layer factor is determined based on PRB usage information at at least one sampling time, and the PRB usage information at at least one sampling time includes the number of Multiple-Input Multiple-Output (MIMO) layers used by the PRBs during data transmission.

[0008] Optionally, at the at least one sampling time, the larger the number of MIMO layers used by the PRB during data transmission, the larger the layer number factor.

[0009] Optionally, the layer number factor is:

[0010] The maximum value of the elements in the first set, which includes at least one average number of MIMO layers, wherein the average number of MIMO layers is the average number of MIMO layers used by the PRB or all PRBs during data transmission in the corresponding first period;

[0011] or

[0012] The average value of the elements in the second set, which includes at least one maximum MIMO layer number, wherein the maximum MIMO layer number is the maximum number of MIMO layers used by the PRB or all PRBs during data transmission in the corresponding first period.

[0013] Optionally, the average number of MIMO layers is:

[0014]

[0015] or

[0016]

[0017] Where T1 is the first period, j is the sampling time within the first period, a is the user equipment (UE) sequence number, k is the MIMO layer category, and M kj (T1) represents the number of PRBs transmitted at the j-th sampling time within the first period, with the k-th type of MIMO layer, L kj (T1) represents the number of MIMO layers corresponding to the k-th type of MIMO layer at the j-th sampling time within the first period; M aj (T1) represents the number of PRBs allocated to the a-th UE at the j-th sampling time within the first period, L aj (T1) represents the number of MIMO layers used by the a-th UE at the j-th sampling time in the first period.

[0018] Optionally, the total number of PRBs corrected by the layer number factor is the product of the layer number factor and the total number of available PRBs.

[0019] Optionally, the total number of available PRBs is:

[0020] In the second period, the product of the number of sampling times and the number of PRBs available at one of the sampling times;

[0021] or

[0022] The sum of the number of PRBs available at all sampling times within the second period.

[0023] Optionally, the second cycle is the same as the first cycle.

[0024] Secondly, embodiments of this application provide a resource utilization rate statistics device, the resource utilization rate statistics device comprising:

[0025] The calculation module is used to calculate resource utilization using the total number of Physical Resource Blocks (PRBs) modified by a layer factor, wherein the layer factor is determined based on PRB usage information at at least one sampling time, and the PRB usage information at at least one sampling time includes at least the number of Multiple-Input Multiple-Output (MIMO) layers used by the PRBs during data transmission.

[0026] Optionally, at the at least one sampling time, the larger the number of MIMO layers used by the PRB during data transmission, the larger the layer number factor.

[0027] Optionally, the layer number factor is:

[0028] The maximum value of the elements in the first set, which includes at least one average number of MIMO layers, wherein the average number of MIMO layers is the average number of MIMO layers used by the PRB or all PRBs during data transmission in the corresponding first period;

[0029] or

[0030] The average value of the elements in the second set, which includes at least one maximum MIMO layer number, wherein the maximum MIMO layer number is the maximum number of MIMO layers used by the PRB or all PRBs during data transmission in the corresponding first period.

[0031] Optionally, the average number of MIMO layers is:

[0032]

[0033] or

[0034]

[0035] Where T1 is the first period, j is the sampling time within the first period, a is the user equipment (UE) sequence number, k is the MIMO layer category, and M kj (T1) represents the number of PRBs transmitted at the j-th sampling time within the first period, with the k-th type of MIMO layer, L kj (T1) represents the number of MIMO layers corresponding to the k-th type of MIMO layer at the j-th sampling time within the first period; M aj (T1) represents the number of PRBs allocated to the a-th UE at the j-th sampling time within the first period, L aj (T1) represents the number of MIMO layers used by the a-th UE at the j-th sampling time in the first period.

[0036] Optionally, the total number of PRBs corrected by the layer number factor is the product of the layer number factor and the total number of available PRBs.

[0037] Optionally, the total number of available PRBs is:

[0038] In the second period, the product of the number of sampling times and the number of PRBs available at one of the sampling times;

[0039] or

[0040] The sum of the number of PRBs available at all sampling times within the second period.

[0041] Optionally, the second cycle is the same as the first cycle.

[0042] Thirdly, embodiments of this application also provide a network-side device, including:

[0043] A processor is configured to calculate resource utilization using the total number of Physical Resource Blocks (PRBs) modified by a layer factor, the layer factor being determined based on PRB usage information at at least one sampling time, the PRB usage information at at least including the number of Multiple-Input Multiple-Output (MIMO) layers used by the PRBs during data transmission.

[0044] Optionally, at the at least one sampling time, the larger the number of MIMO layers used by the PRB during data transmission, the larger the layer number factor.

[0045] Optionally, the layer number factor is:

[0046] The maximum value of the elements in the first set, which includes at least one average number of MIMO layers, wherein the average number of MIMO layers is the average number of MIMO layers used by the PRB or all PRBs during data transmission in the corresponding first period;

[0047] or

[0048] The average value of the elements in the second set, which includes at least one maximum MIMO layer number, wherein the maximum MIMO layer number is the maximum number of MIMO layers used by the PRB or all PRBs during data transmission in the corresponding first period.

[0049] Optionally, the average number of MIMO layers is:

[0050]

[0051] or

[0052]

[0053] Where T1 is the first period, j is the sampling time within the first period, a is the user equipment (UE) sequence number, k is the MIMO layer category, and M kj (T1) represents the number of PRBs transmitted at the j-th sampling time within the first period, with the k-th type of MIMO layer, L kj (T1) represents the number of MIMO layers corresponding to the k-th type of MIMO layer at the j-th sampling time within the first period; M aj (T1) represents the number of PRBs allocated to the a-th UE at the j-th sampling time within the first period, L aj (T1) represents the number of MIMO layers used by the a-th UE at the j-th sampling time in the first period.

[0054] Optionally, the total number of PRBs corrected by the layer number factor is the product of the layer number factor and the total number of available PRBs.

[0055] Optionally, the total number of available PRBs is:

[0056] In the second period, the product of the number of sampling times and the number of PRBs available at one of the sampling times;

[0057] or

[0058] The sum of the number of PRBs available at all sampling times within the second period.

[0059] Optionally, the second cycle is the same as the first cycle.

[0060] Fourthly, embodiments of this application also provide a communication device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method described in the first aspect above.

[0061] Fifthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method described in the first aspect above.

[0062] In this embodiment, the layer factor is determined based on PRB usage information at at least one sampling time. Since different PRB usage information can be obtained under different load conditions of the cell during the at least one sampling time, a dynamic layer factor can be determined. It is understood that during network operation, the layer factor can change according to variations in cell channel conditions, network status, number of users, etc. The total PRB count corrected by this dynamic layer factor can more accurately reflect the actual utilization of PRB resources by the cell, improving the accuracy of the calculated resource utilization rate and making the assessment of cell load more accurate. Attached Figure Description

[0063] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0064] Figure 1 This is a flowchart illustrating the resource utilization statistics method provided in the embodiments of this application;

[0065] Figure 2 This is a statistical diagram of PRB usage provided in an embodiment of this application;

[0066] Figure 3 This is a schematic diagram of the resource utilization statistics device provided in the embodiments of this application;

[0067] Figure 4 This is a schematic diagram of the network-side device provided in this application.

[0068] Figure 5 This is a schematic diagram of the communication equipment provided in this application. Detailed Implementation

[0069] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0070] The terms "first," "second," etc., used in the embodiments of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices. Additionally, the use of "and / or" in this application indicates at least one of the connected objects, such as A and / or B and / or C, representing seven possibilities: including A alone, B alone, C alone, and the presence of both A and B, both B and C, both A and C, and the presence of A, B, and C.

[0071] For ease of understanding, the following explains some aspects of this application:

[0072] Space Division Multiplexing (SDM) refers to the reuse of the same frequency band in different spatial locations. In other words, antenna signals for different data streams can have identical carrier frequencies and completely overlapping spectral bandwidths. Therefore, within the same bandwidth, SDM can multiply the data transmission volume and thus multiply the spectral efficiency.

[0073] MIMO Layers: User Equipment (UE) with good channel conditions can be configured with multi-stream MIMO, which is equivalent to transmitting multiple data copies using the same PRB resource. The number of MIMO layers can also be referred to as the number of MIMO streams, space-division multiplexing streams, space-division multiplexing layers, or scheduling layers. For example, with 2 MIMO layers, the same PRB resource can transmit two data copies; with 3 MIMO layers, the same PRB resource can transmit three data copies.

[0074] The number of PRBs used, also known as the number of PRBs occupied or the number of PRBs scheduled, refers to the number of PRBs used for transmission on the Physical Downlink Shared Channel (PDSCH). Specifically, it can be understood as the number of PRBs that the current cell schedules for all UEs to use.

[0075] Total PRBs: refers to the total number of PRBs currently configured in the cell.

[0076] The resource utilization statistics method provided in the embodiments of this application will be described below.

[0077] See Figure 1 , Figure 1 This is a flowchart illustrating the resource utilization statistics method provided in the embodiments of this application. Figure 1 The resource utilization statistics method shown can be executed by network-side devices.

[0078] like Figure 1 As shown, the resource utilization rate statistical method may include the following steps:

[0079] Step 101: Calculate the resource utilization rate using the total number of PRBs corrected by the layer factor.

[0080] For ease of description, this paper uses β to refer to the layer number factor. The aforementioned layer number factor can also be called the reuse factor, correction factor, multiplication factor, adjustment factor, MIMO stream number factor, or MIMO layer number factor. Its function is to correct the total number of PRBs, determine a more accurate total number of actually usable PRB resources, and better reflect the actual network conditions.

[0081] The layer number factor β is determined based on the PRB usage information at at least one sampling occupancy, wherein the PRB usage information at the at least one sampling occupancy includes at least the number of multiple-input multiple-output (MIMO) layers used by the PRB during data transmission.

[0082] In specific implementation, the PRB usage information includes at least the number of MIMO layers. When a cell's PRB can be configured for multi-stream MIMO, the number of MIMO layers used by the PRB during data transmission is not fixed. The higher the number of MIMO layers, the more data a single PRB can transmit simultaneously, which means the utilization rate of the cell's PRB is greater. Therefore, different layer number factors β should be determined. Furthermore, the number of MIMO layers corresponding to a cell varies under different network environments, thus requiring different layer number factors β to be determined as well.

[0083] In this embodiment, β is determined based on PRB usage information at at least one sampling time; in other words, β is determined based on historical PRB usage information. Since historical usage information faithfully records the number of MIMO layers used by the PRB during data transmission, it can realistically reflect the spatial multiplexing usage of the PRB under different load conditions and network environments (e.g., the number of UEs, communication strength, etc.). Therefore, using β determined based on historical PRB usage information to correct the total number of PRBs can more accurately characterize the total number of PRB resources actually available in a spatial multiplexing scenario, thus obtaining a more accurate resource utilization rate.

[0084] Of course, the PRB usage information may also include other information, such as the number of PRBs used, so that the layer number factor β can be determined together with the number of MIMO layers and other usage information. No specific limitation is made here.

[0085] The at least one sampling moment may include sampling moments within one time period, or sampling moments within multiple time periods. When the at least one sampling moment includes sampling moments within multiple time periods, the layer number factor β can be determined more accurately by combining PRB usage information from multiple time periods. The sampling moment may be in units of slots, symbols, or subframes, and is not specifically limited here.

[0086] In this embodiment of the application, the layer factor β can characterize the spatial multiplexing of PRB at different stages depending on the stage of the collected PRB usage information.

[0087] The PRB usage information at at least one sampling time can characterize the historical PRB usage of the cell, and the historical PRB usage can reflect the historical load of the cell. The total number of available PRB resources in a cell for a certain historical period is determined by the aforementioned layer factor β.

[0088] The PRB usage information at at least one sampling time can also characterize the real-time usage of PRBs. The real-time usage of PRBs can reflect the real-time load of the cell, and the total number of PRB resources that the cell can actually use at present can be determined by the layer factor β mentioned above.

[0089] The aforementioned layer factor β is a stage-related factor based on historical data statistics, and it has the characteristic of varying over time (or can be described as having dynamic characteristics). Compared with the pre-set static layer factor, the total number of PRB resources that can actually be used, adjusted by the aforementioned layer factor β, is more in line with the actual situation of the network.

[0090] The layer factor β obtained under the above conditions can, in one case, serve as a basis for correcting the total number of PRBs in the current stage, thereby making the current cell load situation based on the resource utilization assessment more accurate. In another case, the layer factor β can also be used for the resource utilization assessment in the next stage.

[0091] In this embodiment, the layer factor β is determined based on PRB usage information at at least one sampling time. Since different PRB usage information can be obtained under different load conditions of the cell during the at least one sampling time, a dynamic layer factor β can be determined. It is understood that during network operation, the layer factor β can also change according to variations in cell channel conditions, network status, number of users, etc. The total number of PRBs corrected by this dynamic layer factor β can more accurately reflect the actual utilization of PRB resources by the cell, better reflect the actual network conditions, improve the accuracy of the calculated resource utilization rate, and provide a more accurate assessment of cell load.

[0092] Optionally, at the at least one sampling time, the larger the number of MIMO layers used by the PRB during data transmission, the larger the layer number factor β. That is, the number of MIMO layers is positively correlated with the layer number factor β.

[0093] The determination of the level factor β is explained below:

[0094] In an optional implementation, the layer number factor β is:

[0095] The maximum value of the elements in the first set, which includes at least one average number of MIMO layers, wherein the average number of MIMO layers is the average number of MIMO layers used by the PRB or all PRBs during data transmission in the corresponding first period;

[0096] or

[0097] The average value of the elements in the second set, which includes at least one maximum MIMO layer number, wherein the maximum MIMO layer number is the maximum number of MIMO layers used by the PRB or all PRBs during data transmission in the corresponding first period.

[0098] In other words, in this embodiment, the layer number factor β is determined in at least two ways: Method 1, determining the layer number factor β based on the maximum value of the average MIMO layer number; Method 2, determining the layer number factor β based on the average value of the maximum MIMO layer number.

[0099] For ease of explanation, assume that the at least one sampling moment is distributed across N sampling time intervals (i.e., the first period mentioned above), where N is a positive integer. The first set includes N average MIMO layer counts, with each average MIMO layer count corresponding to one sampling time interval. The second set includes N maximum MIMO layer counts, with each maximum MIMO layer count corresponding to one sampling time interval. The first period can be understood as any one of the N sampling time intervals, denoted here as T1, and includes at least one sampling moment.

[0100] The two determination methods described above are explained below:

[0101] Method 1: Determine the layer number factor β based on the maximum value of the average MIMO layer number.

[0102] The specific process for determining this method is as follows:

[0103] Step 1: Calculate the average number of MIMO layers for each sampling time interval.

[0104] Taking the first cycle as an example, the average number of MIMO layers corresponding to the first cycle can be expressed as Equation 1:

[0105]

[0106] Or formula 2:

[0107]

[0108] Where j represents the sampling time within the first period. The numerators of Equations 1 and 2 above can be understood as follows: first, calculate the sum of the products of the PRB used and the number of MIMO layers corresponding to each sampling time, which is denoted as the first sum value; then, sum the first sum values ​​of all sampling times within the first period.

[0109] The denominator of Equation 1 above can be understood as the sum of the number of PRBs used at all sampling times in the first period (when a PRB is reused n times, the count of that PRB is n accordingly). The denominator of Equation 2 above can be understood as the sum of the number of available PRBs at all sampling times in the first period.

[0110] To make it easier to understand, let's take an example. Suppose that at a certain sampling time, the available PRBs include PRB1, PRB2, and PRB3, and the MIMO layer numbers corresponding to PRB1, PRB2, and PRB3 are 4, 2, and 0, respectively. Then, the number of PRBs used at that sampling time is 2, and the number of available PRBs at that sampling time is 3.

[0111] In practical applications, Equation 1, compared to Equation 2, can more accurately reflect the actual transmission capacity of PRBs because it excludes unused PRBs. The layer factor β, determined based on the average number of MIMO layers obtained from Equation 1, can more accurately reflect the spatial multiplexing situation of the cell, and thus the statistically obtained resource utilization rate can be more accurate.

[0112] When the number of available PRBs is chosen as the denominator, the average number of MIMO layers can be further described as follows:

[0113]

[0114] or

[0115]

[0116] Where T1 is the first period, j is the sampling time within the first period, a is the UE number, k is the type of MIMO layer, and M kj (T1) represents the number of PRBs transmitted at the j-th sampling time within the first period, with the k-th type of MIMO layer, L kj(T1) represents the number of MIMO layers corresponding to the k-th type of MIMO layer at the j-th sampling time within the first period; M aj (T1) represents the number of PRBs allocated to the a-th UE at the j-th sampling time within the first period, L aj (T1) represents the number of MIMO layers used by the a-th UE at the j-th sampling time in the first period.

[0117] The first of the two calculation methods described above determines the average number of MIMO layers corresponding to the first period from the perspective of the category of MIMO layers.

[0118] In practical implementation, the type of MIMO layer, i.e., the value of k, can be predefined globally. In other words, the number of all possible MIMO layers can be predefined globally. Given that all possible values ​​of k are predefined globally, L... kj The defined value of (T1) is the same. In addition, the value of k can also be redefined based on the actual situation at each sampling time.

[0119] To facilitate understanding, let's illustrate with an example: Assuming a globally predefined MIMO layer category, including 6 categories: 0 / 1 / 2 / 3 / 4 / 5, where k can take values ​​of 1, 2, 3, 4, 5, and 6 respectively. For example... Figure 2 As shown, the number of MIMO layers for each RRB is represented by the number of corresponding boxes. Therefore, at all sampling times, L... 1j (T1)=0、L 2j (T1) = 1, L 3j (T1) = 2, L 4j (T1) = 3, L 5j (T1) = 4, L 6j (T1) = 5. In the case of redefining this at each sampling time, such as... Figure 2 As shown, in sampling time 1 (slot 0), the actual number of MIMO layers includes 2 / 3 / 4, a total of 3 types, and k can take values ​​of 1, 2, and 3 respectively. Then L 1j (T1) = 2, L 2j (T1) = 3, L 3j (T1) = 4.

[0120] like Figure 2As shown, the first period includes 5 sampling times: sampling time 1 (slot 0), sampling time 2 (slot 1), sampling time 3 (slot 2), sampling time 4 (slot 3), and sampling time 5 (slot 4). The number of MIMO layers at these 5 sampling times includes 5 categories: 0 / 2 / 3 / 4 / 5. The value of k is defined as 1, 2, 3, 4, and 5 respectively. k=1 corresponds to 0 MIMO layers, k=2 corresponds to 2 MIMO layers, k=3 corresponds to 3 MIMO layers, k=4 corresponds to 4 MIMO layers, and k=5 corresponds to 5 MIMO layers, i.e., L... 1j (T1)=0、L 2j (T1) = 2, L 3j (T1) = 3, L 4j (T1) = 4, L 5j (T1) = 5.

[0121] M 1j (T1) represents the number of PRBs transmitted at the j-th sampling time using the 0-stream, M 2j (T1) = 2 represents the number of PRBs transmitted in 2 streams at the j-th sampling time, M 3j (T1) = 3 represents the number of PRBs transmitted in 3 streams at the j-th sampling time, M 4j (T1) = 4 represents the number of PRBs transmitted in 4 streams at the j-th sampling time, M 5j (T1) = 5 represents the number of PRBs transmitted in 2 streams at the j-th sampling time. Taking slot0 as an example, M 11 (T1) = 0, M 21 (T1) = 1, M 31 (T1) = 1, M 41 (T1) = 4, M 51 (T1) = 0.

[0122] The second of the two calculation methods mentioned above is to determine the average number of MIMO layers corresponding to the first period from the perspective of the UE.

[0123] To facilitate understanding, let's illustrate with an example: Assume there are three UEs connected to the current cell, namely UE1, UE2, and UE3, with 'a' taking values ​​of 1, 2, and 3 respectively. Taking sampling time 1 (slot 0) as an example, UE1 is allocated 1 PRB, and the MIMO layer number is 2. Then M... 11 (T1)=1, L 11 (T1) = 2.

[0124] Step 2: Determine the maximum value of the average number of MIMO layers across N sampling time intervals.

[0125] The process of step one is executed for each sampling time interval to obtain the average number of MIMO layers for each sampling time interval. The maximum value among the N average numbers of MIMO layers is determined as the layer number factor β, which can be specifically expressed as follows:

[0126]

[0127] or

[0128]

[0129] In this determination method, since the average number of MIMO layers is calculated in each sampling time interval, and the maximum value among the multiple average values ​​is determined as the layer factor β, resource utilization can be maximized.

[0130] Method 2: Determine the layer number factor β based on the average of the maximum MIMO layer numbers.

[0131] The specific process for determining this method is as follows:

[0132] Step 1: Calculate the maximum number of MIMO layers for each sampling time interval.

[0133] Taking the first period as an example, the maximum number of MIMO layers corresponding to the first period is the largest number of MIMO layers in at least one sampling moment within the first period.

[0134] To make it easier to understand, here is an example, such as Figure 2 As shown, assuming the first period includes 5 sampling times, namely sampling time 1 (slot 0), sampling time 2 (slot 1), sampling time 3 (slot 2), sampling time 4 (slot 3), and sampling time 5 (slot 4), then the maximum number of MIMO layers corresponding to the first period is 5.

[0135] Step 2: Determine the average of the maximum number of MIMO layers in the N sampling time intervals.

[0136] The process of step one is executed for each sampling time interval to obtain the maximum number of MIMO layers corresponding to each sampling time interval. The average value of the N maximum numbers of MIMO layers is then taken, and the average value can be determined as the layer number factor β.

[0137] In this determination method, since the maximum number of MIMO layers is calculated in each sampling time interval, the average of the maximum values ​​is taken instead of selecting the maximum value from the maximum number of MIMO layers. This avoids overestimating the actual PRB resources used by the cell and further improves the accuracy of resource utilization determination.

[0138] It should be noted that, in addition to the two methods described above, in an optional implementation, the method for determining the layer number factor β may also include the following two:

[0139] Method 3: Determine the layer number factor β based on the average of the average MIMO layer numbers.

[0140] That is, first calculate the average number of MIMO layers corresponding to each sampling time interval, then take the average of the average number of MIMO layers corresponding to N sampling time intervals, and determine the average of the averages as the layer factor β. Specific implementation methods of this verification method can be found in the descriptions of Verification Method 1 and Verification Method 2 above; to avoid repetition, they will not be repeated here.

[0141] Method 4: Determine the layer number factor β based on the maximum value of the maximum MIMO layer number.

[0142] That is, first calculate the maximum number of MIMO layers corresponding to each sampling time interval, and then determine the maximum value among the maximum number of MIMO layers corresponding to N sampling time intervals as the layer number factor β. Specific implementation methods for this verification method can be found in the descriptions of Verification Method 1 and Verification Method 2 above; to avoid repetition, they will not be repeated here.

[0143] The determination of resource utilization rate is explained below:

[0144] In this embodiment of the application, for ease of explanation, the time interval in which the current resource utilization rate needs to be determined is defined as the second period, denoted as T2. The second period includes at least one sampling time.

[0145] In one optional implementation, the second period is the same as the first period. This allows for real-time calculation of resource utilization for the current time period using PRB usage data, resulting in more accurate cell load assessments based on this resource utilization. In another optional implementation, the second period differs from the first period and can be a period following the first period. This reduces computational complexity and simplifies network configuration by using PRB usage data from the first period to calculate resource utilization for subsequent periods.

[0146] In practice, the determination of the resource utilization rate can be carried out according to the following process:

[0147] Step 1: Determine the actual number of PRBs occupied in the community.

[0148] Considering spatial multiplexing, since a single PRB may transmit multiple data simultaneously, the actual number of PRBs occupied by a cell is not necessarily equal to the sum of the number of PRBs occupied by all UEs within the cell. Specifically, the actual number of PRBs occupied by a UE at a sampling time can be the product of the number of PRBs occupied by the UE and the actual number of spatial multiplexing layers used by the UE, i.e., the product of the number of PRBs used by the UE and the actual number of MIMO layers used by the UE, denoted here as the second product. Therefore, the actual number of PRBs occupied by the cell can be the sum of the second products of all UEs within the cell at all sampling times during the second period. Specifically, this can be expressed as:

[0149]

[0150] Alternatively, it can be expressed as:

[0151]

[0152] Where i is the sampling time in the second period, and a is the UE number.

[0153] Step 2: Determine the total number of PRBs corrected by the layer number factor β.

[0154] In an optional implementation, the total number of PRBs corrected by the layer number factor β is the product of the layer number factor and the total number of available PRBs.

[0155] In specific implementation, the total number of available PRBs is used to characterize the sum of the actual number of available PRBs at all sampling moments within the second period. Optionally, the total number of available PRBs is: 1) the product of the number of sampling moments in the second period and the number of available PRBs at one of the sampling moments; or, 2) the sum of the number of available PRBs at all sampling moments in the second period.

[0156] In method 1) above, the number of available PRBs at a sampling moment can be the number of available PRBs corresponding to any sampling moment within the second period, or it can be the number of available PRBs corresponding to the sampling moment with the largest number of available PRBs within the second period. However, determining the total number of available PRBs in this way may be an extreme case, potentially leading to an overestimation of the corrected total number of PRBs. The specific sampling moment within the second period corresponding to the available PRBs can be determined based on the actual situation and is not specifically limited here. In method 2) above, the calculated total number of available PRBs is more accurate than in method 1).

[0157] Step 3: Calculate the community resource utilization rate.

[0158] In specific implementation, the community resource utilization rate = the number of PRBs actually occupied by the community / the total number of PRBs after correction by the layer factor β, where the number of PRBs actually occupied by the community is obtained from step one, and the total number of PRBs after correction by the layer factor β is obtained from step two.

[0159] It should be noted that, when the layer factor β is determined based on the above confirmation method one, the cell resource utilization rate can be expressed as:

[0160]

[0161] The maximum average number of MIMO layers refers to the maximum value among the average numbers of all MIMO layers.

[0162] When the layer factor β is determined based on the above confirmation method two, the cell resource utilization rate can be expressed as:

[0163]

[0164] The average maximum number of MIMO layers refers to the average of the maximum number of MIMO layers.

[0165] To facilitate understanding, the following is an example of determining resource utilization rate. The specific process is as follows:

[0166] Step 1: Determine the actual number of PRBs occupied in the community.

[0167] Assuming the second period (T2) includes i samplings and there are a UEs in the cell, then the number of PRBs actually occupied by the a-th UE in the i-th sampling is denoted as M. ai (T2), the actual number of MIMO layers for the a-th UE in the i-th sampling is denoted as L. ai (T2). Therefore, the actual number of PRBs occupied in the cell can be expressed as:

[0168]

[0169] Step 2: Determine the total number of PRBs corrected by the layer number factor β.

[0170] 1) Determine the layer number factor β

[0171] The layer factor can be expressed as:

[0172]

[0173] or

[0174]

[0175] 2) Determine the total number of available PRBs

[0176] Let N(T2) be the number of sampling times within the second period (T2), P(T2) be the number of available PRBs corresponding to a selected sampling time, and P(T2) be the number of available PRBs corresponding to the i-th sampling time. i (T2). Therefore, the total number of available PRBs can be expressed as:

[0177] N(T2)*P(T2)

[0178] or

[0179]

[0180] 3) Determine the total number of PRBs corrected by the layer number factor β.

[0181] The total number of PRBs corrected by the layer factor β can be expressed as:

[0182] β*N(T2)*P(T2)

[0183] or

[0184]

[0185] Step 3: Calculate the community resource utilization rate.

[0186] The resource utilization rate can be expressed as:

[0187]

[0188] or

[0189]

[0190] It should be noted that in the above formula... The value is rounded up, and the resource utilization rate in the above formula ranges from 0 to 100. It is understood that the value of the resource utilization rate is not limited to this range; it can also be determined as a percentage, i.e., 100 in the expression can be replaced with a percentage, but rounding up is not required. The specific method of describing resource utilization rate can be determined according to the actual situation and is not specifically limited here.

[0191] Substituting β into the formula, we can obtain the formula for calculating resource utilization rate G:

[0192]

[0193] or

[0194]

[0195] or

[0196]

[0197] or

[0198]

[0199] It should be noted that in the embodiments of this application, the average value or the maximum value of each MIMO layer can be calculated first, then the layer factor β can be calculated, and then the resource utilization rate can be calculated. Alternatively, the resource utilization rate can be calculated directly using formula G. The specific method can be determined according to the actual situation and is not limited here.

[0200] It should be noted that the steps of the resource utilization statistics method provided in this application embodiment can be performed entirely by the first network node (base station), or the first network node can determine some parameters, send these parameters to the second network node (e.g., network management), and then the second network node calculates the layer factor β. Afterwards, the second network node sends the layer factor β back to the first network node, and the first network node adjusts the total PRB based on the layer factor β and calculates the resource utilization rate.

[0201] See Figure 3 , Figure 3 This is a structural diagram of the resource utilization statistics device provided in the embodiments of this application.

[0202] like Figure 3 As shown, the resource utilization statistics device 300 includes:

[0203] The calculation module 301 is used to calculate the resource utilization rate using the total number of physical resource blocks (PRBs) corrected by the layer factor, wherein the layer factor is determined based on PRB usage information at at least one sampling time, and the PRB usage information at at least one sampling time includes at least the number of multiple-input multiple-output (MIMO) layers used by the PRBs during data transmission.

[0204] Optionally, at the at least one sampling time, the larger the number of MIMO layers used by the PRB during data transmission, the larger the layer number factor.

[0205] Optionally, the layer number factor is:

[0206] The maximum value of the elements in the first set, which includes at least one average number of MIMO layers, wherein the average number of MIMO layers is the average number of MIMO layers used by the PRB or all PRBs during data transmission in the corresponding first period;

[0207] or

[0208] The average value of the elements in the second set, which includes at least one maximum MIMO layer number, wherein the maximum MIMO layer number is the maximum number of MIMO layers used by the PRB or all PRBs during data transmission in the corresponding first period.

[0209] Optionally, the average number of MIMO layers is:

[0210]

[0211] or

[0212]

[0213] Where T1 is the first period, j is the sampling time within the first period, a is the user equipment (UE) sequence number, k is the MIMO layer category, and M kj (T1) represents the number of PRBs transmitted at the j-th sampling time within the first period, with the k-th type of MIMO layer, L kj (T1) represents the number of MIMO layers corresponding to the k-th type of MIMO layer at the j-th sampling time within the first period; M aj (T1) represents the number of PRBs allocated to the a-th UE at the j-th sampling time within the first period, L aj (T1) represents the number of MIMO layers used by the a-th UE at the j-th sampling time in the first period.

[0214] Optionally, the total number of PRBs corrected by the layer number factor is the product of the layer number factor and the total number of available PRBs.

[0215] Optionally, the total number of available PRBs is:

[0216] In the second period, the product of the number of sampling times and the number of PRBs available at one of the sampling times;

[0217] or

[0218] The sum of the number of PRBs available at all sampling times within the second period.

[0219] Optionally, the second cycle is the same as the first cycle.

[0220] The resource utilization statistics device 300 can achieve the following in the embodiments of this application: Figure 1 The various processes in the method embodiments, and the ways to achieve the same beneficial effects, will not be repeated here to avoid repetition.

[0221] Please see Figure 4 , Figure 4 This is one of the structural diagrams of the network-side device provided in the embodiments of this application, such as... Figure 4As shown, the network-side device includes: bus 401, transceiver 402, antenna 403, bus interface 404, processor 405, and memory 406.

[0222] Processor 405 is configured to calculate resource utilization using the total number of Physical Resource Blocks (PRBs) modified by a layer factor β, the layer factor β being determined based on PRB usage information at at least one sampling time, the PRB usage information at at least including the number of Multiple-Input Multiple-Output (MIMO) layers used by the PRBs during data transmission.

[0223] In this embodiment, the network-side device can achieve Figure 1 The various processes in the method embodiments shown have the same beneficial effects, and will not be described again here to avoid repetition.

[0224] This application also provides a communication device. Please refer to [link to relevant documentation]. Figure 5 The communication device may include a processor 501, a memory 502, and a program 5021 stored in the memory 502 and executable on the processor 501.

[0225] When the communication device is a network-side device, program 5021 can be implemented when executed by processor 501. Figure 1 Any steps in the corresponding method embodiments and the achievement of the same beneficial effects will not be repeated here.

[0226] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by hardware related to program instructions, and the program can be stored in a readable medium. This application also provides a readable storage medium storing a computer program, which, when executed by a processor, can implement the above-described methods. Figure 1 Any step in the corresponding method embodiment can achieve the same technical effect, and will not be repeated here to avoid repetition.

[0227] The storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0228] The above description represents the preferred embodiments of this application. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this invention, and these improvements and modifications should also be considered within the scope of protection of this invention.

Claims

1. A resource utilization statistics method for network-side devices, characterized in that, The resource utilization rate statistical methods include: Resource utilization is calculated using the total number of Physical Resource Blocks (PRBs) corrected by a layer factor, wherein the layer factor is determined based on PRB usage information at at least one sampling time, and the PRB usage information at at least one sampling time includes at least the number of Multiple-Input Multiple-Output (MIMO) layers used by the PRBs during data transmission. Wherein, the total number of PRBs corrected by the layer number factor is: the product of the layer number factor and the total number of available PRBs; The layer number factor is: The maximum value of the elements in the first set, which includes at least one average MIMO layer number, wherein the average MIMO layer number is the average number of MIMO layers used by the PRB or all PRBs during data transmission in the corresponding first period.

2. The resource utilization rate statistical method according to claim 1, characterized in that, At the at least one sampling time, the larger the number of MIMO layers used by the PRB during data transmission, the larger the layer number factor.

3. The resource utilization rate statistical method according to claim 1, characterized in that, The average number of MIMO layers is: ； or ； Where T1 is the first period, j is the sampling time within the first period, a is the user equipment (UE) number, and k is the type of MIMO layer. Let PRB be the number of PRBs transmitted at the j-th sampling time within the first period, using the k-th type of MIMO layer. This refers to the number of MIMO layers corresponding to the k-th type of MIMO layer at the j-th sampling time within the first period; For the j-th sampling time within the first period, the number of PRBs allocated to the a-th UE. The number of MIMO layers used by the a-th UE at the j-th sampling time in the first period.

4. The resource utilization rate statistical method according to claim 1, characterized in that, The total number of available PRBs is: In the second period, the product of the number of sampling times and the number of PRBs available at one of the sampling times; or The sum of the number of PRBs available at all sampling times within the second period.

5. The resource utilization rate statistical method according to claim 4, characterized in that, The second cycle is the same as the first cycle.

6. A resource utilization rate statistical device, characterized in that, The resource utilization rate statistical device includes: The calculation module is used to calculate resource utilization using the total number of physical resource blocks (PRBs) corrected by a layer factor, wherein the layer factor is determined based on PRB usage information at at least one sampling time, and the PRB usage information at at least one sampling time includes at least the number of multiple-input multiple-output (MIMO) layers used by the PRBs during data transmission. Wherein, the total number of PRBs corrected by the layer number factor is: the product of the layer number factor and the total number of available PRBs; The layer number factor is: The maximum value of the elements in the first set, which includes at least one average MIMO layer number, wherein the average MIMO layer number is the average number of MIMO layers used by the PRB or all PRBs during data transmission in the corresponding first period.

7. A network-side device, characterized in that, include: A processor is configured to calculate resource utilization using the total number of Physical Resource Blocks (PRBs) modified by a layer factor, the layer factor being determined based on PRB usage information at at least one sampling time, the PRB usage information at at least including the number of Multiple-Input Multiple-Output (MIMO) layers used by the PRBs during data transmission. Wherein, the total number of PRBs corrected by the layer number factor is: the product of the layer number factor and the total number of available PRBs; The layer number factor is: The maximum value of the elements in the first set, which includes at least one average MIMO layer number, wherein the average MIMO layer number is the average number of MIMO layers used by the PRB or all PRBs during data transmission in the corresponding first period.

8. A communication device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps in the resource utilization statistics method as described in any one of claims 1 to 5.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps in the resource utilization statistics method as described in any one of claims 1 to 5.

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