Resource utilization statistics method, apparatus and related devices

Abstract

The embodiments of the present application provide a resource utilization statistics method, apparatus and related devices, in which the method includes: calculating resource utilization using a total number of physical resource blocks (PRBs) modified by a layer number factor, the layer number factor being determined based on PRB usage information of at least one sampling time, the PRB usage information of the at least one sampling time including at least a number of multiple-input multiple-output (MIMO) layers used by the PRB when transmitting data. The present application can improve the accuracy of resource utilization statistics in a space division multiplexing scenario.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is filed based on and claims priority to a Chinese patent application bearing application number "202111151553.3" and filed on September 29, 2021, the entire contents of which are hereby incorporated into this application in their entirety. [Technical Field]

[0002] TECHNICAL FIELD Embodiments of the present application relate to the field of communications technology, and more particularly to resource utilization statistics methods, apparatus and related devices. [Background technology]

[0003] Statistics on physical resource block (PRB) utilization rates are usually used by carriers and networks to obtain the PRB utilization rate of each cell, allowing them to more intuitively obtain the availability and load status of each cell. For example, if it is known based on the PRB utilization rate that some cells have been in a high load state for a long period of time, it may be considered to expand these cells or adjust the network plan.

[0004] Currently, PRB utilization is usually expressed as the quotient of the number of PRBs used and the total number of PRBs. Space division multiplexing (SDM) technology, which can improve transmission speeds, is widely used. SDM refers to antenna signals for different data streams, whose carrier frequencies are identical and whose spectral widths overlap completely. In other words, SDM reuses the same frequency band in different spaces. Therefore, SDM can double the data that can be transmitted in the same bandwidth, thereby doubling spectral utilization. However, current resource utilization statistics methods do not take SDM into account, resulting in low accuracy in resource utilization in SDM scenarios. Summary of the Invention [Problem to be solved by the invention]

[0005] The embodiments of the present application provide a resource utilization statistics method, apparatus and related devices to solve the problem of inaccurate resource utilization statistics in spatial division multiplexing scenes. [Means for solving the problem]

[0006] In order to solve the above problems, the present application is realized as follows.

[0007] In a first aspect, an embodiment of the present application provides a resource utilization statistics method used in a network side device, the resource utilization statistics method including: calculating a PRB total number resource utilization modified by a layer number factor, where the layer number factor is determined based on PRB usage information of at least one sampling time, and the PRB usage information of the at least one sampling time includes at least the number of Multiple Input Multiple Output (MIMO) layers used by the PRB during data transmission.

[0008] Alternatively, the layer number factor may be larger as the number of MIMO layers used by the PRB during data transmission at the at least one sampling time instant increases.

[0009] Alternatively, the layer number factor may be the maximum value of a first set of elements including at least one average value of the number of MIMO layers, which is the average value of the number of MIMO layers used by the PRB or all PRBs used in the corresponding first period when transmitting data, or the average value of a second set of elements including at least one maximum value of the number of MIMO layers, which is the maximum value of the number of MIMO layers used by the PRB or all PRBs used in the corresponding first period when transmitting data.

[0010] Optionally, the average number of MIMO layers is (Σ ∀j Σ ∀k {Mkj (T1)*L kj (T1)}) / ((Σ ∀j Σ ∀k ){M kj (T1)}), or (Σ ∀j Σ ∀a {M aj (T1)*L aj (T1)}) / (Σ ∀j Σ ∀a {M aj (T1)}), where T1 is the first period, j is the sampling time within the first period, a is a user equipment (UE) number, k is the classification of the number of MIMO layers, and M kj (T1) is the number of PRBs transmitted in the k-th number of MIMO layers at the j-th sampling time in the first period, and L kj (T1) is the number of MIMO layers corresponding to the k-th type of number of MIMO layers at the j-th sampling time in the first period, and M aj (T1) is the number of PRBs allocated to the a-th UE at the j-th sampling time in the first period, and L aj (T1) may be the number of MIMO layers that the a-th UE uses at the j-th sampling time within the first period.

[0011] Optionally, the total number of PRBs modified by the layer number factor may be the product of the layer number factor and the total number of available PRBs.

[0012] Alternatively, the total number of available PRBs may be the product of the number of sampling times and the number of available PRBs at any one of the sampling times within the second period, or the sum of the number of available PRBs at all sampling times within the second period.

[0013] Optionally, the second period may be the same as the first period.

[0014] In a second aspect, an embodiment of the present application provides a resource utilization statistics device, the resource utilization statistics device including: a calculation module that calculates resource utilization using a total number of physical resource blocks (PRBs) modified by a layer number factor, the layer number factor being determined based on PRB usage information for at least one sampling time, and the PRB usage information for the at least one sampling time including at least the number of multiple-input multiple-output (MIMO) layers used by the PRB during data transmission.

[0015] Alternatively, the layer number factor may be larger as the number of MIMO layers used by the PRB during data transmission at at least one of the sampling times increases.

[0016] Alternatively, the layer number factor may be the maximum value of a first set of elements including at least one average value of the number of MIMO layers, which is the average value of the number of MIMO layers used by the PRB or all PRBs used in the corresponding first period when transmitting data, or the average value of a second set of elements including at least one maximum value of the number of MIMO layers, which is the maximum value of the number of MIMO layers used by the PRB or all PRBs used in the corresponding first period when transmitting data.

[0017] Optionally, the average number of MIMO layers is (Σ ∀j Σ ∀k {M kj (T1)*L kj (T1)}) / (Σ ∀j Σ ∀k {M kj (T1)}), or (Σ ∀j Σ ∀a {M aj (T1)*L aj (T1)}) / (Σ ∀j Σ ∀a {M aj(T1)}), where T1 is the first period, j is the sampling time within the first period, a is a user equipment (UE) number, k is the classification of the number of MIMO layers, and M kj (T1) is the number of PRBs transmitted in the k-th number of MIMO layers at the j-th sampling time in the first period, and L kj (T1) is the number of MIMO layers corresponding to the k-th type of number of MIMO layers at the j-th sampling time in the first period, and M aj (T1) is the number of PRBs allocated to the a-th UE at the j-th sampling time in the first period, and L aj (T1) may be the number of MIMO layers that the a-th UE uses at the j-th sampling time within the first period.

[0018] Optionally, the total number of PRBs modified by the layer number factor may be the product of the layer number factor and the total number of available PRBs.

[0019] Alternatively, the total number of available PRBs may be the product of the number of sampling times and the number of PRBs available at any one of the sampling times within the second period, or the sum of the number of PRBs available at all of the sampling times within the second period.

[0020] Optionally, the second period may be the same as the first period.

[0021] In a third aspect, an embodiment of the present application further provides a network side device, the network side device comprising: a processor that calculates resource utilization using a total number of physical resource blocks (PRBs) modified by a layer number factor, the layer number factor being determined based on PRB usage information for at least one sampling time, and the PRB usage information for the at least one sampling time including at least the number of multiple-input multiple-output (MIMO) layers used by the PRB during data transmission.

[0022] Alternatively, the layer number factor may be larger as the number of MIMO layers used by the PRB during data transmission at at least one of the sampling times increases.

[0023] Alternatively, the layer number factor may be the maximum value of a first set of elements including at least one average value of the number of MIMO layers, which is the average value of the number of MIMO layers used by the PRB or all PRBs used in the corresponding first period when transmitting data, or the average value of a second set of elements including at least one maximum value of the number of MIMO layers, which is the maximum value of the number of MIMO layers used by the PRB or all PRBs used in the corresponding first period when transmitting data.

[0024] Optionally, the average number of MIMO layers is (Σ ∀j Σ ∀k {M kj (T1)*L kj (T1)}) / ((Σ ∀j Σ ∀k ){M kj (T1)}), or (Σ ∀j Σ ∀a {M aj (T1)*L aj (T1)}) / (Σ ∀j Σ ∀a {M aj (T1)}), where T1 is the first period, j is the sampling time within the first period, a is a user equipment (UE) number, k is the classification of the number of MIMO layers, and M kj (T1) is the number of PRBs transmitted in the k-th number of MIMO layers at the j-th sampling time in the first period, and L kj (T1) is the number of MIMO layers corresponding to the k-th type of number of MIMO layers at the j-th sampling time in the first period, and M aj (T1) is the number of PRBs allocated to the a-th UE at the j-th sampling time in the first period, and Laj (T1) may be the number of MIMO layers that the a-th UE uses at the j-th sampling time within the first period.

[0025] Optionally, the total number of PRBs modified by the layer number factor may be the product of the layer number factor and the total number of available PRBs.

[0026] Alternatively, the total number of available PRBs may be the product of the number of sampling times and the number of PRBs available at any one of the sampling times within the second period, or the sum of the number of PRBs available at all sampling times within the second period.

[0027] Optionally, the second period may be the same as the first period.

[0028] In a fourth aspect, an embodiment of the present application further provides a communication device, the communication device comprising a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, steps of the resource utilization statistics method described in the first aspect above are performed.

[0029] In a fifth aspect, an embodiment of the present application further provides a computer-readable storage medium having a computer program stored therein, the computer program, when executed by a processor, realizing the steps of the resource utilization statistics method described in the first aspect above. [Effects of the Invention]

[0030] In the embodiment of the present application, the layer number factor is determined based on the PRB usage information of at least one sampling time, and different PRB usage information can be obtained under different load conditions of the cell within at least one sampling time, thereby determining a dynamic layer number factor. Note that in the process of network operation, the layer number factor can change according to changes in circumstances such as cell channel conditions, network status, and the number of users. The total number of PRBs modified by such a dynamic layer number factor can more accurately reflect the actual utilization of PRB resources in the cell, thereby improving the accuracy of the calculated resource utilization rate and making the evaluation of the cell load situation more accurate. [Brief explanation of the drawings]

[0031] In order to more clearly explain the technical solutions of the embodiments of the present application, the drawings used in the description of the embodiments of the present application will be briefly described. The drawings in the following description are only some embodiments of the present invention, and those skilled in the art can derive other drawings from these drawings without any creative efforts. [Figure 1] 1 is a schematic flowchart of a resource utilization statistics method provided by an embodiment of the present application; [Figure 2] FIG. 1 is a schematic diagram of PRB usage statistics provided by an embodiment of the present application. [Figure 3] 1 is a schematic configuration diagram of a resource utilization statistics device provided by an embodiment of the present application; [Figure 4] FIG. 2 is a schematic configuration diagram of a network-side device provided by an embodiment of the present application; [Figure 5] 1 is a schematic configuration diagram of a communication device provided by an embodiment of the present application; DETAILED DESCRIPTION OF THE INVENTION

[0032] The following clearly and completely describes the technical solutions of the embodiments of the present application in combination with the drawings of the embodiments of the present application, and it is clear that the described embodiments are only some of the embodiments of the present invention, and not all of the embodiments, and all other embodiments that can be obtained by those skilled in the art without paying creative labor are all within the protection scope of the present invention.

[0033] The terms "first," "second," etc., in the examples of this application distinguish between similar objects and need not describe a particular order or chronology. The terms "comprises," "includes," and "comprises," as well as any variations thereof, are intended to be inclusive and non-exclusive. For example, a process, method, system, product, or device comprising a series of steps or units is not necessarily limited to those explicitly recited, but may include other steps or units not explicitly recited or inherent in the process, method, product, or device. In this application, "and / or" is used to represent at least one of connected objects. For example, A and / or B and / or C means a single A, a single B, a single C, and seven cases in which A and B exist, B and C exist, A and C exist, and A, B, and C exist.

[0034] For ease of understanding, some of the contents related to this application will be explained below.

[0035] Space Division Multiplexing (SDM) refers to the reuse of the same frequency band in different spaces. That is, the antenna signals of different data streams can have the same carrier frequency and overlapping spectrum widths. Therefore, with the same bandwidth, SDM can double the data transmission capacity and also double the spectrum utilization rate.

[0036] Number of MIMO layers: User equipment (UE) with good channel conditions can configure multi-stream MIMO, which corresponds to transmitting multiple data using the same PRB resource. The number of MIMO layers is also called the number of MIMO streams, the number of spatial division streams, the number of spatial division multiplexing layers, or the number of scheduling layers. For example, if the number of MIMO layers is two streams, the same PRB resource can transmit two data, and if the number of MIMO layers is three streams, the same PRB resource can transmit three data.

[0037] The number of PRBs used, also called the number of occupied PRBs or the number of scheduled PRBs, refers to the number of PRBs used for Physical Downlink Shared Channel (PDSCH) transmission, and specifically can be understood as the number of PRBs scheduled and used by the current cell for all UEs.

[0038] The total number of PRBs refers to the total number of PRBs currently set in the cell.

[0039] The resource utilization statistics method provided by the embodiment of the present application will now be described.

[0040] Please refer to Fig. 1, which is a schematic flowchart of a resource utilization statistics method provided by an embodiment of the present application. The resource utilization statistics method as shown in Fig. 1 can be implemented in a network-side device.

[0041] As shown in FIG. 1, the resource utilization statistics method includes the following steps:

[0042] Step 101: calculate the PRB total resource utilization rate modified by the layer number factor.

[0043] For ease of explanation, the layer count factor is referred to as β in this specification. The layer count factor is also called a multiplexing factor, a correction factor, a doubling factor, an adjustment factor, a MIMO stream count factor, or a MIMO layer count factor, and all of these factors modify the total number of PRBs to more accurately determine the total number of PRB resources that can actually be used, and to better match the actual network situation.

[0044] The layer number factor β is determined based on PRB usage information for at least one sampling occasion, and the PRB usage information for at least one sampling occasion includes at least the number of multiple-input multiple-output (MIMO) layers that the PRB uses when transmitting data.

[0045] In a specific implementation, the PRB usage information includes at least the number of MIMO layers. If the PRB of a cell can configure multi-stream MIMO, the number of MIMO layers used by the PRB when transmitting data is not fixed. The larger the number of MIMO layers, the more data a single PRB can simultaneously transmit, which corresponds to a greater availability of the PRB of the cell, so a different layer number factor β should be determined. At the same time, the number of MIMO layers supported by cells in different network environments is different, so a different layer number factor β should also be determined.

[0046] In the embodiment of the present application, β is determined based on PRB usage information at at least one sampling time, in other words, β is determined based on PRB historical usage information. The historical usage information faithfully records the number of MIMO layers used by the PRB when transmitting data, and can actually reflect the PRB spatial division multiplexing usage situation under different load conditions and different network environments (such as the number of UEs, communication strength, etc.). Therefore, by using β determined based on the PRB historical usage information to correct the total number of PRBs, the total number of PRB resources actually available in spatial division multiplexing scenarios can be more accurately represented, and thus a more accurate resource utilization rate can be obtained.

[0047] Of course, the PRB usage information may include other information, such as the number of PRBs used, which can be combined with the number of MIMO layers and other usage information to determine the layer number factor β, and is not particularly limited here.

[0048] The at least one sampling time may include a sampling time within one time period, or may include sampling times within multiple time periods. When the at least one sampling time includes sampling times within multiple time periods, PRB usage information within the multiple time periods can be integrated to more accurately determine the layer number factor β. The sampling time may be in units of slots, codes, or subframes, and is not particularly limited here.

[0049] In the embodiment of the present application, depending on the stage where the collected PRB usage information is located, the layer number factor β can represent the PRB spatial division multiplexing situation of different stages.

[0050] The PRB usage information for at least one sampling time can represent the historical usage status of the PRB in the cell, and the historical usage status of the PRB can reflect the historical load status of the cell. The total number of available PRB resources in a certain historical period of the cell is determined by the above layer number factor β.

[0051] The PRB usage information at at least one sampling time can also represent the real-time usage status of the PRB, which can reflect the real-time load status of the cell, and the total number of PRB resources that the cell can actually use at present is determined by the above layer number factor β.

[0052] The above layer number factor β is a stage-related factor statistically calculated based on historical data, and has different characteristics (or can be said to have dynamic characteristics) over time. Therefore, the total number of actually available PRB resources adjusted by the above layer number factor β is more in line with the actual network situation than a pre-set static layer number factor.

[0053] The layer number factor β obtained in each of the above cases can be used as a basis for correcting the total number of PRBs in the current stage so that the current load situation of the cell evaluated based on resource utilization becomes more accurate. In another case, the layer number factor β can be used in the evaluation of resource utilization in the next stage.

[0054] In the embodiment of the present application, the layer number factor β is determined based on the PRB usage information of at least one sampling time, and different PRB usage information can be obtained under different load conditions of the cell within at least one sampling time, thereby determining a dynamic layer number factor β. Note that, in the process of network operation, the layer number factor can change according to changes in circumstances such as cell channel conditions, network status, and number of users. The total number of PRBs modified by such a dynamic layer number factor β can more accurately reflect the actual PRB resource usage of the cell, be more in line with the actual situation of the network, improve the accuracy of the calculated resource utilization rate, and make the evaluation of the cell load situation more accurate.

[0055] Optionally, the greater the number of MIMO layers used by the PRB for data transmission at at least one sampling time, the greater the layer number factor β, i.e., the number of MIMO layers and the layer number factor β are positively correlated.

[0056] The determination of the layer number factor β will now be described.

[0057] In one alternative embodiment, the number of layers factor β is the maximum value of a first set of elements including the average value of at least one MIMO layer number, which is the average value of the number of MIMO layers used by the used PRB or all PRBs during data transmission in the corresponding first period, or is the average value of a second set of elements including the maximum value of at least one MIMO layer number, which is the maximum value of the number of MIMO layers used by the used PRB or all PRBs during data transmission in the corresponding first period.

[0058] In other words, in this embodiment, the method for determining the number of layers factor β includes at least determination method 1 for determining the number of layers factor β based on the maximum value of the average value of the number of MIMO layers, and determination method 2 for determining the number of layers factor β based on the average value of the maximum value of the number of MIMO layers.

[0059] For ease of explanation, if at least one sampling time is distributed among N sampling time intervals (i.e., the first period described above), where N is a positive integer, the first set includes the average number of N MIMO layers, where one average number of MIMO layers corresponds to one sampling time interval, and the second set includes the maximum number of N MIMO layers, where one maximum number of MIMO layers corresponds to one sampling time interval. The first period can be understood as any sampling time interval among the N sampling time intervals, denoted here as T1, and at least one sampling time is included within the first period.

[0060] The above two determination methods will be explained below.

[0061] Determination method 1: Determine the layer number factor β based on the maximum value of the average value of the number of MIMO layers.

[0062] In this determination method, the specific processing is as follows.

[0063] Step 1: Calculate the average number of MIMO layers corresponding to each sampling time interval.

[0064] Taking the first cycle as an example, the average number of MIMO layers corresponding to the first cycle is Formula 1: (Σ ∀j {number of PRBs used * number of MIMO layers}) / (Σ ∀j {number of PRBs used}), or Equation 2: (Σ ∀j {number of PRBs used * number of MIMO layers}) / (Σ∀j {number of available PRBs}), Here, j is the sampling time within the first period. The numerators of the above formulas 1 and 2 calculate the sum of the products of the PRB used corresponding to each sampling time and the number of MIMO layers, which is denoted here as the first sum value, and can be understood as adding up the first sum values of all sampling times within the first period.

[0065] The denominator in Equation 1 above can be understood as the sum of the number of PRBs used at all sampling times within the first period (if a PRB is multiplexed n times, the count of that PRB corresponds to n), and the denominator in Equation 2 above can be understood as the sum of the number of PRBs available at all sampling times within the first period.

[0066] For ease of understanding, for example, if the PRBs available at a certain sampling time include PRB1, PRB2, and PRB3, and the numbers of MIMO layers corresponding to PRB1, PRB2, and PRB3 are 4, 2, and 0, respectively, the number of used PRBs corresponding to this sampling time is 2, and the number of available PRBs corresponding to this sampling time is 3.

[0067] In practical applications, the above Equation 1 can more accurately reflect the actual transmission capacity of the PRB compared to Equation 2 because unused PRBs are excluded. By determining the layer number factor β based on the average number of MIMO layers obtained in Equation 1, the spatial division multiplexing status of the cell can be more accurately reflected, and thus the statistical resource utilization rate can be more accurate.

[0068] If the number of available PRBs is selected as the denominator, the average number of MIMO layers is further (Σ ∀j Σ ∀k {M kj (T1)*L kj (T1)}) / (Σ ∀j Σ ∀k {M kj (T1)}), Or, (Σ ∀j Σ ∀a {M aj (T1)*L aj (T1)}) / (Σ ∀j Σ ∀a {M aj (T1)}), It is expressed as where T1 is the first period, j is the sampling time within the first period, a is the UE number, k is the classification of the number of MIMO layers, and M kj (T1) is the number of PRBs transmitted at the jth sampling time in the first period using the kth type of MIMO layer, and L kj (T1) is the number of MIMO layers corresponding to the k-th type of MIMO layer number at the j-th sampling time in the first period, and M aj (T1) is the number of PRBs assigned to the a-th UE at the j-th sampling time in the first period, and L aj (T1) is the number of MIMO layers that the a-th UE uses at the j-th sampling time in the first period.

[0069] The first of the two calculation methods is to determine the average value of the number of MIMO layers corresponding to the first period based on the classification of the number of MIMO layers.

[0070] In specific implementation, the classification of the number of MIMO layers, i.e., the possible values of k, may be globally predefined, that is, the number of MIMO layers that can exist globally may be predefined. When the possible values of k are globally predefined, L kj The defined value of (T1) is the same. Similarly, the possible values of k can be redefined based on the actual situation at each sampling time.

[0071] For ease of understanding, for example, when the classification of the number of MIMO layers is globally predefined, if the globally predefined MIMO layers include six types, 0 / 1 / 2 / 3 / 4 / 5, k can take the values 1, 2, 3, 4, 5, and 6, respectively. As shown in Figure 2, when the number of MIMO layers of each RRB is expressed by the corresponding number of blocks, 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. When multiple MIMO layers are defined at each sampling time, as shown in Figure 2, at sampling time 1 (slot 0), the actual number of MIMO layers includes three types: 2 / 3 / 4, and k takes the values 1, 2, and 3, respectively. 1j (T1)=2, L 2j (T1)=3, L 3j (T1)=4.

[0072] As shown in Figure 2, the first period includes five sampling times, which are 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 present at the five sampling times includes five types, 0 / 2 / 3 / 4 / 5, where k is defined to take values of 1, 2, 3, 4, and 5, respectively. The number of MIMO layers for k=1 is 0, the number of MIMO layers for k=2 is 2, the number of MIMO layers for k=3 is 3, the number of MIMO layers for k=4 is 4, and the number of MIMO layers for k=5 is 5, i.e., L 1j (T1)=0, L 2j (T1)=2, L 3j (T1)=3, L 4j (T1)=4, L 5j (T1)=5.

[0073] M 1j(T1) represents the number of PRBs transmitted in the 0 stream at the j-th sampling time, and M 2j (T1)=2 represents the number of PRBs transmitted in two streams at the j-th sampling time, and M 3j (T1)=3 represents the number of PRBs transmitted in the three streams at the j-th sampling time, and M 4j (T1)=4 represents the number of PRBs transmitted in 4 streams at the j-th sampling time, and M 5j (T1)=5 represents the number of PRBs transmitted in two streams at the j-th sampling time. For example, in slot 0, M 11 (T1)=0, M 21 (T1)=1, M 31 (T1)=1, M 41 (T1)=4, M 51 Let (T1)=0.

[0074] The second of the two calculation methods above determines the average number of MIMO layers corresponding to the first period from the UE's perspective.

[0075] For ease of understanding, for example, assume that three UEs access the current cell, which are users UE1, UE2, and UE3, and a takes the values 1, 2, and 3, respectively. Taking sampling time 1 (slot 0) as an example, if the number of PRBs allocated to UE1 is 1 and the number of MIMO layers is 2, then M 11 (T1)=1, L 11 (T1)=2.

[0076] Step 2: Determine the maximum average value of the number of MIMO layers in N sampling time intervals.

[0077] By performing the process of step 1 for each sampling time interval, the average number of MIMO layers corresponding to each sampling time interval can be obtained, and the maximum value among the average number of N MIMO layers is determined as the layer number factor β. Specifically, β=max((Σ ∀j Σ ∀k {M kj (T1)*Lkj (T1)}) / (Σ ∀j Σ ∀k {M kj (T1)})) Or, β=max((Σ ∀j Σ ∀a {M aj (T1)*L aj (T1)}) / (Σ ∀j Σ ∀a {M aj (T1)})).

[0078] In this determination method, the average number of MIMO layers is calculated for each sampling time interval, and the maximum value among the multiple average values is determined as the layer number factor β, thereby maximizing resource utilization.

[0079] Determination method 2: Determine the layer number factor β based on the average value of the maximum number of MIMO layers.

[0080] In this determination method, the specific processing is as follows.

[0081] Step 1: Calculate the maximum number of MIMO layers corresponding to each sampling time interval.

[0082] Taking the first period as an example, the maximum value of the number of MIMO layers corresponding to the first period is the maximum number of MIMO layers at least at one sampling time within the first period.

[0083] For ease of understanding, for example, as shown in Fig. 2, the first period includes five sampling times, which are 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). In this case, the maximum number of MIMO layers corresponding to the first period is 5.

[0084] Step 2: Determine the average value of the maximum number of MIMO layers in N sampling time intervals.

[0085] By performing the processing of step 1 for each sampling time interval, the maximum number of MIMO layers corresponding to each sampling time interval can be obtained, and the maximum numbers of N MIMO layers can be averaged, and the average value can be determined as the layer number factor β.

[0086] In this determination method, the maximum number of MIMO layers is calculated for each sampling time interval, and the maximum number of MIMO layers is not selected from the maximum numbers of MIMO layers, but each maximum value is averaged, thereby avoiding overestimating the PRB resources actually used by the cell and improving the accuracy of resource utilization determination.

[0087] In addition to the above two determination methods, in one alternative embodiment, the determination method of the layer number factor β may include the following two.

[0088] Determination method 3: Determine the layer number factor β based on the average value of the average values of the number of MIMO layers.

[0089] That is, first, the average value of the number of MIMO layers corresponding to each sampling time interval is calculated, and then the average value of the average values of the number of MIMO layers corresponding to N sampling time intervals is averaged to determine the layer number factor β. For specific embodiments of this determination method, please refer to the relevant descriptions of the above determination method 1 and determination method 2, and to avoid duplication, the description will be omitted here.

[0090] Determination method 4: Determine the layer number factor β based on the maximum value of the maximum number of MIMO layers.

[0091] That is, first, the maximum value of the number of MIMO layers corresponding to each sampling time interval is calculated, and then the maximum value of the maximum values of the number of MIMO layers corresponding to N sampling time intervals is determined as the layer number factor β. For specific embodiments of this determination method, please refer to the relevant descriptions of the above determination method 1 and determination method 2, and to avoid duplication, the description will be omitted here.

[0092] The determination of resource utilization rates will now be described.

[0093] In the embodiment of the present application, for ease of explanation, the time interval for which the resource utilization rate needs to be determined is defined as a second period, here denoted as T2, and the second period includes at least one sampling time.

[0094] In one alternative embodiment, the second period is the same as the first period. In this way, by using the PRB usage data for the current time interval to calculate the resource utilization rate for this time interval in real time, the resource utilization rate calculation has a stronger real-time property, and the cell load situation evaluated based on the resource utilization rate becomes more accurate. In another alternative embodiment, the second period may be different from the first period and may be a time period subsequent to the first period. In this way, by using the PRB usage data for the first period to calculate the resource utilization rate for the subsequent time period, the amount of calculation can be reduced and network configuration can be simplified.

[0095] In a specific implementation, the resource utilization rate can be determined as follows:

[0096] Step 1: Determine the number of PRBs that the cell actually occupies.

[0097] When spatial division multiplexing is taken into consideration, one PRB may transmit multiple data simultaneously, so the number of PRBs actually occupied by a cell is not necessarily equal to the sum of the numbers of PRBs occupied by each UE in the cell. Specifically, the number of PRBs actually occupied by one UE in a cell at one sampling time may be the product of the number of PRBs occupied by this UE and the actual number of spatial division streams of this UE, that is, the product of the number of PRBs used by this UE and the actual number of MIMO layers of this UE, which is referred to here as the second product. In this case, the number of PRBs actually occupied by a cell can be the sum of the second products of all UEs in the cell at all sampling times in the second period. Specifically, Σ ∀a Σ ∀i {Number of occupied PRBs * Actual number of spatial division streams}, Or, Σ ∀a Σ ∀i It is expressed as {number of PRBs used * number of actual MIMO layers}. Here, i is the sampling time within the second period, and a is the UE number.

[0098] Step 2: Determine the total number of PRBs modified by the layer number factor β.

[0099] In one alternative embodiment, the total number of PRBs modified by the layer number factor β is the product of the layer number factor and the total number of available PRBs.

[0100] In a specific implementation, the total number of available PRBs is used to represent the sum of the number of PRBs actually available at all sampling times in the second period. Alternatively, the total number of available PRBs is 1) the product of the number of sampling times and the number of PRBs available at any sampling time in the second period, or 2) the sum of the number of PRBs available at all sampling times in the second period.

[0101] In the above method 1), the number of PRBs available at one sampling time may be the number of PRBs available corresponding to any sampling time in the second period, or the number of PRBs available corresponding to the sampling time with the largest number of PRBs available in the second period. However, the total number of PRBs available determined in this way may be an extreme case, and the revised total number of PRBs may be large. Specifically, the number of PRBs available corresponding to which sampling time in the second period is determined may be determined according to actual circumstances, and is not particularly limited here. The total number of PRBs calculated in the above method 2) is more accurate than that calculated in method 1).

[0102] Step 3: Calculate the cell resource utilization rate.

[0103] In a specific implementation, cell resource utilization rate = number of PRBs actually occupied by a cell / total number of PRBs modified by layer number factor β, where the number of PRBs actually occupied by a cell is obtained in step 1, and the total number of PRBs modified by layer number factor β is obtained in step 2.

[0104] When the layer number factor β is determined based on the above determination method 1, the cell resource utilization rate is (Σ ∀a Σ ∀i {Number of occupied PRBs * Actual number of spatial division streams}) / (Total number of available PRBs * Maximum average number of MIMO layers), Here, the maximum average number of MIMO layers is the maximum value among the average values of the numbers of MIMO layers.

[0105] When the layer number factor β is determined based on the above determination method 2, the cell resource utilization rate is (Σ ∀a Σ ∀i {Number of occupied PRBs * Actual number of spatial division streams}) / (Total number of available PRBs * Average maximum number of MIMO layers), Here, the average maximum number of MIMO layers is the average value of the maximum values of the numbers of MIMO layers.

[0106] For ease of understanding, an example of determining a resource utilization rate will be described below, and the specific process is as follows.

[0107] Step 1: Determine the number of PRBs that the cell actually occupies.

[0108] If the second period (T2) includes the i-th sampling and there are a number of UEs in the cell, the number of PRBs actually occupied by the a-th UE in the i-th sampling is M ai (T2), and the actual number of MIMO layers of the a-th UE at the i-th sampling is denoted as L ai (T2). Therefore, the number of PRBs that a cell actually occupies is Σ ∀a Σ ∀i {M ai (T2)*L ai (T2)}. Step 2: Determine the total number of PRBs modified by the layer number factor β.

[0109] 1) Determine the layer number factor β. The layer number factor is β=max((Σ ∀j Σ ∀k {M kj (T1)*L kj (T1)}) / (Σ ∀j Σ ∀k {M kj (T1)})), Or, β=max((Σ ∀j Σ ∀a {M aj (T1)*L aj (T1)}) / (Σ ∀j Σ ∀a {M aj (T1)})). 2) Determine the total number of PRBs available. The number of sampling times in the second period (T2) is denoted as N(T2), the number of available PRBs corresponding to one selected sampling time is denoted as P(T2), and the number of available PRBs corresponding to the i-th sampling time is denoted as P(T2). i (T2). Therefore, the total number of available PRBs is N(T2)*P(T2), Or,

number

number

[0110] Step 3: Calculate the cell resource utilization rate. The resource utilization is [(Σ ∀a Σ ∀i {M ai (T2)*L ai (T2)}) / (N(T2)*P(T2)*β)*100], Or, [(Σ ∀a Σ ∀i {M ai (T2)*L ai (T2)}) / (Σ ∀i {P i (T2)}*β)*100].

[0111] Note that the square brackets [ ] in the above formula represent rounding upwards, and the resource utilization rate in the above formula can take a value range from 0 to 100. Note that the resource utilization rate is not limited to this range and can also be determined based on a percentage, i.e., 100 in the formula is replaced with a percentage, but it does not need to be rounded upwards. The specific description method for resource utilization can be determined according to the actual situation, and is not particularly limited here.

[0112] When β is introduced, the resource utilization calculation formula G is: [(Σ ∀a Σ ∀i {M ai (T2)*L ai (T2)}) / (N(T2)*P(T2)*max((Σ ∀j Σ ∀k {M kj (T1)*L kj (T1)}) / (Σ ∀j Σ ∀k {M kj (T1)})))*100], Or, [(Σ ∀a Σ ∀i {M ai (T2)*L ai (T2)}) / (N(T2)*P(T2)*max((Σ ∀j Σ ∀a {M aj (T1)*L aj (T1)}) / (Σ ∀j Σ ∀a {M aj (T1)})))*100], Or, [(Σ ∀a Σ ∀i {M ai (T2)*L ai (T2)}) / (Σ ∀i {P i (T2)}*max((Σ ∀j Σ ∀k {M kj (T1)*L kj (T1)}) / (Σ ∀j Σ ∀k {Mkj (T1)})))*100], Or, [(Σ ∀a Σ ∀i {M ai (T2)*L ai (T2)}) / (Σ ∀i {P i (T2)}*max((Σ ∀j Σ ∀a {M aj (T1)*L aj (T1)}) / (Σ ∀j Σ ∀a {M aj (T1)})))*100] is obtained.

[0113] In the embodiments of the present application, the average value of each MIMO layer number or the maximum value of each MIMO layer number may be calculated first to calculate the layer number factor β, and then the resource utilization rate may be calculated. Alternatively, the resource utilization rate may be calculated directly using formula G. Specifically, the resource utilization rate may be determined according to the actual situation, and is not particularly limited here.

[0114] It should be noted that all steps of the resource utilization statistics method provided by the embodiments of the present application may be performed by a first network node (base station), or the first network node may determine some parameters and send the determined parameters to a second network node (e.g., a network administrator), and the second network node may calculate the layer number factor β. The second network node then sends the layer number factor β to the first network node, and the first network node modifies the total number of PRBs based on the layer number factor β to calculate the resource utilization rate.

[0115] Please refer to FIG. 3, which is a structural diagram of a resource utilization statistics device provided by an embodiment of the present application.

[0116] As shown in FIG. 3, the resource utilization rate statistics device 300 The present invention includes a calculation module 301 for calculating a resource utilization rate using a total number of physical resource blocks (PRBs) modified by a layer number factor, the layer number factor being determined based on PRB usage information of at least one sampling time, the PRB usage information of at least one sampling time including at least the number of multiple-input multiple-output (MIMO) layers used by the PRB during data transmission.

[0117] Alternatively, the layer number factor may be larger as the number of MIMO layers used by the PRB during data transmission in at least one sampling time instant increases.

[0118] Alternatively, the layer number factor may be the maximum value of a first set of elements including an average value of at least one MIMO layer number, which is the average value of the number of MIMO layers used by the PRB or all PRBs used in the corresponding first period when transmitting data, or the average value of a second set of elements including the maximum value of at least one MIMO layer number, which is the maximum value of the number of MIMO layers used by the PRB or all PRBs used in the corresponding first period when transmitting data.

[0119] Optionally, the average number of MIMO layers is (Σ ∀j Σ ∀k {M kj (T1)*L kj (T1)}) / (Σ ∀j Σ ∀k {M kj (T1)}) Or, (Σ ∀j Σ ∀a {M aj (T1)*L aj (T1)}) / (Σ ∀j Σ ∀a {M aj (T1)}), where T1 is the first period, j is the sampling time within the first period, a is the user equipment (UE) number, k is the classification of the number of MIMO layers, and M kj(T1) is the number of PRBs transmitted at the jth sampling time in the first period using the kth type of MIMO layer, and L kj (T1) is the number of MIMO layers corresponding to the k-th type of MIMO layer number at the j-th sampling time in the first period, and M aj (T1) is the number of PRBs assigned to the a-th UE at the j-th sampling time in the first period, and L aj (T1) may be the number of MIMO layers that the a-th UE uses at the j-th sampling time in the first period.

[0120] Optionally, the total number of PRBs modified by the layer number factor may be the product of the layer number factor and the total number of available PRBs.

[0121] Alternatively, the total number of available PRBs may be the product of the number of sampling times and the number of PRBs available at any one sampling time within the second period, or may be the sum of the number of PRBs available at all sampling times within the second period.

[0122] Optionally, the second period may be the same as the first period.

[0123] The resource utilization statistics device 300 can implement each process of the method embodiment of FIG. 1 in the embodiment of the present application, and has the same beneficial effects, so to avoid duplication, the description will be omitted here.

[0124] Referring to Figure 4, Figure 4 is one of the structural diagrams of a network side device provided by an embodiment of the present application. As shown in Figure 4, the network side device includes a bus 401, a transceiver 402, an antenna 403, a bus interface 404, a processor 405, and a memory 406.

[0125] The processor 405 calculates the resource utilization rate using a total number of physical resource blocks (PRBs) modified by a layer number factor β, where the layer number factor β is determined based on PRB usage information for at least one sampling time, and the PRB usage information for at least one sampling time includes at least the number of multiple-input multiple-output (MIMO) layers that the PRB uses when transmitting data.

[0126] In this embodiment, the network-side device can realize each process of the method embodiment as shown in FIG. 1, and has the same beneficial effects, and to avoid duplication, the description will be omitted here.

[0127] An embodiment of the present application further provides a communication device. Referring to Figure 5, the communication device includes a processor 501, a memory 502, and a program 5021 stored in the memory 502 and executable by the processor 501.

[0128] If the communication equipment is a network side device, when the processor 501 executes the program 5021, it can realize any step of the method embodiment corresponding to FIG. 1 and achieve the same beneficial effect, so the description will be omitted here.

[0129] Those skilled in the art will understand that all or part of the steps of the method in the above embodiments can be realized by hardware related to program instructions, and the program can be stored in a readable medium. The embodiments of the present application further provide a readable storage medium, which stores a computer program, and when the computer program is executed by a processor, can realize any step of the method in the above embodiment corresponding to FIG. 1 and achieve the same beneficial effects. To avoid redundancy, the description will be omitted here.

[0130] The storage medium may be, for example, a read-only memory (ROM), a random access memory (RAM), a disk, or an optical disk.

[0131] The above describes the preferred embodiments of the present application, but those skilled in the art may make some improvements and retouches without departing from the principle of the present invention, and these improvements and retouches should also be regarded as the protection scope of the present invention.

Claims

1. A resource utilization statistics method used in a network-side device, comprising: calculating a resource utilization rate using a total number of physical resource blocks (PRBs) modified by a layer number factor, wherein the layer number factor is determined based on PRB usage information for at least one sampling time, and the PRB usage information for the at least one sampling time includes at least a number of multiple-input multiple-output (MIMO) layers that the PRB uses when transmitting data; The resource utilization rate = the number of PRBs actually occupied by the cell / the total number of PRBs modified by the layer number factor; The number of layers factor is a maximum value of a first set of elements including the average number of at least one of the MIMO layers, which is the average number of the MIMO layers used by the PRBs or all PRBs used in the corresponding first period when transmitting data; Or, and the PRB or all PRBs used in the corresponding first period are the average value of a second set of elements including at least one maximum number of MIMO layers used during data transmission.

2. The method for calculating resource utilization statistics according to claim 1, wherein the layer number factor increases as the number of MIMO layers used by the PRB for data transmission increases at least at one of the sampling times.

3. The average number of MIMO layers is (Σ ∀ｊ Σ ∀ｋ {M ｋｊ (T1)*L ｋｊ (T1)}) / ((Σ ∀ｊ Σ ∀ｋ ){M ｋｊ (T1)}) Or, (Σ ∀ｊ Σ ∀ａ {M ａｊ (T1)*L ａｊ (T1)}) / (Σ ∀ｊ Σ ∀ａ {M ａｊ (T1)}) where T1 is the first period, j is the sampling time within the first period, a is a user equipment (UE) number, k is the category of the number of MIMO layers, and M ｋｊ (T1) is the number of PRBs transmitted in the k-th type of MIMO layer number at the j-th sampling time within the first period, and L ｋｊ (T1) is the number of MIMO layers corresponding to the k-th type of number of MIMO layers at the j-th sampling time in the first period, and M ａｊ (T1) is the number of PRBs allocated to the a-th UE at the j-th sampling time in the first period, and L ａｊ 2. The method for calculating statistics on resource utilization rates according to claim 1, wherein (T1) is the number of MIMO layers used by the a-th UE at the j-th sampling time within the first period.

4. The method for statistically determining resource utilization rates according to any one of claims 1 to 3, wherein the total number of PRBs modified by the layer number factor is the product of the layer number factor and the total number of available PRBs.

5. The total number of available PRBs is a product of the number of sampling times and the number of PRBs available at any one of the sampling times within a second period; Or, 5. The method for calculating statistics on resource utilization rates according to claim 4, wherein the number of available PRBs is the sum of the number of available PRBs at all the sampling times within the second period.

6. 6. The method for collecting statistics on resource utilization rates according to claim 5, wherein the second period is the same as the first period.

7. A resource utilization statistics device, comprising: a calculation module for calculating a resource utilization rate using a total number of physical resource blocks (PRBs) modified by a layer number factor, the layer number factor being determined based on PRB usage information for at least one sampling time, the PRB usage information for the at least one sampling time including at least a number of multiple-input multiple-output (MIMO) layers used by the PRBs when transmitting data; The resource utilization rate = the number of PRBs actually occupied by the cell / the total number of PRBs modified by the layer number factor; The number of layers factor is a maximum value of a first set of elements including the average number of at least one of the MIMO layers, which is the average number of the MIMO layers used by the PRBs or all PRBs used in the corresponding first period when transmitting data; Or, The resource utilization statistics device is characterized in that the PRB or all PRBs used in the corresponding first period are the average value of a second set of elements including at least one maximum number of MIMO layers that is the maximum number of MIMO layers used during data transmission.

8. A network-side device, a processor for calculating a resource utilization rate using a total number of physical resource blocks (PRBs) modified by a number of layers factor; The layer number factor is determined based on PRB usage information for at least one sampling time, and the PRB usage information for the at least one sampling time includes at least a number of multiple-input multiple-output (MIMO) layers that the PRB uses when transmitting data; The resource utilization rate = the number of PRBs actually occupied by the cell / the total number of PRBs modified by the layer number factor; The number of layers factor is a maximum value of a first set of elements including the average number of at least one of the MIMO layers, which is the average number of the MIMO layers used by the PRBs or all PRBs used in the corresponding first period when transmitting data; Or, The PRB or all PRBs used in the corresponding first period are the average value of a second set of elements including at least one maximum number of MIMO layers that is the maximum number of MIMO layers used during data transmission.

9. A communications device comprising a processor, a memory, and a computer program stored in the memory and executable by the processor, A communication device, characterized in that, when the computer program is executed by the processor, the steps of the resource utilization statistics method according to any one of claims 1 to 6 are performed.

10. A computer-readable storage medium, comprising: A computer-readable storage medium having a computer program stored therein, the computer program performing the steps of the resource utilization statistics method according to any one of claims 1 to 6 when executed by a processor.

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