CN110290540B - Method and device for determining cell capacity - Google Patents
Method and device for determining cell capacity Download PDFInfo
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- CN110290540B CN110290540B CN201810225419.5A CN201810225419A CN110290540B CN 110290540 B CN110290540 B CN 110290540B CN 201810225419 A CN201810225419 A CN 201810225419A CN 110290540 B CN110290540 B CN 110290540B
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Abstract
The invention discloses a method and a device for determining cell capacity, wherein the method comprises the following steps: the base station determines M SINRs of M user equipment according to MR data reported by the M user equipment in the same cell in a reporting period; the base station determines the maximum rate corresponding to the M SINRs according to the M SINRs; determining corresponding resource scheduling weights in the M user equipment according to the signaling data of the M user equipment measured by the base station in the reporting period; the resource scheduling weight is positively correlated with the SINR of the user equipment; and determining the maximum capacity of the cell according to the maximum rate determined by the SINR of the M user equipment and the resource scheduling weight of the M user equipment.
Description
Technical Field
The present invention relates to the field of mobile communications technologies, and in particular, to a method and an apparatus for determining cell capacity.
Background
With the advancement of wide, deep and thick network deployment strategies in LTE networks, continuous coverage and deep coverage have been implemented at present, and with the continuous increase of LTE users, the network load is continuously increased. In the field of wireless communication technology, cell capacity generally refers to the number of online users in a network and the traffic of uplink and downlink data (including circuit domain service data and packet domain service data). The cell capacity is mainly embodied in two aspects, namely, the maximum number of users and the maximum rate of a cell. The determination of the single cell capacity has important significance for network planning, optimization and load sharing work.
The cell capacity may be derived by comparing the cell network design capacity with the cell network actual capacity. In an actual wireless communication system, the actual capacity of a cell network not only depends on the performance of network-side devices (such as base stations, etc.) themselves, but also is limited by the location distribution of user terminals (UEs), the power headroom of the UEs, and other factors in the wireless network environment, such as co-channel interference, adjacent channel interference, and propagation loss variation and uncertainty. The existence of the various factors described above makes it often difficult to accurately determine the actual capacity of a cell network.
For the supportable capacity of a cell of a packet domain network represented by LTE technology, a scheme using network utilization, statistics of the maximum number of access users or the number of active users as a measure is generally used. Because the capacity of the packet domain service depends on the frequency spectrum efficiency and is mutually restricted and influenced by factors such as different service quality requirements, wireless resources, network configuration, wireless environment, characteristic functions and the like, the capacity actually borne by each cell is different from a theoretical value to a certain extent, and meanwhile, because the signal quality of the position of a user has certain randomness, the capacity of the whole cell is simply evaluated from a certain point to have certain limitation. Due to the diversity of cell capacities, the cell load analysis cannot be calculated and analyzed by the traditional simple formula. The capacity of the users supported by the LTE cell can be evaluated only from the network load perspective through the statistics of the network utilization rate, the maximum number of access users or the number of activated users, and the relatively specific number of the supportable users can not be provided for specific services well.
Disclosure of Invention
The invention provides a method and a device for determining cell capacity, which are used for solving the problem that the method for accurately evaluating the cell capacity cannot be used in the prior art.
The embodiment of the invention provides a method for determining cell capacity, which is characterized by comprising the following steps:
a base station acquires MR data reported by M user equipment in the same cell in a reporting period;
the base station determines M SINRs of the M user equipment according to the MR data reported by the M user equipment;
the base station determines the maximum rate corresponding to the M SINRs according to the M SINRs;
the base station determines corresponding resource scheduling weights in the M user equipment according to the signaling data of the M user equipment measured by the base station in the reporting period; the resource scheduling weight is positively correlated with the SINR of the user equipment;
and the base station determines the maximum capacity of the cell according to the maximum rate determined by the SINR of the M user equipment and the resource scheduling weight of the M user equipment.
A possible implementation manner, in which the base station determines the maximum rates corresponding to the M SINRs according to the M SINRs, includes:
for any one of the M SINRs, performing:
the base station determines the CQI corresponding to the SINR according to the SINR;
the base station determines TBS corresponding to the SINR through table look-up according to the RB quantity corresponding to the SINR and the MCS corresponding to the CQI;
and the base station determines the maximum rate corresponding to the SINR according to the TBS of the SINR, the time slot number of each TTI and the RI.
A possible implementation manner is to determine the maximum rate V corresponding to the SINR according to the following formula i ：
Wherein, TBS i TBS, N corresponding to ith SINR in the N SINRs S For the number of available time slots in each TTI, t is the time length of the time slot; RI is a rank indication.
In a possible implementation manner, the M SINRs of the M user equipments are determined according to the following formula:
wherein, the SINR d For the downlink SINR, S is the RSRP of the cell, I is the intra-network interference power, determined according to the RSRP of the cell of the neighboring cell, and N is 0 The noise power.
In one possible implementation, the intra-network interference power is determined according to the following formula:
wherein m is the number of neighboring cells of the cell, and the RSRP j Is the RSRP of the jth neighbor cell.
A possible implementation of the method, the cell capacity V max Determined according to the following formula:
wherein, P i The number of the user equipment with the maximum rate corresponding to different SINRs accounts for the proportion of the M user equipment; PR j Scheduling weight for the resource of the jth user equipment corresponding to the ith SINR; k i The number of the user equipment corresponding to the ith SINR is L, and the number of the carriers is L.
In one possible implementation, the method further includes:
the base station determines the average throughput rate of the cell in the reporting period according to the flow of the M user equipment in the reporting period;
and the base station determines the resource utilization rate of the cell in the reporting period according to the average throughput rate, the cell capacity and the resource waste weight.
In a possible implementation manner, the resource utilization rate of the cell in the reporting period is determined according to the following formula:
wherein, P T For the resource utilization of the cell, the V a Is the average throughput rate of the cell in the reporting period, the V max The cell capacity of the cell in the reporting period is obtained; the f (T) is the weight of wasting of resources of the cell in the reporting period.
The embodiment of the invention provides a device for determining cell capacity, which comprises:
an obtaining unit, configured to obtain MR data reported by M user equipments in the same cell in a reporting period;
a processing unit, configured to determine M SINRs of the M user equipments according to the MR data reported by the M user equipments; determining the maximum rate corresponding to the M SINRs according to the M SINRs; determining corresponding resource scheduling weights in the M user equipment according to the signaling data of the M user equipment measured by the base station in the reporting period; the resource scheduling weight is positively correlated with the SINR of the user equipment; and determining the maximum capacity of the cell according to the maximum rate determined by the SINR of the M pieces of user equipment and the resource scheduling weight of the M pieces of user equipment.
In a possible implementation manner, the processing unit is specifically configured to:
for any one of the M SINRs, performing: determining a CQI corresponding to the SINR according to the SINR; determining TBS corresponding to the SINR through table look-up according to the RB quantity corresponding to the SINR and the MCS corresponding to the CQI; and determining the maximum rate corresponding to the SINR according to the TBS of the SINR, the time slot number of each TTI and the RI.
A possible implementation manner is to determine the maximum rate V corresponding to the SINR according to the following formula i ：
Wherein, TBS i TBS, N corresponding to ith SINR in the N SINRs S The number of available time slots in each TTI is t, and the time length of the time slot is t; RI is a rank indication.
In a possible implementation manner, the M SINRs of the M user equipments are determined according to the following formula:
wherein, the SINR d For the downlink SINR, S is the RSRP of the cell, I is the intra-network interference power, determined according to the RSRP of the cell of the neighboring cell, and N is 0 The noise power.
In one possible implementation, the intra-network interference power is determined according to the following formula:
wherein m is the number of neighboring cells of the cell, and the RSRP j Is the RSRP of the jth neighbor cell.
A possible implementation of the method, the cell capacity V max Determined according to the following formula:
wherein, P i The number of the user equipment with the maximum rate corresponding to different SINRs accounts for the proportion of the M user equipment; PR j Scheduling weight for the resource of the jth user equipment corresponding to the ith SINR; k i The number of the user equipment corresponding to the ith SINR is L, and the number of the carriers is L.
In one possible implementation, the processing unit is further configured to:
determining the average throughput rate of the cell in the reporting period according to the flow of the M pieces of user equipment in the reporting period; and determining the resource utilization rate of the cell in the reporting period according to the average throughput rate, the cell capacity and the resource waste weight.
In a possible implementation manner, the resource utilization rate of the cell in the reporting period is determined according to the following formula:
wherein, P T For the resource utilization of the cell, the V a Is the average throughput rate of the cell in the reporting period, the V max The cell capacity of the cell in the reporting period is set; the f (T) is the weight of wasting of resources of the cell in the reporting period.
The embodiment of the invention provides a method and a device for determining the cell capacity, wherein the SINR directly influences the network rate, and the network bearable rate directly influences the capacity of the whole cell. The capacity determination and load analysis based on the SINR quality reported by the MR can fully consider the actual network quality of a user, reflect the actual bearing capacity of a cell to the maximum extent, can better evaluate the actual capacity of the cell through the relation between the SINR and the network quality, and has important significance for network overall planning and service development strategies.
Drawings
Fig. 1 is a flowchart illustrating a method for determining cell capacity according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an apparatus for determining cell capacity according to an embodiment of the present invention.
Detailed Description
For the convenience of understanding the embodiments of the present invention, Measurement Report (MR) data and signaling data will be briefly described below.
MR data mainly comes from the physical layer of User Equipment (UE) and Evolved Node B (eNodeB), the Radio Link Control (RLC) layer, and the measurement report generated by calculation in the Radio resource management process. The method has the function of collecting quality data, flow data and service signaling related information reported by a user within a certain time. The signaling data is mainly data obtained by the base station through measurement on the user equipment. The method comprises the following steps: RI, QCI, time delay, traffic data of the user equipment, etc.
For example, in Time Division Long Term Evolution (TD-LTE) network structure analysis, MR data and signaling data may be collected as periodic measurements. The main key fields of MR data, signaling data may include:
1) the sample acquisition time, i.e. the reporting time of the user equipment on the MR data, is used to record the acquisition time of the sample measurement point.
2) SINR of the uplink channel and SINR of the downlink channel; the SINR represents the ratio of the effective signal to the interference signal and the noise power, and can effectively reflect the interference condition of the current network. The SINR directly affects the network rate.
3) The cell RSRP measurement information ScRSRP is used for a measurement level when the cell is used as a cell, that is, Reference Signal Received Power (RSRP) of the cell. The Cell basic measurement information is used for frequency points EARFCN and Physical Cell Identifiers (PCIs) recorded by the Cell during measurement.
4) The neighboring cell RSRP measurement information is used for a neighboring cell measurement level measured under the cell, i.e., the RSRP of the neighboring cell. RSRP of neighbor cell: and the reference signal received power of the TD-LTE defined adjacent region relation cell and the undefined adjacent region relation cell is represented. And the basic measurement information of the adjacent cell is used for recording the frequency point EARFCN and the Physical Cell Identity (PCI) in the measurement of the adjacent cell.
7) The cell information ECGI is used for identifying the cell to which the sampling point belongs, and the id is unique in an operator; international Mobile Subscriber Identity (IMSI) is used to identify the user equipment.
8) Qci (qos Class identifier) is a scale value used to measure the packet forwarding behavior (e.g. packet loss rate, packet delay budget) of a specific SDF (service data flow), and it is applied to both GBR and Non-GBR bearers and used to specify the control bearer level packet forwarding scheme (e.g. scheduling weight, admission threshold, queue management threshold, link layer protocol configuration, etc.) defined in the access node.
9) Time delay, etc.
Currently, the determination of cell capacity and load is mainly based on the following ways:
1. and performing theoretical calculation according to the scheduling mode and resource allocation of physical channels such as the PDSCH, the PDCCH and the PUSCH, and determining the maximum number of users which can be borne by a single cell. And calculating the maximum speed of the whole cell according to the channel quality of the single position, or obtaining the maximum speed of the cell through fixed point test.
2. And analyzing the network load through the statistics of the network utilization rate, the maximum access user number or the activated user number so as to evaluate the cell capacity condition.
Both of the above methods have certain disadvantages and limitations.
First, in the method 1, the cell capacity is calculated only according to the theoretical basis, and each cell capacity is determined and unchanged. Because the actual environments of the user equipment are different, the difference of SINR will affect the overall capacity of the cell, and the difference of signal quality in the cell coverage area caused by the actual wireless environment is not considered in the method 1, and meanwhile, the uncertainty of the positions of the user equipment in different cells and the change of signal quality caused by the movement of the user equipment in the same cell both affect the actual carrying capacity of the cell.
Secondly, in the method 2, the network load and the number of users in a period of time can be evaluated through indexes, but the actual SINR of the users in different cells is different, so that the influence of the SINR on the cell capacity cannot be distinguished, the capacity differentiation analysis of different cells cannot be realized, only the indexes at the cell level can be expressed, and the specific influence factors of the load cannot be reflected fundamentally.
Fig. 1 is a schematic flow chart of a method for determining cell capacity according to an embodiment of the present invention, where the method includes:
step 101: the base station determines M SINRs of M user equipment according to MR data reported by the M user equipment in the same cell in a reporting period;
step 102: the base station determines M SINRs of the M user equipment according to the MR data reported by the M user equipment;
step 103: the base station determines the maximum rate corresponding to the M SINRs according to the M SINRs;
step 104: the base station determines corresponding resource scheduling weights in the M user equipment according to the signaling data of the M user equipment measured by the base station in the reporting period; the resource scheduling weight is positively correlated with the SINR of the user equipment;
step 105: and the base station determines the maximum capacity of the cell according to the maximum rate determined by the SINR of the M user equipment and the resource scheduling weight of the M user equipment.
In step 101, MR data in an MR reporting period and signaling data in the reporting period are obtained, the MR data and the signaling data of the same user equipment are associated according to an association rule of the MR data and the signaling data, and a key field in the embodiment of the present invention is extracted for data storage. The key field may be selected according to actual needs, and is not limited herein.
In step 102, taking the example that the MR data is stored in the form of sample data, one measurement sample point of the MR data contains SINRs reported by M user equipments in the cell, where the uplink SINR can be determined by the base station for the MR data reported by the user equipment. Specifically, the power of the useful signal may be measured, for example, the channel quality of the RS, PDSCH, etc.; and the measured power of the signal or channel interference signal, including the interference of other cells in the system, or the different system, etc.
A possible implementation manner may be that the M downlink SINRs of the M user equipments are determined according to RSRP and interference power of the cell in the MR data, that is, intra-network interference and noise power generated by overlapping coverage of neighboring cells. Wherein, the noise power is related to the actual geographic environment and can be set as a preset value. Specifically, the M downlink SINRs of the M user equipments may be determined according to the following formula:
wherein, the SINR d For the M downlink SINRs, S is the RSRP of the cell, I is the intra-network interference power, determined according to the RSRP of the cell of the neighboring cell, and N is the power of the cell 0 The noise power.
In one possible implementation, the intra-network interference power may be determined according to the following formula:
wherein m is the number of neighboring cells of the cell, and the RSRP j Is the RSRP of the jth neighbor cell.
In practical application, the RSRP values of the cells and the neighboring cells in the MR data may be cell Common Reference Signal (CRS) power values received by the terminal, where the value is a linear average of power of a single Resource Element (RE) in a measurement bandwidth, and reflects the strength of the cell signal. The reported RSRP value in the MR data is not a value obtained by actual measurement, but is obtained by adding a preset standard value to an actual measurement value according to the current communication standard protocol.
In the embodiment of the present invention, the MR data may include a plurality of sampling points, each sampling point includes an identification code of a cell, and it can be further determined whether each sampling point uses the cell as the cell, and if the cell is used as the cell in a certain sampling point, cell level measurement information in the certain sampling point can be obtained, that is, a cell RSRP value of the cell in the certain sampling point. And when the cell is acting as a cell, the cell RSRP value of the cell may represent the useful power that the cell uses for communication in this sample point.
In the embodiment of the invention, the adjacent cells and the cells in each sampling point can be identified according to the physical cell identification codes of the cells and the physical cell identification codes of the adjacent cells in the MR data, and whether the cells belong to the same-frequency cells or not is determined according to the cell carrier numbers and the adjacent cell carrier numbers. And then, subtracting a preset standard value from the RSRP value of each adjacent cell to obtain an actual RSRP value of each adjacent cell, and performing logarithmic transformation on the actual RSRP value of each adjacent cell to obtain the RSRP value of each adjacent cell after transformation.
In the embodiment of the present invention, after determining other cells having the same frequency as the cell, if the other cells are used as the cell and the cell is used as an adjacent cell, the adjacent cell level measurement information corresponding to the cell, that is, the adjacent cell RSRP value, may indicate the interference power of the cell when the cell is used as an interference source in this sampling point, and the sum of the adjacent cell level measurement values corresponding to the cell in all sampling points having the same frequency as the cell and using the cell as the adjacent cell may indicate the total interference power of the cell on the entire network structure, that is, the interference power on the network structure.
In step 103, for any SINR of the M SINRs, the following steps may be included:
step one, the base station determines a CQI corresponding to the SINR according to the SINR;
step two, the base station determines the TBS corresponding to the SINR through table look-up according to the RB quantity corresponding to the SINR and the MCS corresponding to the CQI;
and step three, the base station determines the maximum rate corresponding to the SINR according to the TBS of the SINR, the time slot number of each TTI and the RI.
It should be noted that the M SINRs may be uplink SINRs or downlink SINRs, and a specific determination manner is described in detail below.
In the first step, the coding modes of data transmission adopted by the base station are different under different signal qualities, and the following table is an embodiment, and the corresponding SINR and coding mode (Modulation) and block error rate (BLER) under different CQIs are within 10%. Other possible different corresponding relationships may be determined according to specific needs, and are not described herein again.
Table 1: correspondence between CQI and SINR
In the second step, the Coding modes are different, and the size of resources that can be carried by Physical Resource Blocks (PRBs) is different, which can be determined by the corresponding relationship between Modulation and Coding Strategy (MCS) and TBS resource blocks and the TBS bearer byte data table.
In the embodiment of the invention, the number of RBs occupied by the service data of each user is influenced by different wireless environments differently. In the downlink direction, the network acquires the downlink radio quality through the CQI reported by the terminal, and after acquiring the amount of data to be transmitted and the CQI, according to the 3GPP (3rd Generation Partnership Project) specification, it can obtain how many PRBs corresponding to different CQI levels in different radio environments need to be allocated by the network for service use by looking up a table.
Table 2: MCS and TBS correspondence table in 3GPP
The Modulation order corresponds to the encoding method in table 1, for example, 2 corresponds to QPSK, 4 corresponds to 16QAM, 6 corresponds to 64QAM, and 8 corresponds to 256 QAM.
Specifically, taking 3GPP as an example, according to the SINR signal quality of each sampling point reported by the MR, the number of bytes that can be carried by M TBSs corresponding to M SINRs can be determined by associating the CQI with the SINR correspondence table and the MCS with the TBS resource block bearer data correspondence table.
Table 3: TBS resource block size table corresponding to different bandwidths in 3GPP
Further, in order to accurately obtain resources available for service data transmission, the number of downlink PRBs is determined, and overhead such as necessary SIB, Paging, RRC signaling, and the like needs to be removed. For different bandwidths, the number of downlink PRBs is as shown in table 4:
| bandwidth (MHz) | 1.4 | 3 | 5 | 10 | 15 | 20 |
| Total number of RBs in downlink | 6 | 15 | 25 | 50 | 75 | 100 |
TABLE 4 number of downlink PRBs corresponding to different bandwidths
It should be noted that the statistical period of the statistical MR data may be determined according to the traffic period. For example, if the service period is 20ms, when calculating the PRB resources occupied by the SIB message, the RRC signaling, and the Paging message, the calculation in the time domain may use 20ms as the statistical period.
The number of PRBs available for uplink depends mainly on the number of uplink PRBs, and the number of uplink PRBs can be determined by the frequency bandwidth, for example, 100 PRBs in 20MHz bandwidth. Further, in order to accurately obtain resources available for service data transmission, the number of PRBs occupied by the necessary PUCCH and the number of uplink PRBs occupied by the RRC signaling are determined and removed. For different bandwidths, the number of uplink PRBs is as described in table 5:
| bandwidth (MHz) | 1.4 | 3 | 5 | 10 | 15 | 20 |
| Total number of RBs in uplink | 6 | 15 | 25 | 50 | 75 | 100 |
TABLE 5 number of uplink PRBs corresponding to different bandwidths
The number of PRBs occupied by the uplink PUCCH can be determined by parameter configuration. The number of RB resources used for transmitting RRC signaling in the PUSCH may be obtained in the same determination manner as the number of downlink PRB resources.
In step three, one possible implementation manner may determine the maximum rate V corresponding to the SINR according to the following formula i ：
Wherein, TBS i TBS, N corresponding to ith SINR in the N SINRs S For the number of available time slots in each TTI, t is the time length of the time slot; RI is a rank indication.
TBS i For all PRBs that can carry the largest byte, one possible implementation may include N for Ns in the maximum downlink transmission rate Sub-frame For transmitting time slot and P Special sub-frame Is a special subframe; for the maximum transmission rate of the uplink, N s May include only N Sub-frame (ii) a For example, the downlink of the data transmission time of the special subframe may be 0.75, the uplink may be 0, RI is the number of data transmission streams, and t is time. The RI is a statistical value in the MR report data, and indicates the number of times that the UE reports RI-1, RI-2, RI-4, and RI-8 in the statistical period.
In a possible implementation manner, the RI with the largest RI ratio in the reporting period may be used as the number of data transmission streams in the period, for example, the RI in the downlink maximum rate may be based on a statistical value, and the RI in the uplink maximum rate may be 1.
In step 104, according to the M maximum rates determined in step 103, the cell maximum rate corresponding to each sampling point in the statistical period is determined, and then the weighted average is performed according to the ratio of the resource scheduling weight and the M sampling points to determine the maximum rate of the whole cell.
Specifically, the method can comprise the following steps:
step one, determining the occupation ratio of M sampling points under the maximum speed corresponding to different SINRs in a statistical period; specifically, it can be expressed as:
pi is the ratio of sampling points of the maximum rate corresponding to the ith SINR in the statistical period; count (V) i ) Is the number of sampling points of the maximum rate corresponding to the ith SINR.
Step two, determining the user resource scheduling weight corresponding to each maximum rate; in order to simplify the determination method of the resource scheduling weight, the resource scheduling weight and the SINR of the user equipment are related to each other, which is a possible implementation manner, the larger the SINR of the user equipment is, the larger the resource scheduling weight of the user equipment is, that is, the resource scheduling weight and the SINR of the user equipment are positively related to each other; specifically, the algorithm of the user resource scheduling weight may include MaxC/I, RR, RF, EPF, and the like. In the embodiment of the invention, the EPF algorithm is taken as an example, the channel quality, the historical transmission rate, the QCI level of the service and the weight of the service flow of the user equipment are comprehensively considered, and the resource scheduling weight is determined. Taking a data service as a Non-GBR service as an example, the formula for determining the resource scheduling weight may be as follows:
wherein, p (SINR) is a signal quality weight, and a weight value corresponding to SINR can be determined according to an actual application scenario; the p (SINR) is a weight value that positively correlates the resource scheduling weight of the user equipment and the SINR of the user equipment; for example, if the CQI corresponding to the SINR of the user equipment is 2, p (SINR) may be set to 0.2, and if the CQI corresponding to the SINR of the user equipment is 12, p (SINR) may be set to 0.7. One possible way of determining this is to weight the signal quality the better it is; r is a historical transmission rate, and the historical transmission rate can be determined according to the transmission rate of the user in the last statistical period; gamma ray QCI Scheduling priority weighting values for traffic(ii) a And f (delay) is time delay and can be determined by time delay data in the signaling data measured by the base station.
Step three, the cell capacity V max Determined according to the following formula:
wherein, P i The number of the user equipment with the maximum rate corresponding to different SINRs accounts for the proportion of the M user equipment; PR j Scheduling weight for the resource of the jth user equipment corresponding to the ith SINR; k i The number of the user equipment corresponding to the ith SINR is L, and the L is the number of carriers; when the cell is a carrier aggregation cell, L is greater than 1.
In a possible implementation manner, in this embodiment of the present application, the base station may further determine an actual rate of the cell according to traffic actually generated by a user in an MR reporting period, and may determine a resource utilization rate of the cell in the reporting period according to a ratio of the actual rate to a maximum rate. Specifically, the method further comprises:
step one, determining the average throughput rate of the cell in the reporting period according to the flow of the M user equipment in the reporting period;
wherein, the traffic is traffic data of each user equipment in the reporting period, which is included in the signaling data; the user equipment can be distinguished according to the IMSI; the traffic data may be uplink traffic data or downlink traffic data, and may be determined as the uplink average throughput or the downlink average throughput according to the determined average throughput.
The average throughput rate of the cell may be expressed as:
wherein M is the number of users in the reporting period t, F i The traffic generated during the reporting period t is reported for user i.
And step two, determining the resource utilization rate of the cell in the reporting period according to the average throughput rate, the cell capacity and the resource waste weight.
In a possible implementation manner, the resource utilization rate of the cell in the reporting period is determined according to the following formula:
wherein, P T For the resource utilization of the cell, the V a Is the average throughput rate of the cell in the reporting period, the V max The cell capacity of the cell in the reporting period is obtained; the f (t) is the weight of wasting of resources of the cell in the reporting period. For example, the weight of resource waste caused by data retransmission, error code and other factors in the reporting period.
It should be noted that the resource utilization rate may also be determined according to the actual flow generated by the ue in the statistical period, and determine the resource utilization rate of the cell in the statistical period according to the ratio of the actual flow to the maximum flow. The statistical period t may be the reporting period, or may include multiple reporting periods, which is not limited herein.
In this embodiment, the base station may further determine a load index of the cell within the first statistical time according to the cell capacity and the resource utilization rate in the reporting period. Specifically, all resource utilization rates P obtained in the cell may be considered t And performing modeling analysis, namely judging whether the load index of the cell exceeds a preset threshold value according to the calculation result in the step 204, and further determining whether the cell is a high-load cell. For example, when resource utilization P t >P 0 Then, defining the high load of the cell capacity in the reporting period; p 0 Is a preset value of the resource utilization rate of the high-load cell.
Due to the fact that the MR reporting period is short, aggregate analysis can be conducted on the resource utilization rate determined by the reporting period. In a possible implementation manner, the high-load cell may be determined according to N reporting periods, which may specifically be represented as:
wherein, t i Indicating that the cell has high load in the ith reporting period;
when l is>l 0 Then the cell is determined to be a high load cell,/ 0 Is the threshold of a high load cell.
Furthermore, the load influence factor can be determined according to the number of users of the IMSI in the N statistical periods, SINR and other factors, thereby implementing reallocation and scheduling of network resources.
Based on the same inventive concept, the embodiment of the invention also provides a device for determining the cell service support capacity,
as shown in fig. 2, an apparatus for determining cell capacity according to an embodiment of the present invention includes:
an obtaining unit 201, configured to obtain MR data reported by M user equipments in the same cell in a reporting period;
a processing unit 202, configured to determine M SINRs of the M user equipments according to the MR data reported by the M user equipments; determining the maximum rate corresponding to the M SINRs according to the M SINRs; determining corresponding resource scheduling weights in the M user equipment according to the signaling data of the M user equipment measured by the base station in the reporting period; the resource scheduling weight is positively correlated with the SINR of the user equipment; and determining the maximum capacity of the cell according to the maximum rate determined by the SINR of the M user equipment and the resource scheduling weight of the M user equipment.
In a possible implementation manner, the processing unit 202 is specifically configured to:
for any one of the M SINRs, performing: determining a CQI corresponding to the SINR according to the SINR; determining TBS corresponding to the SINR through table look-up according to the RB quantity corresponding to the SINR and the MCS corresponding to the CQI; and determining the maximum rate corresponding to the SINR according to the TBS of the SINR, the time slot number of each TTI and the RI.
A possible implementation manner is to determine the maximum rate V corresponding to the SINR according to the following formula i ：
Wherein, TBS i TBS, N corresponding to ith SINR in the N SINRs S For the number of available time slots in each TTI, t is the time length of the time slot; RI is a rank indication.
In a possible implementation manner, the M SINRs of the M user equipments are determined according to the following formula:
wherein, the SINR d For the downlink SINR, S is the RSRP of the cell, I is the intra-network interference power, determined according to the RSRP of the cell of the neighboring cell, and N is 0 The noise power.
In one possible implementation, the intra-network interference power is determined according to the following formula:
wherein m is the number of neighboring cells of the cell, and the RSRP j Is the RSRP of the jth neighbor cell.
A possible implementation of the method, the cell capacity V max Determined according to the following formula:
wherein, P i User equipment with maximum rate corresponding to different SINRThe number of the user equipments accounts for the proportion of the M user equipments; PR j Scheduling weight for the resource of the jth user equipment corresponding to the ith SINR; k i The number of the user equipment corresponding to the ith SINR is L, and the number of the carriers is L.
In one possible implementation, the processing unit 202 is further configured to:
determining the average throughput rate of the cell in the reporting period according to the flow of the M pieces of user equipment in the reporting period; and determining the resource utilization rate of the cell in the reporting period according to the average throughput rate, the cell capacity and the resource waste weight.
In a possible implementation manner, the resource utilization rate of the cell in the reporting period is determined according to the following formula:
wherein, P T For the resource utilization of the cell, the V a Is the average throughput rate of the cell in the reporting period, the V max The cell capacity of the cell in the reporting period is obtained; the f (T) is the weight of wasting of resources of the cell in the reporting period.
The embodiment of the invention determines the cell capacity based on the SINR quality. The method has the characteristics of strong pertinence and high accuracy. The embodiment of the invention has stronger flexibility and current network adaptability, and forms a complete estimation method of the network capacity. When a network deploys a service, a communication operator can predict how many scales of users can be supported by the existing network resources based on the calculation method provided by the embodiment of the invention, so that a network capacity expansion scheme and a user development strategy are formulated further by combining with a service development target. The method and the device solve the problems that in the prior art, uncertainty of signal quality caused by the fact that the wireless environment where an actual user is located is not considered, the actual bearing capacity of a cell cannot be calculated, the accuracy of cell capacity analysis is low, and the formulation of a subsequent capacity expansion standard is greatly influenced. In addition, the method and the device solve the problems that in the prior art, the network load and the number of users in a period of time can be evaluated only through indexes, the influence of SINR on the cell capacity cannot be distinguished corresponding to different actual SINR of the users in different cells, and the capacity difference analysis of different cells cannot be realized.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (14)
1. A method of determining cell capacity, comprising:
a base station acquires MR data reported by M user equipment in the same cell in a reporting period;
the base station determines M SINRs of the M user equipment according to the MR data reported by the M user equipment;
the base station determines the maximum rate corresponding to the M SINRs according to the M SINRs;
the base station determines corresponding resource scheduling weights in the M user equipment according to the signaling data of the M user equipment measured by the base station in the reporting period; the resource scheduling weight is positively correlated with the SINR of the user equipment;
the base station determines the maximum capacity of the cell according to the maximum rate determined by the SINR of the M user equipment and the resource scheduling weight of the M user equipment;
the cell capacity V max Determined according to the following formula:
wherein, P i The number of the user equipment with the maximum rate corresponding to different SINRs accounts for the proportion of the M user equipment; PR j Scheduling the weight for the resource of the jth user equipment corresponding to the ith SINR; k i The number of the user equipment corresponding to the ith SINR is L, and the number of the carriers is L.
2. The method of claim 1, wherein the base station determines the maximum rate corresponding to the M SINRs according to the M SINRs, and comprises:
for any one of the M SINRs, performing:
the base station determines the CQI corresponding to the SINR according to the SINR;
the base station determines TBS corresponding to the SINR through table look-up according to the RB quantity corresponding to the SINR and the MCS corresponding to the CQI;
and the base station determines the maximum rate corresponding to the SINR according to the TBS of the SINR, the time slot number of each TTI and the RI.
3. The method of claim 2, wherein the maximum rate V corresponding to the SINR is determined according to the following formula i ：
Wherein, TBS i TBS, N corresponding to ith SINR in N SINR S The number of available time slots in each TTI is t, and the time length of the time slot is t; RI is a rank indication.
4. The method of claim 1, wherein the M SINRs for the M user devices are determined according to the following formula:
wherein, the SINR d M downlink SINRs, S is the RSRP of the cell, I is the intra-network interference power, and N is determined according to the RSRP of the cell of the neighboring cell 0 The noise power.
5. The method of claim 4, wherein said in-network interference power is determined according to the following formula:
wherein m is the number of neighbor cells of the cell, and the RSRP j Is the RSRP of the jth neighbor cell.
6. The method of claim 1, wherein the method further comprises:
the base station determines the average throughput rate of the cell in the reporting period according to the flow of the M user equipment in the reporting period;
and the base station determines the resource utilization rate of the cell in the reporting period according to the average throughput rate, the cell capacity and the resource waste weight.
7. The method of claim 6, wherein the resource utilization of the cell in the reporting period is determined according to the following formula:
wherein, P T For the resource utilization of the cell, the V a Is the average throughput rate of the cell in the reporting period, the V max The cell capacity of the cell in the reporting period is obtained; the f (T) is the weight of wasting of resources of the cell in the reporting period.
8. An apparatus for determining cell capacity, comprising:
an obtaining unit, configured to obtain MR data reported by M user equipments in the same cell in a reporting period;
a processing unit, configured to determine M SINRs of the M user equipments according to the MR data reported by the M user equipments; determining the maximum rate corresponding to the M SINRs according to the M SINRs; determining corresponding resource scheduling weights in the M user equipment according to the signaling data of the M user equipment measured by the base station in the reporting period; the resource scheduling weight is positively correlated with the SINR of the user equipment; determining the maximum capacity of the cell according to the maximum rate determined by the SINR of the M user equipment and the resource scheduling weight of the M user equipment;
the cell capacity V max Determined according to the following formula:
wherein, P i The number of the user equipment with the maximum rate corresponding to different SINRs accounts for the proportion of the M user equipment; PR j Scheduling weight for the resource of the jth user equipment corresponding to the ith SINR; k i The number of the user equipment corresponding to the ith SINR is L, and the number of the carriers is L.
9. The apparatus according to claim 8, wherein the processing unit is specifically configured to:
for any one of the M SINRs, performing: determining a CQI corresponding to the SINR according to the SINR; determining TBS corresponding to the SINR through table look-up according to the RB quantity corresponding to the SINR and the MCS corresponding to the CQI; and determining the maximum rate corresponding to the SINR according to the TBS of the SINR, the time slot number of each TTI and the RI.
10. The apparatus of claim 9, wherein the maximum rate V corresponding to the SINR is determined according to the following equation i ：
Wherein, TBS i TBS, N corresponding to ith SINR in N SINR S For availability in each TTIT is the time length of the time slot; RI is a rank indication.
11. The apparatus of claim 8, wherein the M SINRs for the M user devices are determined according to the following formula:
wherein, the SINR d M downlink SINRs, S is the RSRP of the cell, I is the intra-network interference power, and N is determined according to the RSRP of the cell of the neighboring cell 0 The noise power.
12. The apparatus of claim 11, wherein the in-network interference power is determined according to the following equation:
wherein m is the number of neighbor cells of the cell, and the RSRP j Is the RSRP of the jth neighbor cell.
13. The apparatus as recited in claim 8, said processing unit to further:
determining the average throughput rate of the cell in the reporting period according to the flow of the M pieces of user equipment in the reporting period; and determining the resource utilization rate of the cell in the reporting period according to the average throughput rate, the cell capacity and the resource waste weight.
14. The apparatus of claim 13, wherein the resource utilization of the cell in the reporting period is determined according to the following formula:
wherein, P T For the resource utilization of the cell, the V a Is the average throughput rate of the cell in the reporting period, the V max The cell capacity of the cell in the reporting period is set; the f (T) is the weight of wasting of resources of the cell in the reporting period.
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| CN114828050B (en) * | 2022-05-10 | 2024-04-30 | 中国联合网络通信集团有限公司 | Method, device, equipment and medium for determining service capacity |
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101461267A (en) * | 2006-06-12 | 2009-06-17 | 艾利森电话股份有限公司 | Method in a scheduler for reducing inter-cell interference |
| CN106878086A (en) * | 2017-03-06 | 2017-06-20 | 北京理工大学 | A kind of VoLTE video callings user experience quality appraisal procedure |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9060287B2 (en) * | 2013-03-11 | 2015-06-16 | Rohde & Schwarz Gmbh & Co. Kg | Measuring device and measurement method for non-intrusive throughput measurement in communication networks |
| US9794825B2 (en) * | 2014-11-06 | 2017-10-17 | Alcatel-Lucent Usa Inc. | System and method for determining cell congestion level |
| US20160165472A1 (en) * | 2014-12-09 | 2016-06-09 | Futurewei Technologies, Inc. | Analytics assisted self-organizing-network (SON) for coverage capacity optimization (CCO) |
-
2018
- 2018-03-19 CN CN201810225419.5A patent/CN110290540B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101461267A (en) * | 2006-06-12 | 2009-06-17 | 艾利森电话股份有限公司 | Method in a scheduler for reducing inter-cell interference |
| CN106878086A (en) * | 2017-03-06 | 2017-06-20 | 北京理工大学 | A kind of VoLTE video callings user experience quality appraisal procedure |
Non-Patent Citations (2)
| Title |
|---|
| 吉林移动TD-LTE网络深度覆盖评估与精细优化方案;陈力等;《通信世界》;20160225(第05期);全文 * |
| 运营商适应移动互联网时代的运营支撑体系建构之探索;陈志刚等;《移动通信》;20100323(第06期);全文 * |
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