CN113747455A

CN113747455A - Network optimization method and device

Info

Publication number: CN113747455A
Application number: CN202010461526.5A
Authority: CN
Inventors: 彭真; 柯腾辉; 房晨; 程亮; 戴鹏; 苗岩; 周壮; 李涛
Original assignee: China United Network Communications Group Co Ltd
Current assignee: China United Network Communications Group Co Ltd
Priority date: 2020-05-27
Filing date: 2020-05-27
Publication date: 2021-12-03

Abstract

The embodiment of the invention provides a network optimization method and a device, wherein the method comprises the following steps: acquiring the physical resource block PRB utilization rate of a first cell according to a preset time interval; when the PRB utilization rate of the first cell is higher than a first threshold value, acquiring performance data of a second cell, wherein the distance between the second cell and the first cell is smaller than the first threshold value, and the performance data of the second cell is used for indicating the network state of the second cell; and adjusting the cell parameters of the second cell according to the performance data of the second cell, wherein the cell parameters comprise reference signal power, or the cell parameters comprise reference signal power and physical cell identification. The scheme provided by the embodiment of the invention has high real-time performance, does not need to manually predict the network load, and has good network optimization effect.

Description

Network optimization method and device

Technical Field

The embodiment of the invention relates to the technical field of communication, in particular to a network optimization method and device.

Background

In a Long Term Evolution (LTE) network, network optimization is an essential step for maintaining normal operation of the network. By optimizing the network, the high-efficiency and healthy operation of the network can be guaranteed.

In the existing network optimization scheme, network optimization personnel optimize the network based on various data and optimization tools, and the scheme needs the network optimization personnel to estimate network loads at different time intervals, so that the network is adjusted according to the estimated network loads. However, the user terminals in the network may exhibit different geographical location distributions due to different periods of work and rest, so that the conformity of the entire network exhibits a great distribution difference with time. The network load estimation in different time periods by network optimization personnel is not accurate, so that the network optimization effect is poor.

Disclosure of Invention

The embodiment of the invention provides a network optimization method and device, aiming at solving the problem of poor network optimization effect of the existing scheme.

In a first aspect, an embodiment of the present invention provides a network optimization method, including:

acquiring the physical resource block PRB utilization rate of a first cell according to a preset time interval;

when the PRB utilization rate of the first cell is higher than a first threshold value, acquiring performance data of a second cell, wherein the distance between the second cell and the first cell is smaller than the first threshold value, and the performance data of the second cell is used for indicating the network state of the second cell;

and adjusting the cell parameters of the second cell according to the performance data of the second cell, wherein the cell parameters comprise reference signal power, or the cell parameters comprise reference signal power and physical cell identification.

In one possible implementation, before the obtaining of the performance data of the second cell, the method further includes:

acquiring performance data of the first cell, where the performance data of the first cell is used to indicate a network state of the first cell, and the performance data of the first cell includes a PRB utilization rate of the first cell;

and determining that the performance data of the first cell meets a first preset condition.

In one possible implementation, the performance data of the first cell further includes a channel environment quality sample value, a reference signal received power sample value, and a delay sample value of the first cell;

the first preset condition is as follows:

the channel environment quality sampling value of the first cell is smaller than a first channel environment quality preset value;

the reference signal received power sampling value of the first cell is greater than a first reference signal received power preset value;

and the time delay sampling value of the first cell is greater than a first time delay preset value.

In one possible implementation, before the adjusting the cell parameter of the second cell according to the performance data of the second cell, the method further includes:

determining that the performance data of the second cell meets a second preset condition, wherein the second preset condition is as follows:

and the PRB utilization rate of the second cell is lower than a second threshold value.

In one possible implementation, adjusting the cell parameter of the second cell according to the performance data of the second cell includes:

acquiring the number of connected users of the second cell;

and aiming at any one second cell, adjusting the cell parameters of the second cell according to the number of the connected users of the second cell.

In a possible implementation manner, the adjusting the cell parameter of the second cell according to the number of connected users of the second cell includes:

if the number of the connected users of the second cell does not exceed a second threshold, reducing the reference signal power of the second cell;

and if the number of connected users of the second cell exceeds the second threshold, reducing the reference signal power of the second cell and/or modifying the physical cell identifier of the second cell.

acquiring the PRB utilization rate of a third cell, wherein the third cell is a cell located in the same sector as the first cell;

determining that the first cell is in a load balancing state according to the PRB utilization rate of the first cell and the PRB utilization rate of the third cell, wherein the load balancing state indicates that the difference value between the PRB utilization rate of the first cell and the PRB utilization rate of the third cell is smaller than a third threshold value.

In a second aspect, an embodiment of the present invention provides a network optimization apparatus, including:

the acquisition module is used for acquiring the Physical Resource Block (PRB) utilization rate of the first cell according to a preset time interval;

a processing module, configured to obtain performance data of a second cell when a PRB utilization of the first cell is higher than a first threshold, where a distance between the second cell and the first cell is smaller than a first threshold, and the performance data of the second cell is used to indicate a network state of the second cell;

an optimization module, configured to adjust a cell parameter of the second cell according to the performance data of the second cell, where the cell parameter includes a reference signal power, or the cell parameter includes a reference signal power and a physical cell identifier.

In a possible implementation manner, the obtaining module is further configured to, before the obtaining of the performance data of the second cell:

the first preset condition is as follows:

In a possible implementation manner, the optimization module is further configured to, before the adjusting the cell parameter of the second cell according to the performance data of the second cell:

In a possible implementation manner, the optimization module is specifically configured to:

acquiring the number of connected users of the second cell;

In a possible implementation manner, the processing module is further configured to, before the obtaining of the performance data of the second cell:

In a third aspect, an embodiment of the present invention provides a network optimization device, including: at least one processor and memory;

the memory stores computer-executable instructions;

the at least one processor executing the computer-executable instructions stored by the memory causes the at least one processor to perform the network optimization method of any of the first aspects.

In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where computer-executable instructions are stored, and when a processor executes the computer-executable instructions, the network optimization method according to any one of the first aspect is implemented.

The network optimization method and device provided by the embodiment of the invention firstly obtain the PRB utilization rate of a first cell according to a preset time interval, then confirm that the first cell is in a high-load state when the PRB utilization rate of the first cell is higher than a first threshold value, further obtain the performance data of a second cell of which the distance from the first cell is smaller than the first threshold value, obtain the network state of the second cell, and finally adjust the parameters of the second cell according to the performance data of the second cell, wherein the interference of the second cell to the first cell is reduced by adjusting the reference signal power or the physical cell identifier of the second cell, so that the resource utilization rate of the first cell is improved, the communication rate with a user terminal in the first cell is improved, and the effect of reducing the network load of the first cell is achieved. According to the scheme provided by the embodiment of the invention, the process is periodically executed, so that the network load of the first cell is monitored in real time, and when the first cell is overloaded, the network optimization is carried out on the first cell, the network load of the first cell at different time intervals does not need to be estimated manually, the real-time performance is higher, and the network optimization effect is better.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.

Fig. 1 is a schematic view of an application scenario provided in an embodiment of the present invention;

fig. 2 is a schematic flowchart of a network optimization method according to an embodiment of the present invention;

fig. 3 is a schematic flow chart of a network optimization method according to another embodiment of the present invention;

FIG. 4 is a schematic diagram of a base station cell according to an embodiment of the present invention;

fig. 5 is a first schematic diagram of cell terminal connection according to an embodiment of the present invention;

fig. 6 is a schematic diagram of a cell terminal connection according to an embodiment of the present invention;

FIG. 7 is a schematic diagram of an operation class set according to an embodiment of the present invention;

fig. 8 is a schematic structural diagram of a network optimization apparatus according to an embodiment of the present invention;

fig. 9 is a schematic diagram of a hardware structure of a network optimization device according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

First, the concept to which the present invention relates will be explained.

Physical Resource Block (PRB) utilization: the load level of a cell can be represented for the occupation situation of a physical resource block in an LTE carrier.

Reference Signal Receiving Power (RSRP): the parameter is a key parameter representing the wireless signal strength in the LTE network, and the greater the value is, the better the wireless signal strength is.

Time delay (Timing Advance, TA for short): generally, the method is used for UE uplink transmission, and means that in order to enable a UE uplink packet to reach an eNB at a desired time, a radio frequency transmission delay caused by a distance is estimated, and a data packet is sent out at a corresponding time in advance.

Channel Quality indication (CQI for short): the information indication of the channel quality represents the quality of the current channel, the higher the CQI is, the better the channel quality is, and the lower the CQI is, the worse the channel quality is.

Radio Resource Control (RRC) refers to performing Radio Resource management, Control and scheduling by using a certain strategy and means, and making full use of limited Radio network resources under the condition of meeting the requirement of service quality, so as to ensure that the Radio Resource Control (RRC) reaches a planned coverage area, and improve service capacity and Resource utilization rate as much as possible.

Fig. 1 is a schematic view of an application scenario provided by an embodiment of the present invention, as shown in fig. 1, including a base station 10, a first cell 11 and a second cell 12, where the first cell 10 is in a coverage area of the base station 10, and the base station 10 is responsible for contact and control of mobile communication in the coverage area.

The second cell 12 may be located in a coverage area of the same base station as the first cell 11, or may be located in a coverage area of a different base station from the first cell 11, and a distance between the first cell 11 and the second cell 12 is within a certain range, so that the second cell 12 forms a neighboring cell to the first cell 11, and the number of the second cells 12 is one or more, that is, the number of the neighboring cells of the first cell 11 is one or more.

At the edge of the first cell 11 and the second cell 12, there may be a partial area that belongs to the range of both the first cell 11 and the second cell 12, causing signal interference between the two cells.

When the signal interference between the first cell 11 and the second cell 12 is strong, the user terminal in the cell needs to raise the transmission power to be able to meet the demodulation threshold that the signal reaching the base station 10 meets, so that the coverage area of the cell is reduced, and the capacity is reduced.

For the first cell 11, when the load of the first cell 11 is high, in order to alleviate the network load of the first cell 11, the embodiment of the present invention adopts a scheme that, on the premise of not affecting the communication of the user terminal of the second cell 12, the reference signal power of the second cell 12 is appropriately reduced, and the coverage area of the second cell 12 is reduced, so as to reduce the signal interference of the second cell 12 to the first cell. By the above method, the network coverage of the first cell 11 is improved, the signal quality and the communication speed in the first cell 11 are improved, and the effect of relieving the network load of the first cell 11 is achieved.

Hereinafter, the technical means shown in the present disclosure will be described in detail by specific examples. It should be noted that the following embodiments may be combined with each other, and the description of the same or similar contents in different embodiments is not repeated.

Fig. 2 is a schematic flow chart of a network optimization method according to an embodiment of the present invention, as shown in fig. 2, including:

and S21, acquiring the PRB utilization rate of the physical resource block of the first cell according to the preset time interval.

In the embodiment of the invention, the load of the first cell is reflected by the utilization rate of the PRB. For any first cell, the PRB utilization rate of the first cell is obtained according to a preset time interval, which may be set according to actual needs, for example, the PRB utilization rate of the first cell in a certain period may be obtained at the preset time interval, and an average value is obtained, and the PRB utilization rate of the first cell at a certain time may also be used.

Because the utilization rate of the PRB is dynamically changed, the acquisition of the utilization rate of the PRB is also dynamic in the embodiment of the invention. After the preset time interval is set, the PRB utilization rate of the first cell can be obtained again at regular intervals, so that the load level of the first cell can be dynamically grasped.

S22, when the PRB utilization of the first cell is higher than a first threshold, acquiring performance data of a second cell, where a distance between the second cell and the first cell is smaller than a first threshold, and the performance data of the second cell is used to indicate a network state of the second cell.

In the embodiment of the present invention, when the PRB utilization of the first cell is higher than the first threshold, the first cell is considered to be in a high load state, and network optimization is required. And when the PRB utilization rate of the first cell is not higher than a first threshold value, the first cell is not considered to be in a high-load state, and the network optimization of the first cell is not needed.

The second cell is a neighboring cell of the first cell, that is, a cell whose distance from the first cell is smaller than a first threshold, where the first threshold is a preset value. When the PRB utilization rate of the first cell is higher than a first threshold value, network optimization needs to be performed on the first cell, at the moment, performance data of the second cell is obtained, and the performance data of the second cell indicates the network state of the second cell.

The second cell may be adjusted appropriately according to the network status of the second cell, thereby adjusting the load of the first cell.

S23, adjusting a cell parameter of the second cell according to the performance data of the second cell, where the cell parameter includes a reference signal power, or the cell parameter includes a reference signal power and a physical cell identifier.

Variations in reference signal power can affect the coverage of a cell. When the reference signal power of the second cell is reduced, the coverage area of the second cell can be correspondingly reduced, so that the signal interference of the second cell to the first cell is reduced.

The physical cell identifier is used for distinguishing wireless signals of different cells, and the same physical cell identifier is ensured not to exist in the coverage area of the related cell. In practice, it is inevitable to multiplex physical cell identifiers, which may cause collision of the same physical cell identifiers due to too small multiplexing distance. When the first cell and the second cell generate interference between downlink signals of the two cells due to the same physical cell identity, correct synchronization and decoding service of user terminals in the cells are affected. At this time, by adjusting the physical cell identifier of the second cell, it is possible to avoid collision due to too small multiplexing distance of the same physical cell identifier, thereby reducing interference of the second cell to the first cell.

Therefore, by adjusting the cell parameters of the second cell, the signal interference of the second cell to the first cell can be reduced, so that the resource utilization rate of the first cell is improved, the communication rate between the first cell and the user terminal is improved, and the high-load network state of the first cell is relieved.

The network optimization method provided by the embodiment of the invention includes the steps of firstly obtaining the PRB utilization rate of a first cell according to a preset time interval, then confirming that the first cell is in a high-load state when the PRB utilization rate of the first cell is higher than a first threshold value, further obtaining performance data of a second cell, the distance between the second cell and the first cell is smaller than the first threshold value, obtaining the network state of the second cell, and finally adjusting the parameters of the second cell according to the performance data of the second cell, wherein the interference of the second cell to the first cell is reduced by adjusting the reference signal power or the physical cell identification of the second cell, so that the resource utilization rate of the first cell is improved, the communication rate between the first cell and a user terminal is improved, and the effect of reducing the network load of the first cell is achieved. According to the scheme provided by the embodiment of the invention, the process is periodically executed, so that the network load of the first cell is monitored in real time, and when the first cell is overloaded, the network optimization is carried out on the first cell, the network load of the first cell at different time intervals does not need to be estimated manually, the real-time performance is higher, and the network optimization effect is better.

The technical means of the present invention will be described in detail below with specific examples based on the above-described examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.

Fig. 3 is a schematic flow chart of a network optimization method according to another embodiment of the present invention, as shown in fig. 3, including:

s31: and periodically monitoring the load of each cell under the current base station, and starting an optimization process when the load of the cell is monitored to be high.

And aiming at any one first cell, periodically acquiring the PRB utilization rate of the first cell, and judging the load of the first cell according to the PRB utilization rate. Specifically, a period Tc may be set, where Tc is a preset time interval, the PRB utilization rate of the first cell is obtained every time Tc, the load level of the first cell is determined, and the index representing the real-time load of the first cell is defined as the average downlink PRB utilization rate of the cell in the monitoring period Tc.

Specifically, the index monitoring of the downlink PRB utilization rate is performed on the first cell under the base station with a period Tc, and the average downlink PRB utilization rate of the first cell in the period Tc is calculated:

wherein x_prbAnd representing one downlink PRB utilization sampling value of the first cell in the period Tc, and n represents the total sampling times.

To be calculated

And a preset PRB utilization rate high gateLimit Threshold_{prb_high}And (6) comparing.

When in use

Namely, the first cell is considered to have high load, an optimization process needs to be started, and the next judgment process is started. Wherein is Threshold_{prb_high}The first threshold value can be flexibly set for a preset threshold parameter, namely the first threshold value, so that the optimization process can be started under different load levels.

S32: and judging whether the load of the first cell is balanced, if so, performing S33, and if not, performing load balancing operation.

Specifically, the PRB utilization rate of a third cell is first obtained, where the third cell is a cell located in the same sector as the first cell.

And then determining that the first cell is in a load balancing state according to the PRB utilization rate of the first cell and the PRB utilization rate of the third cell, wherein the load balancing state indicates that the difference value between the PRB utilization rate of the first cell and the PRB utilization rate of the third cell is smaller than a third threshold value.

Fig. 4 is a schematic diagram of a base station cell provided in an embodiment of the present invention, as shown in fig. 4, generally, a base station includes 3 cells, each cell covers an area of about 120 degrees, that is, each cell corresponds to a sector of about 120 degrees, and provides communication service for a user terminal within a coverage area of the sector.

In order to alleviate the load of each cell in the base station, in the example of fig. 4, two or more cells may be set in each sector, for example, in fig. 4, a third cell, i.e., cell C, is also included in the sector where cell B is located, and the third cell is an inter-frequency neighboring cell that is in the same sector as the first cell.

When the load of the first cell is high, the load of the third cell is judged firstly, and whether the two cells are in a load balanced state or in a load unbalanced state is judged according to the PRB utilization rate of the third cell and the first cell.

The load imbalance means: first cell and same sectorThe difference of the utilization rates of the downlink PRBs of the third cell of the frequency adjacent cell in the monitoring period Tc exceeds a preset difference Threshold, i.e. a third Threshold_Δprb。

Specifically, the average downlink PRB utilization rate of the first cell and the third cell of the pilot frequency adjacent cell in the same sector as the first cell in the period Tc is differentiated, and the absolute value delta PRB of the final difference result and a preset PRB difference Threshold are set to be a third Threshold_ΔprbAnd (6) comparing.

If Δ prb ≧ Threshold_ΔprbIf the first cell and the third cell are not in the same load distribution, prompting the optimization personnel to intervene manually, marking the first cell, and not monitoring the first cell within the next period Tc. If Δ prb < Threshold_ΔprbIf the load distribution of the first cell and the third cell is balanced, the process proceeds to the next step.

S33: collecting and storing configuration data and performance data of a first cell in real time; performance data of the second cell is collected and stored in real time.

Firstly, acquiring performance data of a first cell, wherein the performance data of the first cell is used for indicating the network state of the first cell, and the performance data of the first cell comprises a PRB utilization rate of the first cell, a channel environment quality sampling value, a reference signal receiving power sampling value and a time delay sampling value of the first cell;

specifically, the configuration data of the first Cell is acquired, including but not limited to pci (physical Cell identifier) information and neighbor list information; the performance data of the first cell is obtained, including but not limited to CQI, TA sampling information, RSRP sampling point value information within a period Tc. The neighbor performance data includes, but is not limited to, a sampling value of downlink PRB utilization rate, a sampling value of TA, the number of RRC connection users, and a value of RSRP sampling point within time Tc.

Starting a period Ts, receiving and storing a CQI sampling value, a RSRP sampling value and a TA sampling value reported by a first cell in the period Ts; and acquiring the neighbor list information of the first cell, namely the list information of the second cell, wherein the list information comprises but is not limited to a second cell ID, a second cell number, a second cell PCI and the like, and the power of the second cell and the like.

And meanwhile, receiving and storing the downlink PRB utilization rate, the RRC connection user number, the RSRP sampling point value and the TA sampling value reported by the second cell in the period Ts. The period Ts and the period Tc may be separately and individually set for each cell, and different values may be configured according to an actual optimization procedure.

The CQI is an information indication of the channel quality, represents the quality of the current channel, and has a value range of 0-31, when the value of the CQI is 0, the channel quality is the worst, and when the value of the CQI is 31, the channel quality is the best.

The RSRP is a key parameter which can represent the wireless signal strength in the LTE network, the value range is-44 dBm to-140 dBm, and the larger the value is, the better the wireless signal strength is.

The TA is generally used for UE uplink transmission, and means to estimate a radio frequency transmission delay caused by a distance in order to make an uplink packet of the UE arrive at the eNB at a desired time, and send a data packet at a corresponding time in advance, where the TA takes a value of 0 to 1282 in a random access process, and the TA takes a value of 0 to 63 in a service. One TA characterizes the distance 78.12 meters.

The PRB utilization rate is the occupation condition of a physical resource block in an LTE carrier, and can represent the load level of a cell.

S34: and judging whether the first cell meets a judgment threshold of starting the data of the adjacent cell in a time period Ts or not according to the performance data of the first cell, if so, executing S35, otherwise, executing S33, and receiving the data of the next period.

If it is determined whether the performance data of the first cell meets the threshold for starting the data of the neighboring cell, it is determined whether the performance data of the first cell meets a first preset condition, where the first preset condition is:

and the time delay sampling value of the first cell is greater than the first time delay preset value.

Specifically, firstly, the received and stored data is calculated and analyzed, and the average value of the CQI sampling values of the first cell in the period Ts is calculated:

wherein x_cqiRepresenting a single CQI sample value, r representing the total number of CQI samples, will

As a channel environment quality sample value of the first cell.

Calculating the RSRP sampling point of the first cell in a period Ts within a certain preset range [ a ]₁,b₁]The internal proportion is as follows:

wherein [ a, b]For a preset RSRP value range, y_a≤RSRP≤bFor one sample point value, p is the total number of RSRP sample points, and Y is_{RSRP_s_Ts}As a reference signal received power sample value for the first cell.

Calculating the proportion of TA of the first cell in a certain preset range [ c, d ] in a period Ts:

wherein [ c, d]For a preset TA distribution range, z_c≤TA≤dFor one sampling point value, q is the total number of TA sampling points, and Z is_{TA_s_Ts}As a delay sample value for the first cell.

Averaging CQI sampled in a first cell period Ts

RSRP sampling in the range [ a, b]Ratio Y of_{RSRP_s_Ts}And TA in the range [ c, d ] at the sampling point]Ratio Z of_{TA_s_Ts}And judging with preset starting adjacent area dataAnd (3) comparing and judging the threshold breaking parameters, namely when:

and when:

Y_{RSRP_s_Ts}＞Threshold_{star2_prb}，

and when:

Z_{TA_s_Ts}＞Threshold_{star3_ta}starting a next judgment process for the adjacent area data; otherwise, continuing to receive and store the data of the first cell and the second cell adjacent to the first cell in the next period Ts.

For judging the quality of the wireless environment of the first cell when

The wireless environment of the first cell is considered to be poor, and the use perception of the user is influenced.

Y_{RSRP_s_Ts}And Z_{TA_s_Ts}Used for judging whether the user distribution is distributed at the edge of the cell or not, when Y is_{RSRP_s_Ts}＞Threshold_{star2_prb}And Z is_{TA_s_Ts}＞Threshold_{star3_ta}The proportion of the signal strength of the position of the user in the first cell in the preset range is larger than the threshold value, and the proportion of the user in the distance range set by the base station is larger than the threshold value. The two are satisfied simultaneously, which means that the user is close to the base station and the received signal strength is enough, i.e. the cell user distribution is reasonably concentrated.

So when

And when Y is_{RSRP_s_Ts}＞Threshold_{star2_prb}And when Z is_{TA_s_Ts}＞Threshold_{star3_ta}When the first cell performance data meets the first preset condition, the cell users are considered to be distributed reasonably and intensively but have informationThe problem of poor environment needs to be further solved by optimizing the process, and the situation of poor channel environment caused by weak coverage formed due to unreasonable user distribution is eliminated.

Threshold parameter Threshold_{star1_CQI}、Threshold_{star2_prb}And Threshold_{star3_ta}The adjustment can be preset according to the accuracy of the optimization, wherein Threshold_{star1_CQI}Is a preset value of the environmental quality of the first channel, Threshold_{star2_prb}For a first reference signal received power preset value, Threshold_{star3_ta}Is a first delay preset value.

S35: and judging whether the performance data of the second cell meets a second preset condition, if so, executing S36, and otherwise, performing the judgment on the next second cell.

Firstly, the statistical indexes of the second cell are sequentially judged, and whether the performance data of the second cell meet a second preset condition in a statistical time period Ts is judged. If the performance data of the second cell is determined to meet a second preset condition, wherein the second preset condition is as follows:

the PRB utilization of the second cell is lower than a second threshold value.

Specifically, the obtained and stored data of the neighboring cell (a second cell) is sequentially determined according to the neighboring cell number in the stored first cell neighboring cell list obtained and stored in S33.

Calculating the average value of the downlink PRB utilization rate of the adjacent cell i in the period Ts:

wherein x is_prbAnd representing a sampling value of the one-time downlink PRB utilization rate of the adjacent cell i, wherein m represents the total sampling times, and the adjacent cell i is a second cell.

The average value of PRB utilization rate of the adjacent cell i in Ts and a second Threshold value Threshold _1_{ex_prb}Make a comparison, i.e. when

When entering the next stepStep (4) judging the flow; otherwise, skipping the adjacent cell i, and continuing to judge the second cell of the next adjacent cell number in the adjacent cell list.

Wherein

Characterizing the load level, Threshold _1, of the neighbor i in a period Ts_{ex_prb}Is a second threshold value when

The load in the period Ts is considered to be low, and the load can be preliminarily taken as a neighbor object to be optimized. Threshold _1_{ex_prb}The threshold parameter can be preset and adjusted according to the accuracy of optimization.

S36: and continuing to judge the adjacent cell meeting the condition of S35, and if the number of the connected users in the statistical time period Ts of the adjacent cell i does not exceed a second threshold, if so, executing S37.1, and if not, executing S37.2.

Firstly, acquiring the number of connected users of a second cell, and then adjusting cell parameters of the second cell according to the number of connected users of the second cell aiming at any second cell.

Fig. 5 is a first schematic diagram of cell terminal connection according to an embodiment of the present invention, as shown in fig. 5, including a second cell 51, where the second cell 51 is under the coverage of a base station. A plurality of UEs are included in the second cell 51, and the number of UEs exceeds the second threshold.

Fig. 5 illustrates a situation where the second cell has a lower load, that is, the number of connected users in the second cell is larger and exceeds the second threshold, but the UEs in the second cell are all performing some communication activities with smaller network traffic, such as social chat.

The resource occupation of each UE is small, so although the number of the UEs is large, the total resource occupation is still small, and the PRB utilization rate of the second cell can still be lower than the second threshold value.

Fig. 6 is a schematic diagram of a cell terminal connection according to an embodiment of the present invention, as shown in fig. 6, including a second cell 61, where the second cell 61 is under the coverage of one base station. A plurality of UEs are included in the second cell 61, and the number of UEs does not exceed the second threshold.

Fig. 6 illustrates another situation where the second cell has a low load, that is, the number of connected users in the second cell is small, the second threshold is not exceeded, and the UEs in the second cell are all performing some communication activities with small network traffic, such as social chat.

The resource occupation of each UE is very small, and the number of connected users is also small, so that the total resource occupation is still very small, and the PRB utilization rate of the second cell can still be lower than the second threshold value.

Although both cases illustrated in fig. 5 and fig. 6 can make the PRB utilization rate of the second cell small, different processing needs to be performed on the second cell for different cases.

For the adjacent cell i meeting the second preset condition in the S35, calculating the average value of the number of RRC connection users in the period Ts of the adjacent cell i

Wherein x_rrcAnd (4) a sampling value representing the number of users of one RRC connection in the adjacent region i, and s represents the total sampling times.

Then, the average value of the number of RRC connection users in the adjacent cell i in the period Ts and a second Threshold value Threshold _2 are used_{ex_rrc}Make a comparison, i.e. when

Then, the next step is carried out to judge the flow S37.1; when in use

Then, the process proceeds to the next step of decision step S37.2.

Wherein Threshold _2_{ex_rrc}Is a preset comparison parameter, the average value of the number of RRC connection users in the adjacent cell i in the period Ts passes through Threshold _2_{ex_rrc}And comparing to control the proportional distribution of the entering operation type set I and the operation type set pi.

S37.1: and adding the second cell into the operation type set I.

And adding the second cell which meets the second preset condition and the number of connected users does not exceed a second threshold value into the operation class set I, wherein the second cell i which meets the second preset condition and the number of connected users does not exceed the second threshold value simultaneously means that the load level and the user level of the second cell i are both in extremely low value bits in the period Ts, and almost no business activity is shown.

S37.2: and judging whether the performance data of the second cell meets the execution threshold A, if so, executing S37.3.

Wherein the execution threshold a is used to determine whether the user distribution in the second cell is reasonable. When the users in the second cell are reasonably distributed, it is indicated that the user distribution in the second cell is relatively concentrated, that is, there are fewer user terminals distributed at the edge of the second cell, and at this time, the cell parameters of the second cell are adjusted, so that the communication of the user terminals in the second cell is not greatly affected. On the contrary, if the user distribution in the second cell is not reasonable, the cell parameters of the second cell cannot be directly adjusted, otherwise, the communication quality of the user terminal at the edge of the second cell is affected.

Calculating the ratio of the RSRP sampling point in a certain preset range [ e, f ] in the period Ts of the second cell i which satisfies the second preset condition in the S35 but does not satisfy the condition that the number of the connected users in the S36 does not exceed a second threshold value:

and e and f are preset RSRP value ranges, the calculation accuracy can be changed by adjusting the range, and t is the total number of RSRP sampling points of the adjacent cell i in a time period Ts.

Calculating the proportion of TA in a certain preset range [ g, h ] of the adjacent region i in a period Ts:

wherein [ g, h]For a preset TA distribution range, z_g≤TA≤hIs a sampling point value, and u is the total number of TA sampling points.

Sampling the RSRP of the adjacent cell i in the period Ts in the range [ e, f]Ratio Y of_{RSRP_n_Ts}And TA in [ g, h]Ratio Z within the range_{TA_n_Ts}And preset Threshold _3_{ex1_rsrp}、Threshold_3_{ex2_ta}Making a comparison, i.e. when Y_{RSRP_n_Ts}≥Threshold_3_{ex1_rsrp}And Z is_{TA_n_Ts}≥Threshold_3_{ex2_ta}And then, the next judgment is carried out. Otherwise, skipping the adjacent cell i, and continuing to judge the second cell of the next adjacent cell number in the adjacent cell list.

Wherein the execution threshold a comprises: threshold _3_{ex1_rsrp}The preset cell RSRP sampling point value is in a certain range [ e, f]Threshold _3, the Threshold parameter of the internal proportion_{ex2_ta}For the preset TA is distributed in [ g, h ]]The threshold parameter is used for comparing with the TA sampling value proportion of the adjacent area in a certain section range.

When Y is_{RSRP_n_Ts}≥Threshold_3_{ex1_rsrp}And Z is_{TA_n_Ts}≥Threshold_3_{ex2_ta}The time indicates that the proportion of the signal intensity of the position of the user in the cell in the preset range is larger than the set threshold value, and the proportion of the user in the distance range set by the base station is larger than the threshold value, that is, the cell users are reasonably distributed and concentrated, and the influence of optimization measures on the users distributed at the edge of the cell is avoided.

S37.3: and adding the second cell into the operation class II.

And adding an operation class set pi to the neighbor cell in which the neighbor cell i meets the execution threshold A in S37.2, wherein the neighbor cell i meeting the execution threshold A in S37.2 means that the load level of the neighbor cell i is at an extremely low value within the period Ts, and only a small amount of services are in process.

Fig. 7 is a schematic diagram of an operation class set according to an embodiment of the present invention, as shown in fig. 7, including a set 70, where the set 70 includes a sub-set 71 and a sub-set 72, where the sub-set 71 is an operation class set I, and the sub-set 72 is an operation class set Π.

The subset 71 includes a plurality of neighboring cells, where a neighboring cell is a second cell, and the neighboring cells in the subset 71 are cells that satisfy a second preset condition and the number of connected users does not exceed a second threshold, which indicates that the neighboring cells in the subset 71 are cells whose load level and user level are both at an extremely low value within a period Ts, and there is almost no service activity.

The subset 72 includes a plurality of neighboring cells, where a neighboring cell is a second cell, and the neighboring cells in the subset 72 are cells that satisfy a second preset condition, the number of connected users exceeds a second threshold, and the execution threshold a is met, which indicates that the neighboring cells in the subset 72 are cells with a load level at an extremely low value within a period Ts, and only have a small amount of service activities.

S38: and after the traversal of the adjacent cell is finished, executing corresponding operation on the second cell in the formed operation class set.

For a second cell in the operation class I set, the number of connected users of the second cell does not exceed a second threshold, and at this time, the reference signal power of the second cell is reduced.

And aiming at a second cell in the II-type operating set, if the number of connected users of the second cell exceeds a second threshold value, reducing the reference signal power of the second cell and/or modifying the physical cell identifier of the second cell.

Specifically, after the neighbor traversal is finished, the modification action is automatically triggered, and the neighbor is marked:

for the cells in the formed operation class set i, almost no service is performed. Therefore, for the cell j in the operation type set I, the reference signal power is reduced by 3dB but not lower than P_{rs_power_low}(ii) a Meanwhile, dividing the PCI value of the first cell and the PCI value of the adjacent cell j by 3 to obtain the remainder, respectively obtaining the modulo three numbers of the first cell and the adjacent cell j, and if the modulo three numbers of the first cell and the adjacent cell j are equal, carrying out PCI modification on the cell j; if the two modulo three numbers are not equal, no operation is performed. After the cell j in the operation class set I finishes the parameter modification action, the counter N_modifyPlus 1, mark field S for cell j_modifyIf the adjacent cell j has PCI modifying action, the marking field S is set as 0_{modify_pci}And simultaneously saving the original PCI value of the cell j to the memory as 1.

For the cells in the formed set of operational classes Π,there is still a small amount of traffic, reducing its reference signal power by 3dB, but not below P_{rs_power_low}. After the cell j in the operation class II finishes the parameter modification action, the counter N_modifyPlus 1, mark field S for cell j_modify＝1。

The PCI modification action specifically includes: and dividing the PCI value of the first cell and the PCI value of the adjacent cell i by 3 to obtain the remainder, respectively obtaining the modulus three numbers of the first cell and the adjacent cell i, comparing the modulus three number of the adjacent cell i with the modulus three number of the first cell, and randomly giving the adjacent cell i by selecting the reserved PCI which is different from the modulus three number of the first cell. One possible but not exclusive approach is: reserving PCIs as 0, 1 and 2, and the corresponding third modules as 0, 1 and 2; if the modulo-three number of the first cell is 0, the reserved PCI may be randomly given to the neighbor i as 1 or 2.

In addition, a mark S_modifyIn order to identify the field of the cell which is dynamically optimized and adjusted, the field of the cell which is not optimized is empty; sign S_{modify_pci}Is to identify if the cell has performed a PCI modify action, S_{modify_pci}If the cell is empty, the cell does not perform the PCI modification action; p_{rs_power_low}Ensuring that the power of the cell reference signal is set with a guarantee parameter in a reasonable range, wherein the parameter is a cell parameter, and each cell can be separately and independently set according to different optimization precisions; counter N_modifyIs to mark the number of dynamic optimization adjustments made to the cell.

S39: and the execution is finished, the performance data stored in the previous period is cleared, and S31 is executed to continue monitoring the load information of the first cell in the next period.

The execution action is completed, the optimization cycle is ended, the data stored in the optimization cycle is cleared, but the mark field S is reserved_modify、S_{modify_pci}And counter N_modifyAnd continuously monitoring the load information of the first cell in the next period Tc.

In the period Tc, the first cell under the current base station monitors the index of the utilization rate of the downlink PRB in the period Tc and reads the mark field S at the same time_modifyIf:

S_modifynull, indicating that the first cell has not been dynamically optimized, willAverage downlink PRB utilization rate of first cell in period Tc

And a preset PRB utilization rate high Threshold_{prb_high}Comparing, and judging whether an optimization process needs to be started;

S_modify0, indicating that the first cell belongs to the operation class set i in the previous period Tc and has been subjected to dynamic optimization parameter adjustment, so as to average downlink PRB utilization rate of the first cell in the period Tc

And a preset PRB utilization rate low Threshold_{prb_low}And comparing, if:

the first cell traffic is considered to have reached a certain level and the previously made optimization adjustments need to be restored. The specific operation is as follows: reading S_{modify_pci}Field, if S_{modify_pci}If the field is empty, only increasing the power of the cell reference signal by 3 dB; if S_{modify_pci}1, increasing the power of the cell reference signal by 3dB, reading the original PCI of the cell stored in the memory and endowing the original PCI to the current cell, and then, S_{modify_pci}Emptying; counter N after modification_modifyDecrease by 1 when N_modifyWhen equal to 0, mark the field S_modifyEmptying;

the first cell service is considered to be still at an extremely low level, and the optimization process is not started in the period and no operation is performed.

S_modify1, indicating that the first cell belongs to the operation class set Π in the previous period Tc and performing dynamic optimization parameter adjustment, and then averaging the downlink PRB utilization rate of the first cell in the period Tc

And a preset PRB utilization rate low Threshold_{prb_low}And comparing, if:

the first cell traffic is considered to have reached a certain level and the previously made optimization adjustments need to be restored. The specific operation is as follows: the power of the cell reference signal is increased by 3 dB; counter N after modification_modifyDecrease by 1 when N_modifyWhen equal to 0, mark the field S_modifyEmptying;

the first cell traffic is considered to be still at an extremely low level and the optimization procedure is not started in this period.

Wherein PRB utilization is a low Threshold_{prb_low}The method can be flexibly set, and the flow trend of the cell can be determined under different load requirements.

The network optimization method provided by the embodiment of the invention includes the steps of firstly obtaining the PRB utilization rate of a first cell according to a preset time interval, then confirming that the first cell is in a high-load state when the PRB utilization rate of the first cell is higher than a first threshold value, further obtaining performance data of a second cell, the distance between the second cell and the first cell is smaller than the first threshold value, obtaining the network state of the second cell, and finally adjusting the parameters of the second cell according to the performance data of the second cell, wherein the interference of the second cell to the first cell is reduced by adjusting the reference signal power or the physical cell identification of the second cell, so that the resource utilization rate of the first cell is improved, the communication rate between the first cell and a user terminal is improved, and the effect of reducing the network load of the first cell is achieved. According to the scheme provided by the embodiment of the invention, the process is periodically executed, so that the network load of the first cell is monitored in real time, and the network optimization is carried out on the first cell when the first cell is overloaded. The scheme provided by the embodiment of the invention is based on the network information of the cell acquired by the base station, has high accuracy, and simultaneously carries out network optimization adjustment based on the real-time index information reported by the network, has high real-time performance, does not need to manually estimate the network load of the first cell at different time intervals, and has small workload and good network optimization effect.

Fig. 8 is a schematic structural diagram of a network optimization apparatus according to an embodiment of the present invention, as shown in fig. 8, including an obtaining module 81, a processing module 82, and an optimizing module 83, where:

the obtaining module 81 is configured to obtain a physical resource block PRB utilization rate of the first cell according to a preset time interval;

the processing module 82 is configured to obtain performance data of a second cell when the PRB utilization of the first cell is higher than a first threshold, where a distance between the second cell and the first cell is smaller than a first threshold, and the performance data of the second cell is used to indicate a network state of the second cell;

the optimization module 83 is configured to adjust a cell parameter of the second cell according to the performance data of the second cell, where the cell parameter includes a reference signal power, or the cell parameter includes a reference signal power and a physical cell identifier.

In a possible implementation manner, the obtaining module 81 is further configured to, before the obtaining of the performance data of the second cell:

the first preset condition is as follows:

In a possible implementation manner, the optimizing module 83 is further configured to, before the adjusting the cell parameter of the second cell according to the performance data of the second cell:

In a possible implementation manner, the optimization module 83 is specifically configured to:

acquiring the number of connected users of the second cell;

In a possible implementation manner, the processing module 82 is further configured to, before the obtaining of the performance data of the second cell:

The apparatus provided in the embodiment of the present invention may be used to implement the technical solutions of the above method embodiments, and the implementation principles and technical effects are similar, which are not described herein again.

Fig. 9 is a schematic diagram of a hardware structure of a network optimization device according to an embodiment of the present invention, and as shown in fig. 9, the network optimization device includes: at least one processor 91 and a memory 92. The processor 91 and the memory 92 are connected by a bus 93.

Optionally, the model determination further comprises a communication component. For example, the communication component may include a receiver and/or a transmitter.

In a specific implementation, the at least one processor 91 executes computer-executable instructions stored by the memory 92 to cause the at least one processor 91 to perform the network optimization method as described above.

For a specific implementation process of the processor 91, reference may be made to the above method embodiments, which implement similar principles and technical effects, and this embodiment is not described herein again.

In the embodiment shown in fig. 9, it should be understood that the Processor may be a Central Processing Unit (CPU), other general-purpose processors, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.

The memory may comprise high speed RAM memory and may also include non-volatile storage NVM, such as at least one disk memory.

The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.

The present invention also provides a computer-readable storage medium, in which computer-executable instructions are stored, and when a processor executes the computer-executable instructions, the network optimization method as described above is implemented.

The computer-readable storage medium may be implemented by any type of volatile or non-volatile memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk. Readable storage media can be any available media that can be accessed by a general purpose or special purpose computer.

An exemplary readable storage medium is coupled to the processor such the processor can read information from, and write information to, the readable storage medium. Of course, the readable storage medium may also be an integral part of the processor. The processor and the readable storage medium may reside in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the readable storage medium may also reside as discrete components in the apparatus.

The division of the units is only a logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for network optimization, comprising:

2. The method of claim 1, wherein prior to the obtaining performance data for the second cell, the method further comprises:

3. The method of claim 2, wherein the performance data for the first cell further comprises channel environmental quality, reference signal received power, and delay samples for the first cell;

the first preset condition is as follows:

4. The method of claim 3, wherein prior to the adjusting the cell parameter of the second cell based on the performance data of the second cell, the method further comprises:

5. The method of claim 4, wherein adjusting the cell parameter of the second cell according to the performance data of the second cell comprises:

acquiring the number of connected users of the second cell;

6. The method of claim 5, wherein the adjusting the cell parameter of the second cell according to the number of connected users of the second cell comprises:

7. The method according to any of claims 1-6, wherein prior to said obtaining performance data of the second cell, the method further comprises:

8. A network optimization apparatus, comprising:

9. A network optimization device, comprising: at least one processor and memory;

the memory stores computer-executable instructions;

the at least one processor executing the computer-executable instructions stored by the memory causes the at least one processor to perform the network optimization method of any of claims 1 to 7.

10. A computer-readable storage medium having computer-executable instructions stored thereon, which when executed by a processor, implement the network optimization method of any one of claims 1 to 7.