CN117279021A - Cell quality identification method and device, electronic equipment and storage medium - Google Patents
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Abstract
The disclosure provides a cell quality identification method, a device, an electronic device and a storage medium, wherein the cell quality identification method comprises the following steps: acquiring partial bandwidth BWP data of a user in a target cell; calculating the user throughput rate of the target cell based on BWP data; and identifying the quality of the target cell based on the user throughput rate of the target cell. The method and the device improve the accuracy of identifying the cell quality and eliminate misjudgment of the cell quality.
Description
Technical Field
The disclosure relates to the technical field of mobile communication, and in particular relates to a cell quality identification method, a cell quality identification device, electronic equipment and a storage medium.
Background
With the continuous development of network technology, the demands of users on network quality are also higher and higher, and the network quality is an important index for checking the running state of the network, and directly reflects the running quality of the network, so that the perceived experience of the users on the network is affected.
The existing method for identifying the quality of the cell is to monitor the throughput of the user in the cell, and when the throughput rate of a certain user equipment in the cell is lower than a preset threshold value, the cell is regarded as a quality disqualified cell, but as the 5G (5 th Generation Mobile Communication Technology, fifth generation mobile communication technology) is introduced into the BandWidth adaptation (Bandwidth Adaptation, BA), the BWP (BandWidth Part) of the 5GNR (New Radio, new air interface) user can be configured with flexible BandWidth, if the user is configured with narrow BandWidth, the throughput of the user will necessarily be reduced, so that the existing method for identifying the quality of the cell has a problem of misjudgment.
Based on this, how to improve the accuracy of cell quality identification becomes a technical problem to be solved.
It should be noted that the information disclosed in the above background section is only for enhancing understanding of the background of the present disclosure and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The disclosure provides a cell quality identification method, a cell quality identification device, an electronic device and a storage medium, which at least overcome the problem of misjudgment of cell quality identification in the related art to a certain extent.
Other features and advantages of the present disclosure will be apparent from the following detailed description, or may be learned in part by the practice of the disclosure.
According to one aspect of the present disclosure, there is provided a cell quality identification method, including: acquiring partial bandwidth BWP data of a plurality of users in a target cell; calculating the user throughput rate of the target cell based on BWP data; and identifying the quality of the target cell based on the user throughput rate of the target cell.
In one embodiment of the present disclosure, calculating the user throughput rate of the target cell based on BWP data includes: based on the BWP data, user throughput rates under different BWP are calculated.
In one embodiment of the present disclosure, calculating the user throughput rate of the target cell based on BWP data includes: and calculating the user throughput rate under the same BWP based on the BWP data, wherein the user throughput rate under the same BWP is the sum of all user throughput rates under the BWP.
In one embodiment of the present disclosure, calculating the user throughput rate of the target cell based on BWP data includes: and calculating the user throughput rates under all the activated BWPs based on the BWP data, and taking the user throughput rates under all the activated BWPs as the user throughput rate of the target cell so as to judge the quality of the target cell according to the user throughput rate of the target cell.
In one embodiment of the present disclosure, identifying the quality of the target cell based on the user throughput rate of the target cell comprises: setting a threshold value of cell quality judgment according to the BWP data; and identifying the quality of the target cell based on the user throughput rate and the threshold value of the cell quality judgment.
In one embodiment of the present disclosure, identifying the quality of the target cell based on the user throughput rate of the target cell comprises: setting a threshold value of cell quality judgment according to user throughput rates under different BWPs; and identifying the quality of the target cell based on the user throughput rate and the threshold value of the cell quality judgment.
In one embodiment of the present disclosure, identifying the quality of the target cell based on the user throughput rate of the target cell comprises: calculating the user weighted throughput rate of the target cell according to the user throughput rates under the different BWPs and the BWP data; and identifying the quality of the target cell based on the user weighted throughput rate.
In one embodiment of the present disclosure, the method further comprises: acquiring Resource Block (RB) occupation data of the target cell; calculating an activation factor of the target cell based on the RB occupation data of the target cell, wherein the activation factor represents the number of occupied resource blocks of the target cell in a certain time period; the quality of the target cell is identified based on the user weighted throughput rate and the activation factor of the target cell.
In one embodiment of the present disclosure, calculating the user weighted throughput rate of the target cell from the user throughput rates under the different BWP and the BWP data includes: calculating the user weighted throughput rate of the target cell by the following formula:
wherein Weighted gNB Throughput denotes the user weighted Throughput rate of the target cell, throughput ij Representing the user throughput rate, BWP, of the ith user of the target cell at the jth time ij BWP of the ith user of the target cell at the jth moment is represented, period represents total duration of statistical network data, users represent total number of user equipment in the target cell, and both i and j are positive integers.
In one embodiment of the present disclosure, calculating an activation factor of the target cell based on RB occupation data of the target cell includes: calculating the activation factor of the target cell by the following formula:
wherein Activation Efficiency represents the activation factor of the target cell, count (RB) j represents the number of RBs occupied by the target cell at time j, and period represents the total duration of the statistical network data.
In one embodiment of the present disclosure, identifying the quality of the target cell based on the user weighted throughput rate and the activation factor of the target cell comprises: and under the condition that the user weighted throughput rate of the target cell is smaller than a preset throughput rate threshold and the activating factor is larger than a preset activating factor threshold, determining that the quality of the target cell is unqualified.
In one embodiment of the present disclosure, identifying the quality of the target cell based on the user weighted throughput rate and the activation factor of the target cell comprises: when the user weighted throughput rate of the target cell is smaller than a preset throughput rate threshold and the activating factor is larger than a preset activating factor threshold, determining that the quality of the target cell meets a disqualification condition; counting the total times of the target cell meeting the disqualification condition in a preset time period; and when the total times of the target cell meeting the disqualification condition is greater than or equal to the preset times, determining that the quality of the target cell is disqualified.
According to another aspect of the present disclosure, there is provided a cell quality identifying apparatus including: the data acquisition module is used for acquiring partial bandwidth BWP data of a plurality of users in the target cell; a calculating module, configured to calculate a user throughput rate of the target cell based on BWP data; and the quality identification module is used for identifying the quality of the target cell based on the user throughput rate of the target cell.
In an embodiment of the present disclosure, the calculating module is further configured to calculate a user throughput rate under different BWP based on the BWP data.
In an embodiment of the present disclosure, the calculating module is further configured to calculate a user throughput rate under the same BWP based on the BWP data, where the user throughput rate under the same BWP is a sum of all user throughput rates under the BWP.
In an embodiment of the present disclosure, the calculating module is further configured to calculate, based on the BWP data, user throughput rates under all active BWP, and use the user throughput rates under all active BWP as the user throughput rate of the target cell, so as to determine quality of the target cell according to the user throughput rate.
In one embodiment of the present disclosure, the quality identification module is further configured to set a threshold value for cell quality judgment according to the BWP data; and identifying the quality of the target cell based on the user throughput rate and the threshold value of the cell quality judgment.
In an embodiment of the present disclosure, the quality identification module is further configured to set a threshold for cell quality judgment according to user throughput rates under the different BWP; and identifying the quality of the target cell based on the user throughput rate and the threshold value of the cell quality judgment.
In an embodiment of the present disclosure, the quality identifying module is further configured to calculate a user weighted throughput rate of the target cell according to user throughput rates under the different BWP; and identifying the quality of the target cell based on the user weighted throughput rate.
In an embodiment of the present disclosure, the data obtaining module is further configured to obtain RB occupation data of a resource block of the target cell; the calculation module is further configured to calculate an activation factor of the target cell based on RB occupation data of the target cell, where the activation factor represents a number of resource blocks occupied by the target cell in a certain period of time; the quality identification module is further configured to identify a quality of the target cell based on the user weighted throughput rate and the activation factor of the target cell.
In one embodiment of the present disclosure, the calculating module is further configured to calculate the user weighted throughput rate of the target cell by the following formula:
Wherein Weighted gNB Throughput denotes the user weighted Throughput rate of the target cell, throughput ij Representing the user throughput rate, BWP, of the ith user of the target cell at the jth time ij BWP of the ith user of the target cell at the jth moment is represented, period represents total duration of statistical network data, users represent total number of user equipment in the target cell, and both i and j are positive integers.
In one embodiment of the present disclosure, the calculating module is further configured to calculate the activation factor of the target cell by the following formula:
wherein Activation Efficiency represents the activation factor of the target cell, count (RB) j represents the number of RBs occupied by the target cell at time j, and period represents the total duration of the statistical network data.
In an embodiment of the present disclosure, the quality identifying module is further configured to determine that the quality of the target cell is failed when the user weighted throughput rate of the target cell is less than a preset throughput rate threshold and the activation factor is greater than a preset activation factor threshold.
In an embodiment of the present disclosure, the quality identifying module is further configured to determine that the quality of the target cell meets a failure condition when a user weighted throughput rate of the target cell is less than a preset throughput rate threshold and the activation factor is greater than a preset activation factor threshold; counting the total times of the target cell meeting the disqualification condition in a preset time period; and when the total times of the target cell meeting the disqualification condition is greater than or equal to the preset times, determining that the quality of the target cell is disqualified.
According to still another aspect of the present disclosure, there is provided an electronic apparatus including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the cell quality identification method described above via execution of the executable instructions.
According to yet another aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the above-described cell quality identification method.
The embodiment of the disclosure provides a cell quality identification method, a device, an electronic device and a storage medium, wherein the cell quality identification method comprises the following steps: acquiring partial bandwidth BWP data of a user in a target cell; calculating the user throughput rate of the target cell based on BWP data; and identifying the quality of the target cell based on the user throughput rate of the target cell. The method and the device judge the quality of the target cell based on the user throughput rate of the target cell, improve the accuracy of identifying the quality of the cell, and eliminate the misjudgment of identifying the quality of the cell.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure. It will be apparent to those of ordinary skill in the art that the drawings in the following description are merely examples of the disclosure and that other drawings may be derived from them without undue effort.
Fig. 1 is a schematic diagram showing a configuration of a communication system in an embodiment of the present disclosure;
fig. 2 illustrates a flowchart of a cell quality identification method in an embodiment of the present disclosure;
fig. 3 illustrates another cell quality identification method flow chart in an embodiment of the present disclosure;
fig. 4 illustrates another cell quality identification method flow chart in an embodiment of the present disclosure;
fig. 5 illustrates a flowchart of yet another cell quality identification method in an embodiment of the present disclosure;
fig. 6 is a schematic diagram of a cell quality identifying apparatus according to an embodiment of the disclosure;
fig. 7 is a schematic diagram of another cell quality identifying apparatus according to an embodiment of the disclosure; and
fig. 8 shows a block diagram of an electronic device in an embodiment of the disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor devices and/or microcontroller devices.
As mentioned in the background, the current method of determining the quality of a cell in network optimization is to evaluate the quality of service of the cell by monitoring the throughput of user equipment in the cell, and consider a cell with the throughput of the user equipment lower than a certain threshold as a quality failure cell, but as bandwidth adaptation is introduced in 5G, the receiving and transmitting bandwidths of the user equipment can be freely adjusted, for example, bandwidth is shrunk during inactivity to save power consumption. That is, the BWP of the 5G NR user can flexibly configure the bandwidth, and in the case that the user configures the narrow bandwidth, the rate of the ue is necessarily reduced, so that the conventional judgment method may have misjudgment of the cell quality.
For example, when monitoring the quality of a cell, a certain cell bandwidth is 100Mhz, if all users only activate BWP of 100 Mhz. At this time, when the throughput rate of a certain user in the cell is lower than a fixed threshold, it is reasonable to consider the cell as a quality reject cell. However, after the small bandwidth BWP is started, a part of users under the cell only activate the special BWP with the bandwidth of 20Mhz, and a part of users activate the special BWP with the bandwidth of 100Mhz, so that the traditional judging method is not applicable. At this time, the corresponding threshold needs to be set according to different bandwidths of the special BWP, so as to more accurately determine the cell quality.
Based on the above, the present disclosure provides a cell quality identification method, apparatus, electronic device and storage medium, by introducing BWP parameters of a user into user throughput rate calculation of a target cell, and identifying the quality of the target cell based on the user throughput rate of the target cell, the accuracy of identifying the cell quality is improved, and misjudgment of identifying the cell quality is eliminated.
Fig. 1 shows a schematic diagram of an exemplary communication system architecture to which a cell quality identification method or a cell quality identification apparatus of an embodiment of the present disclosure may be applied.
As shown in fig. 1, the communication system may include a base station 110 and an unlimited number of user equipments 120 in each cell.
The user device 120 may be a wireless terminal or a wired terminal, where the wireless terminal may be a device that provides voice and/or data connectivity to a user, a handheld device with wireless connection, or other processing device connected to a wireless modem. A wireless terminal may communicate with one or more core networks via a radio access network (e.g., english: radio Access Network, abbreviated: RAN), which may be mobile terminals such as mobile phones (or "cellular" phones) and computers with mobile terminals, e.g., portable, pocket, hand-held, computer-built-in or vehicle-mounted mobile devices that exchange voice and/or data with the radio access network. For example, personal communication services (English: personal Communication Service, abbreviation: PCS) phones, cordless phones, session initiation protocol phones, wireless local loop (English: wireless Local Loop, abbreviation: WLL) stations, personal digital assistants (English: personal Digital Assistant, abbreviation: PDA) and the like. A wireless Terminal may also be called a system, a Subscriber Unit (english: subscriber Unit), a Subscriber Station (english Subscriber Station), a Mobile Station (english: mobile Station, abbreviation: MS), a Remote Station (english: remote Station, abbreviation: RS), an Access Point (english: access Point, abbreviation: AP), a Remote Terminal (english: remote Terminal), an Access Terminal (english: access Terminal), a User Terminal (english: user Terminal), a User Agent (english: user Agent), a User Device (english: user Device), or a User Equipment (english: user Equipment).
The ue 120 may also be implemented as a Base Station (BS), an Access Point (AP), a remote wireless device (Remote Radio Equipment, RRE), a remote wireless port (Remote Radio Head, RRH), a remote wireless unit (Remote Radio Unit, RRU), a Relay node (Relay node), etc. The relationship between the network device and the cells is not limited, and one network device may correspond to one or more cells, or one cell may correspond to one or more network devices. The network device may perform the transmission or reception operation directly or indirectly by controlling the device connected to the network device through a wired or wireless manner.
Base station 110, a base station (e.g., an access point) may refer to a device in an access network that communicates over the air-interface, through one or more sectors, with wireless terminals. The base station may be configured to inter-convert the received air frames with IP packets as a router between the wireless terminal and the rest of the access network, which may include an internet protocol (abbreviated: IP) network. The base station may also coordinate attribute management for the air interface. For example, the base station may be a base station in GSM or CDMA (english: base Transceiver Station, abbreviated: BTS), a base station in WCDMA (english: nodeB), or an evolved base station in LTE (english: nodeB or abbreviated: eNB or english: e-NodeB, english: evolutional Node B), which is not limited in this disclosure.
Alternatively, the base station 110 and the user equipment 120 may be connected through a wireless network or a wired network, where the wireless network or the wired network uses standard communication technologies and/or protocols. The network is typically the Internet, but may be any network including, but not limited to, a local area network (Local Area Network, LAN), metropolitan area network (Metropolitan Area Network, MAN), wide area network (Wide Area Network, WAN), mobile, wired or wireless network, private network, or any combination of virtual private networks. In some embodiments, data exchanged over a network is represented using techniques and/or formats including HyperText Mark-up Language (HTML), extensible markup Language (Extensible MarkupLanguage, XML), and the like. All or some of the links may also be encrypted using conventional encryption techniques such as secure sockets layer (Secure Socket Layer, SSL), transport layer security (Transport Layer Security, TLS), virtual private network (Virtual Private Network, VPN), internet protocol security (Internet ProtocolSecurity, IPsec), etc. In other embodiments, custom and/or dedicated data communication techniques may also be used in place of or in addition to the data communication techniques described above.
The user device 120 may be a variety of electronic devices including, but not limited to, a smart phone, a tablet computer, a laptop portable computer, a desktop computer, a wearable device, an augmented reality device, a virtual reality device, and the like.
Those skilled in the art will appreciate that the number of base stations, cells and user equipment in fig. 1 is merely illustrative and that any number of base stations, cells and user equipment may be provided as desired. The embodiments of the present disclosure are not limited in this regard.
The present exemplary embodiment will be described in detail below with reference to the accompanying drawings and examples.
First, in the embodiment of the present disclosure, a cell quality identifying method is provided, and the method may be applied to the communication system shown in fig. 1, where the method may be performed by any electronic device having computing processing capability.
Fig. 2 shows a flowchart of a cell quality identification method in an embodiment of the present disclosure, and as shown in fig. 2, the cell quality identification method provided in the embodiment of the present disclosure includes the following steps:
s202, partial bandwidth BWP data of users in the target cell are acquired.
It should be noted that, the BWP data includes downlink dedicated BWP and uplink dedicated BWP of the user, and the present disclosure may acquire network data of the target cell from the base station, including, but not limited to, BWP data of each user at different moments, network rate, and number of occupied resource blocks, etc., to acquire BWP data of multiple users in the target cell from the network data.
S204, calculating the user throughput of the target cell based on the BWP data.
It should be noted that, the user throughput rate is the data amount that the user successfully transmits in a unit time, which may also refer to the average UE throughput of the downlink dedicated BWP or the uplink dedicated BWP, where the unit kbit/s is limited by the BWP, the larger the BWP, the higher the upper limit of the user throughput rate; the present disclosure may divide users according to their BWP data, and calculate user throughput rates under the same BWP, user throughput rates under different BWP, and user throughput rates under all BWP, respectively, according to the BWP data of the users.
Note that when Σ UEs When Sigma ThpTimeDl > 0, the user throughput rate isWhen sigma UEs When Σthptimidl=0, then the user throughput rate is 0[ kbit/s ]]The method comprises the steps of carrying out a first treatment on the surface of the Wherein thptimdl is the time of transmitting a burst of Data when the buffer is empty, excluding Data transmitted in the slot, and a sample of "thptimdl" is emptied one DL (Data Link) buffer at a time of DRB (Data Radio Bearer ); RLC-level volume of ThpVolDl data burst, excluding data transmitted in slots when buffer is empty, the sample of ThpVolDl being the amount of data successfully transmitted (acknowledged by UE) in DL for one DRB during thptimeddl samples, calculated at RLC (Radio Link Control, radio link layer control protocol) SDU (segment data unit, segmented data unit) level, the volume of the last segment of data that is empty of buffer should be excluded; UEs are the amount of data for users in the target cell, which refers to the predetermined total amount of each dedicated BWP in the primary carrier activated by the UE.
For small data bursts, thptimiddl=0 when all buffered data is contained in one initial HARQ (Hybrid Automatic Repeat Request ) transmission, otherwise thptimiddl=t1-T2 ms; wherein T1 is a point in time after T2 acknowledged by the UE, in the transmitted data burst, until the second last segment of data of the RLC SDU available for transmission of the specific DRB is emptied is successfully transmitted; t2 is the point in time when the first transmission starts after RLC SDUs are available for transmission, before which no RLC SDUs are available for transmission of a specific DRB.
S206, based on the user throughput rate of the target cell, identifying the quality of the target cell.
It should be noted that, according to the present disclosure, a throughput rate threshold may be set according to a user requirement or a user experience of a user on a network, and when a relationship between a user throughput rate of a target cell and the throughput rate threshold meets a certain condition, it is determined whether quality of the target cell is qualified, for example, when the user throughput rate of the target cell is less than a preset throughput rate threshold, it is determined that quality of the target cell is unqualified; and when the user throughput rate of the target cell is larger than a preset throughput rate threshold, determining the quality of the target cell as qualified.
The cell quality identification method provided in the embodiment of the disclosure comprises the following steps: acquiring BWP data of a user in a target cell; calculating the user throughput rate of the target cell based on the BWP data; the quality of the target cell is identified based on the user throughput rate of the target cell. The quality of the target cell is identified based on the user throughput rate of the target cell, so that the identification accuracy is improved. Meanwhile, the BWP is introduced into the user throughput rate calculation of the target cell, so that the problem of misjudgment caused by users with different BWPs due to 5G NR in the prior art is solved, and the accuracy rate of cell quality identification is improved.
In one embodiment of the present disclosure, calculating a user throughput rate of a target cell based on BWP data includes: based on the BWP data, user throughput rates under different BWP are calculated. Wherein the user throughput rate under different BWP may be the sum of the ratio of the network speed to the BWP of each user in the target cell.
In one embodiment of the present disclosure, calculating a user throughput rate of a target cell based on BWP data includes: based on the BWP data, the user throughput rate under the same BWP is calculated, wherein the user throughput rate under the same BWP is the sum of all user throughput rates under the BWP.
In one embodiment of the present disclosure, calculating a user throughput rate of a target cell based on BWP data includes: based on the BWP data, calculating the user throughput rate under all the activated BWPs, and taking the user throughput rate under all the activated BWPs as the user throughput rate of the target cell so as to judge the quality of the target cell through the user throughput rate of the target cell. The present disclosure may also identify the quality of the target cell based on the user throughput rate of the target cell.
In one embodiment of the present disclosure, the larger the BWP of the user, the greater the peak throughput rate that the user can reach.
In one embodiment of the present disclosure, identifying the quality of the target cell based on the user throughput rate of the target cell includes: setting a threshold value of cell quality judgment according to BWP data; based on the user throughput rate and the threshold value of cell quality judgment, the quality of the target cell is identified.
In one embodiment of the present disclosure, identifying the quality of the target cell based on the user throughput rate of the target cell includes: setting a threshold value for cell quality judgment according to user throughput rates under different BWPs; based on the user throughput rate and the threshold value of cell quality judgment, the quality of the target cell is identified.
In one embodiment of the present disclosure, identifying the quality of the target cell based on the user throughput rate of the target cell comprises: calculating the user weighted throughput rate of the target cell according to the user throughput rates under the different BWPs and the BWP data; and identifying the quality of the target cell based on the user weighted throughput rate. The BWP is introduced into the calculation of the user weighted throughput rate of the target cell, so that the problem of misjudgment caused by users with different BWPs existing in 5G NR in the prior art is solved, and the accuracy of cell quality identification is improved.
It should be noted that, according to the throughput rate and BWP of each user in the target cell at each time, the ratio of the throughput rate to the bandwidth of each user equipment at each time may be calculated, and the sum of the ratios of the throughput rates and the bandwidths of all the devices in the preset time period is taken as the user weighted throughput rate of the target cell.
It should be noted that, the user weighted throughput rate of the target cell may be calculated by the following formula:
wherein Weighted gNB Throughput denotes the user weighted Throughput rate of the target cell, throughput ij Representing the user throughput rate, BWP, of the ith user of the target cell at the jth time ij BWP of the ith user of the target cell at the jth moment is represented, period represents total duration of statistical network data, users represent total number of user equipment in the target cell, and both i and j are positive integers. Here, the present disclosure may also modify equation (1) using BWP ij Bandwidth function f (BWP ij ) Substitution of BWP in equation (1) ij The formula after deformation is as follows:
f (BWP) in the above formula (3) ij ) The function may be in BWP ij Is an arbitrary function of the variables, here, the number of variables for f (BWP ij ) The function is not particularly limited.
In an embodiment of the present disclosure, the above cell quality identification method may further include the steps disclosed in fig. 3, referring to another cell quality identification method flowchart shown in fig. 3, and may include the following steps:
S302, acquiring the Resource Block (RB) occupation data of the target cell.
S304, calculating an activation factor of the target cell based on the RB occupation data of the target cell, wherein the activation factor represents the number of occupied resource blocks of the target cell in a certain time period.
It should be noted that, according to the resource block occupation data of the target cell obtained from the base station, the number of resource block occupation of the target cell in the preset time period may be used as an activation factor of the target cell, where the RB occupation data of the target cell includes the number of RB occupation of multiple users in the target cell at different times.
S306, identifying the quality of the target cell based on the user weighted throughput rate and the activation factor of the target cell.
It should be noted that, according to the present disclosure, a throughput rate threshold and an activation factor threshold may be set according to a user requirement or a user experience of a user on a network, and when a user weighted throughput rate and a throughput rate threshold of a target cell meet a certain condition, and an activation factor threshold of the target cell also meet a certain condition, it is determined that quality of the target cell is unqualified; or when the user weighted throughput rate and the throughput rate threshold value of the target cell meet certain conditions and the activating factor threshold value of the target cell also meet certain conditions, determining that the target cell meets the disqualification conditions, recording the times that the target cell meets the disqualification conditions in the statistical time period of the network data, and determining that the quality of the target cell is disqualification when the times exceed the preset times threshold value.
The method and the device take the activating factor of the target cell as a standard for identifying the quality of the cell, set an activating factor threshold, and determine that the quality of the target cell is unqualified when the occupied number of the resource blocks of the target cell meets a certain condition, so that misjudgment on idle cells is avoided.
In one embodiment of the present disclosure, calculating an activation factor of a target cell based on RB occupation data of the target cell includes: calculating the activation factor of the target cell by the following formula:
wherein Activation Efficiency represents the activation factor of the target cell, count (RB) j represents the number of RBs occupied by the target cell at time j, and period represents the total duration of the statistical network data.
In one embodiment of the present disclosure, determining the quality of the target cell based on the user weighted throughput rate and the activation factor of the target cell comprises: and under the condition that the user weighted throughput rate of the target cell is smaller than a preset throughput rate threshold and the activating factor is larger than a preset activating factor threshold, determining the quality of the target cell as unqualified.
In one embodiment of the present disclosure, the quality of the target cell may be determined through the steps disclosed in fig. 4, referring to another cell quality identification method flowchart shown in fig. 4, may include the steps of:
S402, when the user weighted throughput rate of the target cell is smaller than a preset throughput rate threshold value and the activating factor is larger than a preset activating factor threshold value, determining that the target cell meets the disqualification condition;
s404, counting the total times of the target cell meeting the disqualification condition in a preset time period;
and S406, when the total times of the target cell meeting the disqualification condition is greater than or equal to the preset times, determining the quality of the target cell as disqualification.
It should be noted that the preset time period may be the same as a duration of collecting data in the network data.
The cell quality identification method in the embodiment of the disclosure can comprehensively judge the quality of the target cell by combining the data such as BWP of the user, throughput of the user, RB occupation number and the like, and refers to the throughput rate threshold value, so that the problem of misjudgment caused by users with different BWPs due to 5G NR in the prior art is solved; and introducing an activation factor threshold, namely a threshold of the RB occupation number, so as to solve the problem of misjudgment of the idle cell, thereby improving the accuracy of identifying the cell quality.
In one embodiment of the present disclosure, referring to another cell quality identification method flowchart disclosed in fig. 5, the method includes:
s502, BWP data and RB occupation data of a target cell are acquired;
S504, calculating the user weighted throughput rate and the activation factor of the target cell;
s506, judging whether the user weighted throughput rate of the target cell is smaller than the throughput rate threshold, and the activating factor is smaller than the activating factor threshold, if not, executing S508; if yes, executing S510;
s508, satisfying the condition number counter=counter+0, with the Counter initial value being 0, executing S512;
s510, satisfying the condition number counter=counter+1, with the Counter initial value being 0, executing S512;
s512, judging whether the Counter > N is met, if yes, executing S514; if not, then S516 is performed;
s514, determining the quality of the target cell as unqualified, and triggering quality unqualified alarm;
s516, judging whether the preset statistical time is exceeded, if not, executing S502; if yes, then execute S518;
and S518, determining the quality of the target cell as qualified.
In one embodiment of the present disclosure, network data of a target cell is obtained, where the network data may include BWP configuration, rate, RB occupation number, and the like of a user equipment at different times, see values given in table 1, table 2, and table 3, a throughput rate threshold (Poor Throughput Threshold) is set to 20, an activation factor threshold (Efficiency Threshold) is set to 600, a statistical duration is set to 5 times, a preset statistical time is set to 15 times, and when a user weighted throughput rate of a cell is smaller than the throughput rate threshold and an activation factor is greater than the activation factor threshold, it is determined that quality of the cell is unacceptable; and calculating the user weighted throughput rate and the activation factor of the target cell on the condition, and giving out a process for determining the quality of the target cell.
The data configured by different user equipments at different moments BWP is shown in table 1 below:
TABLE 1
The rates of different user equipments at different times are shown in table 2 below:
TABLE 2
/>
The RB occupation data of the target cell at different times are shown in the following table 3:
TABLE 3 Table 3
According to the data in the above tables 1 and 2, the weighted rates of each ue at different moments are calculated, the weighted rates=user rate/BWP bandwidth, and the weighted rates of each ue are shown in the following table 4:
TABLE 4 Table 4
/>
The user weighted throughput rate of all the user equipments at every 5 times of the target cell is calculated from the data in the above table 4, the user weighted throughput rate is the sum of the weighted rates of all the users at every 5 times, the user weighted throughput rate of the target cell at every 5 times is as shown in the following table 5, and the above throughput rate threshold is set to 20 by comparing the user weighted throughput rate with the throughput rate threshold, so that the reject condition is not satisfied when the user weighted throughput rate is greater than 20, and the reject condition is satisfied when the user weighted throughput rate is less than 20, see the following table 5.
TABLE 5
According to the RB occupation data of the target cell at different moments shown in table 3, the value of the activating factor of the target cell at each 5 moments is calculated, the sum of the RB occupation numbers of the target cell at the 5 moments is compared with the magnitude of the preset activating factor, and the preset activating factor is set to 600, so that when the activating factor is smaller than 600, the disqualification condition is not satisfied, and when the activating factor is larger than 600, the disqualification condition is satisfied, see the following table 6.
TABLE 6
In summary, when the user weighted throughput rate and the activation factor of the cell meet the disqualification condition, determining the quality of the cell as disqualification.
At time 1-5, the quality of the target cell in the time period is qualified because the user weighted throughput rate of the target cell does not meet the condition.
At the time of 6-10, the activation factor of the target cell does not meet the condition, so the quality of the target cell in the time period is qualified.
At 11-15, when the user weighted throughput rate and the activation factor of the target cell meet the disqualification conditions, the quality of the target cell in the time period is disqualification.
Based on the same inventive concept, the embodiments of the present disclosure also provide a cell quality identifying device, as follows. Since the principle of solving the problem of the embodiment of the device is similar to that of the embodiment of the method, the implementation of the embodiment of the device can be referred to the implementation of the embodiment of the method, and the repetition is omitted.
Fig. 6 is a schematic diagram of a cell quality identifying apparatus according to an embodiment of the disclosure, as shown in fig. 6, where the apparatus includes:
a data acquisition module 610, configured to acquire partial bandwidth BWP data of a plurality of users in a target cell;
A calculation module 620, configured to calculate a user throughput rate of the target cell based on the BWP data; and
a quality identification module 630, configured to identify a quality of the target cell based on a user throughput rate of the target cell.
In one embodiment of the present disclosure, the calculation module 620 is further configured to calculate the user throughput rate under different BWP based on the BWP data.
In one embodiment of the present disclosure, the calculating module 620 is further configured to calculate a user throughput rate under the same BWP based on the BWP data, where the user throughput rate under the same BWP is a sum of all user throughput rates under the BWP.
In one embodiment of the present disclosure, the calculating module 620 is further configured to calculate, based on the BWP data, user throughput rates under all the active BWP, and use the user throughput rates under all the active BWP as the user throughput rate of the target cell, so as to determine the quality of the target cell according to the user throughput rate.
In one embodiment of the present disclosure, the calculation module 620 is further configured to calculate the weighted throughput rate of the target cell according to formula (1).
In one embodiment of the present disclosure, the calculation module 620 is further configured to calculate the activation factor of the target cell according to formula (3).
In one embodiment of the present disclosure, the quality identification module 630 is further configured to set a threshold for cell quality determination according to BWP data.
In one embodiment of the present disclosure, the quality identification module 630 is further configured to set a threshold for cell quality determination according to user throughput rates under different BWP.
In one embodiment of the present disclosure, the quality identification module 630 is further configured to calculate a user weighted throughput rate of the target cell according to the user throughput rates under different BWP to determine the quality of the target cell.
In one embodiment of the present disclosure, the data obtaining module 610 is further configured to obtain RB occupation data of a resource block of the target cell; the calculating module 620 is further configured to calculate an activation factor of the target cell based on RB occupation data of the target cell, where the activation factor represents a number of resource blocks occupied by the target cell in a certain period of time; the quality identification module 630 is further configured to identify a quality of the target cell based on the user weighted throughput rate and the activation factor of the target cell.
In an embodiment of the present disclosure, the quality identifying module 610 is further configured to determine that the quality of the target cell is not acceptable if the user weighted throughput rate of the target cell is less than a preset throughput rate threshold and the activation factor is greater than a preset activation factor threshold.
In one embodiment of the present disclosure, the quality identifying module 610 is further configured to determine that the quality of the target cell meets the failure condition when the user weighted throughput rate of the target cell is less than a preset throughput rate threshold and the activation factor is greater than a preset activation factor threshold; counting the total times of the target cell meeting the disqualification condition in a preset time period; and when the total times of the target cell meeting the disqualification condition is greater than or equal to the preset times, determining that the quality of the target cell is disqualified.
In one embodiment of the present disclosure, referring to another schematic diagram of a cell quality identifying apparatus shown in fig. 7, as shown in fig. 7, the apparatus may further include an alarm module 640, where the alarm module 640 is configured to trigger a quality failure alarm after determining that the quality of the target cell is failed. By triggering the quality failure alarm, relevant staff is reminded to discover the network quality condition of the target cell in time, and the subsequent processing of the network problem of the target cell is facilitated.
Those skilled in the art will appreciate that the various aspects of the present disclosure may be implemented as a system, method, or program product. Accordingly, various aspects of the disclosure may be embodied in the following forms, namely: an entirely hardware embodiment, an entirely software embodiment (including firmware, micro-code, etc.) or an embodiment combining hardware and software aspects may be referred to herein as a "circuit," module "or" system.
An electronic device 800 according to such an embodiment of the present disclosure is described below with reference to fig. 8. The electronic device 800 shown in fig. 8 is merely an example and should not be construed to limit the functionality and scope of use of embodiments of the present disclosure in any way.
As shown in fig. 8, the electronic device 800 is embodied in the form of a general purpose computing device. Components of electronic device 800 may include, but are not limited to: the at least one processing unit 810, the at least one memory unit 820, and a bus 830 connecting the various system components, including the memory unit 820 and the processing unit 810.
Wherein the storage unit stores program code that is executable by the processing unit 810 such that the processing unit 810 performs steps according to various exemplary embodiments of the present disclosure described in the above section of the present specification. For example, the processing unit 810 may perform the following steps of the method embodiment described above: acquiring partial bandwidth BWP data of a plurality of users in a target cell; calculating the user throughput rate of the target cell based on the BWP data; the quality of the target cell is identified based on the user throughput rate of the target cell.
The storage unit 820 may include readable media in the form of volatile storage units, such as Random Access Memory (RAM) 8201 and/or cache memory 8202, and may further include Read Only Memory (ROM) 8203.
Storage unit 820 may also include a program/utility 8204 having a set (at least one) of program modules 8205, such program modules 8205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
Bus 830 may be one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.
The electronic device 800 may also communicate with one or more external devices 840 (e.g., keyboard, pointing device, bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 800, and/or any device (e.g., router, modem, etc.) that enables the electronic device 800 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 850. Also, electronic device 800 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through network adapter 860. As shown, network adapter 860 communicates with other modules of electronic device 800 over bus 830. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 800, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, including several instructions to cause a computing device (may be a personal computer, a server, a terminal device, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, a computer-readable storage medium, which may be a readable signal medium or a readable storage medium, is also provided. On which a program product is stored which enables the implementation of the method described above of the present disclosure. In some possible implementations, various aspects of the disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps according to the various exemplary embodiments of the disclosure as described in the "exemplary methods" section of this specification, when the program product is run on the terminal device.
More specific examples of the computer readable storage medium in the present disclosure may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
In this disclosure, a computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Alternatively, the program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
In particular implementations, the program code for carrying out operations of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
It should be noted that although in the above detailed description several modules or units of a device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.
Furthermore, although the steps of the methods in the present disclosure are depicted in a particular order in the drawings, this does not require or imply that the steps must be performed in that particular order or that all illustrated steps be performed in order to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform, etc.
From the description of the above embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, including several instructions to cause a computing device (may be a personal computer, a server, a mobile terminal, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any adaptations, uses, or adaptations of the disclosure following the general principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (15)
1. A cell quality identification method, comprising:
acquiring partial bandwidth BWP data of a user in a target cell;
calculating the user throughput rate of the target cell based on BWP data;
and identifying the quality of the target cell based on the user throughput rate of the target cell.
2. The cell quality identification method according to claim 1, wherein calculating the user throughput rate of the target cell based on BWP data comprises:
based on the BWP data, user throughput rates under different BWP are calculated.
3. The cell quality identification method according to claim 1, wherein calculating the user throughput rate of the target cell based on BWP data comprises:
and calculating the user throughput rate under the same BWP based on the BWP data, wherein the user throughput rate under the same BWP is the sum of all user throughput rates under the BWP.
4. The cell quality identification method according to claim 1, wherein calculating the user throughput rate of the target cell based on BWP data comprises:
and calculating the user throughput rates under all the activated BWPs based on the BWP data, and taking the user throughput rates under all the activated BWPs as the user throughput rate of the target cell so as to judge the quality of the target cell according to the user throughput rate of the target cell.
5. The cell quality identification method according to claim 1, wherein identifying the quality of the target cell based on the user throughput rate of the target cell comprises:
setting a threshold value of cell quality judgment according to the BWP data;
and identifying the quality of the target cell based on the user throughput rate and the threshold value of the cell quality judgment.
6. The cell quality identification method according to claim 2, wherein identifying the quality of the target cell based on the user throughput rate of the target cell comprises:
setting a threshold value of cell quality judgment according to user throughput rates under different BWPs;
and identifying the quality of the target cell based on the user throughput rate and the threshold value of the cell quality judgment.
7. The cell quality identification method according to claim 2, wherein identifying the quality of the target cell based on the user throughput rate of the target cell comprises:
calculating the user weighted throughput rate of the target cell according to the user throughput rates under the different BWPs and the BWP data;
and identifying the quality of the target cell based on the user weighted throughput rate.
8. The cell quality identification method according to claim 7, characterized in that the method further comprises:
acquiring Resource Block (RB) occupation data of the target cell;
calculating an activation factor of the target cell based on the RB occupation data of the target cell, wherein the activation factor represents the number of occupied resource blocks of the target cell in a certain time period;
the quality of the target cell is identified based on the user weighted throughput rate and the activation factor of the target cell.
9. The cell quality identification method according to claim 7, wherein calculating the user weighted throughput rate of the target cell from the user throughput rates under the different BWP and the BWP data comprises:
calculating the user weighted throughput rate of the target cell by the following formula:
wherein Weighted gNB Throughput denotes the user weighted Throughput rate of the target cell, throughput ij Representing the user throughput rate, BWP, of the ith user of the target cell at the jth time ij BWP of ith user of target cell at jth moment, period of time of the ith user of target cell, total duration of statistical network data, users of total number of user equipment in target cell, i and j being A positive integer.
10. The cell quality identification method according to claim 8, wherein calculating an activation factor of the target cell based on RB occupation data of the target cell comprises:
calculating the activation factor of the target cell by the following formula:
wherein Activation Efficiency represents the activation factor of the target cell, count (RB) j represents the number of RBs occupied by the target cell at time j, and period represents the total duration of the statistical network data.
11. The cell quality identification method of claim 8, wherein identifying the quality of the target cell based on the user weighted throughput rate and the activation factor of the target cell comprises:
and under the condition that the user weighted throughput rate of the target cell is smaller than a preset throughput rate threshold and the activating factor is larger than a preset activating factor threshold, determining that the quality of the target cell is unqualified.
12. The cell quality identification method of claim 8, wherein identifying the quality of the target cell based on the user weighted throughput rate and the activation factor of the target cell comprises:
when the user weighted throughput rate of the target cell is smaller than a preset throughput rate threshold and the activating factor is larger than a preset activating factor threshold, determining that the quality of the target cell meets a disqualification condition;
Counting the total times of the target cell meeting the disqualification condition in a preset time period;
and when the total times of the target cell meeting the disqualification condition is greater than or equal to the preset times, determining that the quality of the target cell is disqualified.
13. A cell quality identification apparatus, comprising:
the data acquisition module is used for acquiring partial bandwidth BWP data of a plurality of users in the target cell;
a calculating module, configured to calculate a user throughput rate of the target cell based on BWP data; and
and the quality identification module is used for identifying the quality of the target cell based on the user throughput rate of the target cell.
14. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the cell quality identification method of any of claims 1-12 via execution of the executable instructions.
15. A computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the cell quality identification method of any of claims 1 to 12.
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