CN112188569A - Communication method and device in wireless communication network - Google Patents
Communication method and device in wireless communication network Download PDFInfo
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Abstract
The present application provides a method performed by a base station, a UE or a server in a wireless communication network and a corresponding base station, UE, server and non-transitory machine-readable storage medium. The method performed by a base station in a wireless communication network comprises: receiving UE history information of the UE in response to the UE entering a serving cell of the base station, wherein the UE history information indicates information of a past serving cell serving the UE; responding to the UE entering a service cell of the base station, receiving an enhanced neighbor cell relation table of the service cell, wherein the enhanced neighbor cell relation table indicates time-varying relation information of the service cell and each neighbor cell of the service cell; predicting measurement interval information of the UE for measuring the signal quality of each adjacent cell based on the UE historical information and the enhanced adjacent cell relation table; and transmitting the predicted measurement interval to the UE.
Description
Technical Field
The present application relates to the field of wireless communication technologies, and in particular, to a communication method and apparatus in a wireless communication network.
Background
With the explosive growth of the number of wireless devices and wireless data traffic, operators have built more and more dense networks in order to provide better wireless services. In dense networks, the cell radius is getting smaller and the frequency of User Equipment (UE) handover is getting higher. Therefore, the task of neighbor cell measurement accompanying UE handover also increases. The increase of the measurement task brings about excessive power consumption on the UE side. Therefore, there is a need in the art for a more efficient measurement task allocation mechanism to save power for the UE.
Disclosure of Invention
An aspect of the present application provides a method performed by a base station in a wireless communication network. The method comprises the following steps: receiving UE history information of the UE in response to the UE entering a serving cell of the base station, wherein the UE history information indicates information of a past serving cell serving the UE; responding to the UE entering a service cell of the base station, receiving an enhanced neighbor cell relation table of the service cell, wherein the enhanced neighbor cell relation table indicates time-varying relation information of the service cell and each neighbor cell of the service cell; predicting measurement interval information of the UE for measuring the signal quality of each adjacent cell based on the UE historical information and the enhanced adjacent cell relation table; and transmitting the predicted measurement interval information to the UE.
According to an embodiment of the present application, the information of the past history cell includes at least one of the following information: PRB, PRBG, throughput, number of UEs, and load amount.
According to an embodiment of the application, the time-varying relationship information includes at least one of the following information: the handover probability relationship between the serving cell and each of the neighboring cells, the topological relationship between the serving cell and each of the neighboring cells, the cooperative relationship between the serving cell and each of the neighboring cells, and a future newly defined neighboring cell relationship.
According to an embodiment of the present application, predicting, based on the UE history information and the enhanced neighbor relation table, measurement interval information at which the UE measures the signal quality of each neighbor cell includes: predicting the probability of the UE switching from the serving cell to each adjacent cell of the serving cell based on the UE historical information and the enhanced adjacent cell relation table; and inversely correlatively mapping the predicted probability to the measurement interval information.
According to an embodiment of the present application, predicting, based on the UE history information and the enhanced neighbor relation table, a probability of the UE switching from the serving cell to each of neighbor cells of the serving cell includes: mapping UE history information and an enhanced neighbor relation table of a plurality of UEs switched to the serving cell in a past predetermined period to an Euclidean space to form a plurality of reference points; mapping the UE historical information and the enhanced neighbor relation table to the Euclidean space to form a point to be measured; and predicting the probability of the UE switching from the serving cell to each adjacent cell of the serving cell based on Euclidean distances between the point to be measured and the reference points.
According to an embodiment of the present application, predicting the probability of the UE switching from the serving cell to each of the neighboring cells of the serving cell based on the euclidean distances between the point to be measured and the reference points includes: sorting the reference points according to the Euclidean distances between the point to be measured and the reference points from small to large; intercepting the sorted first number of reference points; and predicting the probability of the UE being switched from the serving cell to each of the neighboring cells of the serving cell based on the number of the switched neighboring cells corresponding to each of the first number of reference points.
According to an embodiment of the present application, predicting the probability of the UE switching from the serving cell to each of the neighboring cells of the serving cell based on the euclidean distances between the point to be measured and the reference points includes: sorting the reference points according to the Euclidean distances between the point to be measured and the reference points from small to large; intercepting the sorted first number of reference points; and predicting the probability of the UE being switched from the serving cell to each adjacent cell of the serving cell based on the average distance between the point to be measured and each reference point corresponding to the same switched adjacent cell.
According to an embodiment of the present application, mapping the predicted probability inversely correlated to the measurement interval information comprises: the predicted probabilities are mapped to intervals over which measurements are made for the respective neighbors in an inverse relationship.
According to an embodiment of the application, the method further comprises: receiving cell handover information related to a neighboring cell to which the UE is handed over from the UE; and updating the enhanced neighbor relation table based on the cell switching information.
Another aspect of the present application provides a method performed by a UE in a wireless communication network. The method comprises the following steps: in response to the UE entering a serving cell of a base station, sending UE history information of the UE to a server in the wireless communication network via the base station, the UE history information indicating information of past serving cells serving the UE; receiving measurement interval information from the base station, the measurement interval information being based on the UE history information and an enhanced neighbor relation table prediction indicating time-varying relation information of the serving cell and each of neighbor cells of the serving cell; and measuring signal quality of the UE in the respective neighbor cells based on the measurement interval information.
According to an embodiment of the present application, the information of the past history cell includes at least one of the following information: PRB, PRBG, throughput, number of UEs, and load amount.
According to an embodiment of the application, the time-varying relationship information includes at least one of the following information: the handover probability relationship between the serving cell and each of the neighboring cells, the topological relationship between the serving cell and each of the neighboring cells, the cooperative relationship between the serving cell and each of the neighboring cells, and a future newly defined neighboring cell relationship.
According to an embodiment of the present application, transmitting the UE history information of the UE to a server in the wireless communication network via the base station includes: sending information of up to 16 (including 16) past serving cells that have recently served the UE to a server in the wireless communication network.
According to an embodiment of the present application, the measuring the signal quality of the UE in the respective neighboring cells based on the measurement interval information includes: and measuring the signal quality of the UE in each adjacent cell based on the measurement interval information in response to the signal quality of the UE in the serving cell being smaller than a first threshold value.
According to an embodiment of the application, the method further comprises: switching from the serving cell to one of the neighboring cells in response to a first measurement that the UE's signal quality in the one neighboring cell is greater than a second threshold.
Another aspect of the present application provides a method performed by a server in a wireless communication network. The method comprises the following steps: establishing an enhanced neighbor relation table of a serving cell based on time-varying relation information of the serving cell of a base station in the wireless communication network and each neighbor cell of the serving cell; receiving UE history information from the UE in response to the UE entering the serving cell, the UE history information indicating information of a past serving cell serving the UE; and responding to the UE entering the service cell, and sending the enhanced neighbor relation table and the UE history information to the base station.
According to an embodiment of the present application, the information of the past history cell includes at least one of the following information: PRB, PRBG, throughput, number of UEs, and load amount.
According to an embodiment of the application, the time-varying relationship information includes at least one of the following information: the handover probability relationship between the serving cell and each of the neighboring cells, the topological relationship between the serving cell and each of the neighboring cells, the cooperative relationship between the serving cell and each of the neighboring cells, and a future newly defined neighboring cell relationship.
According to an embodiment of the application, the method further comprises: receiving cell handover information related to a neighboring cell to which the UE is handed over from the UE; and updating the enhanced neighbor relation table based on the cell switching information.
Another aspect of the present application provides a base station in a wireless communication network. The base station includes: a transceiver; and a processor coupled with the transceiver and configured to control the transceiver to perform the method performed by the base station.
Another aspect of the present application provides a UE in a wireless communication network. The UE includes: a transceiver; and a processor coupled with the transceiver and configured to control the transceiver to perform the method performed by the UE.
Another aspect of the present application provides a server in a wireless communication network. The server includes: a transceiver; and a processor coupled with the transceiver and configured to control the transceiver to perform the method performed by the server.
Further, a non-transitory machine-readable storage medium is provided that stores machine-readable instructions which, when executed by a processor, cause the processor to perform the method performed by a base station, a UE, or a server in the wireless communication network described above.
According to the technical scheme, the time characteristic and the space characteristic of the UE switching in the serving cell are considered, the differential measurement of the adjacent cells is realized, the measurement efficiency is improved, and the energy consumption of the UE side is reduced.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
fig. 1 is a diagram illustrating a neighbor cell measurement method of equal measurement interval in the related art;
fig. 2 is a general flow diagram illustrating a communication method related to cell handover in a wireless communication network as proposed herein;
FIG. 3 is a schematic diagram illustrating the meaning of an enhanced neighborhood relationship table of the present application;
FIG. 4 is a schematic diagram showing the distribution of points to be measured and reference points in Euclidean space in the embodiment of the application;
fig. 5 is a diagram illustrating differential measurement of neighboring cells proposed by the present application;
FIG. 6 is a diagram showing hardware entities suitable for use in the present application; and
fig. 7 is a detailed schematic diagram showing hardware entities suitable for the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Fig. 1 is a schematic diagram illustrating a neighbor cell measurement method of equal measurement interval in the related art. In the related art neighbor cell measurement method, when the received signal quality of the UE in the serving cell is below a threshold, the UE starts measuring the signal quality of neighbor cells neighboring the serving cell. As an example, three neighboring cells are shown in fig. 1: neighbor cell 1, neighbor cell 2, and neighbor cell 3. After the UE starts measuring the signal quality of the neighbor cell 1, the neighbor cell 2, and the neighbor cell 3, the UE measures all neighbor cells with a fixed measurement duration τ and a fixed measurement interval Δ T until after measuring that the signal quality of a certain neighbor cell (e.g., the neighbor cell 1) reaches a predetermined strength after a time period T, the measurement process stops and the UE switches from the serving cell to the neighbor cell.
In a complex network environment such as 5G, the cells are densely distributed and the UE is handed over more frequently between cells. However, for a specific UE entering a specific serving cell at a specific time point, the probability (or probability) of the UE switching to each neighboring cell is not the same. The switching of the UE between the cells has certain statistical rules in time and space. If signal quality measurements are made for all neighboring cells at the same time interval each time, the measurement efficiency is relatively low and the UE side energy consumption is relatively high. Therefore, the above measurement method may be difficult to adapt to such a complex network environment due to poor flexibility.
Fig. 2 is a general flow diagram illustrating a communication method related to cell handover in a wireless communication network as proposed in the present application. The wireless communication network shown in fig. 2 includes a UE100, a base station 200, and a server 300.
The server 300 may establish an enhanced neighbor relation table of a serving cell based on time-varying relation information of the serving cell and its respective neighbor cells of the base station 200 in the wireless communication network in step S2010.
In the conventional neighbor relation table, only the IDs of all neighbor cells neighboring the serving cell are included. For example, the conventional neighbor relation table may indicate neighbor cell B, neighbor cell C, and neighbor cell D that neighbor serving cell a. However, the enhanced neighbor relation table proposed in the present application includes time-varying relation information between the serving cell and each neighbor cell.
The time-varying relationship information may include a time-varying handover probability relationship between the serving cell and the neighboring cell, a topological relationship between the serving cell and the neighboring cell, a collaborative relationship between the serving cell and the neighboring cell, and/or a newly defined neighboring cell relationship in the future, and the like.
As shown in fig. 3 (a), at time T, the enhanced neighbor relation table of the serving cell a may be denoted as Tt＝[B:0.7；C:0.2；D:0.1]. The enhanced neighbor relation table indicates the probability of switching the UE in the serving cell a to each neighbor cell at the current time t. At this time, the probability of switching from the UE in the serving cell a to the serving cell B is 0.7; the probability of switching from the UE in the serving cell A to the serving cell C is 0.2; the probability of the UE in the serving cell A switching to the serving cell C is0.1. However, the enhanced neighbor relation table evolves with time, with significant time variability. As shown in fig. 3 (b), at the next time T +1, the enhanced neighbor relation table of the serving cell a may be represented as Tt+1＝[B:0.1；C:0.3；D:0.6]. At this time, the probability of switching from the UE in the serving cell a to the serving cell B is 0.1; the probability of switching from the UE in the serving cell A to the serving cell C is 0.3; the probability of a handover of a UE in serving cell a to serving cell C is 0.6. Such time-varying is common in communication environments such as 5G communications. Since the daily activities of users have a certain statistical regularity, the relationship between a serving cell and surrounding neighboring cells changes with time. Because the enhanced neighbor relation table is proposed in the present application to reflect such dynamics, the enhanced neighbor relation table embodies the time-space characteristics of UE handover in the serving cell. The enhanced neighbor relation table may reflect both time information and spatial information. Essentially, the enhanced neighbor relation table embodies: (1) information of time dimension (2) association information between time information and spatial information.
In steps S2020 and S2030, in response to the UE100 entering the serving cell of the base station 200, the UE100 transmits UE history information of the UE100, which indicates information of a past serving cell serving the UE100, to the server 300 in the wireless communication network via the base station 100. The information of past history cells comprises at least one of the following information: PRB, PRBG, throughput, number of UEs, and load amount. The reporting of UE history information may be performed as specified in 3GPP protocol 36.423. Under the protocol, the number of past serving cells contained in the UE history information does not exceed 16. The server 300 may store and update the UE history information in real time. The UE history information reflects the spatial characteristics of the UE100 in past moves and handovers.
In step S2040 and step S2050, the server 300 sends the UE history information and the enhanced neighbor relation table to the base station 200, respectively. Then, in step S2060, the base station 200 that receives the UE history information and the enhanced neighbor relation table predicts the measurement interval information based on the two items of information, where the measurement interval information may be time interval information or predefined index interval information. The time interval information may indicate a time interval at which measurement is performed on each neighboring cell.
According to one embodiment of the present application, the predicted measurement interval information may be divided into two staged tasks. First, the probability of the UE100 switching from the serving cell of the base station 200 to each neighbor cell of the serving cell is predicted based on the UE history information and the enhanced neighbor relation table. The predicted probability is then inversely correlated mapped to measurement interval information. In other words, a smaller measurement interval is allocated to a neighboring cell having a higher handover probability. In this way, it is convenient for the UE100 to perform differentiated measurement on each neighboring cell, so as to improve measurement efficiency and reduce measurement energy consumption.
In step S2070, the base station 200 transmits the predicted measurement interval information to the UE 100. The UE100 having received the measurement interval information performs differential measurement on each neighboring cell based on the measurement interval information in step S2080.
According to an embodiment of the present application, the starting of the measurement procedure of step S2080 may be triggered based on an event that the signal quality of the UE100 in the serving cell of the base station 200 is less than a first threshold value. According to another embodiment of the present application, the end of the measurement procedure of step S2080 may be based on the first measurement that the signal quality of the UE100 in one neighboring cell is greater than the second threshold value. The second threshold may be the same as or different from the first threshold.
In step S2090, the UE100 may switch from the serving cell to a neighboring cell in response to the first measurement that the signal quality of the UE100 in the neighboring cell is greater than the second threshold.
In steps S2100 and S2110, the UE100 transmits cell handover information about a neighboring cell to which the UE is handed over to the server 300. For example, the UE100 may transmit cell handover information to the server 300 via the original base station 200 before cell handover. However, this transmission procedure is merely an example, and the UE100 may also transmit cell handover information to the server 300 via a new base station after cell handover. In step S2120, the server 300 having received the cell switching information updates the enhanced neighbor relation table of the serving cell of the base station 200.
However, the execution subject of the enhanced neighbor relation table is not limited to the server 300. For example, after the UE100 sends the cell handover information to the base station 200 in step S2100, the base station 200 that receives the cell handover information may also update the enhanced neighbor relation table.
As described above, the base station 200 may predict the probability of the UE100 switching from the serving cell of the base station 200 to each neighbor cell of the serving cell based on the UE history information and the enhanced neighbor relation table. The prediction process embodies consideration of spatial information covered by UE historical information and spatio-temporal information covered by an enhanced neighbor relation table.
Fig. 2 is merely an exemplary general flow diagram suitable for use with the inventive concepts of the present application. However, those skilled in the art will appreciate that the specific steps and bodies of transmission of the various information therein may not be performed as illustrated in the figures. For example, the enhanced neighbor relation table may be created, stored, and transmitted by the server, or may be created, stored, and transmitted by the base station or a network node added in the future. As another example, UE history information may also be stored and transmitted by the base station itself.
According to one embodiment of the application, UE history information and an enhanced neighbor relation table of a plurality of UEs switched to a serving cell in a past predetermined period can be mapped to an Euclidean space to form a plurality of reference points. The selected UEs are UEs that were handed over into the serving cell and then to other cells. The cell ID after handover may be used as a reference.
Assuming that the number of UEs handed over into the serving cell in the past predetermined period is M, the number of reference points is M. The reference point may be denoted as Ref1＝[H,T]. H denotes UE history information, and H ═ H may be used1,h2,h3,…,hN]The form of N is the number of past serving cells reported as described above. T is an enhanced neighbor relation table, and if the neighbor cell IDs are ordered according to a predetermined rule, the enhanced neighbor relation table at the time T can adopt Tt＝[w1,w2,w3,…,wL]In the form of (1). M reference points Ref1To RefMMapping into the Euclidean space of (N + L) dimension.
Then, the UE history information of the UE100 currently entering the serving cell of the base station 200 and the enhanced neighbor relation table may be mapped to the euclidean space to form a point to be measured. It can be expressed in a similar manner to the above reference point to be mapped also into the euclidean space of the (N + L) dimension.
Finally, the probability of the UE switching from the serving cell to each of the neighboring cells of the serving cell may be predicted based on euclidean distances of the points to be measured and the plurality of reference points. By the prediction mode, the historical information of the UE received by the current UE and the enhanced adjacent area relation table can be compared with some historical information, and the cell switching possibly performed by the current UE can be accurately predicted by referring to the historical information in the past period.
In this prediction process, a classification rule of K-Nearest Neighbor (KNN, K-Nearest Neighbor) may be used. According to the application, the reference points can be sorted from near to far according to the Euclidean distance between the point to be measured and the reference points, namely, the reference points are sorted from small to large according to the Euclidean distance, and then the sorted first number of reference points are intercepted. The first number here is the number K in the K-nearest neighbor method. The following is an exemplary illustration of K10. However, one skilled in the art will appreciate that K can be set based on the particular data size and data distribution.
Fig. 4 is a schematic diagram showing the distribution of points to be measured and reference points in euclidean space in the embodiment of the present application. For the sake of intuition, a multi-dimensional space is presented in fig. 4 in a two-dimensional view, and the distance of a point in the multi-dimensional space from the point is represented by the distance between the point and the point in a two-dimensional plane. Following the setup of fig. 3, assume that serving cell a has three neighboring cells, respectively neighboring cell B, neighboring cell C, and neighboring cell D.
In fig. 4, the point to be measured 4100 mapped in the euclidean space is represented by an open circle, the reference point 4200 handed over to the adjacent cell B is represented by a triangle, the reference point 4300 handed over to the adjacent cell C is represented by a square, and the reference point 4400 handed over to the adjacent cell D is represented by a pentagram. The distance sequence of each reference point from the point to be measured 4100 shown in fig. 4 can be represented by the following table 1.
| Sorting | Switching cell |
| 1 | B |
| 2 | B |
| 3 | C |
| 4 | C |
| 5 | D |
| 6 | B |
| 7 | C |
| 8 | C |
| 9 | C |
| 10 | D |
TABLE 1
According to an embodiment of the present application, the probability of the UE100 switching from the serving cell to each of the neighboring cells of the serving cell may be predicted based on the number of the switched neighboring cells corresponding to each of the first number of reference points.
For example, in the case where the first number K shown above is 10: the number of the reference points of the adjacent cell B after switching is 3; the number of reference points of the adjacent cell C after switching is 5; and the number of reference points of the neighboring cell D after handover is 2. Thus, it is predictable that:
the probability of the UE100 switching to the neighboring cell B is 3/10 ═ 0.3;
the probability of the UE100 switching to the neighboring cell C is 5/10 ═ 0.5; and is
The probability of the UE100 switching to the neighboring cell D is 2/10 ═ 0.2.
According to another embodiment of the present application, the probability of the UE switching from the serving cell to each of the neighboring cells of the serving cell may be predicted based on the average distance of the point to be measured 4100 from each of the reference points corresponding to the same neighboring cells after switching.
For example, it is assumed that the distances of the point to be measured 4100 from the respective reference points are represented as table 2 below.
TABLE 2
The average distance from the point 4100 to be measured to the reference point switched to the neighboring cell B is: dB ═ (d1+ d2+ d 6)/3; the average distance from the point 4100 to be measured to the reference point switched to the neighboring cell C is: dC ═ 5 (d3+ d4+ d7+ d8+ d 9); and the average distance of the point to be measured 4100 from the reference point switched to the neighboring cell D is: dD ═ (d5+ d 10)/2. In this case, it is predictable that:
the probability of the UE100 switching to the neighbor cell B is dB/(dB + dC + dD);
the probability of the UE100 switching to the neighbor cell C is dC/(dB + dC + dD); and is
The probability of the UE100 switching to the neighbor cell D is dD/(dB + dC + dD).
According to one embodiment of the present application, inversely correlating the predicted probability to the measurement interval information may include: the predicted probabilities are mapped to intervals over which measurements are made for the respective neighbors in an inverse relationship.
For example, in the case of the embodiment described with reference to table 1, the probabilities of the UE100 switching from the serving cell a to the neighbor cells B, C, and D are 0.3, 0.5, and 0.2, respectively, and with reference to the neighbor cell B of the maximum switching probability, the interval times at which the UE100 measures the signal qualities of the neighbor cells B, C, and D may be respectively set as: τ/0.3 × 0.5; τ/0.5 × 0.5; and τ/0.2 × 0.5. Based on such configuration, a smaller measurement interval may be arranged for a neighboring cell with a high handover probability and a larger measurement interval may be arranged for a neighboring cell with a low handover probability, so that the UE100 may perform differential measurement on each neighboring cell, thereby improving measurement efficiency and reducing measurement energy consumption.
Fig. 5 is a schematic diagram illustrating differential measurement of neighboring cells proposed in the present application. Referring to fig. 5, the UE100 measures received signal quality of respective neighboring cells based on different measurement interval information. Specifically, the UE100 is based on the measurement interval Δ t1Measurements are made on the neighbouring cell 1 based on the measurement interval Δ t2The neighbouring cell 2 is measured and based on the measurement interval at3Measurements are made on the neighbouring cell 3. Since the total measurement time is reduced, the energy consumption of the UE100 is correspondingly reduced.
Fig. 6 is a schematic diagram showing hardware entities suitable for the present application. Hardware entity 6000 as shown in fig. 6 may be suitable as a base station, a UE or a server in various embodiments of the present application. Hardware entity 6000 may include transceiver 6100 and processor 6200. A processor 6200 may be coupled with the transceiver 6100 and configured to control the transceiver 6100 to perform operations performed by the base station, the UE, or the server.
Fig. 7 is a detailed schematic diagram showing hardware entities suitable for the present application. The hardware entities shown in fig. 7 may be suitable as a base station, a UE or a server in various embodiments of the present application. The hardware entities include one or more processors, transceivers, etc., such as: one or more Central Processing Units (CPUs) 701, and/or one or more coprocessors 713, and the like. The processor may perform various appropriate actions and processes according to executable instructions stored in a Read Only Memory (ROM)702 or loaded from a storage section 708 into a Random Access Memory (RAM) 703. The transceiver 712 may include a transmitter and a receiver.
The processor may communicate with the read only memory 702 and/or the random access memory 703 to execute the executable instructions, connect with the transceiver 712 through the bus 704, and communicate with other entities via the transceiver 712 to perform operations corresponding to any of the methods provided by the embodiments of the present application.
In addition, in the RAM 703, various programs and data necessary for the operation of the device can also be stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. The ROM 702 is an optional module in case of the RAM 703. The RAM 703 stores or writes executable instructions into the ROM 702 at runtime, and the executable instructions cause the CPU 701 to execute operations corresponding to the above-described communication method. An input/output (I/O) interface 705 is also connected to bus 704. The transceiver 712 may be integrated or configured with multiple sub-modules (e.g., IB cards) and be linked to a bus.
The following components may be connected to the I/O interface 705: an input section 706 including a keyboard, a mouse, and the like; an output section 707 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage unit 708 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. A drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like, is mounted on the drive 710 as necessary, so that a computer program read out therefrom is mounted into the storage section 708 as necessary.
It should be noted that the architecture shown in fig. 7 is only an optional implementation manner, and in a specific practical process, the number and types of the components in fig. 7 may be selected, deleted, added or replaced according to actual needs; in different functional component settings, separate settings or integrated settings may also be used, for example, the GPU and the CPU may be separately set or the GPU may be integrated on the CPU, the transceiver may be separately set, or the GPU may be integrated on the CPU or the GPU, and so on. These alternative embodiments are all within the scope of the present disclosure.
Further, according to an embodiment of the present application, the processes described above with reference to the flowcharts may be implemented as a computer software program. For example, the present application provides a non-transitory machine-readable storage medium having stored thereon machine-readable instructions executable by a processor to perform instructions corresponding to the method steps provided herein. In such embodiments, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 711. The computer program, when executed by a Central Processing Unit (CPU)701, performs the above-described functions defined in the method of the present application.
The methods and apparatus of the present application may be implemented in a number of ways. For example, the methods and apparatus of the present application may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order for the steps of the method described above is for illustrative purposes only, and the steps of the method of the present application are not limited to the order specifically described above unless specifically stated otherwise. Further, in some embodiments, the present application may also be embodied as a program recorded in a recording medium, the program including machine-readable instructions for implementing a method according to the present application. Thus, the present application also covers a recording medium storing a program for executing the method according to the present application.
The above description is only a preferred embodiment of the present application and is illustrative of the principles of the technology employed. It will be appreciated by a person skilled in the art that the scope of protection covered by the present application is not limited to the embodiments with a specific combination of the features described above, but also covers other embodiments with any combination of the features described above or their equivalents without departing from the technical idea described above. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (20)
1. A method performed by a base station in a wireless communication network, the method comprising:
receiving UE history information of the UE in response to the UE entering a serving cell of the base station, wherein the UE history information indicates information of a past serving cell serving the UE;
responding to the UE entering a service cell of the base station, receiving an enhanced neighbor cell relation table of the service cell, wherein the enhanced neighbor cell relation table indicates time-varying relation information of the service cell and each neighbor cell of the service cell;
predicting measurement interval information of the UE for measuring the signal quality of each adjacent cell based on the UE historical information and the enhanced adjacent cell relation table; and
transmitting the predicted measurement interval information to the UE.
2. The method of claim 1, wherein the time-varying relationship information comprises at least one of: the handover probability relationship between the serving cell and each of the neighboring cells, the topological relationship between the serving cell and each of the neighboring cells, the cooperative relationship between the serving cell and each of the neighboring cells, and a future newly defined neighboring cell relationship.
3. The method of claim 1, wherein predicting measurement interval information for the UE to measure the signal quality of the neighbor cells based on the UE history information and the enhanced neighbor relation table comprises:
predicting the probability of the UE switching from the serving cell to each adjacent cell of the serving cell based on the UE historical information and the enhanced adjacent cell relation table; and
inversely correlating the predicted probability to the measurement interval information.
4. The method of claim 3, wherein predicting the probability of the UE switching from the serving cell to each of the neighbor cells of the serving cell based on the UE history information and the enhanced neighbor relation table comprises:
mapping UE history information and an enhanced neighbor relation table of a plurality of UEs switched to the serving cell in a past predetermined period to an Euclidean space to form a plurality of reference points;
mapping the UE historical information and the enhanced neighbor relation table to the Euclidean space to form a point to be measured; and
and predicting the probability of the UE switching from the serving cell to each adjacent cell of the serving cell based on Euclidean distances between the point to be measured and the reference points.
5. The method of claim 4, wherein predicting the probability of the UE switching from the serving cell to each of the neighboring cells of the serving cell based on the Euclidean distances between the point to be measured and the plurality of reference points comprises:
sorting the reference points according to the Euclidean distances between the point to be measured and the reference points from small to large;
intercepting the sorted first number of reference points; and
predicting the probability of the UE switching from the serving cell to each adjacent cell of the serving cell based on the number of the switched adjacent cells corresponding to each reference point in the first number of reference points.
6. The method of claim 4, wherein predicting the probability of the UE switching from the serving cell to each of the neighboring cells of the serving cell based on the Euclidean distances between the point to be measured and the plurality of reference points comprises:
sorting the reference points according to the Euclidean distances between the point to be measured and the reference points from small to large;
intercepting the sorted first number of reference points; and
and predicting the probability of the UE switching from the serving cell to each adjacent cell of the serving cell based on the average distance between the point to be measured and each reference point corresponding to the same switched adjacent cell.
7. The method of any of claims 2-6, wherein inversely correlating the predicted probability to the measurement interval information comprises:
the predicted probabilities are mapped to intervals over which measurements are made for the respective neighbors in an inverse relationship.
8. The method of claim 1, further comprising:
receiving cell handover information related to a neighboring cell to which the UE is handed over from the UE; and
and updating the enhanced neighbor relation table based on the cell switching information.
9. A method performed by a UE in a wireless communication network, the method comprising:
in response to the UE entering a serving cell of a base station, sending UE history information of the UE to a server in the wireless communication network via the base station, the UE history information indicating information of past serving cells serving the UE;
receiving measurement interval information from the base station, the measurement interval information being based on the UE history information and an enhanced neighbor relation table prediction indicating time-varying relation information of the serving cell and each of neighbor cells of the serving cell; and
measuring signal quality of the UE in the respective neighbor cells based on the measurement interval information.
10. The method of claim 9, wherein the time-varying relationship information comprises at least one of: the handover probability relationship between the serving cell and each of the neighboring cells, the topological relationship between the serving cell and each of the neighboring cells, the cooperative relationship between the serving cell and each of the neighboring cells, and a future newly defined neighboring cell relationship.
11. The method of claim 9, wherein sending, via the base station, the UE history information for the UE to a server in the wireless communication network comprises:
sending information of up to 16 past serving cells that have recently served the UE to a server in the wireless communication network.
12. The method of claim 9, wherein measuring the signal quality of the UE in the respective neighboring cells based on the measurement interval information comprises:
and measuring the signal quality of the UE in each adjacent cell based on the measurement interval information in response to the signal quality of the UE in the serving cell being smaller than a first threshold value.
13. The method of claim 12, further comprising:
switching from the serving cell to one of the neighboring cells in response to a first measurement that the UE's signal quality in the one neighboring cell is greater than a second threshold.
14. A method performed by a server in a wireless communication network, the method comprising:
establishing an enhanced neighbor relation table of a serving cell based on time-varying relation information of the serving cell of a base station in the wireless communication network and each neighbor cell of the serving cell;
receiving UE history information from the UE in response to the UE entering the serving cell, the UE history information indicating information of a past serving cell serving the UE;
and responding to the UE entering the service cell, and sending the enhanced neighbor relation table and the UE history information to the base station.
15. The method of claim 14, wherein the time-varying relationship information comprises at least one of: the handover probability relationship between the serving cell and each of the neighboring cells, the topological relationship between the serving cell and each of the neighboring cells, the cooperative relationship between the serving cell and each of the neighboring cells, and a future newly defined neighboring cell relationship.
16. The method of claim 14, further comprising:
receiving cell handover information related to a neighboring cell to which the UE is handed over from the UE; and
and updating the enhanced neighbor relation table based on the cell switching information.
17. A base station in a wireless communication network, the base station comprising:
a transceiver; and
a processor coupled with the transceiver and configured to control the transceiver to perform the method of any of claims 1-8.
18. A UE in a wireless communication network, the UE comprising:
a transceiver; and
a processor coupled with the transceiver and configured to control the transceiver to perform the method of any of claims 9 to 13.
19. A server in a wireless communication network, the server comprising:
a transceiver; and
a processor coupled with the transceiver and configured to control the transceiver to perform the method of any of claims 14-16.
20. A non-transitory machine-readable storage medium storing machine-readable instructions that, when executed by a processor, cause the processor to perform the method of any of claims 1-16.
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