CN108123812B - Base station switching prediction method and device - Google Patents
Base station switching prediction method and device Download PDFInfo
- Publication number
- CN108123812B CN108123812B CN201611063070.7A CN201611063070A CN108123812B CN 108123812 B CN108123812 B CN 108123812B CN 201611063070 A CN201611063070 A CN 201611063070A CN 108123812 B CN108123812 B CN 108123812B
- Authority
- CN
- China
- Prior art keywords
- base station
- time window
- past time
- switching
- rate
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 24
- 238000004891 communication Methods 0.000 claims description 9
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 239000000872 buffer Substances 0.000 claims description 3
- 230000002093 peripheral effect Effects 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/147—Network analysis or design for predicting network behaviour
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The invention provides a base station switching prediction method and a base station switching prediction device, which are used for predicting whether base station switching is possible to occur in a short time window in the future by extracting base station data characteristics on a mobile terminal. Through analysis, some data characteristics in a short time window before the base station switching are found to have certain correlation with whether the base station switching occurs. Therefore, depending on the base station signal at the mobile terminal, it is possible to determine in advance with a relatively high probability whether a base station handover is likely to occur. The invention predicts whether the mobile terminal will have base station switching in the next time window by extracting the base station information on the mobile terminal, and the prediction result can be used for improving the mobile internet surfing experience of the user.
Description
Technical Field
The invention relates to the technical field of communication, in particular to a base station switching prediction method and a base station switching prediction device.
Background
Base station handover is a technique for ensuring continuity of communication for mobile communication users. When the user is in a mobile state, the mobile phone moves from a signal coverage area of one base station to a signal coverage area of another base station, or is positioned at a boundary where the signal strengths of the two base stations are not greatly different, base station switching occurs. The base station switching can ensure the continuity of user communication, and the communication quality is also ensured by switching to the base station with strong signal at any time.
However, some handover operations must be performed during the handover of the base station, consuming some handover time. When performing the switching operation, a momentary network obstruction may occur, and although the switching operation takes a short time, generally in the order of milliseconds, the mobile internet surfing experience of the user may still be affected, for example, the user may feel a momentary network pause when surfing the internet with a mobile phone. From the perspective of creating a good product experience for the user, it is better to predict in advance whether the base station switching will occur in the next time window, so as to cache some data for the user in advance to optimize the internet experience.
Disclosure of Invention
Therefore, the invention provides a base station switching prediction method and a base station switching prediction device, which predict whether base station switching is possible to occur in a short time window in the future by extracting the data characteristics of the base station on a mobile terminal. Through analysis, some data characteristics in a short time window before the base station switching are found to have certain correlation with whether the base station switching occurs. Therefore, depending on the base station signal at the mobile terminal, it is possible to determine in advance with a relatively high probability whether a base station handover is likely to occur.
The specific scheme is as follows:
a base station switching prediction method comprises the following steps:
s1, the mobile terminal buffers the base station signal data once at intervals, and the base station signal data comprises a main base station ID, main base station intensity and a base station active set;
s2, setting a time window Tw, and respectively calculating a base station switching rate P1 in the past time window Tw, the size P2 of an average effective base station set in the past time window Tw, an effective base station set updating rate P3 in the past time window Tw and a main base station signal intensity fluctuation rate P4 in the past time window Tw according to the base station signal data;
s3, converting the base station switching rate P1 in the past time window Tw, the size P2 of the average effective base station set in the past time window Tw, the updating rate P3 of the effective base station set in the past time window Tw and the main base station signal strength fluctuation rate P4 in the past time window Tw into corresponding fuzzy probability values P1, P2, P3 and P4 respectively;
s4, carrying out weighted summation on the fuzzy probability values p1, p2, p3 and p4, wherein the weighted summation value is X;
s5, comparing the weighted sum value X with a preset threshold value Y, if X is larger than Y, considering that the base station switching can occur in the next time window Tw, otherwise, considering that the base station switching can not occur in the next time window Tw;
s6, returning to the prediction result of the step S5;
s7, steps S1 to S6 are executed for each time when entering a time window Tw.
In step S2, the specific method for calculating the base station switching rate P1 in the past time window Tw is:
counting the switching times N of the base station in a past time window Tw according to the signal data of the base station;
the ratio of the number of base station switching times N to the time window Tw in the past time window Tw is calculated as the base station switching rate P1 in the past time window Tw, P1= N/Tw.
In step S2, the specific method for calculating the size P2 of the average effective bss in the past time window Tw is:
the number of available neighboring bss detected by the mobile terminal in the past time window Tw is counted according to the bs signal data, i.e. the size P2 of the average effective bs set.
In step S2, the specific method for calculating the effective bs set update rate P3 in the past time window Tw is:
counting the change times M of an effective base station set in a past time window Tw according to the base station signal data, wherein the change of the effective base station set comprises the addition and the reduction of any base station in the effective base station set;
calculating the ratio of the number of changes M of the active bss in the past time window Tw to the time window Tw, which is the update rate P3 of the active bss in the past time window Tw, P3= M/Tw.
In step S2, the specific method for calculating the fluctuation rate P4 of the signal strength of the master base station in the past time window Tw is:
counting the change times K of the signal intensity of the main base station in a past time window Tw according to the base station signal data;
and calculating the ratio of the change times K of the signal intensity of the main base station in the past time window Tw to the time window Tw, namely the fluctuation rate P4, P4= K/Tw of the signal intensity of the main base station in the past time window Tw, wherein the main base station is the base station of the mobile terminal which currently establishes communication connection.
A base station handover prediction apparatus comprising:
the data caching module is used for caching base station signal data once at intervals by the mobile terminal, wherein the base station signal data comprises a main base station ID, main base station strength and a base station active set;
a first calculating module, configured to set a time window Tw, and calculate, according to the bs signal data, a bs switching rate P1 in the past time window Tw, a size P2 of an average active bs set in the past time window Tw, an active bs set update rate P3 in the past time window Tw, and a main bs signal strength fluctuation rate P4 in the past time window Tw, respectively;
a conversion module, configured to convert the base station switching rate P1 in the past time window Tw, the size P2 of the average effective base station set in the past time window Tw, the effective base station set update rate P3 in the past time window Tw, and the main base station signal strength fluctuation rate P4 in the past time window Tw into corresponding fuzzy probability values P1, P2, P3, and P4, respectively;
the second calculation module is used for weighting and summing the fuzzy probability values p1, p2, p3 and p4, and the weighted and summed value is X;
the comparison and prediction module is used for comparing the weighted sum value X with a preset threshold value Y, if X is larger than Y, the base station switching can be considered to occur in the next time window Tw, otherwise, the base station switching can not occur in the next time window Tw;
the return module is used for returning the prediction result of the comparison prediction module;
and the repeated execution module is used for entering all the modules for processing every time when entering a time window Tw.
The first calculating module is further configured to calculate a base station switching rate P1 in a past time window Tw:
counting the switching times N of the base station in a past time window Tw according to the signal data of the base station;
the ratio of the number of base station switching times N to the time window Tw in the past time window Tw is calculated as the base station switching rate P1 in the past time window Tw, P1= N/Tw.
The first calculating module is further configured to calculate a size P2 of the average effective bs set in the past time window Tw:
the number of available neighboring bss detected by the mobile terminal in the past time window Tw is counted according to the bs signal data, i.e. the size P2 of the average effective bs set.
The first calculating module is further configured to calculate an effective bs set update rate P3 in a past time window Tw:
counting the change times M of an effective base station set in a past time window Tw according to the base station signal data, wherein the change of the effective base station set comprises the addition and the reduction of any base station in the effective base station set;
calculating the ratio of the number of changes M of the active bss in the past time window Tw to the time window Tw, which is the update rate P3 of the active bss in the past time window Tw, P3= M/Tw.
The first calculating module is further configured to calculate a main base station signal strength fluctuation rate P4 in a past time window Tw:
counting the change times K of the signal intensity of the main base station in a past time window Tw according to the base station signal data;
and calculating the ratio of the change times K of the signal intensity of the main base station in the past time window Tw to the time window Tw, namely the fluctuation rate P4, P4= K/Tw of the signal intensity of the main base station in the past time window Tw, wherein the main base station is the base station of the mobile terminal which currently establishes communication connection.
The invention has the beneficial effects that: the invention predicts whether the mobile terminal will have base station switching in the next time window by extracting the base station information on the mobile terminal, and the prediction result can be used for improving the mobile internet surfing experience of the user.
Drawings
FIG. 1 is a flow chart of a method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an apparatus according to an embodiment of the present invention.
Detailed Description
To further illustrate the various embodiments, the invention provides the accompanying drawings. The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the embodiments. Those skilled in the art will appreciate still other possible embodiments and advantages of the present invention with reference to these figures. The invention will now be further described with reference to the accompanying drawings and detailed description.
Fig. 1 shows a flow chart of a base station handover prediction method, where the extracted data features on the mobile phone include: the base station switching rate of the past time window, the size of the effective base station set, the updating rate of the effective base station set and the fluctuation rate of the signal intensity of the main base station.
Every minute, the four data characteristics are extracted in a time period before one minute, and are converted into a fuzzy probability according to the correlation relationship between the characteristic value and the switching. And weighting the four fuzzy probability values to obtain a prediction probability value. And predicting whether the base station switching can occur in the next one-minute time window according to the prediction probability value.
Base station handover rate for past time window: the past time window Tw =60s (other values may be taken according to actual application needs, but all subsequent time window values must be equal to Tw), and the ratio of the number of times of base station switching N to the length of the time window in the past time window is counted, which is the base station switching rate P1= N/Tw. The base station switching rate P1 in the past time window has a certain correlation with whether switching is likely to occur in the future, for example, when the past time window P1 of the user is 0, it indicates that the user's handset basically does not have base station switching in the past time, and is likely to be in an area where the base station signal is strong and stable, and the probability of switching in the future is low; the higher the P1, indicating that the user has frequently switched base stations in the past, possibly in a zone where the signals of multiple base stations intersect, the higher the probability of future switching.
Effective base station set size: an effective base station set is generally cached in the mobile phone, and the base stations in the base station set are peripheral available base stations detected by the mobile phone. The average active bs set size P2 in the past time window Tw has a certain correlation with whether bs handover is likely to occur in the future: the larger the effective base station set size P2 is, the more likely it is that the user is in a dense base station area (e.g., a busy urban area), and the base station handover will occur in the future; the smaller the P2, the less probability that the user will deal with a sparse area of base stations (e.g., a suburban area), and the base station switching in the future will occur.
Effective base station set update rate: and counting the change times M of the effective base station set in the past time window Tw of the mobile phone. Update rate P3= M/Tw. The change of the effective base station set comprises the addition and the reduction of any base station in the effective base station set. The larger the effective base station set update rate P3 is, the more unstable the area signal where the user is located is or the user is in a moving state, and the probability of base station switching in the future is high; the smaller the effective base station set update rate P3 is, the more stationary the user is in relative signal stability, and the lower the probability of base station handover in the future.
Main base station signal intensity fluctuation rate: in the effective base station set, the base station to which the user mobile phone is currently connected is a main base station, and the change times K of the signal intensity of the main base station in the past time window are counted. The main base station signal intensity fluctuation ratio P4= K/Tw. The smaller P4 is, the more stable the signal of the main base station where the user is located is, and the probability of switching the base station in the future is low; the larger P4 is, the higher the probability that the switching of the base station occurs in the future when the signal of the main base station where the user is located is stable is shown;
fuzzy probability conversion: since the value ranges of P1, P2, P3 and P4 are different, the weighted integration is difficult. They need to be normalized to the fuzzy probabilities with the same range of values.
Where the fuzzy probability of P1 is transformed as follows: if P1 is zero, indicating that the base station switch never occurred before, then the fuzzy probability of the base station switch occurring in the future is also 0; since the base station switching speed is about 20ms, the switching is performed 5 times per second at the fastest speed, so that the maximum number of times of switching in the past time window is N =5Tw, and when P1= N/Tw =5Tw/Tw =5, it indicates that the base station is frequently switched at the highest rate before, the ambiguity probability that the base station switching will occur in the future is considered to be 1. The formula for converting P1 into the fuzzy probability P1 is as follows: p1= P1/5.
The fuzzy probability of P2 is transformed as follows: if the size of the active set P2=1, it indicates that there is only one base station around the mobile phone, so the fuzzy probability of the base station switching in the future is 0; since the hexagonal cell has a maximum number of 7 peripheral base stations plus the number of main base stations, and P2=7 indicates that the number of peripheral base stations of the mobile phone is the most dense, the ambiguity probability of the future occurrence of base station handover is 1. Therefore, the formula for converting P2 into the fuzzy probability P2 is as follows: p2= (P2-1)/(7-1) = (P2-1)/6.
The fuzzy probability of P3 is transformed as follows: if P3=0, it indicates that the mobile phone signal is stable or substantially static, and the state of the peripheral base station detected by the mobile phone is unchanged, so the fuzzy probability of the future occurrence of base station switching is 0; in the same way, since the base station switches 5 times per second at the fastest, the active set has 7 base stations at the maximum, and therefore, theoretically, the number of the base stations can be changed by 5 × 7 =35 times per second at the maximum. Therefore, the maximum number of changes of the effective base station set in the past time window is M =35 Tw. Then P3=35 indicates that the effective set of base stations of the handset changes most frequently, so the ambiguity probability of a future base station handover is 1. Therefore, the formula for converting P3 into the fuzzy probability P3 is as follows: p3= P3/35.
The fuzzy probability of P4 is transformed as follows: if P4=0, it indicates that the mobile phone main base station signal is stable and never fluctuates, so the fuzzy probability of the base station switching in the future is 0; data statistics shows that the mobile phone main base station signal fluctuates 10 times per second and then has high probability of base station switching, so that the fuzzy probability of base station switching in the future is 1. Therefore, the formula for converting P4 into the fuzzy probability P4 is as follows: p4= P4/10.
The maximum values of p1, p2, p3 and p4 are 1, and if the maximum values exceed 1, the maximum values are 1.
Fuzzy probability weighted sum: different weighted values are given according to the correlation strength of the p1, p2, p3 and p4 values and the base station switching happening in the future time window Tw, and the weighted values are summed to obtain a comprehensive prediction metric:
X = 0.15p1 + 0.2p2 + 0.35p3 + 0.3p4。
predicting whether a handover occurs: and judging whether the base station switching can occur in the next time window or not according to the X value. If X is greater than 0.9, it is determined that more than 1 base station handover will occur in the next time window Tw; otherwise, the base station switching will not occur in the next time window Tw.
And returning the prediction result to the application program, wherein the application program can cache some data which may be used in the future (such as the sub-link content of the current browsing page of the user) from the network in advance according to the prediction result so as to improve the internet surfing experience of the user.
The specific steps of this example are as follows:
the method comprises the following steps: the mobile phone buffers the base station signal once every 10ms, including the main base station ID, the main base station strength and the base station active set.
Step two: the P1, P2, P3 and P4 values are calculated every other time window Tw by using the data buffered in the step 1 during the previous time Tw.
Step three: these values are converted into fuzzy probability values p1, p2, p3, p 4.
Step four: a weighted sum X of the ambiguity probability values is found.
Step five: judging whether X is greater than 0.9, if so, considering that more than 1 time of base station switching can occur in the next time window Tw; otherwise, the base station switching will not occur in the next time window Tw.
Step six: and returning to the prediction result of the step five.
Step seven: and executing the first step to the fifth step every time the time window Tw is entered, and continuously predicting.
Based on the foregoing method for predicting base station handover, the present invention further provides a device for predicting base station handover, as shown in fig. 2, the device comprising:
the data caching module is used for caching base station signal data once at intervals by the mobile terminal, wherein the base station signal data comprises a main base station ID, main base station strength and a base station active set;
a first calculating module, configured to set a time window Tw, and calculate, according to the bs signal data, a bs switching rate P1 in the past time window Tw, a size P2 of an average active bs set in the past time window Tw, an active bs set update rate P3 in the past time window Tw, and a main bs signal strength fluctuation rate P4 in the past time window Tw, respectively;
a conversion module, configured to convert the base station switching rate P1 in the past time window Tw, the size P2 of the average effective base station set in the past time window Tw, the effective base station set update rate P3 in the past time window Tw, and the main base station signal strength fluctuation rate P4 in the past time window Tw into corresponding fuzzy probability values P1, P2, P3, and P4, respectively;
the second calculation module is used for weighting and summing the fuzzy probability values p1, p2, p3 and p4, and the weighted and summed value is X;
the comparison and prediction module is used for comparing the weighted sum value X with a preset threshold value Y, if X is larger than Y, the base station switching can be considered to occur in the next time window Tw, otherwise, the base station switching can not occur in the next time window Tw;
the return module is used for returning the prediction result of the comparison prediction module;
and the repeated execution module is used for entering all the modules for processing every time when entering a time window Tw.
The first calculating module is further configured to calculate a base station switching rate P1 in a past time window Tw:
counting the switching times N of the base station in a past time window Tw according to the signal data of the base station;
the ratio of the number of base station switching times N to the time window Tw in the past time window Tw is calculated as the base station switching rate P1 in the past time window Tw, P1= N/Tw.
The first calculating module is further configured to calculate a size P2 of the average effective bs set in the past time window Tw:
the number of available neighboring bss detected by the mobile terminal in the past time window Tw is counted according to the bs signal data, i.e. the size P2 of the average effective bs set.
The first calculating module is further configured to calculate an effective bs set update rate P3 in a past time window Tw:
counting the change times M of an effective base station set in a past time window Tw according to the base station signal data, wherein the change of the effective base station set comprises the addition and the reduction of any base station in the effective base station set;
calculating the ratio of the number of changes M of the active bss in the past time window Tw to the time window Tw, which is the update rate P3 of the active bss in the past time window Tw, P3= M/Tw.
The first calculating module is further configured to calculate a main base station signal strength fluctuation rate P4 in a past time window Tw:
counting the change times K of the signal intensity of the main base station in a past time window Tw according to the base station signal data;
and calculating the ratio of the change times K of the signal intensity of the main base station in the past time window Tw to the time window Tw, namely the fluctuation rate P4, P4= K/Tw of the signal intensity of the main base station in the past time window Tw, wherein the main base station is the base station of the mobile terminal which currently establishes communication connection.
The invention predicts whether the mobile terminal will have base station switching in the next time window by extracting the base station information on the mobile terminal, and the prediction result can be used for improving the mobile internet surfing experience of the user.
While the invention has been particularly shown and described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A base station switching prediction method is characterized by comprising the following steps:
s1, the mobile terminal buffers the base station signal data once at intervals, and the base station signal data comprises a main base station ID, main base station intensity and a base station active set;
s2, setting a time window Tw, and respectively calculating a base station switching rate P1 in the past time window Tw, the size P2 of an average effective base station set in the past time window Tw, an effective base station set updating rate P3 in the past time window Tw and a main base station signal intensity fluctuation rate P4 in the past time window Tw according to the base station signal data;
s3, converting the base station switching rate P1 in the past time window Tw, the size P2 of the average effective base station set in the past time window Tw, the updating rate P3 of the effective base station set in the past time window Tw and the main base station signal strength fluctuation rate P4 in the past time window Tw into corresponding fuzzy probability values P1, P2, P3 and P4 respectively;
s4, carrying out weighted summation on the fuzzy probability values p1, p2, p3 and p4, wherein the weighted summation value is X;
s5, comparing the weighted sum value X with a preset threshold value Y, if X is larger than Y, considering that the base station switching can occur in the next time window Tw, otherwise, considering that the base station switching can not occur in the next time window Tw;
s6, returning to the prediction result of the step S5;
s7, steps S1 to S6 are executed for each time when entering a time window Tw.
2. The method of claim 1, wherein the specific method of calculating the BS switching ratio P1 in the past time window Tw in the step S2 is:
counting the switching times N of the base station in a past time window Tw according to the signal data of the base station;
the ratio of the number of base station switching times N to the time window Tw in the past time window Tw is calculated as the base station switching rate P1 in the past time window Tw, P1= N/Tw.
3. The method for predicting base station handover as claimed in claim 1, wherein the step S2
The specific method for calculating the size P2 of the average effective bs set in the past time window Tw is:
the number of available neighboring bss detected by the mobile terminal in the past time window Tw is counted according to the bs signal data, i.e. the size P2 of the average effective bs set.
4. The method for predicting base station handover as claimed in claim 1, wherein the step S2
The specific method for calculating the effective bs set update rate P3 in the past time window Tw is:
counting the change times M of an effective base station set in a past time window Tw according to the base station signal data, wherein the change of the effective base station set comprises the addition and the reduction of any base station in the effective base station set;
calculating the ratio of the number of changes M of the active bss in the past time window Tw to the time window Tw, which is the update rate P3 of the active bss in the past time window Tw, P3= M/Tw.
5. The method for predicting base station handover as claimed in claim 1, wherein the step S2
The specific method for calculating the fluctuation rate P4 of the signal strength of the main base station in the past time window Tw is:
counting the change times K of the signal intensity of the main base station in a past time window Tw according to the base station signal data;
and calculating the ratio of the change times K of the signal intensity of the main base station in the past time window Tw to the time window Tw, namely the fluctuation rate P4, P4= K/Tw of the signal intensity of the main base station in the past time window Tw, wherein the main base station is the base station of the mobile terminal which currently establishes communication connection.
6. A base station handover prediction apparatus, comprising:
the data caching module is used for caching base station signal data once at intervals by the mobile terminal, wherein the base station signal data comprises a main base station ID, main base station strength and a base station active set;
a first calculating module, configured to set a time window Tw, and calculate, according to the bs signal data, a bs switching rate P1 in the past time window Tw, a size P2 of an average active bs set in the past time window Tw, an active bs set update rate P3 in the past time window Tw, and a main bs signal strength fluctuation rate P4 in the past time window Tw, respectively;
a conversion module, configured to convert the base station switching rate P1 in the past time window Tw, the size P2 of the average effective base station set in the past time window Tw, the effective base station set update rate P3 in the past time window Tw, and the main base station signal strength fluctuation rate P4 in the past time window Tw into corresponding fuzzy probability values P1, P2, P3, and P4, respectively;
the second calculation module is used for weighting and summing the fuzzy probability values p1, p2, p3 and p4, and the weighted and summed value is X;
the comparison and prediction module is used for comparing the weighted sum value X with a preset threshold value Y, if X is larger than Y, the base station switching can be considered to occur in the next time window Tw, otherwise, the base station switching can not occur in the next time window Tw;
the return module is used for returning the prediction result of the comparison prediction module;
and the repeated execution module is used for entering all the modules for processing every time when entering a time window Tw.
7. The base station switching prediction device of claim 6 wherein the first calculating module is further configured to calculate a base station switching rate P1 in a past time window Tw:
counting the switching times N of the base station in a past time window Tw according to the signal data of the base station;
the ratio of the number of base station switching times N to the time window Tw in the past time window Tw is calculated as the base station switching rate P1 in the past time window Tw, P1= N/Tw.
8. The base station switching prediction device of claim 6, wherein the first calculating module is further configured to calculate a size P2 of the average effective bs set in a past time window Tw:
the number of available neighboring bss detected by the mobile terminal in the past time window Tw is counted according to the bs signal data, i.e. the size P2 of the average effective bs set.
9. The base station switching prediction device of claim 6 wherein the first calculating module is further configured to calculate an effective bs set update rate P3 in a past time window Tw:
counting the change times M of an effective base station set in a past time window Tw according to the base station signal data, wherein the change of the effective base station set comprises the addition and the reduction of any base station in the effective base station set;
calculating the ratio of the number of changes M of the active bss in the past time window Tw to the time window Tw, which is the update rate P3 of the active bss in the past time window Tw, P3= M/Tw.
10. The base station switching prediction device of claim 6 wherein the first calculating module is further configured to calculate a fluctuation rate P4 of the signal strength of the primary base station in a past time window Tw:
counting the change times K of the signal intensity of the main base station in a past time window Tw according to the base station signal data;
and calculating the ratio of the change times K of the signal intensity of the main base station in the past time window Tw to the time window Tw, namely the fluctuation rate P4, P4= K/Tw of the signal intensity of the main base station in the past time window Tw, wherein the main base station is the base station of the mobile terminal which currently establishes communication connection.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611063070.7A CN108123812B (en) | 2016-11-28 | 2016-11-28 | Base station switching prediction method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611063070.7A CN108123812B (en) | 2016-11-28 | 2016-11-28 | Base station switching prediction method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108123812A CN108123812A (en) | 2018-06-05 |
| CN108123812B true CN108123812B (en) | 2021-07-30 |
Family
ID=62224840
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611063070.7A Active CN108123812B (en) | 2016-11-28 | 2016-11-28 | Base station switching prediction method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108123812B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2014044639A (en) * | 2012-08-28 | 2014-03-13 | Denso Corp | Communication control system |
| CN104469864A (en) * | 2014-12-01 | 2015-03-25 | 林志均 | Mobile terminal cross-zone switching method and system |
| CN105472671A (en) * | 2014-09-10 | 2016-04-06 | 中兴通讯股份有限公司 | Cell switching method in GSM system and base station device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004289226A (en) * | 2003-03-19 | 2004-10-14 | Nec Corp | Mobile information terminal and hand-over solving method |
-
2016
- 2016-11-28 CN CN201611063070.7A patent/CN108123812B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2014044639A (en) * | 2012-08-28 | 2014-03-13 | Denso Corp | Communication control system |
| CN105472671A (en) * | 2014-09-10 | 2016-04-06 | 中兴通讯股份有限公司 | Cell switching method in GSM system and base station device |
| CN104469864A (en) * | 2014-12-01 | 2015-03-25 | 林志均 | Mobile terminal cross-zone switching method and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108123812A (en) | 2018-06-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108712747B (en) | Link quick establishment method based on spectrum prediction | |
| US7864727B2 (en) | Congestion control method for wireless communication system and base station control apparatus | |
| US20060003768A1 (en) | Method for detecting and reducing ping-pong handover effect of cellular network | |
| CN102088748B (en) | Method for selecting handover trigger time of user based on auto-regressive (AR) model prediction | |
| US20240040544A1 (en) | User equipment tracking and paging area selection in wireless communication systems | |
| CN102647767A (en) | Method, device and terminal device for reselecting and measuring cell | |
| JP2006165972A (en) | Radio wave status monitoring method and device, cell transition method and device using the same and mobile radio equipment | |
| Alhammadi et al. | Fuzzy logic based negotiation approach for spectrum handoff in cognitive radio network | |
| CN110708733A (en) | Network connection control method and device, storage medium and electronic equipment | |
| WO2004025975A2 (en) | Cellular network handoff decision mechanism | |
| CN104244269B (en) | A kind of method and apparatus of cell networking | |
| CN108076489A (en) | A kind of method and device of cell selection | |
| Roslee et al. | Efficient handoff spectrum scheme using fuzzy decision making in cognitive radio system | |
| KR100619646B1 (en) | Reselection optimization in mobile wireless communication devices and methods therefor | |
| CN108123812B (en) | Base station switching prediction method and device | |
| CN108924888B (en) | Switching method and device suitable for multi-connection network and LTE base station | |
| CN112235780B (en) | Data service switching method, equipment, device and storage medium | |
| CN103476080A (en) | Self-adaption vertical handoff method based on residence time | |
| WO2023207957A1 (en) | Cell reselection method for space-air-ground integrated network, and communication system and related device | |
| Santucci et al. | A general analysis of signal strength handover algorithms with cochannel interference | |
| WO2023103995A1 (en) | Cell measurement method and apparatus, terminal, storage medium, and program product | |
| CN115843050A (en) | Network slice configuration method and system, computer storage medium | |
| CN108462980B (en) | Switching method and device of voice call network | |
| CN106792882B (en) | Network evaluation method and device | |
| WO2012073059A1 (en) | Methods, apparatuses and computer program products for using downlink and uplink over separate radio channels or different operators |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP03 | Change of name, title or address | ||
| CP03 | Change of name, title or address |
Address after: 303-e, Zone C, innovation building, software park, torch hi tech Zone, Xiamen City, Fujian Province Patentee after: Xiamen Yaxun Zhilian Technology Co.,Ltd. Country or region after: China Address before: 303-e, Zone C, innovation building, software park, torch hi tech Zone, Xiamen City, Fujian Province Patentee before: XIAMEN YAXON NETWORK Co.,Ltd. Country or region before: China |