CN111818587B - Data interaction method based on 5G network - Google Patents
Data interaction method based on 5G network Download PDFInfo
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- CN111818587B CN111818587B CN202010607370.7A CN202010607370A CN111818587B CN 111818587 B CN111818587 B CN 111818587B CN 202010607370 A CN202010607370 A CN 202010607370A CN 111818587 B CN111818587 B CN 111818587B
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Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
- H04W28/18—Negotiating wireless communication parameters
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
- H04W28/18—Negotiating wireless communication parameters
- H04W28/22—Negotiating communication rate
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention provides a data interaction method based on a 5G network, and provides a judging method for determining data exchange between a base station and a plurality of users, so that the problem of uneven load of each base station can be avoided, and the overall network connection quality is improved. In addition, different weight values are set according to different online users in the judging process, so that the high-quality online users can keep better 5G online quality.
Description
Technical Field
The invention relates to the technical field of 5G, in particular to a data interaction method based on a 5G network.
Background
With the advancement of technology, the 4G wireless communication is not capable of meeting the requirements of users, especially for automatic driving, remote surgery and the like, limited by the 4G, and still has a delay of more than 10ms, which makes the technical development of the 5G wireless communication imperative.
In general, in terms of data interaction, the maximum received signal strength is usually adopted as an on-line policy, but this policy easily causes an increase in the number of users connected to a part of base stations, while the number of users connected to a part of base stations is poor, or when the users are located in two adjacent base stations, the on-line policy may cause the users to continuously switch between two base stations in the on-line process, which cannot effectively achieve the 5G transmission speed, and easily causes waste of resources, so the creator of the present invention recognizes that there is a need for improvement.
Disclosure of Invention
The problem to be solved by the invention is that the maximum received signal strength is adopted to bring various negative effects to the online strategy in the aspect of data interaction in general 5G wireless communication.
In order to solve the problems, the invention provides a data interaction method based on a 5G network, which has the following technical scheme:
a data interaction method based on a 5G network, comprising:
(1) Detecting online users in a local supply range of a 5G network to obtain online data, detecting base stations in the local supply range of the 5G network to obtain base station data, estimating online rates between each online user and each base station to obtain rate value data, and a plurality of Lagrange multipliers lambda corresponding to the number of the base stations k ，λ k A Lagrangian multiplier for the kth base station;
(2) The processor sets the initial value of each Lagrange multiplier, and judges several kinds of base station connection number distribution data according to the base station data and the connection data, and according to the formula sigma k∈A n k (λ k -logn k ) Calculating the operation value of the connection number distribution data of each base station respectively, and taking out the connection number distribution data of the base station corresponding to the maximum operation value to obtain distribution result data, wherein n is as follows k A number of connections denoted as kth base station;
(3) Subtracting the Lagrangian multiplier of the corresponding base station from each rate value data to obtain a plurality of subtracted values, and judging the base station better connected with each user according to each subtracted value to obtain online data x ik Wherein x is ik =1 indicates that the ith user is online to the kth base station, x ik =0 indicates that the ith user is disconnected from the kth base station and each user is connected to only one base station;
(4) Taking the online data and the distribution result data according to n k -∑ i∈C x ik Performing operation, wherein when the result is 0, the step (6) is executed, and when the result is not 0, the step (5) is executed;
(5) According to lambda k ＝λ k -μ(n k -∑ i∈C x ik ) Obtaining new lambda k According to new lambda k Re-executing steps (2) to (4), wherein μ is a lagrangian multiplier transformed amplitude value;
(6) And controlling the online mode of each base station and each online user according to the distribution result data.
The invention determines the data interaction method between the base station and the user in the 5G network through the steps, can effectively balance the transmission rate and the number of online users, and can not cause the problems of overload of part of the base stations, lighter load of part of the base stations and the like, thereby improving the online quality of the whole 5G network.
Drawings
FIG. 1 is a flow chart of embodiment 1 of the present invention
FIG. 2 is a flow chart of embodiment 2 of the invention
FIG. 3 is a flow chart of embodiment 4 of the invention
Detailed Description
In order that the above objects, features and advantages of the invention will be readily understood, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings.
Example 1:
referring to fig. 1, the present invention relates to a data interaction method based on a 5G network, which is characterized by comprising:
(1) Detecting online users in a local supply range of a 5G network to obtain online data, detecting base stations in the local supply range of the 5G network to obtain base station data, estimating online rates between each online user and each base station to obtain rate value data, and a plurality of Lagrange multipliers lambda corresponding to the number of the base stations k ，λ k Indicating the lagrangian multiplier for the kth base station.
(2) The processor sets the initial value of each Lagrange multiplier, judges the distribution online data of several base stations according to the base station data and the online data, and calculates the formula sigma k∈A n k (λ k -logn k ) Calculating the operation value of the distribution online data of each base station respectively, and taking out the distribution data corresponding to the maximum operation value to obtain distribution result data, wherein n is as follows k Denoted as the number of connections to the kth base station.
(3) Subtracting the Lagrangian multiplier of the corresponding base station from each rate value data to obtain a plurality of subtracted values, and judging the users according to each subtracted valueConnected base station to obtain on-line data x ik Wherein x is ik =1 indicates that the ith user is online to the kth base station, x ik =0 indicates that the ith user is disconnected from the kth base station and each user is connected to only one base station.
(4) Taking the online data and the distribution result data according to n k -∑ i∈C x ik And (3) performing operation, when the result is 0, executing the step (6), and when the result is not zero, executing the step (5).
(5) According to lambda k ＝λ k -μ(n k -∑ i∈C x ik ) Obtaining new lambda k According to new lambda k Re-executing steps (2) to (4), wherein μ is a lagrangian multiplier transformed amplitude value.
(6) And controlling the connection mode of each base station and each connection user according to the better connection data of each user.
For example, step (1) is performed first: firstly, detecting the number of base stations and the number of users in a range, and then detecting the online rate between each online user and each base station, wherein the rate value data comprises the following steps: the connection speed of the first user (i=1) to the first base station (k=1) is 12, the connection speed of the first user (i=1) to the second base station (k=2) is 5, the connection speed of the second user (i=2) to the first base station (k=1) is 12, and the connection speed of the second user (i=2) to the second base station (k=2) is 10.
Next, step (2) is performed: initial values of the Lagrangian multipliers, e.g. (lambda) 1 ,λ 2 ) For (5, 0), then assume that the base station assigns the number of connections to (n) respectively 1 ,n 2 ) Three ways of assigning the number of connections, such as= (2, 0), (1, 1), (0, 2). And then according to sigma k∈A nk (λk-lognk) respectively calculates the calculation value of the allocated connection number data of each base station.
(n 1 ,n 2 )＝(2,0)：2(5-log2)+0(0-log0)＝9.4；
(n 1 ,n 2 )＝(1,1)：1(5-log1)+1(0-log1)＝5；
(n 1 ,n 2 )＝(0,2)：0(5-log0)+2(0-log2)＝-0.6；
From the above, when (n 1 ,n 2 ) When= (2, 0), the operation value is the maximum, and therefore, the allocation result data is (n) 1 ,n 2 )＝(2,0)。
And then executing the step (3): looking at the first user first, when the first user is connected with the first base station, the subtraction value is: 12-5=7. When the first user is connected to the second base station, the subtraction value is 5-0=5, and the first user preferably selects the first base station to be connected, so x is 11 ＝1、x 12 =0. And similarly judging the second user, and then x 21 ＝0、x 22 ＝1。
Following step (4) according to nk- Σ i∈C xik, performing operation:
n1＝2，∑ i∈C xik =x11+x12=1, so nk- Σ i∈C xik＝1
n2＝0，∑ i∈C xik =x21+x22=1, so nk- Σ i∈C xik＝-1
Since none of the above results is 0, step (5) is performed to adjust λ k According to λk=λk- μ (nk- Σ) i∈C xik) to obtain a new λk, λ assuming that the Lagrangian multiplier transformation amplitude value is 1 1 ＝5-1(2-1)＝4，λ 2 =0-1 (0-1) =1, and then steps (2) to (5) are repeated. Finally get the lambda 1 ＝3，λ 2 When=2, then (n 1 ,n 2 ) = (2, 0) is the preferred connection data of each user, and then the connection mode of each base station and each connection user is controlled according to the preferred connection data of each user, so that each user can obtain the best connection quality.
As can be seen from the above description, the present invention provides a method for determining data exchange between each base station and a user, which can effectively allocate the connection number and connection mode of each base station, so that the problem of uneven load of the base stations is not easy to occur, and the connection quality of the overall 5G network is improved. In addition, the above numerical operations are only used as references, and are mainly used for assisting in explaining the method flow of the present invention, so that the method flow created by the present invention is clearer.
Example 2:
referring to fig. 2, in order to provide a good quality user with better online quality, the present invention further sets weight values for each user, and the implementation manner is as follows: the online data respectively comprises a weight value W of each online user i Wherein W is i A weight value representing an ith online user; the difference between this embodiment 2 and embodiment 1 is that: in step (4), according to n k -∑ i∈C W i x ik Performing operation; in step (5), according to lambda k ＝λ k -μ(n k -∑ i∈C W i x ik ) Obtaining new lambda k 。
The manner in which the present embodiment determines the data exchange between the users with various weights and the base station is described in embodiment 1. In this way, in the process of considering the data exchange manner between the base station and the users, the embodiment considers the weight value of each user, so that the high-quality user with higher weight value can obtain the online quality with better quality.
Example 3:
in embodiment 1, the method for estimating the connection rate between each connection user and each base station is preferably: the distance between each online user and each base station is detected, the signal-to-noise power ratio (signal to noise ratio, SNR) between each online user and each base station is estimated according to the distance, and then the R=Blog is used 2 (1+SNR), estimating the on-line rate between each on-line user and each base station to obtain rate value data.
In this way, more accurate rate value data can be obtained, so that the embodiment 1 or 2 can obtain more accurate judgment, thereby improving the overall online quality.
Example 4:
referring to fig. 3, the present invention further considers the online rate requirement of each online user by: in the step (1), each online user corresponds to one minimum online rate demand data, when the result is 0 in the step (4), the corresponding rate value data is firstly taken out according to the online data, then each rate value data is compared with each minimum online rate demand data, when each rate value data meets each minimum online rate demand data, the step (6) is executed, and when each rate value data does not meet each minimum online rate demand data, the step (5) is executed.
For example, when the result of the online data is that the first online user is online to the first base station and the estimated rate value data according to embodiment 3 is a, if each minimum online rate requirement of the first online user is b, but a < b indicates that the online mode is not the optimal online mode, then step (5) is performed; if a > b, indicating that the first online user's online rate requirement has been met, then consider the online rate requirements of other online users, and execute step (6) when all online users' online rate requirements are met.
Therefore, the online rate requirement of each online user can be met through the creation of the invention.
Example 5:
because the present invention is actually executed, the situation that the online rate requirement of each online user cannot be met may also happen, and therefore, the present invention can be set to enable the online rate requirement of most online users to be met during the implementation, so as to avoid the situation that the steps are continuously executed during the actual implementation of embodiment 4.
Therefore, the present embodiment may further be implemented as: in step (4), when the number of rate data not meeting the minimum connection rate requirement data exceeds the default number, step (5) is performed. In addition, the preset number can be set according to the requirement.
Although the present disclosure is described above, the scope of protection of the present disclosure is not limited thereto. Various changes and modifications may be made by one skilled in the art without departing from the spirit and scope of the disclosure, and these changes and modifications will fall within the scope of the invention.
Claims (5)
1. A data interaction method based on a 5G network, comprising:
(1) Detecting online users in a local supply range of a 5G network to obtain online data, detecting base stations in the local supply range of the 5G network to obtain base station data, estimating online rates between each online user and each base station to obtain rate value data, and a plurality of Lagrange multipliers lambda corresponding to the number of the base stations k ，λ k A Lagrangian multiplier for the kth base station;
(2) The processor sets the initial value of each Lagrange multiplier, and judges several kinds of base station connection number distribution data according to the base station data and the connection data, and according to the formula sigma k∈A n k (λ k -logn k ) Calculating the operation value of the connection number distribution data of each base station respectively, and taking out the connection number distribution data of the base station corresponding to the maximum operation value to obtain distribution result data, wherein n is as follows k A number of connections denoted as kth base station;
(3) Subtracting the Lagrangian multiplier of the corresponding base station from each rate value data to obtain a plurality of subtracted values, and judging the base station better connected with each user according to each subtracted value to obtain online data x ik Wherein x is ik =1 indicates that the ith user is online to the kth base station, x ik =0 indicates that the ith user is disconnected from the kth base station and each user is connected to only one base station;
(4) Taking on-line data and distribution result data according to n k -∑ i∈C x ik Performing operation, wherein when the result is 0, the step (6) is executed, and when the result is not 0, the step (5) is executed;
(5) According to lambda k ＝λ k -μ(n k -∑ i∈C x ik ) Obtaining new lambda k According to new lambda k Re-executing steps (2) to (4), wherein μ is a lagrangian multiplier transformed amplitude value;
(6) And controlling the online mode of each base station and each online user according to the distribution result data.
2. The method for 5G network based data interaction according to claim 1, wherein each online data includes a weight W of each online user i Wherein W is i A weight value representing an ith online user; in step (4), according to n k -∑ i∈C W i x ik Performing operation; in step (5), according to lambda k ＝λ k -μ(n k -∑ i∈C W i x ik ) Obtaining new lambda k 。
3. The method of claim 1 or 2, wherein distances between each on-line user and each base station are detected, and signal-to-noise-and-power ratios (signal to noise ratio, SNR) between each on-line user and each base station are estimated based on the distances, and r=blog 2 (1+SNR), estimating the on-line rate between each on-line user and each base station to obtain rate value data.
4. The data interaction method based on 5G network as claimed in claim 3, wherein in step (1), each online user corresponds to a minimum online rate demand data, in step (4), when the result is 0, the corresponding rate value data is first extracted according to the online data, then each rate value data is compared with each minimum online rate demand data, when each rate value data meets each minimum online rate demand data, step (6) is executed, and when each rate value data does not meet each minimum online rate demand data, step (5) is executed.
5. The method of claim 4, wherein step (4) is performed when the rate value data does not satisfy the minimum connection rate requirement data by more than a predetermined amount.
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