CN114071580B - Data transmission method and device and electronic equipment - Google Patents
Data transmission method and device and electronic equipment Download PDFInfo
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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
- H04W28/20—Negotiating bandwidth
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
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- H04W72/0453—Resources in frequency domain, e.g. a carrier in FDMA
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- H04W—WIRELESS COMMUNICATION NETWORKS
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Abstract
The invention provides a data transmission method, a data transmission device and electronic equipment, relates to the technical field of communication, and solves the problem of how to select proper configuration parameters according to actual requirements by a wireless node in the related technology. Receiving perception information reported by each wireless node in at least one wireless node served in the current period; determining at least one parameter configuration combination according to at least one configuration information of each wireless node in the at least one wireless node; determining the total uplink throughput corresponding to each parameter configuration combination according to the at least one parameter configuration combination and the network parameters reported by each terminal in at least one terminal in the coverage area reported by each wireless node; determining a parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination; and each wireless node operates in the next period according to the configuration parameters of each wireless node in the parameter configuration combination corresponding to the target uplink throughput.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a data transmission method, a data transmission device, and an electronic device.
Background
In the prior art, in order to promote the development of the internet of things, a sixth Generation mobile communication technology (6-Generation, 6G) has been developed. The 6G network configures a plurality of configuration parameters for each wireless node in the initial stage of design, so that the method is applicable to various use scenes to the greatest extent, and the deployment cost is reduced. However, since the 6G network is still under study, there is no theory related to how the wireless node in the 6G network selects appropriate configuration parameters according to actual requirements.
Therefore, how to select appropriate configuration parameters according to actual requirements of wireless nodes in the 6G network becomes a research hotspot.
Disclosure of Invention
The invention provides a data transmission method, a data transmission device and electronic equipment, which solve the problem of how to select proper configuration parameters according to actual requirements by a wireless node in the related technology.
In order to achieve the above purpose, the invention adopts the following technical scheme:
in a first aspect, an embodiment of the present invention provides a data transmission method, including: receiving perception information reported by each wireless node in at least one wireless node served in the current period; the sensing information at least comprises at least one configuration information and network parameters reported by each terminal in at least one terminal in a coverage area; determining at least one parameter configuration combination according to at least one configuration information of each wireless node in the at least one wireless node; the parameter configuration combination comprises configuration parameters of each wireless node in the next period; determining the total uplink throughput corresponding to each parameter configuration combination according to the at least one parameter configuration combination and the network parameters reported by each terminal in at least one terminal in the coverage area reported by each wireless node; determining a parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination; the target uplink throughput is any one of the total uplink throughput corresponding to each parameter configuration combination; and notifying each wireless node to operate in the next period according to the configuration parameters of each wireless node in the parameter configuration combination corresponding to the target uplink throughput.
As can be seen from the foregoing, in the data transmission method provided by the present invention, the electronic device can know the actual requirement of each wireless node of the current service at any time by receiving the sensing information reported by each wireless node in at least one wireless node of the current period service. The electronic device then determines at least one parameter configuration combination based on at least one configuration information for each of the at least one wireless node. And the electronic equipment determines the total uplink throughput corresponding to each parameter configuration combination according to the at least one parameter configuration combination and the network parameters reported by each terminal in at least one terminal in the coverage area reported by each wireless node. And then, the electronic equipment determines the parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination. Finally, the electronic device informs each wireless node to operate in the next period according to the configuration parameters of each wireless node in the parameter configuration combination corresponding to the target uplink throughput, so that each wireless node can be ensured to select proper configuration parameters according to actual requirements, and the problem of how the wireless node selects proper configuration parameters according to the actual requirements in the related technology is solved.
In one implementation, determining, according to at least one parameter configuration combination and network parameters reported by each terminal in at least one terminal in a coverage area reported by each wireless node, a total uplink throughput corresponding to each parameter configuration combination includes: and inputting the at least one parameter configuration combination and the network parameters reported by each terminal in at least one terminal in the coverage area reported by each wireless node into a pre-trained neural network model, and determining the total uplink throughput corresponding to each parameter configuration combination.
In an implementation manner, before receiving the sensing information reported by each wireless node in at least one wireless node served in the current period, the data transmission method provided by the embodiment of the invention further includes: acquiring training sample data and actual total uplink throughput corresponding to the training sample data; the training sample data comprises perception information of each wireless node in at least one wireless node in different periods; inputting training sample data into a deep learning model; determining whether the predicted total uplink throughput of training sample data output by the deep learning model is matched with the actual total uplink throughput based on the target loss function; and when the predicted total uplink throughput is not matched with the actual total uplink throughput, repeatedly and circularly iteratively updating the network parameters of the deep learning model until the model converges to obtain the neural network model.
In one implementation, determining a parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination includes: and determining the parameter configuration combination corresponding to the maximum total uplink throughput as the parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination.
In a second aspect, the present invention provides a data transmission apparatus comprising: a receiving and transmitting unit and a processing unit.
The receiving and transmitting unit is used for receiving the perception information reported by each wireless node in at least one wireless node served in the current period; the sensing information at least comprises at least one configuration information and network parameters reported by each terminal in at least one terminal in a coverage area; the processing unit is used for determining at least one parameter configuration combination according to the at least one configuration information of each wireless node in the at least one wireless node received by the receiving and transmitting unit; the parameter configuration combination comprises configuration parameters of each wireless node in the next period; the processing unit is further used for determining the total uplink throughput corresponding to each parameter configuration combination according to the at least one parameter configuration combination and the network parameters reported by each terminal in the coverage area reported by each wireless node and received by the receiving and transmitting unit; the processing unit is further used for determining a parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination; the target uplink throughput is any one of the total uplink throughput corresponding to each parameter configuration combination; the processing unit is further configured to control the transceiver unit to notify each wireless node to operate in a configuration parameter of a next period according to the configuration parameter of each wireless node in the parameter configuration combination corresponding to the target uplink throughput in the next period.
In one implementation, the processing unit is specifically configured to input at least one parameter configuration combination and a network parameter reported by each terminal in at least one terminal in a coverage area reported by each wireless node and received by the transceiver unit into a pre-trained neural network model, and determine a total uplink throughput corresponding to each parameter configuration combination.
In one implementation, the transceiver unit is further configured to obtain training sample data and an actual total uplink throughput corresponding to the training sample data; the training sample data comprises perception information of each wireless node in at least one wireless node in different periods; the processing unit is also used for inputting the training sample data acquired by the receiving and transmitting unit into the deep learning model; the processing unit is further used for determining whether the predicted total uplink throughput of the training sample data output by the deep learning model is matched with the actual total uplink throughput or not based on the target loss function; and the processing unit is also used for repeatedly and circularly updating the network parameters of the deep learning model until the model converges to obtain the neural network model when the predicted total uplink throughput is not matched with the actual total uplink throughput.
In one implementation, the processing unit is specifically configured to determine, according to the total uplink throughput corresponding to each parameter configuration combination, a parameter configuration combination corresponding to the maximum total uplink throughput as a parameter configuration combination corresponding to the target uplink throughput.
In a third aspect, the present invention provides an electronic device comprising: communication interface, processor, memory, bus; the memory is used for storing computer execution instructions, and the processor is connected with the memory through a bus. When the electronic device is running, the processor executes the computer-executable instructions stored in the memory to cause the electronic device to perform the data transmission method as provided in the first aspect described above.
In a fourth aspect, the present invention provides a computer-readable storage medium comprising instructions. The instructions, when executed on a computer, cause the computer to perform the data transmission method as provided in the first aspect above.
In a fifth aspect, the present invention provides a computer program product for causing a computer to carry out the data transmission method according to the design of the first aspect when said computer program product is run on the computer.
It should be noted that the above-mentioned computer instructions may be stored in whole or in part on the first computer readable storage medium. The first computer readable storage medium may be packaged together with the processor of the electronic device or may be packaged separately from the processor of the electronic device, which is not limited in the present invention.
The description of the second, third, fourth and fifth aspects of the present invention may refer to the detailed description of the first aspect; further, the advantageous effects described in the second aspect, the third aspect, the fourth aspect, and the fifth aspect may refer to the advantageous effect analysis of the first aspect, and are not described herein.
In the present invention, the names of the above-mentioned electronic devices do not constitute limitations on the devices or function modules themselves, and in actual implementation, these devices or function modules may appear under other names. Insofar as the function of each device or function module is similar to that of the present invention, it falls within the scope of the claims of the present invention and the equivalents thereof.
These and other aspects of the invention will be more readily apparent from the following description.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of a communication system to which a data transmission method is applied according to an embodiment of the present invention;
Fig. 2 is a schematic flow chart of a data transmission method according to an embodiment of the present invention;
FIG. 3 is a second flowchart of a data transmission method according to an embodiment of the present invention;
FIG. 4 is a third flow chart of a data transmission method according to the embodiment of the invention;
FIG. 5 is a schematic diagram of an electronic device according to an embodiment of the present invention;
FIG. 6 is a second schematic diagram of an electronic device according to an embodiment of the present invention;
Fig. 7 is a schematic structural diagram of a computer program product of a data transmission method according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention are described below with reference to the accompanying drawings.
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to clearly describe the technical solution of the embodiments of the present invention, in the embodiments of the present invention, the terms "first", "second", etc. are used to distinguish the same item or similar items having substantially the same function and effect, and those skilled in the art will understand that the terms "first", "second", etc. do not limit the number and execution order.
Fig. 1 is a schematic diagram of a communication system to which the embodiment of the present invention may be applied, where, as shown in fig. 1, the communication system may include:
Server 1, wireless node 2, terminal 3 and core network 4.
The wireless node 2 is configured to send, to the server 1, the sensing information including the network parameter reported by each terminal 3 in at least one terminal in the coverage area and at least one configuration information corresponding to the wireless node 2. The server 1 receives the awareness information reported by each wireless node 2 of the at least one wireless node 2 served in the current period. The server 1 determines at least one parameter configuration combination from at least one configuration information of each of the at least one wireless node 2. And the server 1 determines the total uplink throughput corresponding to each parameter configuration combination according to the at least one parameter configuration combination and the network parameters reported by each terminal 3 in at least one terminal in the coverage area reported by each wireless node 2. And the server 1 determines the parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination. The server 1 informs each wireless node 2 to operate in the next period according to the configuration parameters of each wireless node 2 in the parameter configuration combination corresponding to the target uplink throughput. After receiving the configuration parameters of the next period sent by the server 1, the wireless node 2 needs to reconfigure the configuration parameters of the current operation according to the configuration parameters of the next period sent by the server 1. Meanwhile, the wireless node 2 also needs to notify each terminal 3 in the coverage area to communicate with the wireless node 2 according to the reconfigured configuration parameters in the next period. After receiving the reconfigured configuration parameters sent by the wireless node 2, the terminal 3 needs to configure the parameters for the communication between the next period and the wireless node 2 as the reconfigured configuration parameters sent by the wireless node 2, so as to ensure that the terminal 3 can normally communicate with the wireless node 2. After receiving the configuration completion information sent by each terminal in the coverage area, the wireless node 2 sends configuration success information to the core network 4, where the configuration success information is used to indicate that the wireless node 2 and each terminal 3 in the coverage area of the wireless node 2 complete bandwidth configuration. After receiving the configuration completion information, the core network 4 establishes a data connection with the wireless node 2 and each terminal 3 of the coverage area of the wireless node 2.
Specifically, in the uplink data triggering process, the terminal 3 needs to extract the service requirement of the next sending time slot or longer, and can acquire the current position information of the terminal 3, and compress and transmit the information as required.
In some examples, the above-described server 1 may also be referred to as a central processing unit (central processing unit, CPU).
The electronic device in the embodiment of the present invention may be the server 1 shown in fig. 1, or may be a part of the devices in the server 1. Such as a chip system in the server 1. The chip system is for supporting the server 1 to implement the functions involved in the first aspect and any one of its possible implementations. For example, the at least one wireless node 2 receiving the current periodic service is configured to periodically report the identification code corresponding to the wireless node 2 and the perception information reported by each terminal 3 of the at least one terminal 3 in the coverage area. The chip system includes a chip, and may also include other discrete devices or circuit structures.
The terminal is used for providing voice and/or data connectivity services to the user. The terminals may be variously named, for example, user Equipment (UE), access terminals, terminal units, terminal stations, mobile stations, remote terminals, mobile devices, wireless communication devices, vehicle user equipment, terminal agents or end devices, etc. Optionally, the terminal may be a handheld device, an in-vehicle device, a wearable device, or a computer with a communication function, which is not limited in any way in the embodiment of the present invention. For example, the handheld device may be a smart phone. The in-vehicle device may be an in-vehicle navigation system. The wearable device may be a smart bracelet. The computer may be a Personal Digital Assistant (PDA) computer, a tablet computer, or a laptop computer (laptop computer).
Some terms used in this disclosure have their ordinary and customary meaning in the industry. In addition, some terms will be explained when they appear in the present specification. It will be helpful to understand that several terms are specifically used herein. When referring to
The neural network (Neural Networks, NN) is a complex network system formed by a large number of simple processing units (called neurons) widely interconnected, reflecting many basic features of human brain function, and is a highly complex nonlinear power learning system.
MATLAB is commercial mathematical software available from MathWorks corporation of america for use in the fields of data analysis, wireless communications, deep learning, image processing and computer vision, signal processing, quantitative finance and risk management, robotics, control systems, and the like.
The following describes a data transmission method provided by the embodiment of the present invention, taking an electronic device as a server 1 as an example, in conjunction with the communication system shown in fig. 1.
As shown in fig. 2, the data transmission method includes the contents of the following steps S11 to S15:
S11, the server 1 receives the perception information reported by each wireless node in at least one wireless node served in the current period. The sensing information at least comprises at least one configuration information and network parameters reported by each terminal in at least one terminal in a coverage area.
In one embodiment, the server 1 only obtains the sensing information reported by each wireless node of the current service, and communication can be performed between different servers 1. When the terminal reports the network parameters, the terminal only reports the network parameters to the wireless node serving the terminal currently.
For example, the terminal may periodically obtain network parameters, such as once every 1 transmission time interval (Transport TIME INTERVAL, TTI). In order to report network parameters to a wireless node, the terminal may report network parameters encapsulated in Channel State Information (CSI) Information to the wireless node, or the terminal may report network parameters encapsulated in measurement report (Measurement Report, MR) data to the wireless node, or the terminal may report network parameters encapsulated in Physical Uplink control channel (Physical Uplink Control Channel, PUCCH) to the wireless node, or the terminal may report network parameters encapsulated in Physical Uplink SHARED CHANNEL, PUSCH to the wireless node, or the terminal may extend the original random access or radio resource control layer (Radio Resource Control, RRC) connection signaling, i.e. add location Information and requirements of the terminal.
Specifically, the configuration information at least includes location information, an uplink frequency point, an uplink bandwidth and a transmitting power. The network parameters include location information. The location information may be obtained by a global positioning system (Global Positioning System, GPS) or by a beidou satellite navigation system (BeiDou Navigation SATELLITE SYSTEM, BDS) in china, for example.
In some examples, the network parameters reported by the terminal further include an identification code of the wireless node currently serving and an identification code of the wireless node to be accessed by the terminal. Because the data transmission method provided by the embodiment of the invention only considers the wireless nodes in the same server, the configuration parameters of the wireless nodes in the next period under the same server only need to be determined.
In one embodiment, at least one configuration information corresponding to the wireless node is stored in the network management system. When the wireless node needs to send the perception information to the server 1, the wireless node can send a configuration inquiry request carrying the identification code corresponding to the wireless node to the network management system. After receiving the configuration query request, the network management system queries at least one piece of configuration information corresponding to the identification code in the configuration query request, and sends the at least one piece of configuration information corresponding to the identification code to the wireless node corresponding to the identification code.
For example, taking the total number of wireless nodes currently served by the server 1 as N, each wireless node provides services for J terminals, the network parameters include location information, the location information is obtained through GPS, the terminal reports a random access procedure signaling containing the location information to the wireless node on a PUCCH channel, and the wireless node 2 can determine the location information reported by each terminal in the coverage area shown in table 1 by extracting and separating the information reported by the terminal on the PUCCH.
TABLE 1
Wherein Laij denotes the longitude of the jth terminal served by the wireless node with the identification code i, loij denotes the latitude of the jth terminal served by the wireless node with the identification code i, i e [1, N ], J e [1, J ], and i, J, and N are integers.
Illustratively, taking J configuration information of each wireless node as an example, at least one configuration information corresponding to the identification code of each wireless node stored in the network management system is shown in table 2.
TABLE 2
Wherein,Representing uplink frequency point in jth configuration information supported by ith wireless node,/>The uplink bandwidth in the J-th configuration information supported by the i-th wireless node is represented, P ij represents the transmitting power in the J-th configuration information supported by the i-th wireless node, and J are integers.
Thus, when the wireless node needs to determine at least one configuration information, a configuration query request carrying an identification code corresponding to the wireless node can be sent to the network management system. After receiving the configuration query request, the network management system queries at least one configuration information corresponding to the identification code in the configuration query request in table 1, so as to determine at least one configuration information corresponding to the wireless node.
The above example is illustrated by taking a wireless node sending a configuration query request carrying an identifier code corresponding to the wireless node to a network management system, and after the network management system receives the configuration query request, querying at least one configuration information corresponding to the identifier code in the configuration query request, and sending at least one configuration information corresponding to the identifier code to the wireless node corresponding to the identifier code. In other examples, the wireless node locally stores at least one configuration information supported by the wireless node, so that when the wireless node needs to determine the supported at least one configuration information, the wireless node can directly query the supported at least one configuration information, thereby reducing processing delay.
It should be noted that, after obtaining at least one configuration information corresponding to the wireless node and the network parameters reported by each terminal in at least one terminal in the coverage area, the wireless node needs to encapsulate the at least one configuration information and the network parameters reported by each terminal in at least one terminal in the coverage area, and send the encapsulated network parameters to the server 1 in a signaling manner.
S12, the server 1 determines at least one parameter configuration combination according to at least one configuration information of each wireless node in the at least one wireless node. The parameter configuration combination comprises configuration parameters of each wireless node in the next period.
In some examples, each wireless node contains the same total number of configuration information. In this way, the server 1 can re-combine the configuration information so that at least one parameter configuration combination can be obtained.
Taking the example that the wireless node currently served by the server 1 is the wireless node with the identification code of 1 and the wireless node with the identification code of 2 as the example, the process of determining at least one parameter configuration combination by the server 1 is as follows:
In connection with the example given in S11 above, the server 1 combines the configuration information 1 of the wireless node with the identification code 1 with the configuration information 1 of the wireless node with the identification code 2, thereby forming the parameter configuration combination 1. Similarly, the server 1 combines the configuration information 2 of the wireless node with the identification code 1 with the configuration information 2 of the wireless node with the identification code 2, thereby forming a parameter configuration combination 2. The process of forming the parameter configuration combination 3 to the parameter configuration combination j is similar to the process of forming the parameter configuration combination 1 and the parameter configuration combination 2, and will not be repeated here.
Then, the server 1 sums up the obtained parameter configuration combinations, thereby obtaining a result of the sum up as shown in table 3.
TABLE 3 Table 3
The above example is described taking as an example that the total number of at least one configuration information contained in each wireless node currently served by the server 1 is the same. In some other examples, the total number of at least one configuration information contained by each wireless node currently served by server 1 is not necessarily the same. Illustratively, assume that a wireless node with an identification code of 1 contains a total number of configuration information of 3 and a wireless node with an identification code of 2 contains a total number of configuration information of 2.
After that, the server 1 combines the configuration information 1 of the wireless node of the identification code 1 with the configuration information 1 of the wireless node of the identification code 2, thereby forming a parameter configuration combination 1. The server 1 combines the configuration information 2 of the wireless node with the identification code 1 with the configuration information 2 of the wireless node with the identification code 2, thereby forming a parameter configuration combination 2. When the server generates the parameter configuration combination 3, since the total number of configuration information included in the wireless node with the identification code of 2 is 2, the server 1 only needs to form the parameter configuration combination 3 according to the configuration information 3 of the wireless node with the identification code of 1.
S13, the server 1 determines the total uplink throughput corresponding to each parameter configuration combination according to at least one parameter configuration combination and the network parameters reported by each terminal in at least one terminal in the coverage area reported by each wireless node.
S14, the server 1 determines the parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination. The target uplink throughput is any one of the total uplink throughput corresponding to each parameter configuration combination.
S15, the server 1 informs each wireless node to operate in the next period according to the configuration parameters of each wireless node in the parameter configuration combination corresponding to the target uplink throughput.
As can be seen from the above, in the data transmission method provided by the present invention, the server 1 receives the sensing information reported by each wireless node in at least one wireless node served in the current period, so as to know the actual requirement of each wireless node served at the current time. The server 1 then determines at least one parameter configuration combination from at least one configuration information of each of the at least one wireless node. And the electronic equipment determines the total uplink throughput corresponding to each parameter configuration combination according to the at least one parameter configuration combination and the network parameters reported by each terminal in at least one terminal in the coverage area reported by each wireless node. Then, the server 1 determines a parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination. Finally, the server 1 informs each wireless node to operate according to the configuration parameters of each wireless node in the next period in the parameter configuration combination corresponding to the target uplink throughput, so that each wireless node can be ensured to select proper configuration parameters according to actual requirements, and the problem of how the wireless node selects proper configuration parameters according to actual requirements in the related art is solved.
In some embodiments, in conjunction with fig. 2, as shown in fig. 3, S13 may be specifically implemented by S130 described below.
S130, the server 1 inputs at least one parameter configuration combination and network parameters reported by each terminal in at least one terminal in a coverage area reported by each wireless node into a pre-trained neural network model, and determines the total uplink throughput corresponding to each parameter configuration combination.
In some examples, when the server 1 inputs the at least one parameter configuration combination and the network parameters reported by each terminal in the at least one terminal in the coverage area reported by each wireless node into the pre-trained neural network model, it is required to determine the average distance of the area corresponding to the server 1. Then, the server 1 inputs at least one parameter configuration combination and the area average distance into a pre-trained neural network model, and determines the total uplink throughput corresponding to each parameter configuration combination.
Specifically, the process of calculating the average distance of the region is as follows:
1. The server 1 calculates a first distance of each terminal from each wireless node currently serving. Such as: the server 1 determines a first distance between each terminal and each wireless node currently serving according to the position information of each terminal and the position information of each wireless node currently serving.
2. The server 1 determines an area average distance based on the total number of currently served terminals, the total number of currently served wireless nodes, and the first distance of each terminal from each currently served wireless node.
Wherein Len m represents a first distance of an mth terminal currently served by the server 1, M represents a total number of terminals currently served by the server 1, W represents a total number of wireless nodes currently served by the server 1, len Average of represents an area average distance, M e [1, M ], M, and W are integers.
Specifically, the total number of terminals currently served by the server 1 is equal to the sum of the total number of terminals within the coverage area of each wireless node currently served by the server 1. Such as: the wireless nodes currently served by the server 1 are a wireless node with an identification code of 1 and a wireless node with an identification code of 2, the coverage area of the wireless node with the identification code of 1 contains 3 terminals, the coverage area of the wireless node with the identification code of 2 contains 4 terminals, and then the total number of the terminals currently served by the server 1 is 4+3=7.
In some examples, the server 1 inputs at least one parameter configuration combination and the region average distance into a pre-trained neural network model, determines a corresponding total upstream throughput for each parameter configuration combination, including:
The server 1 sequentially inputs each parameter configuration combination and the region average distance into a pre-trained neural network model, and determines the total uplink throughput corresponding to each parameter configuration combination.
The above example is described by taking the server 1 as an example, inputting at least one parameter configuration combination and network parameters reported by each terminal in at least one terminal in a coverage area reported by each wireless node into a pre-trained neural network model, and determining a total uplink throughput corresponding to each parameter configuration combination. In other examples, the server 1 stores therein a correspondence between at least one parameter configuration combination, the region average distance set, and the total uplink throughput corresponding to the parameter configuration combination. Illustratively, the correspondence is shown in table 4.
TABLE 4 Table 4
| Region average distance set | Combination name | Total uplink throughput |
| [0，10] | Parameter configuration combination 1 | x1 |
| [0，10] | Parameter configuration combination 2 | x2 |
| [0，10] | … | … |
| [0，10] | Parameter configuration combination j | x3 |
| (11，50] | Parameter configuration combination 1 | x4 |
| (11，50] | Parameter configuration combination 2 | x5 |
| (11，50] | … | … |
| (11，50] | Parameter configuration combination j | x6 |
| … | … | … |
| (a，+∞) | Parameter configuration combination J | xJ |
When the server 1 needs to determine the total uplink throughput corresponding to each parameter configuration combination, the server can determine the region average distance set (e.g., [1, 10 ]) in which the region average distance corresponding to the parameter configuration combination falls by querying the corresponding relation shown in table 4, and then determine the total uplink throughput corresponding to each parameter configuration combination.
In some embodiments, in conjunction with fig. 2, as shown in fig. 4, the data transmission method provided by the embodiment of the present invention further includes: S16-S19.
S16, the server 1 acquires training sample data and actual total uplink throughput corresponding to the training sample data. Wherein the training sample data includes perception information of each of the at least one wireless node in different periods.
In some examples, the data transmission method provided by the embodiments of the present invention is applied to a sixth Generation mobile communication technology (6G) network. The 6G network is not deployed at present, so in the data transmission method provided by the embodiment of the present invention, the training sample data is obtained by using system simulation, and may be constructed by using MATLAB or other simulation platforms.
Specifically, after the 6G network is deployed, the neural network model can be used as training sample data according to real test data acquired by drive test, so that the accuracy of an output result of the neural network model is ensured.
Specifically, the training sample data extraction process is as follows:
By randomly scattering points to wireless nodes and terminals in the coverage area of the server 1, and recording the position information of each wireless node and each terminal. And setting each wireless node according to the uplink frequency point, the uplink bandwidth and the transmitting power supported by each wireless node. Since terminals typically communicate with a wireless node based on uplink frequency points, uplink bandwidth, transmit power, and interference between terminals is limited. Therefore, the uplink frequency point, the uplink bandwidth and the transmitting power of the wireless node need to be set first.
Specifically, the simulation process is as follows:
1) The simulation configuration list shown in table 5 is generated according to the uplink frequencies, uplink bandwidths and transmission powers supported by different wireless nodes.
TABLE 5
2) And 1) carrying out random spreading point configuration according to the simulation configuration list given in the step 1), simulating, and recording the total uplink throughput corresponding to each parameter configuration combination in the simulation configuration list.
3) A first distance is calculated for each terminal from each wireless node currently being served.
4) And determining the area average distance according to the total number of the terminals currently served, the total number of the wireless nodes currently served and the first distance between each terminal and each wireless node currently served.
5) And summarizing the total uplink throughput and the area average distance corresponding to each parameter configuration combination in the simulation configuration list to obtain training sample data shown in table 6.
TABLE 6
S17, the server 1 inputs training sample data into the deep learning model.
S18, the server 1 determines whether the predicted total uplink throughput of the training sample data output by the deep learning model is matched with the actual total uplink throughput based on the target loss function.
And S19, when the predicted total uplink throughput is not matched with the actual total uplink throughput, the server 1 repeatedly and circularly iteratively updates the network parameters of the deep learning model until the model converges, and a neural network model is obtained.
In some examples, through the operations of S16-S19, the neural network model has been trained and converged multiple times according to the simulation data, so that after the server 1 inputs at least one parameter configuration combination and the area average distance into the neural network model, the neural network model can determine the total uplink throughput corresponding to each parameter configuration combination.
In some embodiments, as shown in fig. 3 in conjunction with fig. 2, S14 may be specifically implemented by S140 described below.
And S140, the server 1 determines the parameter configuration combination corresponding to the maximum total uplink throughput as the parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination.
In some possible modes, in the data transmission method provided by the embodiment of the invention, the parameter configuration combination corresponding to the maximum total uplink throughput is selected as the parameter configuration combination corresponding to the target uplink throughput, so that the resource utilization rate of the wireless node can be ensured.
For example, in connection with the above example of S130, in the region average distance set [1, 10] in which the region average distance determined in the current period of the server 1 falls, and the wireless node currently served by the server 1 is a wireless node with an identification code of 1 and a wireless node with an identification code of 2, respectively, the server 1 determines that the parameter configuration combination corresponding to the target uplink throughput is the parameter configuration combination 1 if the total uplink throughput x1 corresponding to the parameter configuration combination 1 is the maximum total uplink throughput.
Then, the server 1 configures the combination 1 according to the parameters recorded in table 3, and determines configuration parameters of the wireless node with the next period of 1 and the wireless node with the identification code of 2. As can be seen from table 3, the wireless node with the identification code of 1 is at the uplink frequency point of the next periodUpstream Bandwidth is/>The transmitting power is P 11; the wireless node with the identification code of 2 is/>, at the uplink frequency point of the next periodUpstream Bandwidth is/>The transmission power is P 21.
Then, the server 1 notifies the wireless node with the identification code 1 to configure the uplink frequency point as the next periodUpstream Bandwidth configuration is/>The transmission power is configured as P 11; the server 1 notifies the wireless node with the identification code of 2 to configure the uplink frequency point as/>, in the next periodUpstream Bandwidth configuration is/>The transmit power is configured as P 21.
After the wireless node with the identification code of 1 is configured with the uplink frequency point of the next period, the wireless node needs to inform each terminal in the coverage area of the wireless node to configure the uplink frequency point of the next period as the uplink bandwidth and the transmitting powerThe upstream bandwidth is configured asThe transmit power is configured as P 11. After the wireless node with the identification code of 2 is configured with the uplink frequency point, the uplink bandwidth and the transmitting power of the next period, each terminal in the coverage area of the wireless node needs to be informed of configuring the uplink frequency point of the next period as/>Upstream Bandwidth configuration is/>The transmit power is configured as P 21.
After the terminal has configured the uplink frequency point, the uplink bandwidth and the transmitting power of the next period, the terminal needs to report configuration completion information to the wireless node currently providing service.
After receiving the configuration completion information sent by each terminal in the coverage area, the wireless node with the identification code of 1 sends configuration success information to the core network, wherein the configuration success information is used for indicating that the wireless node and each terminal in the coverage area of the wireless node complete bandwidth configuration. After receiving the configuration completion information, the core network establishes data connection with the wireless node with the identification code of 1 and each terminal with the coverage area of the wireless node with the identification code of 1. After receiving the configuration completion information sent by each terminal in the coverage area, the wireless node with the identification code of 2 sends configuration success information to the core network, wherein the configuration success information is used for indicating that the wireless node and each terminal in the coverage area of the wireless node complete bandwidth configuration. After receiving the configuration completion information, the core network establishes data connection with the wireless node with the identification code of 2 and each terminal with the coverage area of the wireless node with the identification code of 2.
The foregoing description of the solution provided by the embodiments of the present invention has been mainly presented in terms of a method. To achieve the above functions, it includes corresponding hardware structures and/or software modules that perform the respective functions. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The embodiment of the invention can divide the functional modules of the data transmission device according to the method example, for example, each functional module can be divided corresponding to each function, or two or more functions can be integrated in one processing module. The integrated modules may be implemented in hardware or in software functional modules. It should be noted that, in the embodiment of the present invention, the division of the modules is schematic, which is merely a logic function division, and other division manners may be implemented in actual implementation.
Fig. 5 is a schematic structural diagram of an electronic device 10 according to an embodiment of the present invention. The electronic device 10 is configured to receive sensing information reported by each wireless node in at least one wireless node served in a current period; determining at least one parameter configuration combination according to at least one configuration information of each wireless node in the at least one wireless node; determining the total uplink throughput corresponding to each parameter configuration combination according to the at least one parameter configuration combination and the network parameters reported by each terminal in at least one terminal in the coverage area reported by each wireless node; determining a parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination; and notifying each wireless node to operate in the next period according to the configuration parameters of each wireless node in the parameter configuration combination corresponding to the target uplink throughput. The electronic device 10 may include a transceiver unit 101 and a processing unit 102.
The transceiver 101 is configured to receive the sensing information reported by each wireless node in the at least one wireless node served in the current period. For example, in connection with fig. 2, the transceiving unit 101 may be used to perform S11 and S15.
A processing unit 102, configured to determine at least one parameter configuration combination according to at least one configuration information of each wireless node in the at least one wireless nodes received by the transceiver unit 101; the processing unit 102 is further configured to determine, according to the at least one parameter configuration combination and the network parameter reported by each terminal in the at least one terminal in the coverage area reported by each wireless node and received by the transceiver unit 101, a total uplink throughput corresponding to each parameter configuration combination; the processing unit 102 is further configured to determine a parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination; the processing unit 102 is further configured to control the transceiver unit 101 to notify each wireless node to operate in a next period according to the configuration parameters of each wireless node in the parameter configuration combination corresponding to the target uplink throughput. For example, in connection with fig. 2, the processing unit 102 may be used to perform S12, S13, S14 and S15.
All relevant contents of each step related to the above method embodiment may be cited to the functional descriptions of the corresponding functional modules, and their effects are not described herein.
Of course, the electronic device 10 provided in the embodiment of the present invention includes, but is not limited to, the above modules, for example, the electronic device 10 may further include the storage unit 103. The storage unit 103 may be used for storing program code of the write electronics 10, and may also be used for storing data generated by the write electronics 10 during operation, such as data in a write request, etc.
Fig. 6 is a schematic structural diagram of an electronic device 10 according to an embodiment of the present invention, as shown in fig. 6, the electronic device 10 may include: at least one processor 51, a memory 52, a communication interface 53 and a communication bus 54.
The following describes the respective constituent elements of the electronic device 10 in detail with reference to fig. 6:
The processor 51 is a control center of the electronic device 10, and may be one processor or a collective term of a plurality of processing elements. For example, processor 51 is a central processing unit (Central Processing Unit, CPU), but may also be an Application SPECIFIC INTEGRATED Circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention, such as: one or more DSPs, or one or more field programmable gate arrays (Field Programmable GATE ARRAY, FPGA).
In a particular implementation, processor 51 may include one or more CPUs, such as CPU0 and CPU1 shown in FIG. 6, as an example. Also, as one embodiment, the electronic device 10 may include multiple processors, such as the processor 51 and the processor 55 shown in FIG. 6. Each of these processors may be a Single-core processor (Single-CPU) or a Multi-core processor (Multi-CPU). A processor herein may refer to one or more devices, circuits, and/or processing cores for processing data (e.g., computer program instructions).
The Memory 52 may be, but is not limited to, a Read-Only Memory (ROM) or other type of static storage device that can store static information and instructions, a random access Memory (Random Access Memory, RAM) or other type of dynamic storage device that can store information and instructions, or an electrically erasable programmable Read-Only Memory (ELECTRICALLY ERASABLE PROGRAMMABLE READ-Only Memory, EEPROM), a compact disc (Compact Disc Read-Only Memory, CD-ROM) or other optical storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory 52 may be stand alone and be coupled to the processor 51 via a communication bus 54. Memory 52 may also be integrated with processor 51.
In a specific implementation, the memory 52 is used to store data in the present invention and to execute software programs of the present invention. The processor 51 may perform various functions of the air conditioner by running or executing a software program stored in the memory 52 and calling data stored in the memory 52.
The communication interface 53 uses any transceiver-like means for communicating with other devices or communication networks, such as a radio access network (Radio Access Network, RAN), a wireless local area network (Wireless Local Area Networks, WLAN), a terminal, a cloud, etc. The communication interface 53 may include a transceiver unit implementing a receiving function and a transmitting function.
The communication bus 54 may be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (PERIPHERAL COMPONENT INTERCONNECT, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in fig. 6, but not only one bus or one type of bus.
As an example, in connection with fig. 5, the transceiver unit 101 in the electronic device 10 performs the same function as the communication interface 53 in fig. 6, the processing unit 102 performs the same function as the processor 51 in fig. 6, and the storage unit 103 performs the same function as the memory 52 in fig. 6.
Another embodiment of the present invention also provides a computer-readable storage medium having stored therein instructions which, when executed on a computer, cause the computer to perform the method shown in the above-described method embodiment.
In some embodiments, the disclosed methods may be implemented as computer program instructions encoded on a computer-readable storage medium in a machine-readable format or encoded on other non-transitory media or articles of manufacture.
Fig. 7 schematically illustrates a conceptual partial view of a computer program product provided by an embodiment of the invention, the computer program product comprising a computer program for executing a computer process on a computing device.
In one embodiment, a computer program product is provided using signal bearing medium 410. The signal bearing medium 410 may include one or more program instructions that when executed by one or more processors may provide the functionality or portions of the functionality described above with respect to fig. 2. Thus, for example, referring to the embodiment shown in FIG. 2, one or more features of S11-S15 may be carried by one or more instructions associated with signal bearing medium 410. Further, the program instructions in fig. 7 also describe example instructions.
In some examples, signal bearing medium 410 may comprise a computer readable medium 411 such as, but not limited to, a hard disk drive, compact Disk (CD), digital Video Disk (DVD), digital tape, memory, read-only memory (ROM), or random access memory (random access memory, RAM), among others.
In some implementations, the signal bearing medium 410 may include a computer recordable medium 412 such as, but not limited to, memory, read/write (R/W) CD, R/W DVD, and the like.
In some implementations, the signal bearing medium 410 may include a communication medium 413 such as, but not limited to, a digital and/or analog communication medium (e.g., fiber optic cable, waveguide, wired communications link, wireless communications link, etc.).
The signal bearing medium 410 may be conveyed by a communication medium 413 in wireless form (e.g., a wireless communication medium conforming to the IEEE802.41 standard or other transmission protocol). The one or more program instructions may be, for example, computer-executable instructions or logic-implemented instructions.
In some examples, a data-writing apparatus such as described with respect to fig. 2 may be configured to provide various operations, functions, or actions in response to program instructions through one or more of computer-readable medium 411, computer-recordable medium 412, and/or communication medium 413.
From the foregoing description of the embodiments, it will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of functional modules is illustrated, and in practical application, the above-described functional allocation may be implemented by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to implement all or part of the functions described above.
In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another apparatus, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and the parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed in a plurality of different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a readable storage medium. Based on such understanding, the technical solution of the embodiments of the present invention may be essentially or a part contributing to the prior art or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, including several instructions for causing a device (may be a single-chip microcomputer, a chip or the like) or a processor (processor) to perform all or part of the steps of the method described in the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, etc.
The foregoing is merely illustrative of specific embodiments of the present invention, and the scope of the present invention is not limited thereto, but any changes or substitutions within the technical scope of the present invention should be covered by the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. A data transmission method, comprising:
Receiving perception information reported by each wireless node in at least one wireless node served in the current period; the sensing information at least comprises at least one configuration information and network parameters reported by each terminal in at least one terminal in a coverage area; the network parameters include location information, and the configuration information includes: the position information, the uplink frequency point, the uplink bandwidth and the transmitting power;
Determining at least one parameter configuration combination according to at least one configuration information of each wireless node in the at least one wireless node; the parameter configuration combination comprises configuration parameters of each wireless node in the next period;
Determining the total uplink throughput corresponding to each parameter configuration combination according to the at least one parameter configuration combination and the network parameters reported by each terminal in at least one terminal in the coverage area reported by each wireless node;
Determining a parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination; the target uplink throughput is any one of the total uplink throughput corresponding to each parameter configuration combination;
notifying each wireless node to operate in the next period according to the configuration parameters of each wireless node in the parameter configuration combination corresponding to the target uplink throughput;
The determining, according to the at least one parameter configuration combination and the network parameters reported by each terminal in the at least one terminal in the coverage area reported by each wireless node, a total uplink throughput corresponding to each parameter configuration combination includes:
And inputting the at least one parameter configuration combination and network parameters reported by each terminal in at least one terminal in a coverage area reported by each wireless node into a pre-trained neural network model, and determining the total uplink throughput corresponding to each parameter configuration combination.
2. The method according to claim 1, wherein before receiving the perception information reported by each of the at least one wireless node served in the current period, the method further comprises:
Acquiring training sample data and actual total uplink throughput corresponding to the training sample data; wherein the training sample data comprises perception information of each wireless node in at least one wireless node in different periods;
Inputting the training sample data into a deep learning model;
Determining whether the predicted total uplink throughput of the training sample data output by the deep learning model is matched with the actual total uplink throughput based on a target loss function;
and repeatedly and circularly iteratively updating the network parameters of the deep learning model until the model converges to obtain the neural network model when the predicted total uplink throughput is not matched with the actual total uplink throughput.
3. The method for data transmission according to any one of claims 1-2, wherein determining a parameter configuration combination corresponding to a target uplink throughput according to a total uplink throughput corresponding to each of the parameter configuration combinations includes:
and determining the parameter configuration combination corresponding to the maximum total uplink throughput as the parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination.
4. A data transmission apparatus, comprising:
The receiving and transmitting unit is used for receiving the perception information reported by each wireless node in at least one wireless node served in the current period; the sensing information at least comprises at least one configuration information and network parameters reported by each terminal in at least one terminal in a coverage area; the network parameters include location information, and the configuration information includes: the position information, the uplink frequency point, the uplink bandwidth and the transmitting power;
the processing unit is used for determining at least one parameter configuration combination according to the at least one configuration information of each wireless node in the at least one wireless node received by the receiving and transmitting unit; the parameter configuration combination comprises configuration parameters of each wireless node in the next period;
the processing unit is further configured to determine, according to the at least one parameter configuration combination and the network parameters reported by each terminal in at least one terminal in a coverage area reported by each wireless node and received by the transceiver unit, a total uplink throughput corresponding to each parameter configuration combination;
the processing unit is further configured to determine a parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination; the target uplink throughput is any one of the total uplink throughput corresponding to each parameter configuration combination;
The processing unit is further configured to control the transceiver unit to notify each wireless node to operate in a next period according to a configuration parameter of each wireless node in a parameter configuration combination corresponding to the target uplink throughput;
The processing unit is specifically configured to input the at least one parameter configuration combination and the network parameter reported by each terminal in at least one terminal in the coverage area reported by each wireless node and received by the transceiver unit into a pre-trained neural network model, and determine a total uplink throughput corresponding to each parameter configuration combination.
5. The data transmission device according to claim 4, wherein the transceiver unit is further configured to obtain training sample data and an actual total uplink throughput corresponding to the training sample data; wherein the training sample data comprises perception information of each wireless node in at least one wireless node in different periods;
the processing unit is further used for inputting the training sample data acquired by the receiving and transmitting unit into a deep learning model;
The processing unit is further used for determining whether the predicted total uplink throughput of the training sample data output by the deep learning model is matched with the actual total uplink throughput or not based on a target loss function;
And the processing unit is further used for repeatedly and circularly updating the network parameters of the deep learning model until the model converges to obtain the neural network model when the predicted total uplink throughput is not matched with the actual total uplink throughput.
6. The data transmission device according to any one of claims 4 to 5, wherein the processing unit is specifically configured to determine, according to a total uplink throughput corresponding to each of the parameter configuration combinations, a parameter configuration combination corresponding to a maximum total uplink throughput as the parameter configuration combination corresponding to the target uplink throughput.
7. A computer readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the data transmission method according to any of the preceding claims 1-3.
8. An electronic device, comprising: communication interface, processor, memory, bus;
the memory is used for storing computer execution instructions, and the processor is connected with the memory through the bus;
the processor executing computer-executable instructions stored in the memory to cause the electronic device to perform the data transmission method of any one of the preceding claims 1-3 when the electronic device is operating.
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Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2117239A1 (en) * | 2007-01-26 | 2009-11-11 | Fujitsu Limited | Base station device and cell switching determination method |
| CN102572927A (en) * | 2010-12-30 | 2012-07-11 | 中国移动通信集团设计院有限公司 | Method, device and system for base station power distribution |
| CN102958170A (en) * | 2011-08-30 | 2013-03-06 | 华为技术有限公司 | Up-link interference coordination method and base station |
| CN103945450A (en) * | 2013-01-17 | 2014-07-23 | 中兴通讯股份有限公司 | Data transmission method and device |
| CN104012137A (en) * | 2012-12-21 | 2014-08-27 | 华为技术有限公司 | Method for minimization of drive test measurement, user equipment and network device |
| EP2947943A1 (en) * | 2013-01-18 | 2015-11-25 | Huawei Technologies Co., Ltd. | Scheduling method and scheduling apparatus for user equipment in communications system |
| CN105392158A (en) * | 2014-08-29 | 2016-03-09 | 英特尔Ip公司 | communication terminal and method for controlling a data transmission |
| CN106211204A (en) * | 2015-04-30 | 2016-12-07 | 中兴通讯股份有限公司 | A kind of method knowing unlicensed spectrum wireless environment and device, terminal |
| CN107251580A (en) * | 2015-02-24 | 2017-10-13 | 日本电信电话株式会社 | Wireless communication system and wireless communications method |
| CN107294571A (en) * | 2017-06-26 | 2017-10-24 | 维沃移动通信有限公司 | A kind of data transmission method, base station and mobile terminal |
| CN108881045A (en) * | 2018-06-04 | 2018-11-23 | 河南科技大学 | A kind of jamming control method ensured in heterogeneous network based on QoS |
| CN109547278A (en) * | 2017-09-22 | 2019-03-29 | 中兴通讯股份有限公司 | A kind of method and device promoting super cell network throughput |
| CN111356232A (en) * | 2018-12-21 | 2020-06-30 | 中国电信股份有限公司 | Parameter configuration method, device and system and computer readable storage medium |
| EP3726891A1 (en) * | 2019-04-19 | 2020-10-21 | T-Mobile USA, Inc. | Selection of frequency band for user equipment by radio access network |
| CN112312415A (en) * | 2019-07-25 | 2021-02-02 | 中国移动通信有限公司研究院 | Uplink data distribution method and terminal |
| CN112333753A (en) * | 2020-11-27 | 2021-02-05 | 中国联合网络通信集团有限公司 | Method and device for evaluating number of accessible users |
| CN112512077A (en) * | 2020-12-15 | 2021-03-16 | 中国联合网络通信集团有限公司 | Uplink rate evaluation method and device |
| CN112995057A (en) * | 2021-05-20 | 2021-06-18 | 布比（北京）网络技术有限公司 | Maximum transmission rate determining method, maximum transmission rate determining device, electronic equipment and storage medium |
| CN113056016A (en) * | 2021-03-17 | 2021-06-29 | 中国联合网络通信集团有限公司 | Co-construction shared resource block configuration method and access network equipment |
| CN113115371A (en) * | 2021-03-17 | 2021-07-13 | 中国联合网络通信集团有限公司 | Co-construction shared resource block configuration method and access network equipment |
| CN113453239A (en) * | 2021-06-17 | 2021-09-28 | 西安电子科技大学 | Channel resource allocation method and system, storage medium and electronic device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5781101B2 (en) * | 2013-02-06 | 2015-09-16 | 株式会社東芝 | Control device, representative base station, radio communication system, and base station control method |
-
2021
- 2021-11-04 CN CN202111302321.3A patent/CN114071580B/en active Active
Patent Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2117239A1 (en) * | 2007-01-26 | 2009-11-11 | Fujitsu Limited | Base station device and cell switching determination method |
| CN102572927A (en) * | 2010-12-30 | 2012-07-11 | 中国移动通信集团设计院有限公司 | Method, device and system for base station power distribution |
| CN102958170A (en) * | 2011-08-30 | 2013-03-06 | 华为技术有限公司 | Up-link interference coordination method and base station |
| CN104012137A (en) * | 2012-12-21 | 2014-08-27 | 华为技术有限公司 | Method for minimization of drive test measurement, user equipment and network device |
| CN103945450A (en) * | 2013-01-17 | 2014-07-23 | 中兴通讯股份有限公司 | Data transmission method and device |
| EP2947943A1 (en) * | 2013-01-18 | 2015-11-25 | Huawei Technologies Co., Ltd. | Scheduling method and scheduling apparatus for user equipment in communications system |
| CN105392158A (en) * | 2014-08-29 | 2016-03-09 | 英特尔Ip公司 | communication terminal and method for controlling a data transmission |
| CN107251580A (en) * | 2015-02-24 | 2017-10-13 | 日本电信电话株式会社 | Wireless communication system and wireless communications method |
| CN106211204A (en) * | 2015-04-30 | 2016-12-07 | 中兴通讯股份有限公司 | A kind of method knowing unlicensed spectrum wireless environment and device, terminal |
| CN107294571A (en) * | 2017-06-26 | 2017-10-24 | 维沃移动通信有限公司 | A kind of data transmission method, base station and mobile terminal |
| CN109547278A (en) * | 2017-09-22 | 2019-03-29 | 中兴通讯股份有限公司 | A kind of method and device promoting super cell network throughput |
| CN108881045A (en) * | 2018-06-04 | 2018-11-23 | 河南科技大学 | A kind of jamming control method ensured in heterogeneous network based on QoS |
| CN111356232A (en) * | 2018-12-21 | 2020-06-30 | 中国电信股份有限公司 | Parameter configuration method, device and system and computer readable storage medium |
| EP3726891A1 (en) * | 2019-04-19 | 2020-10-21 | T-Mobile USA, Inc. | Selection of frequency band for user equipment by radio access network |
| CN112312415A (en) * | 2019-07-25 | 2021-02-02 | 中国移动通信有限公司研究院 | Uplink data distribution method and terminal |
| CN112333753A (en) * | 2020-11-27 | 2021-02-05 | 中国联合网络通信集团有限公司 | Method and device for evaluating number of accessible users |
| CN112512077A (en) * | 2020-12-15 | 2021-03-16 | 中国联合网络通信集团有限公司 | Uplink rate evaluation method and device |
| CN113056016A (en) * | 2021-03-17 | 2021-06-29 | 中国联合网络通信集团有限公司 | Co-construction shared resource block configuration method and access network equipment |
| CN113115371A (en) * | 2021-03-17 | 2021-07-13 | 中国联合网络通信集团有限公司 | Co-construction shared resource block configuration method and access network equipment |
| CN112995057A (en) * | 2021-05-20 | 2021-06-18 | 布比（北京）网络技术有限公司 | Maximum transmission rate determining method, maximum transmission rate determining device, electronic equipment and storage medium |
| CN113453239A (en) * | 2021-06-17 | 2021-09-28 | 西安电子科技大学 | Channel resource allocation method and system, storage medium and electronic device |
Non-Patent Citations (3)
| Title |
|---|
| "5G: A Tutorial Overview of Standards, Trials, Challenges, Deployment, and Practice";Mansoor Shafi等;《IEEE Journal on Selected Areas in Communications ( Volume: 35, Issue: 6, June 2017)》;20170407;全文 * |
| "基于5G关键技术的行业应用研究";熊杰;《长江信息通信》;20211015;全文 * |
| CMCC.RP-191223 "Status report for SI on RAN-centric data collection and utilization for LTE and NR".3GPP tsg_ran\tsg_ran.2019,(tsgr_84),全文. * |
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