CN114071580A - Data transmission method and device and electronic equipment - Google Patents
Data transmission method and device and electronic equipment Download PDFInfo
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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. The method comprises the steps of receiving perception information reported by each wireless node in at least one wireless node which is served at the current period; determining at least one parameter configuration combination according to at least one configuration information of each wireless node in 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 the at least one terminal in the coverage range 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 and apparatus, 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) is produced. The 6G network configures a plurality of configuration parameters for each wireless node in the initial design stage, so that the method can be applied to various use scenes to the maximum extent, and the deployment cost is reduced. However, as the 6G network is still in research phase, there is no theory about how the wireless nodes in the 6G network can select the appropriate configuration parameters according to actual requirements.
Therefore, how to select appropriate configuration parameters according to actual requirements by wireless nodes in the 6G network becomes a hot point of research.
Disclosure of Invention
The invention provides a data transmission method, a data transmission device and electronic equipment, and solves 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 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 which is served at the current period; the perception information at least comprises at least one piece of 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 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 the at least one terminal in the coverage range 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 throughputs corresponding to each parameter configuration combination; and informing 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 in the next period.
In the data transmission method provided by the invention, the electronic device can know the actual demand of each wireless node currently served by the electronic device at any moment by receiving the sensing information reported by each wireless node in at least one wireless node currently served by the electronic device in a periodic manner. The electronic device then determines at least one parameter configuration combination based on the 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 the at least one terminal in the coverage range 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 of the next period to operate according to the configuration parameters of the next period in the parameter configuration combination corresponding to the target uplink throughput, so that each wireless node can select proper configuration parameters according to actual requirements, and the problem of how to select proper configuration parameters according to actual requirements by the wireless nodes in the related art is solved.
In an implementation, determining a total uplink throughput corresponding to each parameter configuration combination according to 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, includes: and inputting the at least one parameter configuration combination and the network parameters reported by each terminal in the at least one terminal in the coverage range 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 of the at least one wireless node currently periodically served, the data transmission method provided in the embodiment of the present 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 or not based on a target loss function; and when the predicted total uplink throughput is not matched with the actual total uplink throughput, iteratively updating the network parameters of the deep learning model repeatedly and circularly until the model converges to obtain the neural network model.
In an implementation, determining a parameter configuration combination corresponding to a target uplink throughput according to a 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, including: a transceiving unit and a processing unit.
The receiving and sending unit is used for receiving the sensing information reported by each wireless node in at least one wireless node which is served in the current period; the perception information at least comprises at least one piece of 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 transceiving 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 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, a total uplink throughput corresponding to each parameter configuration combination; the processing unit is further used for determining 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 throughputs corresponding to each parameter configuration combination; and the processing unit is further used for controlling the transceiver unit to inform each wireless node of the next period to operate according to the configuration parameters of the next period in the parameter configuration combination corresponding to the target uplink throughput.
In an implementation, the processing unit is specifically configured to input, to a pre-trained neural network model, at least one parameter configuration combination and a network parameter, which is reported by each terminal in at least one terminal in a coverage area reported by each wireless node and received by the transceiver unit, 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 transceiving unit into the deep learning model; the processing unit is further used for determining whether the predicted total uplink throughput of the deep learning model for the training sample data is matched with the actual total uplink throughput based on the target loss function; and the processing unit is also used for iteratively updating the network parameters of the deep learning model repeatedly and circularly when the predicted total uplink throughput is not matched with the actual total uplink throughput until the model converges to obtain the neural network model.
In an implementation, the processing unit is specifically configured to determine, according to the total uplink throughput corresponding to each parameter configuration combination, that the parameter configuration combination corresponding to the maximum total uplink throughput is the 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 operating, the processor executes the computer-executable instructions stored by the memory to cause the electronic device to perform the data transmission method as provided by the first aspect above.
In a fourth aspect, the 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 above in the first aspect.
In a fifth aspect, the present invention provides a computer program product, which when run on a computer, causes the computer to execute the data transmission method according to the first aspect.
It should be noted that all or part of the above computer instructions may be stored on the first computer readable storage medium. The first computer readable storage medium may be packaged with a 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.
For the description of the second, third, fourth and fifth aspects of the present invention, reference may be made to the detailed description of the first aspect; in addition, for the beneficial effects described in the second aspect, the third aspect, the fourth aspect and the fifth aspect, reference may be made to beneficial effect analysis of the first aspect, and details are not repeated here.
In the present invention, the names of the electronic devices mentioned above do not limit the devices or the functional modules themselves, and in actual implementation, the devices or the functional modules may appear by other names. Insofar as the functions of the respective devices or functional blocks are similar to those of the present invention, they are within the scope of the claims of the present invention and their equivalents.
These and other aspects of the invention will be more readily apparent from the following description.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
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 flowchart illustrating a data transmission method according to an embodiment of the present invention;
FIG. 3 is a second flowchart illustrating a data transmission method according to an embodiment of the present invention;
fig. 4 is a third schematic flow chart of a data transmission method according to an embodiment of the present invention;
FIG. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention;
fig. 6 is a second schematic structural diagram of an electronic device according to an embodiment of the 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 will be described below with reference to the accompanying drawings.
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
For the convenience of clearly describing the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, the words "first", "second", and the like are used to distinguish the same items or similar items with basically the same functions and actions, and those skilled in the art can understand that the words "first", "second", and the like do not limit the quantity and execution order.
Fig. 1 is a schematic diagram of a communication system to which an embodiment of the present invention may be applied, as shown in fig. 1, where 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, sensing information including a network parameter reported by each terminal 3 in at least one terminal within a coverage area and at least one configuration information corresponding to the wireless node 2. The server 1 receives the sensing information reported by each wireless node 2 in at least one wireless node 2 which is currently served in a period. The server 1 determines at least one parameter configuration combination based on at least one configuration information of each of the at least one wireless node 2. 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 the 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 of the operation of the configuration parameters of each wireless node 2 in the next period according to 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 currently running configuration parameters according to the configuration parameters of the next period sent by the server 1. Meanwhile, the wireless node 2 further needs to notify each terminal 3 in the coverage area to communicate with the wireless node 2 in the next period according to the reconfigured configuration parameters. After receiving the reconfigured configuration parameters sent by the wireless node 2, the terminal 3 needs to configure the parameters for communicating with the wireless node 2 in the next period as the reconfigured configuration parameters sent by the wireless node 2, so as to ensure that the terminal 3 can communicate with the wireless node 2 normally. After receiving the configuration completion information sent by each terminal within the coverage, 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 within the coverage of the wireless node 2 have completed 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 in 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 time, and can acquire the current position information of the terminal 3, and compress and transmit the information as required.
In some examples, the server 1 may also be referred to as a 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 server 1. For example a system of chips in the server 1. The system-on-chip is arranged to support the server 1 to implement the functionality referred to in the first aspect and any one of its possible implementations. For example, at least one wireless node 2 receiving the current periodic service is configured to periodically use the identification code corresponding to the wireless node 2 and the sensing information reported by each terminal 3 of at least one terminal 3 within the coverage area. The chip system includes a chip and may also include other discrete devices or circuit structures.
Terminals are used to provide voice and/or data connectivity services to users. The terminal may be referred to by different names, such as User Equipment (UE), access terminal, terminal unit, terminal station, mobile station, remote terminal, mobile device, wireless communication device, vehicular user equipment, terminal agent or terminal device, and the like. Optionally, the terminal may be various handheld devices, vehicle-mounted devices, wearable devices, and computers with communication functions, which is not limited in this embodiment of the present invention. For example, the handheld device may be a smartphone. 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, and a 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 appearing in the present specification. It is to be understood that several terms specifically used herein may be helpful. When it comes to
Neural Networks (NN) are complex network systems formed by a large number of simple processing units (called neurons) widely interconnected, reflect many basic features of human brain functions, and are highly complex nonlinear dynamical learning systems.
MATLAB is a commercial mathematical software produced by MathWorks company in America, and is used in the fields of data analysis, wireless communication, deep learning, image processing and computer vision, signal processing, quantitative finance and risk management, robots, control systems and the like.
The following describes a data transmission method provided by an embodiment of the present invention, with reference to the communication system shown in fig. 1 and taking an electronic device as a server 1 as an example.
As shown in fig. 2, the data transmission method includes the following steps S11-S15:
s11, the server 1 receives the sensing information reported by each wireless node in at least one wireless node currently served in a period. The sensing information at least comprises at least one piece of configuration information and network parameters reported by each terminal in at least one terminal in a coverage area.
In a practical manner, the server 1 only obtains the sensing information reported by each wireless node currently served, and different servers 1 may also perform communication. When reporting the network parameters, the terminal only reports the network parameters to the wireless node currently serving the terminal.
For example, the terminal may acquire the network parameter periodically, for example, the terminal acquires the network parameter once every 1 Transmission Time Interval (TTI). In order to Report the network parameters to the wireless node, the terminal may encapsulate the network parameters in Channel State Information (CSI) Information and Report the network parameters to the wireless node, or the terminal encapsulates the network parameters in Measurement Report (MR) data and reports the network parameters to the wireless node, or the terminal encapsulates the network parameters in a Physical Uplink Control Channel (PUCCH) and reports the network parameters to the wireless node, or the terminal encapsulates the network parameters in an Uplink Shared Channel (PUSCH) and reports the network parameters to the wireless node, or the terminal expands an original random access or Radio Resource Control (RRC) connection signaling, that is, adds the location Information and the requirement of the terminal.
Specifically, the configuration information at least includes position information, uplink frequency points, uplink bandwidth, and transmission power. The network parameters include location information. For example, the position information may be obtained through a Global Positioning System (GPS) or a BeiDou Navigation Satellite System (BDS).
In some examples, the network parameters reported by the terminal further include an identification code of a currently serving wireless node and an identification code of a wireless node to which the terminal intends to access. Since the data transmission method provided by the embodiment of the present invention only considers the wireless nodes in the same server, it is only necessary to determine the configuration parameters of the wireless nodes in the same server in the next period.
In one practical way, at least one configuration message corresponding to the wireless node is stored in the network management system. When the wireless node needs to send the sensing information to the server 1, the wireless node can send a configuration query 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 parameter includes location information, the location information is acquired by a 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 extracts and separates information reported by the terminal on the PUCCH, so as to determine the location information reported by each terminal within the coverage range shown in table 1.
TABLE 1
Wherein Laij represents the longitude of the J terminal served by the wireless node with the identification code i, Loij represents the latitude of the J terminal served by the wireless node with the identification code i, i belongs to [1, N ], J belongs to [1, J ], and the i, J, J and N are integers.
For example, it is described that each wireless node has J pieces of configuration information, and at least one piece of 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 the content of the first and second substances,
indicating the uplink frequency point in the jth configuration information supported by the ith wireless node,
indicates the uplink bandwidth, P, in the jth configuration information supported by the ith wireless nodeijAnd J and J are integers, and the J and the J represent the transmission power supported by the ith wireless node in the jth configuration information.
Therefore, when the wireless node needs to determine at least one piece of configuration information, a configuration query request carrying the 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 piece of configuration information corresponding to the identification code in the configuration query request in table 1, so as to determine at least one piece of configuration information corresponding to the wireless node.
The above example is described by taking an example in which a wireless node sends a configuration query request carrying an identification code corresponding to the wireless node to a network management system, and 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. In some other examples, the local storage of the wireless node stores at least one piece of configuration information supported by the wireless node, so that when the wireless node needs to determine the at least one piece of configuration information supported by the wireless node, the wireless node can directly query the at least one piece of configuration information supported by the wireless node, thereby reducing the processing delay.
It should be noted that, after obtaining the at least one piece of configuration information corresponding to the wireless node and the network parameters reported by each terminal in the at least one terminal in the coverage, the wireless node needs to encapsulate the at least one piece of configuration information and the network parameters reported by each terminal in the at least one terminal in the coverage, and send the encapsulated configuration information and 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 of the at least one wireless node. The parameter configuration combination comprises configuration parameters of each wireless node in the next period.
In some examples, the total number of configuration information included by each wireless node is the same. In this way, the server 1 may recombine the configuration information, so that at least one parameter configuration combination may be obtained.
Illustratively, taking the wireless node currently served by the server 1 as the wireless node with the identification code 1 and the wireless node with the identification code 2 as an example, the process of the server 1 determining at least one parameter configuration combination is as follows:
in connection with the example given at S11 above, the server 1 combines the configuration information 1 of the wireless node whose identification code is 1 with the configuration information 1 of the wireless node whose identification code is 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 the parameter configuration combination 2. The forming process of the parameter configuration combination 3 to the parameter configuration combination j is similar to the forming process of the parameter configuration combination 1 and the parameter configuration combination 2, and is not described again here.
After that, the server 1 summarizes each obtained parameter configuration combination, thereby obtaining a summary result as shown in table 3.
TABLE 3
The above example is described by taking as an example that the total number of the at least one piece of configuration information included in each wireless node currently served by the server 1 is the same. In other examples, the total number of the at least one configuration information contained by each wireless node currently served by the server 1 is not necessarily the same. For example, it is assumed that the wireless node with the identification code 1 contains 3 configuration information in total, and the wireless node with the identification code 2 contains 2 configuration information in total.
After that, the server 1 combines the configuration information 1 of the wireless node whose identification code is 1 with the configuration information 1 of the wireless node whose identification code is 2, thereby forming a parameter configuration combination 1. The server 1 combines the configuration information 2 of the wireless node having the identification code 1 with the configuration information 2 of the wireless node having 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 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.
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. And the target uplink throughput is any one of the total uplink throughputs corresponding to each parameter configuration combination.
S15, the server 1 notifies each wireless node of the next period of operation of the configuration parameters of each wireless node in the parameter configuration combination corresponding to the target uplink throughput.
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 currently periodically served, so that the actual demand of each wireless node currently served can be known at any time. The server 1 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 the at least one terminal in the coverage range reported by each wireless node. Then, 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. Finally, the server 1 informs each wireless node of the next period of operation of the configuration parameters of each wireless node in the parameter configuration combination corresponding to the target uplink throughput in the next period, so that each wireless node can select appropriate configuration parameters according to actual requirements, and the problem of how to select appropriate configuration parameters according to actual requirements by the wireless nodes in the related art is solved.
In some implementations, in conjunction with fig. 2, as shown in fig. 3, S13 described above may be specifically implemented by S130 described below.
S130, 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 range 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 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 into a pre-trained neural network model, it needs to determine the area average distance 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 regions is as follows:
1. the server 1 calculates a first distance of each terminal from each wireless node currently being served. Such as: the server 1 determines a first distance between each terminal and each wireless node currently being served, based on the location information of each terminal and the location information of each wireless node currently being served.
2. The server 1 determines the area average distance based on the total number of currently served terminals, the total number of currently served wireless nodes, and the first distance between each terminal and each currently served wireless node.
Wherein LenmDenotes a first distance of an M-th terminal currently served by the server 1, M denotes a total number of terminals currently served by the server 1, W denotes a total number of wireless nodes currently served by the server 1, LENAverageRepresents the average distance of the regions, M ∈ [1, M ∈ >]And 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 in 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 respectively 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 includes 3 terminals, the coverage area of the wireless node with the identification code of 2 includes 4 terminals, and then the total number of the terminals currently served by the server 1 is 4+3 ═ 7.
In some examples, the inputting, by the server 1, at least one parameter configuration combination and the area average distance into a pre-trained neural network model, and determining the total uplink throughput corresponding to each parameter configuration combination includes:
the server 1 sequentially inputs each 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.
The above example is described by taking an example in which the server 1 inputs 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 into a pre-trained neural network model, and determines a total uplink throughput corresponding to each parameter configuration combination. In other examples, the server 1 stores a correspondence relationship between at least one parameter configuration combination, the area average distance set, and the total uplink throughput corresponding to the parameter configuration combination. Illustratively, the correspondence is shown in table 4.
TABLE 4
| Set of average distances of regions | Name of combination | 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 total uplink throughput corresponding to each parameter configuration combination needs to be determined, the server 1 may determine a 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 relationship shown in table 4, and then determine the total uplink throughput corresponding to each parameter configuration combination.
In some practical manners, in conjunction with fig. 2, as shown in fig. 4, the data transmission method provided in the embodiment of the present invention further includes: S16-S19.
S16, the server 1 obtains 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.
In some examples, the data transmission method provided by the embodiment of the invention is applied to a 6-Generation (6G) network. At present, the 6G network is not deployed, and therefore in the data transmission method provided in the embodiment of the present invention, training sample data is acquired 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 the drive test, so as to ensure the accuracy of the output result of the neural network model.
Specifically, the training sample data extraction process is as follows:
by randomly scattering points of 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 transmission power supported by each wireless node. Because the terminal usually communicates with the wireless node according to the uplink frequency point, the uplink bandwidth and the transmission power issued by the wireless node, and the interference between the terminals is also limited. Therefore, the uplink frequency point, the uplink bandwidth, and the transmission power of the wireless node need to be set first.
Specifically, the simulation process is as follows:
1) a simulation configuration list as shown in table 5 is generated according to uplink frequencies, uplink bandwidths and transmission powers supported by different wireless nodes.
TABLE 5
2) And (2) carrying out random point scattering 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 of each terminal from each wireless node currently being served is calculated.
4) Determining an area average distance according to the total number of the currently served terminals, the total number of the currently served wireless nodes and the first distance between each terminal and each currently served wireless node.
5) 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 the 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 matches 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 updates the network parameters of the deep learning model in an iterative manner until the model converges to obtain the neural network model.
In some examples, the neural network model has been trained and converged multiple times according to the simulation data through the operations of S16-S19, so that when 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 practical manners, in conjunction with fig. 2, as shown in fig. 3, the above S14 can be specifically realized by the following S140.
S140, the server 1 determines, according to the total uplink throughput corresponding to each parameter configuration combination, the parameter configuration combination corresponding to the maximum total uplink throughput as the parameter configuration combination corresponding to the target uplink throughput.
In some realizable manners, in the data transmission method provided in the embodiments of the present 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, with reference to the above example of S130, taking an example that the area average distance determined by the server 1 in the current period falls into the area average distance set [1, 10], and the wireless nodes currently served by the server 1 are the wireless node with the identification code 1 and the wireless node with the identification code 2, at this time, if the total uplink throughput x1 corresponding to the parameter configuration combination 1 is the maximum total uplink throughput, the server 1 determines that the parameter configuration combination corresponding to the target uplink throughput is the parameter configuration combination 1.
Thereafter, the server 1 configures combination 1 according to the parameters recorded in table 3, and determines configuration parameters of the wireless node having the identification code 1 and the wireless node having the identification code 2 in the next cycle. As can be seen from Table 3, the uplink frequency point of the wireless node with the identification code of 1 in the next cycle is
An uplink bandwidth of
Transmitting power of P11(ii) a The wireless node with the identification code of 2 has the uplink frequency point of the next period
An uplink bandwidth of
Transmitting power of P21。
Then, the server 1 informs the wireless node with the identification code 1 to configure the uplink frequency point in the next period
Upstream bandwidth configuration
Transmit power configuration is P11(ii) a Server 1 informs wireless node with identification code 2 to configure uplink frequency point in next period
Upstream bandwidth configuration
Transmit power configuration is P21。
After configuring the uplink frequency point, the uplink bandwidth and the transmission power of the next cycle, the wireless node with the identifier code of 1 needs to inform each terminal in its coverage area to configure the uplink frequency point of the next cycle
Upstream bandwidth configuration
Transmit power configuration is P11. After configuring the uplink frequency point, the uplink bandwidth and the transmission power of the next cycle, the wireless node with the identifier 2 needs to inform each terminal in its coverage area to configure the uplink frequency point of the next cycle
Upstream bandwidth configuration
Transmit power configuration is P21。
After the uplink frequency point, the uplink bandwidth and the transmission power of the next period are configured, the terminal needs to report configuration completion information to the wireless node which currently provides service.
And after receiving 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 in the coverage area of the wireless node with the identification code of 1. And 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 in the coverage area of the wireless node with the identification code of 2.
The scheme provided by the embodiment of the invention is mainly introduced from the perspective of a method. To implement the above functions, it includes hardware structures and/or software modules for performing the respective functions. Those of skill in the art will readily appreciate that the present invention can be implemented in hardware or a combination of hardware and computer software, with the exemplary elements and algorithm steps described in connection with the embodiments disclosed herein. Whether a function is performed as hardware or computer software drives 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.
In the embodiment of the present invention, the data transmission device may be divided into the functional modules according to the method example, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. It should be noted that, the division of the modules in the embodiment of the present invention is schematic, and is only a logic function division, and there may be another division manner 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 of at least one wireless node currently periodically served; determining at least one parameter configuration combination according to at least one configuration information of each wireless node in 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 the at least one terminal in the coverage range 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 informing 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 in the next period. The electronic device 10 may comprise a transceiving unit 101 and a processing unit 102.
The transceiver unit 101 is configured to receive sensing information reported by each wireless node in at least one wireless node currently served in a period. For example, in conjunction with fig. 2, the transceiving unit 101 may be configured 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 node 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, according to the total uplink throughput corresponding to each parameter configuration combination, a parameter configuration combination corresponding to the target uplink throughput; the processing unit 102 is further configured to control the transceiver unit 101 to notify each wireless node of a next period of operation according to the configuration parameters of each wireless node in the parameter configuration combination corresponding to the target uplink throughput. For example, in conjunction with FIG. 2, the processing unit 102 may be configured to perform S12, S13, S14, and S15.
All relevant contents of each step related to the above method embodiment may be referred to the functional description of the corresponding functional module, and the function thereof is not described herein again.
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 codes of the writing electronic device 10, and may also be used for storing data generated by the writing electronic device 10 during operation, such as data in a write request.
Fig. 6 is a schematic structural diagram of an electronic device 10 according to an embodiment of the present invention, and 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 each component 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 a single processor or a collective term for a plurality of processing elements. For example, the processor 51 is a Central Processing Unit (CPU), 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 (FPGAs).
In particular implementations, processor 51 may include one or more CPUs such as CPU0 and CPU1 shown in fig. 6 as one example. Also, for 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 a Read-Only Memory (ROM) or other type of static storage device that can store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that can store information and instructions, an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc Read-Only Memory (CD-ROM) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, 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, but is not limited to such. The memory 52 may be self-contained and coupled to the processor 51 via a communication bus 54. The memory 52 may also be integrated with the processor 51.
In a particular implementation, the memory 52 is used for storing data and software programs for implementing the present invention. The processor 51 may perform various functions of the air conditioner by running or executing software programs stored in the memory 52 and calling data stored in the memory 52.
The communication interface 53 is a device such as any transceiver, and is used for communicating with other devices or communication Networks, such as a Radio Access Network (RAN), a Wireless Local Area Network (WLAN), a terminal, and a cloud. The communication interface 53 may include a transceiving unit implementing a receiving function and a transmitting function.
The communication bus 54 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 6, but this is not intended to represent only one bus or type of bus.
As an example, in conjunction with fig. 5, the transceiver unit 101 in the electronic device 10 implements the same function as the communication interface 53 in fig. 6, the processing unit 102 implements the same function as the processor 51 in fig. 6, and the storage unit 103 implements the same function as the memory 52 in fig. 6.
Another embodiment of the present invention further provides a computer-readable storage medium, which stores instructions that, when executed on a computer, cause the computer to perform the method shown in the above 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 comprising a computer program for executing a computer process on a computing device provided by an embodiment of the invention.
In one embodiment, the computer program product is provided using a 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 functions or portions of the functions 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 undertaken by one or more instructions associated with the signal bearing medium 410. Further, the program instructions in FIG. 7 also describe example instructions.
In some examples, signal bearing medium 410 may include a computer readable medium 411, such as, but not limited to, a hard disk drive, a Compact Disc (CD), a Digital Video Disc (DVD), a digital tape, a memory, a read-only memory (ROM), a Random Access Memory (RAM), or the like.
In some implementations, the signal bearing medium 410 may comprise a computer recordable medium 412 such as, but not limited to, a memory, a read/write (R/W) CD, a 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., a fiber optic cable, a waveguide, a wired communications link, a wireless communication link, etc.).
The signal bearing medium 410 may be conveyed by a wireless form of communication medium 413, such as a wireless communication medium compliant with the IEEE802.41 standard or other transport protocol. The one or more program instructions may be, for example, computer-executable instructions or logic-implementing instructions.
In some examples, a data writing apparatus, such as that described with respect to fig. 2, may be configured to provide various operations, functions, or actions in response to one or more program instructions via the computer-readable medium 411, the computer-recordable medium 412, and/or the communication medium 413.
Through the above description of the embodiments, it is clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete all or part of the above described functions.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical functional division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another device, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may be one physical unit or a plurality of physical units, that is, may be located in one place, or may be distributed in a plurality of different places. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, 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 partially contributed to by the prior art, or all or part of the technical solution may be embodied in the form of a software product, where the software product is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions within the technical scope of the present invention are intended to 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 appended claims.
Claims (10)
1. A method of data transmission, comprising:
receiving perception information reported by each wireless node in at least one wireless node which is served at the current period; the perception information at least comprises at least one piece of 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 of 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 a target uplink throughput according to the total uplink throughput corresponding to each parameter configuration combination; wherein the target uplink throughput is any one of total uplink throughputs corresponding to the parameter configuration combinations;
and informing 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.
2. The data transmission method according to claim 1, wherein the determining, 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, the 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 the at least one terminal in the coverage range reported by each wireless node into a pre-trained neural network model, and determining the total uplink throughput corresponding to each parameter configuration combination.
3. The data transmission method according to claim 2, wherein before receiving the awareness information reported by each of the at least one wireless node currently periodically serving, 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 deep learning model for the training sample data is matched with the actual total uplink throughput based on a target loss function;
and when the predicted total uplink throughput is not matched with the actual total uplink throughput, iteratively updating the network parameters of the deep learning model repeatedly and circularly until the model converges to obtain the neural network model.
4. The data transmission method according to any one of claims 1 to 3, wherein the determining the parameter configuration combination corresponding to the target uplink throughput according to the total uplink throughput corresponding to each of the parameter configuration combinations comprises:
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.
5. A data transmission apparatus, comprising:
the receiving and sending unit is used for receiving the sensing information reported by each wireless node in at least one wireless node which is served in the current period; the perception information at least comprises at least one piece of 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 transceiving 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 parameter, received by the transceiver unit, 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;
the processing unit is further configured to determine a parameter configuration combination corresponding to a target uplink throughput according to a total uplink throughput corresponding to each parameter configuration combination; wherein the target uplink throughput is any one of total uplink throughputs corresponding to the parameter configuration combinations;
the processing unit is further configured to control the transceiver unit to notify each wireless node of a next period to operate according to the configuration parameters of each wireless node in the parameter configuration combination corresponding to the target uplink throughput.
6. The data transmission apparatus according to claim 5, wherein the processing unit is specifically configured to input the at least one parameter configuration combination and the network parameter, which is received by the transceiver unit and reported by each terminal in the coverage area reported by each wireless node, into a pre-trained neural network model, and determine a total uplink throughput corresponding to each parameter configuration combination.
7. The data transmission apparatus according to claim 5, 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 configured to input the training sample data acquired by the transceiver unit into a deep learning model;
the processing unit is further configured to determine whether a predicted total uplink throughput of the deep learning model for the training sample data is matched with the actual total uplink throughput based on a target loss function;
and the processing unit is further configured to iteratively update the network parameters of the deep learning model repeatedly and circularly 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.
8. The data transmission apparatus according to any one of claims 5 to 7, wherein the processing unit is specifically configured to determine, according to the total uplink throughput corresponding to each of the parameter configuration combinations, that the parameter configuration combination corresponding to the maximum total uplink throughput is the parameter configuration combination corresponding to the target uplink throughput.
9. A computer-readable storage medium comprising instructions which, when executed on a computer, cause the computer to perform the data transmission method of any one of claims 1 to 4.
10. 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 executes computer-executable instructions stored by the memory when the electronic device is operating to cause the electronic device to perform the data transfer method of any of claims 1-4 above.
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Citations (14)
| 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 |
| US20140219122A1 (en) * | 2013-02-06 | 2014-08-07 | Kabushiki Kaisha Toshiba | Control apparatus, representative base station and base station control method |
| 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 |
| 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 |
| 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 |
| 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 |
-
2021
- 2021-11-04 CN CN202111302321.3A patent/CN114071580A/en active Pending
Patent Citations (14)
| 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 |
| EP2947943A1 (en) * | 2013-01-18 | 2015-11-25 | Huawei Technologies Co., Ltd. | Scheduling method and scheduling apparatus for user equipment in communications system |
| US20140219122A1 (en) * | 2013-02-06 | 2014-08-07 | Kabushiki Kaisha Toshiba | Control apparatus, representative base station and base station control method |
| CN105392158A (en) * | 2014-08-29 | 2016-03-09 | 英特尔Ip公司 | communication terminal and method for controlling a data transmission |
| 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 |
| 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 |
| 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 |
|---|
| CMCC: "RP-191223 "Status report for SI on RAN-centric data collection and utilization for LTE and NR"", 3GPP TSG_RAN\\TSG_RAN, no. 84, 27 May 2019 (2019-05-27) * |
| MANSOOR SHAFI等: ""5G: A Tutorial Overview of Standards, Trials, Challenges, Deployment, and Practice"", 《IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS ( VOLUME: 35, ISSUE: 6, JUNE 2017)》, 7 April 2017 (2017-04-07) * |
| 熊杰: ""基于5G关键技术的行业应用研究"", 《长江信息通信》, 15 October 2021 (2021-10-15) * |
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