CN110225530B - Wireless data analysis method and device and CUDA entity - Google Patents
Wireless data analysis method and device and CUDA entity Download PDFInfo
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Abstract
The invention provides a wireless data analysis method and device and a CUDA entity, and belongs to the technical field of wireless communication. The method for analyzing the CUDA entity by the first centralized unit data comprises the following steps: receiving a computing task sent by a second CUDA entity; sending the computing data and the reporting configuration which need to be reported by the second CUDA entity to the second CUDA entity according to the received computing task; receiving the calculation data reported by the second CUDA entity according to the reporting configuration; and calculating the second CUDA entity according to the calculation data reported by the second CUDA entity, and sending the calculation result to the second CUDA entity. The technical scheme of the invention can effectively solve the problems of calculation and data interaction in the wireless access network enabled by the wireless big data and better enable the real-time wireless resource optimization assisted by the big data.
Description
Technical Field
The present invention relates to the field of wireless communication technologies, and in particular, to a method and an apparatus for analyzing wireless data, and a CUDA entity.
Background
With the advent of the 5G era, the rapid development of various communication and processing technologies such as mobile internet, internet of things, cloud computing and the like has led to the explosive growth of data traffic, and wireless communication networks have entered the big data era. At present, wireless big data is mainly applied to network planning optimization, mobile edge storage, content distribution and the like. The network planning is based on offline big data analysis, network blind spots and hot spots are found, and network deployment is guided. At present, the main work of the network optimization is to focus on optimizing network parameters such as power, interoperation, timers, mobility parameter optimization and the like from a management plane for road test data or MR data, signaling acquisition, network management indexes, engineering parameter (station address longitude and latitude, station height, RF parameter) data and the like at a terminal side and a base station side.
The scheme in the prior art mainly considers the planning of wireless big data to a network and the semi-static parameter optimization at a site level, and cannot better support the real-time wireless resource management and the physical layer transmission optimization. In order to better support data-driven real-time radio resource management and physical layer transmission optimization, a big data analysis function needs to be introduced into a radio access network. Wireless big data processing function usually has strong requirement on the computing power of the network, and devices in the wireless access network may have different computing processing capabilities, for example, a Centralized Unit (CU) is usually implemented by using clouding in 5G, which has strong processing capability, a Distributed Unit (DU) usually has weak data processing capability, and an integrated micro station also usually has weak processing capability. How to better utilize the capability of equipment in a wireless access network and better realize the real-time optimization of wireless big data to the wireless access network is an important problem to be solved.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a wireless data analysis method, a wireless data analysis device and a CUDA entity, which can effectively solve the calculation and data interaction in a wireless access network enabled by wireless big data and better enable real-time wireless resource optimization assisted by big data.
To solve the above technical problem, embodiments of the present invention provide the following technical solutions:
in one aspect, a wireless data analysis method applied to a first centralized unit data analysis CUDA entity is provided, and the method includes:
receiving a computing task sent by a second CUDA entity;
sending the computing data and the reporting configuration which need to be reported by the second CUDA entity to the second CUDA entity according to the received computing task;
receiving the calculation data reported by the second CUDA entity according to the reporting configuration;
and calculating the second CUDA entity according to the calculation data reported by the second CUDA entity, and sending the calculation result to the second CUDA entity.
Further, before the step of receiving the computing task sent by the second CUDA entity, the method further includes:
broadcasting self main mode identity and entity information in the network;
receiving a registration request which is sent by the second CUDA entity and requests to register a slave mode identity, wherein the registration request comprises identity information and capability information of the second CUDA entity;
and sending confirmation registration information to the second CUDA entity.
Further, the method further comprises:
and receiving a data interaction request sent by the second CUDA entity, wherein the data interaction request indicates that the first CUDA entity replaces the second CUDA entity to perform data interaction with a network element of a core network.
Further, the method further comprises:
sending a registration request for requesting registration of slave mode identity to the second CUDA entity, wherein the registration request comprises identity information and capability information of the first CUDA entity;
and receiving the registration confirmation information sent by the second CUDA entity.
Further, after the step of receiving the registration confirmation information sent by the second CUDA entity, the method further includes:
sending a computing task to the second CUDA entity;
receiving the computing data and the reporting configuration which are sent by the second CUDA entity and need to be reported by the first CUDA entity;
reporting the calculation data to the second CUDA entity according to the reporting configuration;
and receiving a calculation result sent by the second CUDA entity.
Further, the method further comprises:
and sending a data interaction request to the second CUDA entity, wherein the data interaction request indicates that the second CUDA entity replaces the first CUDA entity to perform data interaction with a network element of a core network.
The embodiment of the invention also provides a wireless data analysis device, which is applied to the CUDA entity of the data analysis of the first centralized unit, and the device comprises a transceiver and a processor:
the transceiver is used for receiving a computing task sent by a second CUDA entity, sending computing data and reporting configuration which need to be reported by the second CUDA entity to the second CUDA entity according to the received computing task, and receiving the computing data reported by the second CUDA entity according to the reporting configuration;
the processor is used for calculating the second CUDA entity according to the calculation data reported by the second CUDA entity;
the transceiver is further configured to send the calculation result to the second CUDA entity.
Further, the transceiver is further configured to broadcast a master mode identity and entity information of the transceiver in a network, receive a registration request, which is sent by the second CUDA entity and requests to register the slave mode identity, where the registration request includes the identity information and capability information of the second CUDA entity, and send registration confirmation information to the second CUDA entity.
Further, the transceiver is further configured to receive a data interaction request sent by the second CUDA entity, where the data interaction request indicates that the first CUDA entity replaces the second CUDA entity to perform data interaction with a core network element.
Further, the transceiver is further configured to send a registration request requesting registration of a slave mode identity to the second CUDA entity, where the registration request includes identity information and capability information of the first CUDA entity, and receive registration confirmation information sent by the second CUDA entity.
Further, the transceiver is further configured to send a computation task to the second CUDA entity, receive computation data and reporting configuration sent by the second CUDA entity and requiring reporting by the first CUDA entity, report the computation data to the second CUDA entity according to the reporting configuration, and receive a computation result sent by the second CUDA entity.
Further, the transceiver is further configured to send a data interaction request to the second CUDA entity, where the data interaction request indicates that the second CUDA entity replaces the first CUDA entity to perform data interaction with a core network element.
The embodiment of the invention also provides a CUDA entity for centralized unit data analysis, which comprises a memory, a processor and a computer program, wherein the computer program is stored in the memory and can run on the processor; the processor, when executing the program, implements the wireless data analysis method as described above.
Embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps in the wireless data analysis method as described above.
The embodiment of the invention has the following beneficial effects:
in the scheme, the wireless data analysis system is composed of a plurality of CUDA entities, each CUDA entity has two working states, namely a master mode state and a slave mode state, the CUDA entities in the slave mode state can send the calculation tasks to the CUDA entities in the master mode state, and the CUDA entities in the master mode state help the CUDA entities in the slave mode state to perform calculation.
Drawings
FIG. 1 is a flow chart illustrating a wireless data analysis method according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a wireless data analysis method according to an embodiment of the present invention;
fig. 3 is a block diagram of a wireless data analysis device according to an embodiment of the invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages to be solved by the embodiments of the present invention clearer, the following detailed description will be given with reference to the accompanying drawings and specific embodiments.
Embodiments of the present invention provide a wireless data analysis method and apparatus, and a CUDA entity, which can effectively solve the problem of computation and data interaction in a wireless access network enabled by big wireless data, and better enable real-time wireless resource optimization assisted by big data.
The embodiment of the invention provides a wireless data analysis method, which is applied to a first CUDA (Central Unit data analysis) entity, and comprises the following steps:
step 101: receiving a computing task sent by a second CUDA entity;
step 102: sending the computing data and the reporting configuration which need to be reported by the second CUDA entity to the second CUDA entity according to the received computing task;
the reporting configuration includes, but is not limited to, a reporting period, a data volume, and the like. The first CUDA entity indicates that the calculation data reported by the second CUDA entity can be divided into two parts of optional reported data and optional enhanced reported data.
Step 103: receiving the calculation data reported by the second CUDA entity according to the reporting configuration;
step 104: and calculating the second CUDA entity according to the calculation data reported by the second CUDA entity, and sending the calculation result to the second CUDA entity.
The calculation result may be a decision parameter or a calculation model.
In this embodiment, the wireless data analysis system is composed of a plurality of CUDA entities, each CUDA entity has two working states, namely a master mode state and a slave mode state, the CUDA entity in the slave mode state can send a calculation task to the CUDA entity in the master mode state, and the CUDA entity in the master mode state helps the CUDA entity in the slave mode state to perform calculation.
In this embodiment, each centralized unit data analysis entity has two working states, a master mode and a slave mode. When the centralized unit data analysis entity A commissions the centralized unit data analysis entity B to help calculation, then A works in the slave mode state, and B works in the master mode state. Each centralized unit data analysis entity may also collect data for the distributed units connected to it and assist the distributed units in performing the corresponding calculations.
Further, before the step of receiving the computing task sent by the second CUDA entity, the method further includes:
broadcasting self main mode identity and entity information in the network;
receiving a registration request which is sent by the second CUDA entity and requests to register a slave mode identity, wherein the registration request comprises identity information and capability information of the second CUDA entity;
and sending confirmation registration information to the second CUDA entity.
If the centralized unit data analysis entity is willing to provide data computing capability, then it can broadcast its own master mode identity and entity information in the network, wherein the entity information is an entity capability specification, including at least one of the following information: an entity identity and address; an entity type; a list of supported computing tasks; the scope of the service provided. When other centralized data analysis entities have the demand of entrusting calculation, selecting the centralized unit data analysis entity in the corresponding main mode state according to the identity and the capability of the centralized unit data analysis entity in the main mode state, and requesting registration. When registering, providing identity information and capability information, and after registering, submitting task information (such as model calculation) needing to be entrusted to the centralized unit data analysis entity in the master mode state. The capability information includes at least one of the following information: an entity identity and address; an entity type; the area of the site.
Further, the method further comprises:
and receiving a data interaction request sent by the second CUDA entity, wherein the data interaction request indicates that the first CUDA entity replaces the second CUDA entity to perform data interaction with a network element of a core network.
When the CUDA in the slave mode state submits all the model training and decision-making computation tasks to the CUDA in the master mode state, the CUDA in the slave mode state can also apply for data interaction with an NWDA (network data analysis) entity of a core network, which is hosted by the CUDA in the master mode state.
When the CUDA in the master mode state is connected with CUDAs in the plurality of slave mode states, and when the CUDA in the master mode state performs task calculation, calculation can be performed according to the target and the type of a calculation task, not only based on data provided by the CUDA in the slave mode state of the delegation task, but also based on data of other CUDAs or NWDAs, according to a self algorithm, for example, network cooperation among the CUDAs in the plurality of slave mode states is considered in model training.
Further, the method further comprises:
sending a registration request for requesting registration of slave mode identity to the second CUDA entity, wherein the registration request comprises identity information and capability information of the first CUDA entity;
and receiving the registration confirmation information sent by the second CUDA entity.
Further, after the step of receiving the registration confirmation information sent by the second CUDA entity, the method further includes:
sending a computing task to the second CUDA entity;
receiving the computing data and the reporting configuration which are sent by the second CUDA entity and need to be reported by the first CUDA entity;
reporting the calculation data to the second CUDA entity according to the reporting configuration;
and receiving a calculation result sent by the second CUDA entity.
Further, the method further comprises:
and sending a data interaction request to the second CUDA entity, wherein the data interaction request indicates that the second CUDA entity replaces the first CUDA entity to perform data interaction with a network element of a core network.
Further, the entity information includes at least one of the following information:
an entity identity and address;
an entity type;
a list of supported computing tasks;
the scope of the service provided.
Further, the capability information includes at least one of the following information:
an entity identity and address;
an entity type;
the area of the site.
The wireless data analysis of the present invention is further analyzed with reference to the drawings and the specific embodiments, as shown in fig. 2, the wireless data analysis of the present embodiment includes the following steps:
in a mixed networking scene of a CU, a DU and a gNodeB, the CU deploys a CUDA functional entity, the DU has a DUDA (Distributed unit data analysis) function, the gNodeB has a CUDA and a DUDA, and the CUDA collects DUDA data and helps the DUDA to calculate.
Due to the fact that the CUDA in the CU has rich computing resources and strong computing capacity, the CUDA in the CU broadcasts the main mode identity and entity information (including entity identification and address, entity type, a computing task list capable of being supported, a service providing range and the like) of the CUDA in the CU in the network.
The CUDA in the gNode needs to provide a computational model training of MCS (Modulation and Coding Scheme, Modulation and Coding strategy) decision for the DUDA, but since the computational resources of the CUDA are limited, the CUDA in the master mode state needs to be searched to help the DUDA to perform computation. The CUDA in the master mode state in the CU is found in the network, and a registration application containing entity information (entity identification and address, entity type and located area) of the CUDA in the master mode state is submitted to the CUDA in the master mode state. And the CUDA in the master mode state in the CU receives the registration application and replies confirmation.
And submitting a calculation task application list to the CUDA in the CU by the CUDA in the gNode, entrusting the CUDA to help train an MCS selection model, and identifying the task type identifier applied by the CUDA in the application.
The CUDA in the master mode state replies to a data set that needs to be provided by the task type, and includes feedback CQI (Channel Quality Indicator) (optional), TM (optional), MCS (optional), ACK/NACK result or PER estimation (optional), wideband SINR (Signal to Interference plus Noise Ratio) estimation (optional), mobile speed estimation (optional), UE type (optional), and reporting configuration configured to be reported periodically.
And the gNode reports the data which can be provided by the gNode to the CUDA in the master mode state periodically according to the requirement of the data set.
And the CUDA in the master mode state continuously inputs the data of the CUDA in the slave mode state for model training and updating according to the calculation model, and the model update after Ready is periodically pushed to the CUDA in the slave mode state.
After receiving the model from the CUDA in the mode state, the model is updated and provided to the DUDA for calculation of the MCS decision.
An embodiment of the present invention further provides a wireless data analysis apparatus, which is applied to a first centralized unit data analysis CUDA entity, and as shown in fig. 3, the apparatus includes a transceiver 32 and a processor 31:
the transceiver 32 is configured to receive a computation task sent by a second CUDA entity, send computation data and reporting configuration that need to be reported by the second CUDA entity to the second CUDA entity according to the received computation task, and receive the computation data reported by the second CUDA entity according to the reporting configuration;
the processor 32 is configured to perform calculation for the second CUDA entity according to the calculation data reported by the second CUDA entity;
the transceiver 32 is further configured to send the calculation result to the second CUDA entity.
In this embodiment, the wireless data analysis system is composed of a plurality of CUDA entities, each CUDA entity has two working states, namely a master mode state and a slave mode state, the CUDA entity in the slave mode state can send a calculation task to the CUDA entity in the master mode state, and the CUDA entity in the master mode state helps the CUDA entity in the slave mode state to perform calculation.
Further, the transceiver 32 is further configured to broadcast a master mode identity and entity information of itself in the network, receive a registration request, which is sent by the second CUDA entity and requests to register the slave mode identity, where the registration request includes the identity information and capability information of the second CUDA entity, and send registration confirmation information to the second CUDA entity.
Further, the transceiver 32 is further configured to receive a data interaction request sent by the second CUDA entity, where the data interaction request indicates that the first CUDA entity replaces the second CUDA entity to perform data interaction with a core network element.
Further, the transceiver 32 is further configured to send a registration request requesting to register a slave mode identity to the second CUDA entity, where the registration request includes identity information and capability information of the first CUDA entity, and receive registration confirmation information sent by the second CUDA entity.
Further, the transceiver 32 is further configured to send a computation task to the second CUDA entity, receive computation data and reporting configuration sent by the second CUDA entity and needing to be reported by the first CUDA entity, report the computation data to the second CUDA entity according to the reporting configuration, and receive a computation result sent by the second CUDA entity.
Further, the transceiver 32 is further configured to send a data interaction request to the second CUDA entity, where the data interaction request indicates that the second CUDA entity performs data interaction with a core network element instead of the first CUDA entity.
Further, the entity information includes at least one of the following information:
an entity identity and address;
an entity type;
a list of supported computing tasks;
the scope of the service provided.
Further, the capability information includes at least one of the following information:
an entity identity and address;
an entity type;
the area of the site.
The embodiment of the invention also provides a CUDA entity for centralized unit data analysis, which comprises a memory, a processor and a computer program, wherein the computer program is stored in the memory and can run on the processor; the processor, when executing the program, implements the wireless data analysis method as described above.
Embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps in the wireless data analysis method as described above.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (14)
1. A wireless data analysis method applied to a first centralized unit data analysis CUDA entity, the method comprising:
receiving a computing task sent by a second CUDA entity;
sending the computing data and the reporting configuration which need to be reported by the second CUDA entity to the second CUDA entity according to the received computing task;
receiving the calculation data reported by the second CUDA entity according to the reporting configuration;
and calculating the second CUDA entity according to the calculation data reported by the second CUDA entity, and sending the calculation result to the second CUDA entity.
2. The method of claim 1, wherein the step of receiving the computing task sent by the second CUDA entity is preceded by the method further comprising:
broadcasting self main mode identity and entity information in the network;
receiving a registration request which is sent by the second CUDA entity and requests to register a slave mode identity, wherein the registration request comprises identity information and capability information of the second CUDA entity;
and sending confirmation registration information to the second CUDA entity.
3. The wireless data analysis method of claim 1, wherein the method further comprises:
and receiving a data interaction request sent by the second CUDA entity, wherein the data interaction request indicates that the first CUDA entity replaces the second CUDA entity to perform data interaction with a network element of a core network.
4. The wireless data analysis method of claim 1, wherein the method further comprises:
sending a registration request for requesting registration of slave mode identity to the second CUDA entity, wherein the registration request comprises identity information and capability information of the first CUDA entity;
and receiving the registration confirmation information sent by the second CUDA entity.
5. The method of claim 4, wherein after the step of receiving the confirmed registration information sent by the second CUDA entity, the method further comprises:
sending a computing task to the second CUDA entity;
receiving the computing data and the reporting configuration which are sent by the second CUDA entity and need to be reported by the first CUDA entity;
reporting the calculation data to the second CUDA entity according to the reporting configuration;
and receiving a calculation result sent by the second CUDA entity.
6. The wireless data analysis method of claim 4, wherein the method further comprises:
and sending a data interaction request to the second CUDA entity, wherein the data interaction request indicates that the second CUDA entity replaces the first CUDA entity to perform data interaction with a network element of a core network.
7. A wireless data analysis apparatus, for use in a first centralized unit data analysis, CUDA, entity, the apparatus comprising a transceiver and a processor:
the transceiver is used for receiving a computing task sent by a second CUDA entity, sending computing data and reporting configuration which need to be reported by the second CUDA entity to the second CUDA entity according to the received computing task, and receiving the computing data reported by the second CUDA entity according to the reporting configuration;
the processor is used for calculating the second CUDA entity according to the calculation data reported by the second CUDA entity;
the transceiver is further configured to send the calculation result to the second CUDA entity.
8. The wireless data analysis device of claim 7,
the transceiver is further configured to broadcast a master mode identity and entity information of the transceiver in a network, receive a registration request, which is sent by the second CUDA entity and requests to register the slave mode identity, where the registration request includes the identity information and capability information of the second CUDA entity, and send registration confirmation information to the second CUDA entity.
9. The wireless data analysis device of claim 7,
the transceiver is further configured to receive a data interaction request sent by the second CUDA entity, where the data interaction request indicates that the first CUDA entity replaces the second CUDA entity to perform data interaction with a core network element.
10. The wireless data analysis device of claim 7,
the transceiver is further configured to send a registration request requesting registration of a slave mode identity to the second CUDA entity, where the registration request includes identity information and capability information of the first CUDA entity, and receive registration confirmation information sent by the second CUDA entity.
11. The wireless data analysis device of claim 10,
the transceiver is further configured to send a computation task to the second CUDA entity, receive computation data and reporting configuration sent by the second CUDA entity and requiring reporting by the first CUDA entity, report the computation data to the second CUDA entity according to the reporting configuration, and receive a computation result sent by the second CUDA entity.
12. The wireless data analysis device of claim 10,
the transceiver is further configured to send a data interaction request to the second CUDA entity, where the data interaction request indicates that the second CUDA entity replaces the first CUDA entity to perform data interaction with a core network element.
13. A centralized unit data analysis, CUDA, entity comprising a memory, a processor, and a computer program stored on the memory and executable on the processor; characterized in that the processor, when executing the program, implements the wireless data analysis method according to any one of claims 1 to 6.
14. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the wireless data analysis method according to any one of claims 1 to 6.
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