WO2023179801A1 - 数据处理方法、装置、通信系统、电子设备及存储介质 - Google Patents

数据处理方法、装置、通信系统、电子设备及存储介质 Download PDF

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Publication number
WO2023179801A1
WO2023179801A1 PCT/CN2023/088871 CN2023088871W WO2023179801A1 WO 2023179801 A1 WO2023179801 A1 WO 2023179801A1 CN 2023088871 W CN2023088871 W CN 2023088871W WO 2023179801 A1 WO2023179801 A1 WO 2023179801A1
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Prior art keywords
data processing
unit layer
user terminal
processed
artificial intelligence
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PCT/CN2023/088871
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English (en)
French (fr)
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韩书君
曹晖
许晓东
董辰
王碧舳
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北京邮电大学
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Publication of WO2023179801A1 publication Critical patent/WO2023179801A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/24—Traffic characterised by specific attributes, e.g. priority or QoS
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/50—Service provisioning or reconfiguring
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W88/00—Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
    • H04W88/18—Service support devices; Network management devices

Definitions

  • the present disclosure relates to the field of communication technology, and in particular, to data processing methods, devices, communication systems, electronic equipment and storage media.
  • the 5G network is the latest generation of mobile communication network.
  • the 5G network mainly consists of three parts, namely the access network, the bearer network and the core network.
  • the access network is no longer composed of the BBU (Building Base Band Unit, indoor baseband processing unit), RRU (Remote Radio Unit, radio frequency remote unit), and antennas of the traditional communication network architecture, but has been reconstructed It includes three parts: CU (Centralized Unit), DU (Distributed Unit), and AAU (Active Antenna Unit).
  • CU responsible for processing non-real-time protocols and services
  • DU responsible for processing physical layer protocols and real-time services
  • some of the physical layer processing functions of the BBU Combined with the original RRU and passive antenna to form an AAU.
  • CU and DU are distinguished by the real-time nature of processing content.
  • Artificial Intelligence is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. As a branch of computer science, it attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a similar way to human intelligence. Research in this field includes robotics, language recognition, image recognition, natural language processing and expert systems, etc. At present, with the development of science and technology, artificial intelligence models can realize more and more functions, bringing great convenience to human life. For example, WeChat voice can be converted into text through artificial intelligence models to obtain more intuitive Get information. The implementation of this technology is based on the user terminal transmitting the voice to the core network through the access network, and finally accessing the Internet. It is converted into text through the artificial intelligence model of the server on the other end of the Internet and then transmitted back. This method of processing data by transmitting it to the Internet not only has a high transmission delay, but also cannot be used when the Internet is interrupted.
  • the present disclosure provides a method, device, equipment, communication system and storage medium for processing service data of a user terminal.
  • a data processing method including:
  • Obtain the task to be processed determine whether the business type of the task to be processed is an artificial intelligence service, and in response to the task to be processed not being the artificial intelligence service, process the task to be processed according to a regular business type ;
  • the centralized unit layer obtains the data processing request sent by the user terminal;
  • the centralized unit layer determines whether it can process the to-be-processed task according to the data processing request, and in response to the centralized unit layer being unable to process the to-be-processed task, processes the to-be-processed task according to a regular business type;
  • the centralized unit layer In response to the centralized unit layer being able to process the pending task, the centralized unit layer generates a response signal and returns it to the user terminal;
  • the centralized unit layer obtains the business data related to the tasks to be processed sent by the user terminal, and uses the artificial intelligence model to execute the tasks to be processed and process the business data;
  • the centralized unit layer returns the processed service data to the user terminal.
  • the centralized unit layer obtains the data processing request sent by the user terminal including: the user terminal sends a first data processing request to the distribution unit layer through the active antenna unit, and the distribution unit layer performs the processing according to the first data
  • the processing request generates a second data processing request and sends it to the centralized unit layer as the data processing request.
  • the centralized unit layer generating a response signal and returning it to the user terminal includes: the centralized unit layer generates a first response signal and sends it to the distribution unit layer, and the distribution unit layer generates a third response signal based on the first response signal.
  • the second response signal is sent to the user terminal through the active antenna unit.
  • the first data processing request includes an artificial intelligence identifier, and/or a business type identifier, and/or indication information;
  • the second data processing request includes the identity information of the user terminal, and/or the artificial intelligence identification, and/or the business type identification, and/or the indication information.
  • the first response signal includes identity information of the user terminal, and/or artificial intelligence identification, and/or business type identification, and/or indication information;
  • the second response signal includes the artificial intelligence identifier, and/or the service type identifier, and/or the indication information.
  • a data processing apparatus including:
  • the first judgment unit is configured to obtain the task to be processed, and judge whether the service type of the task to be processed is an artificial intelligence service, and in response to the task to be processed not being the artificial intelligence service, process the task according to the conventional service type. Process the pending tasks;
  • An acquisition unit configured to acquire the data processing request sent by the user terminal to the centralized unit layer in response to the task to be processed being the artificial intelligence service;
  • the second judgment unit is configured to judge whether the centralized unit layer can process the to-be-processed task according to the data processing request, and in response to the centralized unit layer being unable to process the to-be-processed task, process the task according to a regular business type. Process the pending tasks;
  • a feedback unit configured to generate a response signal back to the user terminal in response to the centralized unit layer being able to process the pending task
  • a data processing unit configured to obtain the business data related to the tasks to be processed sent by the user terminal to the centralized unit layer, and to use the artificial intelligence model to execute the tasks to be processed and process the business data;
  • a data transmission unit is configured to return the service data processed by the data processing unit to the user terminal.
  • the obtaining unit obtaining the data processing request includes: the user terminal sends a first data processing request to the distribution unit layer through an active antenna unit, and the distribution unit layer generates a data processing request based on the first data processing request.
  • a second data processing request is sent to the acquisition unit of the centralized unit layer as the data processing request.
  • the feedback unit generating the response signal and returning it to the user terminal includes: the feedback unit generates a first response signal and sends it to the distribution unit layer, and the distribution unit layer generates a third response signal according to the first response signal.
  • the second response signal is sent to the user terminal through the active antenna unit.
  • the first data processing request includes an artificial intelligence identifier, and/or a business type identifier, and/or indication information;
  • the second data processing request includes the identity information of the user terminal, and/or the artificial intelligence identification, and/or the business type identification, and/or the indication information.
  • the first response signal includes identity information of the user terminal, and/or artificial intelligence identification, and/or business type identification, and/or indication information;
  • the second response signal includes the artificial intelligence identifier, and/or the service type identifier, and/or the indication information.
  • the present disclosure also provides a communication system architecture, including a user terminal, an antenna unit, a distribution unit layer and a concentration unit layer.
  • the concentration unit layer is provided with an artificial intelligence model for performing artificial intelligence tasks.
  • the user terminal passes through the The centralized unit layer processes business data.
  • the present disclosure also provides an electronic device, including:
  • the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the above technical solution.
  • the present disclosure also provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to execute the data processing method according to any one of the above embodiments.
  • the present disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the data processing method according to any one of the above embodiments.
  • the present disclosure is based on the above-mentioned data processing methods, devices, communication system architecture, electronic equipment and storage media, and uses the artificial intelligence model of the centralized unit layer to process the business data of the user terminal.
  • uses the artificial intelligence model to process data at the centralized unit layer It reduces the data transmission steps, reduces the communication delay, and improves the data processing efficiency of the terminal.
  • Figure 1 is a step flow chart of a data processing method in an embodiment of the present disclosure
  • Figure 2 is a schematic diagram of the principle of a data processing method in an embodiment of the present disclosure
  • Figure 3 is a functional block diagram of a data processing device in an embodiment of the present disclosure
  • Figure 4 is a communication system architecture diagram in an embodiment of the present disclosure.
  • This disclosure provides a data processing method, as shown in Figure 1, including:
  • Step S101 Obtain the task to be processed after the business is generated, determine whether the business type of the task to be processed is an artificial intelligence business, and in response to the task to be processed not being an artificial intelligence business, turn to process the task to be processed according to the regular business type;
  • Step S102 in response to the task to be processed being an artificial intelligence service, the centralized unit layer obtains the data processing request sent by the user terminal;
  • Step S103 the centralized unit layer determines whether it can process the pending task according to the data processing request, and responds to the centralized unit layer being unable to process the pending task, and processes the pending task according to the normal business type;
  • Step S104 in response to the centralized unit layer being able to process the pending tasks, the centralized unit layer generates a response signal and returns it to the user terminal;
  • Step S105 The centralized unit layer obtains the business data related to the tasks to be processed sent by the user terminal, and uses the artificial intelligence model to execute the tasks to be processed and process the business data;
  • Step S106 The centralized unit layer returns the processed service data to the user terminal.
  • the present disclosure provides a solution and process for connecting a user terminal to a centralized unit layer for AI (Artificial Intelligence, artificial intelligence) processing.
  • AI Artificial Intelligence, artificial intelligence
  • the centralized unit layer adds an intelligent plane and deploys the artificial intelligence model in the intelligent plane of the CU.
  • the user terminal transmits business data to the intelligent side of the CU layer for AI processing, rather than the Internet side. For example, the following steps may be included: In step S101, the UE determines whether the service to be processed is an AI-type service. If so, it goes to step S102.
  • Step S102 the UE The CU layer user plane sends a data processing request; step S103, the CU layer determines whether it can handle the pending tasks of the user terminal, and if it can handle it, it goes to step S104; step S104, the user of the CU layer sends a response signal to the user terminal to respond Data processing request from the user terminal; step S105, the UE sends the service data to the CU intelligent It can perform AI processing; in step S106, the CU returns the processed service data to the UE.
  • user terminals do not need to transmit business data to the Internet-side server for processing, reducing transmission path nodes, reducing transmission delays, improving data processing efficiency, and providing users with a better experience.
  • the centralized unit layer obtains the data processing request sent by the user terminal including: the user terminal sends the first data processing request to the distribution unit layer through the active antenna unit, and the distribution unit layer responds to the first data
  • the processing request generates a second data processing request and sends it to the centralized unit layer as a data processing request.
  • the centralized unit layer generates a response signal and returns it to the user terminal, including: the centralized unit layer generates a first response signal and sends it to the distribution unit layer, and the distribution unit layer generates a second response signal based on the first response signal and transmits it through the active antenna. unit is sent to the user terminal.
  • step S102 the UE can send an AI DataProcess Request (first data processing request) to the DU through the AAU, and the DU generates the UE AI DataProcess Request ( The second data processing request) is sent to the user plane of the CU layer.
  • step S104 the user at the CU layer sends the UE AI DataProcess Response (first response signal) to the DU, and the DU generates the AI DataProcess Response (the second response signal) and sends it to the UE through the AAU.
  • the artificial intelligence model is deployed on the intelligent plane of the CU layer of the communication access network.
  • the UE communicates with the CU layer through AAU and DU, and the AI processing is directly performed on the intelligent plane of the CU layer, reducing the need for access to the Internet.
  • the data processing steps reduce communication delays and improve the data processing efficiency of the terminal.
  • the first data processing request may include, but is not limited to, one or more of artificial intelligence identification, business type identification, and indication information; the second data processing request may include, but is not limited to, the identity of the user terminal.
  • One or more types of information, artificial intelligence identification, business type identification, and instruction information may include but is not limited to one or more of the user terminal's identity information, artificial intelligence identification, business type identification, and indication information; the second response signal The response signal may include but is not limited to one or more types of information including artificial intelligence identification, business type identification, and indication information.
  • the present disclosure also provides a data processing device, as shown in Figure 3, including:
  • the first judgment unit 301 is configured to obtain the task to be processed, and determine whether the business type of the task to be processed is an artificial intelligence service, and in response to the task to be processed not being an artificial intelligence service, process the task to be processed according to the regular business type;
  • the acquisition unit 302 is configured to acquire the data processing request sent by the user terminal to the centralized unit layer in response to the task to be processed being an artificial intelligence service;
  • the second judgment unit 303 is configured to judge whether the centralized unit layer can process the pending tasks according to the data processing request, and in response to the centralized unit layer being unable to process the pending tasks, process the pending tasks according to the normal business type;
  • the feedback unit 304 is configured to generate a response signal and return it to the user terminal in response to the centralized unit layer being able to process the pending tasks;
  • the data processing unit 305 is configured to obtain the business data related to the pending tasks sent by the user terminal to the centralized unit layer, and use the artificial intelligence model to execute the pending tasks and process the business data;
  • the data transmission unit 306 returns the service data processed by the data processing unit 305 to the user terminal.
  • the embodiment of the present disclosure provides a device for connecting a user terminal to a centralized unit layer for AI processing.
  • the device includes a first judgment unit 301, an acquisition unit 302, a second judgment unit 303, a feedback unit 304, a data processing unit Unit 305, wherein the first judgment unit 301 can be set in the user terminal (UE), and the acquisition unit 302, the second judgment unit 303, the feedback unit 304, and the data processing unit 305 can be set in the centralized unit layer (CU).
  • the CU layer adds an intelligent plane and deploys the artificial intelligence model in the intelligent plane of the CU layer.
  • the UE transmits business data to the intelligent side of the CU layer for AI processing, rather than the Internet side.
  • the specific data processing flow may include the following steps: Step S101. First, the first judgment unit 301 judges whether the business to be processed is an AI-type business. If so, it goes to step S102. Otherwise, there is no need to perform AI processing and it is processed according to the general business type processing method; Step S102, the UE sends a data processing request to the CU layer user plane, and the acquisition unit 302 obtains the data processing request; Step S103, the second judgment unit 303 of the CU layer judges whether the CU layer can process the pending tasks of the user terminal.
  • step S104 the feedback unit 304 of the CU layer sends a response signal to the user terminal in response to the user terminal's data processing request;
  • step S105 and step S106 the UE sends the service data to the CU smart plane, and the data processing of the CU layer Unit 305 returns the processed service data to the UE.
  • step S102 the acquisition unit 302 of the centralized unit layer obtains the data processing request sent by the user terminal including: the user terminal sends the first data processing request to the distribution unit layer through the active antenna unit, and the distribution unit layer A second data processing request is generated according to the first data processing request and sent to the centralized unit layer as a data processing request.
  • step S104 the feedback unit 304 of the centralized unit layer generates a response signal and returns it to the user terminal, including: the centralized unit layer generates a first response signal and sends it to the distribution unit layer, the distribution unit layer generates a second response signal according to the first response signal, and Sent to the user terminal through the active antenna unit.
  • the UE can send an AI DataProcess Request (first data processing request) to the DU through the AAU, and the DU generates a UE AI DataProcess Request (a second data processing request) according to the first data processing request. ), sent to the user plane of the CU layer.
  • the user at the CU layer sends a UE AI DataProcess Response (first response signal) to the DU, and the DU generates an AI DataProcess Response (a second response signal) and sends it to the UE through the AAU.
  • the artificial intelligence model is deployed on the intelligent plane of the CU layer of the communication access network.
  • the UE communicates with the CU layer through AAU and DU, and the AI processing is directly performed on the intelligent plane of the CU layer, which reduces By accessing the Internet for data processing, the communication delay is reduced and the data processing efficiency of the terminal is improved.
  • the first data processing request may include, but is not limited to, one or more of artificial intelligence identification, business type identification, and indication information;
  • the second data processing request may include, but is not limited to, the identity of the user terminal.
  • the first response signal may include, but is not limited to, one or more of the user terminal's identity information, artificial intelligence identification, business type identification, and indication information;
  • the second response signal may include, but is not limited to, artificial intelligence identification, business type identification , one or more types of information in the instruction information.
  • the present disclosure also provides a communication system architecture, as shown in Figure 4, including a user terminal UE, an antenna unit AAU, a distribution unit layer DU and a centralized unit layer CU.
  • the centralized unit layer CU is provided with artificial intelligence for performing artificial intelligence tasks.
  • the user terminal UE processes business data through the centralized unit layer CU. It does not need to transmit the business data to the Internet server for processing. Instead, it performs AI processing at the CU layer of the communication access network, which can reduce the transmission steps of business data. Reduce transmission delays and improve data processing efficiency.
  • the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.
  • electronic devices are intended to mean various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers.
  • Electronic devices may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices.
  • the components shown herein, their connections and relationships, and their functions are examples only and are not intended to limit implementations of the disclosure described and/or claimed herein.
  • the device includes a computing unit that can perform operations based on computer data stored in a read-only memory (ROM). Programs or computer programs loaded from storage units into random access memory (RAM) to perform various appropriate actions and processes. In RAM, various programs and data required for device operation can also be stored.
  • the computing unit, ROM and RAM are connected to each other via buses. Input/output (I/O) interfaces are also connected to the bus.
  • I/O interface Multiple components in the device are connected to the I/O interface, including: input units, such as keyboards, mice, etc.; output units, such as various types of monitors, speakers, etc.; storage units, such as disks, optical disks, etc.; and communication units, For example, network cards, modems, wireless communication transceivers, etc.
  • the communication unit allows the device to exchange information/data with other devices through computer networks such as the Internet and/or various telecommunications networks.
  • Computing units may be various general and/or special purpose processing components having processing and computing capabilities. Some examples of computing units include, but are not limited to, central processing units (CPUs), graphics processing units (GPUs), various dedicated artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processors (DSP), and any appropriate processor, controller, microcontroller, etc.
  • the computing unit performs each method and processing described above, such as the data processing method in the above embodiment.
  • the data processing method may be implemented as a computer software program that is tangibly embodied in a machine-readable medium, such as a storage unit.
  • part or all of the computer program may be loaded and/or installed onto the device via the ROM and/or communication unit.
  • the computing unit When the computer program is loaded into RAM and executed by the computing unit, one or more steps of the data processing method described above may be performed.
  • the computing unit may be configured to perform the data processing method in any other suitable manner (eg, by means of firmware).
  • Various implementations of the systems and techniques described above may be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip implemented in a system (SOC), load programmable logic device (CPLD), computer hardware, firmware, software, and/or a combination thereof.
  • FPGAs field programmable gate arrays
  • ASICs application specific integrated circuits
  • ASSPs application specific standard products
  • SOC system
  • CPLD load programmable logic device
  • computer hardware firmware, software, and/or a combination thereof.
  • Implementations may include implementation in one or more computer programs executable and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or a general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device .
  • a programmable processor which may be a special purpose or a general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device .
  • Program code for implementing the data processing methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that the program codes, when executed by the processor or controller, cause the functions specified in the flowcharts and/or block diagrams/ The operation is implemented.
  • the program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
  • a machine-readable medium may be a tangible medium that may contain or store a program for use by or in connection with an instruction execution system, apparatus, or device.
  • the machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium.
  • Machine-readable media may include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any suitable combination of the foregoing.
  • machine-readable storage media would include one or more wire-based electrical connections, laptop disks, hard drives, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.
  • RAM random access memory
  • ROM read only memory
  • EPROM or flash memory erasable programmable read only memory
  • CD-ROM portable compact disk read-only memory
  • magnetic storage device or any suitable combination of the above.
  • the systems and techniques described herein may be implemented on a computer having a display device (eg, a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user ); and a keyboard and pointing device (eg, a mouse or a trackball) through which a user can provide input to the computer.
  • a display device eg, a CRT (cathode ray tube) or LCD (liquid crystal display) monitor
  • a keyboard and pointing device eg, a mouse or a trackball
  • Other kinds of devices may also be used to provide interaction with the user; for example, feedback provided to the user may be any Any form of sensory feedback (eg, visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).
  • the systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., A user's computer having a graphical user interface or web browser through which the user can interact with implementations of the systems and technologies described herein), or including such backend components, middleware components, or any combination of front-end components in a computing system.
  • the components of the system may be interconnected by any form or medium of digital data communication (eg, a communications network). Examples of communication networks include: local area network (LAN), wide area network (WAN), and the Internet.
  • Computer systems may include clients and servers.
  • Clients and servers are generally remote from each other and typically interact over a communications network.
  • the relationship of client and server is created by computer programs running on corresponding computers and having a client-server relationship with each other.
  • the server can be a cloud server, a distributed system server, or a server combined with a blockchain.

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Abstract

一种数据处理方法、装置、通信系统、电子设备及存储介质。具体实现方案为：判断待处理任务的业务类型是否为人工智能业务，若否，则按常规业务类型处理；若是，集中单元层获取用户终端发送的数据处理请求；集中单元层根据数据处理请求判断是否能够处理待处理任务，若否，则按常规业务类型处理；若是，集中单元层生成响应信号返回给用户终端；集中单元层获取用户终端发送的待处理任务相关的业务数据，并利用人工智能模型执行待处理任务，对业务数据进行处理后返回给用户终端。

Description

数据处理方法、装置、通信系统、电子设备及存储介质
本公开要求于2022年03月24日提交中国专利局、申请号为202210292403.2、发明名称为"数据处理方法、装置、通信系统、电子设备及存储介质"的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本公开涉及通信技术领域，尤其涉及数据处理方法、装置、通信系统、电子设备及存储介质。
背景技术
5G网络是当前最新一代的移动通信网络。5G网络主要包括三个部分组成，分别是接入网、承载网和核心网。在5G网络中，接入网不再是由传统通信网络架构的BBU(Building Base band Unit，室内基带处理单元)、RRU(Remote Radio Unit，射频拉远单元)、天线组成，而是被重构为包括CU(Centralized Unit，集中单元)、DU(Distribute Unit，分布单元)、AAU(Active Antenna Unit，有源天线单元)三个部分。其中，传统BBU的非实时部分将分割出来，重新定义为CU，负责处理非实时协议和服务；BBU的剩余功能重新定义为DU，负责处理物理层协议和实时服务；BBU的部分物理层处理功能与原RRU及无源天线合并为AAU。简而言之，以处理内容的实时性对CU和DU进行区分。
人工智能(Artificial Intelligence，AI)是研究、开发用于模拟、延伸和扩展人的智能的理论、方法、技术及应用系统的一门新的技术科学。作为计算机科学的一个分支，它企图了解智能的实质，并生产出一种新的能以人类智能相似的方式做出反应的智能机器，该领域的研究包括机器人、语言识别、图像识别、自然语言处理和专家系统等。目前，随着科技的发展，人工智能模型能够实现越来越多的功能，为人类的生活带来了极大的便利。例如，可以将微信语音通过人工智能模型转化为文字，更直观地获 取信息。该技术的实现方式是基于用户终端将语音通过接入网传入核心网，最后接入互联网，通过互联网另一端的服务器的人工智能模型转换成文字后再进行回传。这种通过将数据传输到互联网进行处理的方式，不但传输时延较高，且在互联网中断的情况下无法使用。
发明内容
本公开提供了一种用于处理用户终端的业务数据的方法、装置、设备、通信系统以及存储介质。
根据本公开的一方面，提供了一种数据处理方法，包括：
获取所述待处理任务，并判断所述待处理任务的业务类型是否为人工智能业务，并响应于所述待处理任务不是所述人工智能业务，按常规业务类型对所述待处理任务进行处理；
响应于所述待处理任务为所述人工智能业务，集中单元层获取用户终端发送的数据处理请求；
所述集中单元层根据所述数据处理请求判断是否能够处理所述待处理任务，并响应于所述集中单元层不能处理所述待处理任务，按常规业务类型对所述待处理任务进行处理；
响应于所述集中单元层能够处理所述待处理任务，所述集中单元层生成响应信号返回给所述用户终端；
所述集中单元层获取所述用户终端发送的所述待处理任务相关的业务数据，并利用人工智能模型执行所述待处理任务，对所述业务数据进行处理；
所述集中单元层将处理后的所述业务数据返回给所述用户终端。
可选的，所述集中单元层获取用户终端发送的数据处理请求包括：所述用户终端通过有源天线单元向分布单元层发送第一数据处理请求，所述分布单元层根据所述第一数据处理请求生成第二数据处理请求作为所述数据处理请求向所述集中单元层发送。
可选的，所述集中单元层生成响应信号返回给所述用户终端包括：所述集中单元层生成第一响应信号发送给分布单元层，所述分布单元层根据所述第一响应信号生成第二响应信号，并通过有源天线单元发送给所述用户终端。
可选的，所述第一数据处理请求包括人工智能标识，和/或业务类型标识，和/或指示信息；
所述第二数据处理请求包括所述用户终端的身份信息，和/或所述人工智能标识，和/或所述业务类型标识，和/或所述指示信息。
可选的，所述第一响应信号包括用户终端的身份信息，和/或人工智能标识，和/或业务类型标识，和/或指示信息；
所述第二响应信号包括所述人工智能标识，和/或所述业务类型标识，和/或所述指示信息。
根据本公开的另一方面，提供了一种数据处理装置，包括：
第一判断单元，被配置为获取待处理任务，并判断所述待处理任务的业务类型是否为人工智能业务，并响应于所述待处理任务不是所述人工智能业务，按常规业务类型对所述待处理任务进行处理；
获取单元，被配置为响应于所述待处理任务为所述人工智能业务，获取用户终端向集中单元层发送的数据处理请求；
第二判断单元，被配置为根据所述数据处理请求判断所述集中单元层是否能够处理所述待处理任务，并响应于所述集中单元层不能处理所述待处理任务，按常规业务类型对所述待处理任务进行处理；
反馈单元，被配置为响应于所述集中单元层能够处理所述待处理任务，生成响应信号返回给所述用户终端；
数据处理单元，被配置为获取所述用户终端向所述集中单元层发送的所述待处理任务相关的业务数据，并利用人工智能模型执行所述待处理任务，对所述业务数据进行处理；
数据传输单元，被配置为将所述数据处理单元处理后的所述业务数据返回给所述用户终端。
可选的，所述获取单元获取所述数据处理请求包括：所述用户终端通过有源天线单元向分布单元层发送第一数据处理请求，所述分布单元层根据所述第一数据处理请求生成第二数据处理请求作为所述数据处理请求向所述集中单元层的所述获取单元发送。
可选的，所述反馈单元生成所述响应信号返回给所述用户终端包括：所述反馈单元生成第一响应信号发送给分布单元层，所述分布单元层根据所述第一响应信号生成第二响应信号，并通过有源天线单元发送给所述用户终端。
可选的，所述第一数据处理请求包括人工智能标识，和/或业务类型标识，和/或指示信息；
所述第二数据处理请求包括所述用户终端的身份信息，和/或所述人工智能标识，和/或所述业务类型标识，和/或所述指示信息。
可选的，所述第一响应信号包括用户终端的身份信息，和/或人工智能标识，和/或业务类型标识，和/或指示信息；
所述第二响应信号包括所述人工智能标识，和/或所述业务类型标识，和/或所述指示信息。
本公开还提供了一种通信系统架构，包括用户终端、天线单元、分布单元层以及集中单元层，所述集中单元层中设有用于执行人工智能任务的人工智能模型，所述用户终端通过所述集中单元层处理业务数据。
本公开还提供了一种电子设备，包括：
至少一个处理器；以及
与所述至少一个处理器通信连接的存储器；其中，
所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行上述技术方案中 任一项所述的数据处理方法。
本公开还提供了一种存储有计算机指令的非瞬时计算机可读存储介质，其中，所述计算机指令用于使所述计算机执行根据上述实施例中任一项所述的数据处理方法。
本公开还提供了一种计算机程序产品，包括计算机程序，所述计算机程序在被处理器执行时实现根据上述实施例中任一项所述的数据处理方法。
本公开基于上述数据处理方法、装置、通信系统架构、电子设备及存储介质，利用集中单元层的人工智能模型处理用户终端的业务数据，通过在集中单元层直接利用人工智能模型处理数据的方式，减少了数据的传输步骤，降低了通信时延，提升了终端的数据处理效率。
应当理解，本部分所描述的内容并非旨在标识本公开的实施例的关键或重要特征，也不用于限制本公开的范围。本公开的其它特征将通过以下的说明书而变得容易理解。
附图说明
附图用于更好地理解本方案，不构成对本公开的限定。其中：
图1是本公开实施例中的数据处理方法的步骤流程图；
图2是本公开实施例中的数据处理方法的原理示意图；
图3是本公开实施例中的数据处理装置的原理框图；
图4是本公开实施例中的通信系统架构图。
具体实施方式
以下结合附图对本公开的示范性实施例做出说明，其中包括本公开实施例的各种细节以助于理解，应当将它们认为仅仅是示范性的。因此，本领域普通技术人员应当认识到，可以对这里描述的实施例做出各种改变和修改，而不会背离本公开的范围和精神。同样，为了清楚和简明，以下的描述中省 略了对公知功能和结构的描述。
本公开提供了一种数据处理方法，如图1所示，包括：
步骤S101，在业务产生后获取待处理任务，判断待处理任务的业务类型是否为人工智能业务，并响应于待处理任务不是人工智能业务，转向按常规业务类型对待处理任务进行处理；
步骤S102，响应于待处理任务为人工智能业务，集中单元层获取用户终端发送的数据处理请求；
步骤S103，集中单元层根据数据处理请求判断是否能够处理待处理任务，并响应于集中单元层不能处理待处理任务，按常规业务类型对待处理任务进行处理；
步骤S104，响应于集中单元层能够处理待处理任务，集中单元层生成响应信号返回给用户终端；
步骤S105，集中单元层获取用户终端发送的待处理任务相关的业务数据，并利用人工智能模型执行所述待处理任务，对业务数据进行处理；
步骤S106，集中单元层将处理后的业务数据返回给用户终端。
具体地，本公开提供了将用户终端接入集中单元层进行AI(Artificial Intelligence，人工智能)处理的方案及流程。集中单元层(CU)除了包括控制面和用户面外，增加智能面，将人工智能模型部署在CU的智能面中。用户终端(UE)将业务数据传输至CU层的智能面进行AI处理，而非互联网端。示例性地，具体可以包括以下步骤：步骤S101，UE判断待处理业务是否为AI类业务，若是则转向步骤S102，若否则无需进行AI处理，按一般业务类型处理方式处理；步骤S102，UE向CU层用户面发送数据处理请求；步骤S103，CU层判断自身是否能处理用户终端的待处理任务，如果能够处理则转向步骤S104；步骤S104，CU层的用户面向用户终端发送响应信号，以响应用户终端的数据处理请求；步骤S105，UE将业务数据发送至CU智 能面进行AI处理；步骤S106，CU将处理后的业务数据返回至UE。通过上述技术方案，用户终端无需将业务数据传输到互联网端的服务器中进行处理，减少了传输的途径节点，降低传输时延，提升数据处理效率，提供给用户更好的体验。
作为可选的实施方式，在步骤S102中，集中单元层获取用户终端发送的数据处理请求包括：用户终端通过有源天线单元向分布单元层发送第一数据处理请求，分布单元层根据第一数据处理请求生成第二数据处理请求作为数据处理请求向集中单元层发送。在步骤S104中，集中单元层生成响应信号返回给用户终端包括：集中单元层生成第一响应信号发送给分布单元层，分布单元层根据第一响应信号生成第二响应信号，并通过有源天线单元发送给用户终端。
示例性地，如图2所示的传输流程图，在步骤S102中，UE可以通过AAU向DU发送AI DataProcess Request(第一数据处理请求),DU根据第一数据处理请求生成UE AI DataProcess Request(第二数据处理请求)，向CU层的用户面发送。在步骤S104中，CU层的用户面向DU发送UE AI DataProcess Response(第一响应信号)，DU生成AI DataProcess Response(第二响应信号)通过AAU向UE发送。本实施例中将人工智能模型部署在通信接入网CU层的智能面，UE通过AAU和DU与CU层进行通信，在CU层的智能面直接进行AI处理的方式，减少了通过接入互联网进行数据处理的步骤，降低了通信时延，提升了终端的数据处理效率。
作为可选的实施方式，第一数据处理请求可以包括但不限于人工智能标识、业务类型标识、指示信息中的一种或多种信息；第二数据处理请求可以包括但不限于用户终端的身份信息、人工智能标识、业务类型标识、指示信息中的一种或多种信息。第一响应信号可以包括但不限于用户终端的身份信息、人工智能标识、业务类型标识、指示信息中的一种或多种信息；第二响 应信号可以包括但不限于人工智能标识、业务类型标识、指示信息中的一种或多种信息。
本公开还提供了一种数据处理装置，如图3所示，包括：
第一判断单元301，被配置为获取待处理任务，并判断待处理任务的业务类型是否为人工智能业务，并响应于待处理任务不是人工智能业务，按常规业务类型对待处理任务进行处理；
获取单元302，被配置为响应于待处理任务为人工智能业务，获取用户终端向集中单元层发送的数据处理请求；
第二判断单元303，被配置为根据数据处理请求判断集中单元层是否能够处理待处理任务，并响应于集中单元层不能处理待处理任务，按常规业务类型对待处理任务进行处理；
反馈单元304，被配置为响应于集中单元层能够处理待处理任务，生成响应信号返回给用户终端；
数据处理单元305，被配置为获取用户终端向集中单元层发送的待处理任务相关的业务数据，并利用人工智能模型执行待处理任务，对业务数据进行处理；
数据传输单元306，将数据处理单元305处理后的业务数据返回给用户终端。
具体地，本公开实施例提供了一种将用户终端接入集中单元层进行AI处理的装置，该装置包括第一判断单元301、获取单元302、第二判断单元303、反馈单元304、数据处理单元305，其中，第一判断单元301可以设置在用户终端(UE)中，获取单元302、第二判断单元303、反馈单元304、数据处理单元305可以设置在集中单元层(CU)中。CU层除了包括控制面和用户面外，增加智能面，将人工智能模型部署在CU层的智能面中。UE将业务数据传输至CU层的智能面进行AI处理，而非互联网端。示例性地， 具体数据处理流程可以包括以下步骤：步骤S101，首先第一判断单元301判断待处理业务是否为AI类业务，若是则转向步骤S102，若否则无需进行AI处理，按一般业务类型处理方式处理；步骤S102，UE向CU层用户面发送数据处理请求，获取单元302获取该数据处理请求；步骤S103，CU层的第二判断单元303判断CU层是否能处理用户终端的待处理任务，如果能够处理则转向步骤S104；步骤S104，CU层的反馈单元304向用户终端发送响应信号，以响应用户终端的数据处理请求；步骤S105和步骤S106，UE将业务数据发送至CU智能面，CU层的数据处理单元305将处理后的业务数据返回至UE。通过上述技术方案，用户终端无需将业务数据传输到互联网端的服务器中进行处理，减少了传输的途径节点，降低传输时延，提升数据处理效率，提供给用户更好的体验。
作为可选的实施方式，在步骤S102中，集中单元层的获取单元302获取用户终端发送的数据处理请求包括：用户终端通过有源天线单元向分布单元层发送第一数据处理请求，分布单元层根据第一数据处理请求生成第二数据处理请求作为数据处理请求向集中单元层发送。在步骤S104中，集中单元层的反馈单元304生成响应信号返回给用户终端包括：集中单元层生成第一响应信号发送给分布单元层，分布单元层根据第一响应信号生成第二响应信号，并通过有源天线单元发送给用户终端。
示例性地，如图2所示的传输流程图，UE可以通过AAU向DU发送AI DataProcess Request(第一数据处理请求),DU根据第一数据处理请求生成UE AI DataProcess Request(第二数据处理请求)，向CU层的用户面发送。CU层的用户面向DU发送UE AI DataProcess Response(第一响应信号)，DU生成AI DataProcess Response(第二响应信号)通过AAU向UE发送。本实施例中将人工智能模型部署在通信接入网CU层的智能面，UE通过AAU和DU与CU层进行通信，在CU层的智能面直接进行AI处理的方式，减少了 通过接入互联网进行数据处理的步骤，降低了通信时延，提升了终端的数据处理效率。
作为可选的实施方式，第一数据处理请求可以包括但不限于人工智能标识、业务类型标识、指示信息中的一种或多种信息；第二数据处理请求可以包括但不限于用户终端的身份信息、人工智能标识、业务类型标识、指示信息中的一种或多种信息。第一响应信号可以包括但不限于用户终端的身份信息、人工智能标识、业务类型标识、指示信息中的一种或多种信息；第二响应信号可以包括但不限于人工智能标识、业务类型标识、指示信息中的一种或多种信息。
本公开还提供了一种通信系统架构，如图4所示，包括用户终端UE、天线单元AAU、分布单元层DU以及集中单元层CU，集中单元层CU中设有用于执行人工智能任务的人工智能模型，用户终端UE通过集中单元层CU处理业务数据，无需将业务数据传入互联网的服务器中进行处理，而是在通信接入网的CU层进行AI处理，可以减少业务数据的传输步骤，降低传输时延，提升数据处理效率。
根据本公开的实施例，本公开还提供了一种电子设备、一种可读存储介质和一种计算机程序产品。
具体地，电子设备旨在表示各种形式的数字计算机，诸如，膝上型计算机、台式计算机、工作台、个人数字助理、服务器、刀片式服务器、大型计算机、和其它适合的计算机。电子设备还可以表示各种形式的移动装置，诸如，个人数字处理、蜂窝电话、智能电话、可穿戴设备和其它类似的计算装置。本文所示的部件、它们的连接和关系、以及它们的功能仅仅作为示例，并且不意在限制本文中描述的和/或者要求的本公开的实现。
设备包括计算单元，其可以根据存储在只读存储器(ROM)中的计算机 程序或者从存储单元加载到随机访问存储器(RAM)中的计算机程序，来执行各种适当的动作和处理。在RAM中，还可存储设备操作所需的各种程序和数据。计算单元、ROM以及RAM通过总线彼此相连。输入/输出(I/O)接口也连接至总线。
设备中的多个部件连接至I/O接口，包括：输入单元，例如键盘、鼠标等；输出单元，例如各种类型的显示器、扬声器等；存储单元，例如磁盘、光盘等；以及通信单元，例如网卡、调制解调器、无线通信收发机等。通信单元允许设备通过诸如因特网的计算机网络和/或各种电信网络与其他设备交换信息/数据。
计算单元可以是各种具有处理和计算能力的通用和/或专用处理组件。计算单元的一些示例包括但不限于中央处理单元(CPU)、图形处理单元(GPU)、各种专用的人工智能(AI)计算芯片、各种运行机器学习模型算法的计算单元、数字信号处理器(DSP)、以及任何适当的处理器、控制器、微控制器等。计算单元执行上文所描述的各个方法和处理，例如上述实施例中的数据处理方法。例如，在一些实施例中，数据处理方法可被实现为计算机软件程序，其被有形地包含于机器可读介质，例如存储单元。在一些实施例中，计算机程序的部分或者全部可以经由ROM和/或通信单元而被载入和/或安装到设备上。当计算机程序加载到RAM并由计算单元执行时，可以执行上文描述的数据处理方法的一个或多个步骤。备选地，在其他实施例中，计算单元可以通过其他任何适当的方式(例如，借助于固件)而被配置为执行数据处理方法。
本文中以上描述的系统和技术的各种实施方式可以在数字电子电路系统、集成电路系统、现场可编程门阵列(FPGA)、专用集成电路(ASIC)、专用标准产品(ASSP)、芯片上系统的系统(SOC)、负载可编程逻辑设备(CPLD)、计算机硬件、固件、软件、和/或它们的组合中实现。这些各种实 施方式可以包括：实施在一个或者多个计算机程序中，该一个或者多个计算机程序可在包括至少一个可编程处理器的可编程系统上执行和/或解释，该可编程处理器可以是专用或者通用可编程处理器，可以从存储系统、至少一个输入装置、和至少一个输出装置接收数据和指令，并且将数据和指令传输至该存储系统、该至少一个输入装置、和该至少一个输出装置。
用于实施本公开的数据处理方法的程序代码可以采用一个或多个编程语言的任何组合来编写。这些程序代码可以提供给通用计算机、专用计算机或其他可编程数据处理装置的处理器或控制器，使得程序代码当由处理器或控制器执行时使流程图和/或框图中所规定的功能/操作被实施。程序代码可以完全在机器上执行、部分地在机器上执行，作为独立软件包部分地在机器上执行且部分地在远程机器上执行或完全在远程机器或服务器上执行。
在本公开的上下文中，机器可读介质可以是有形的介质，其可以包含或存储以供指令执行系统、装置或设备使用或与指令执行系统、装置或设备结合地使用的程序。机器可读介质可以是机器可读信号介质或机器可读储存介质。机器可读介质可以包括但不限于电子的、磁性的、光学的、电磁的、红外的、或半导体系统、装置或设备，或者上述内容的任何合适组合。机器可读存储介质的更具体示例会包括基于一个或多个线的电气连接、便携式计算机盘、硬盘、随机存取存储器(RAM)、只读存储器(ROM)、可擦除可编程只读存储器(EPROM或快闪存储器)、光纤、便捷式紧凑盘只读存储器(CD-ROM)、光学储存设备、磁储存设备、或上述内容的任何合适组合。
为了提供与用户的交互，可以在计算机上实施此处描述的系统和技术，该计算机具有：用于向用户显示信息的显示装置(例如，CRT(阴极射线管)或者LCD(液晶显示器)监视器)；以及键盘和指向装置(例如，鼠标或者轨迹球)，用户可以通过该键盘和该指向装置来将输入提供给计算机。其它种类的装置还可以用于提供与用户的交互；例如，提供给用户的反馈可以是任 何形式的传感反馈(例如，视觉反馈、听觉反馈、或者触觉反馈)；并且可以用任何形式(包括声输入、语音输入或者、触觉输入)来接收来自用户的输入。
可以将此处描述的系统和技术实施在包括后台部件的计算系统(例如，作为数据服务器)、或者包括中间件部件的计算系统(例如，应用服务器)、或者包括前端部件的计算系统(例如，具有图形用户界面或者网络浏览器的用户计算机，用户可以通过该图形用户界面或者该网络浏览器来与此处描述的系统和技术的实施方式交互)、或者包括这种后台部件、中间件部件、或者前端部件的任何组合的计算系统中。可以通过任何形式或者介质的数字数据通信(例如，通信网络)来将系统的部件相互连接。通信网络的示例包括：局域网(LAN)、广域网(WAN)和互联网。
计算机系统可以包括客户端和服务器。客户端和服务器一般远离彼此并且通常通过通信网络进行交互。通过在相应的计算机上运行并且彼此具有客户端-服务器关系的计算机程序来产生客户端和服务器的关系。服务器可以是云服务器，也可以为分布式系统的服务器，或者是结合了区块链的服务器。
应该理解，可以使用上面所示的各种形式的流程，重新排序、增加或删除步骤。例如，本公开中记载的各步骤可以并行地执行也可以顺序地执行也可以不同的次序执行，只要能够实现本公开公开的技术方案所期望的结果，本文在此不进行限制。
上述具体实施方式，并不构成对本公开保护范围的限制。本领域技术人员应该明白的是，根据设计要求和其他因素，可以进行各种修改、组合、子组合和替代。任何在本公开的精神和原则之内所作的修改、等同替换和改进等，均应包含在本公开保护范围之内。

Claims (14)

  1. 一种数据处理方法，其特征在于，包括：
    获取待处理任务，并判断所述待处理任务的业务类型是否为人工智能业务，并响应于所述待处理任务不是所述人工智能业务，按常规业务类型对所述待处理任务进行处理；
    响应于所述待处理任务为所述人工智能业务，集中单元层获取用户终端发送的数据处理请求；
    所述集中单元层根据所述数据处理请求判断是否能够处理所述待处理任务，并响应于所述集中单元层不能处理所述待处理任务，按常规业务类型对所述待处理任务进行处理；
    响应于所述集中单元层能够处理所述待处理任务，所述集中单元层生成响应信号返回给所述用户终端；
    所述集中单元层获取所述用户终端发送的所述待处理任务相关的业务数据，并利用人工智能模型执行所述待处理任务，对所述业务数据进行处理；
    所述集中单元层将处理后的所述业务数据返回给所述用户终端。
  2. 根据权利要求1所述的数据处理方法，其特征在于，所述集中单元层获取用户终端发送的数据处理请求包括：所述用户终端通过有源天线单元向分布单元层发送第一数据处理请求，所述分布单元层根据所述第一数据处理请求生成第二数据处理请求作为所述数据处理请求向所述集中单元层发送。
  3. 根据权利要求1所述的数据处理方法，其特征在于，所述集中单元层生成响应信号返回给所述用户终端包括：所述集中单元层生成第一响应信号发送给分布单元层，所述分布单元层根据所述第一响应信号生成第二响应信号，并通过有源天线单元发送给所述用户终端。
  4. 根据权利要求2所述的数据处理方法，其特征在于，所述第一数据处理请求包括人工智能标识，和/或业务类型标识，和/或指示信息；
    所述第二数据处理请求包括所述用户终端的身份信息，和/或所述人工智能标识，和/或所述业务类型标识，和/或所述指示信息。
  5. 根据权利要求3所述的数据处理方法，其特征在于，所述第一响应信号包括用户终端的身份信息，和/或人工智能标识，和/或业务类型标识，和/或指示信息；
    所述第二响应信号包括所述人工智能标识，和/或所述业务类型标识，和/或所述指示信息。
  6. 一种数据处理装置，其特征在于，包括：
    第一判断单元，被配置为获取所述待处理任务，并判断所述待处理任务的业务类型是否为人工智能业务，并响应于所述待处理任务不是所述人工智能业务，按常规业务类型对所述待处理任务进行处理；
    获取单元，被配置为响应于所述待处理任务为所述人工智能业务，获取用户终端向集中单元层发送的数据处理请求；
    第二判断单元，被配置为根据所述数据处理请求判断所述集中单元层是否能够处理所述待处理任务，并响应于所述集中单元层不能处理所述待处理任务，按常规业务类型对所述待处理任务进行处理；
    反馈单元，被配置为响应于所述集中单元层能够处理所述待处理任务，生成响应信号返回给所述用户终端；
    数据处理单元，被配置为获取所述用户终端向所述集中单元层发送的所述待处理任务相关的业务数据，并利用人工智能模型执行所述待处理任务，对所述业务数据进行处理；
    数据传输单元，被配置为将所述数据处理单元处理后的所述业务数据返回给所述用户终端。
  7. 根据权利要求6所述的数据处理装置，其特征在于，所述获取单元获取所述数据处理请求包括：所述用户终端通过有源天线单元向分布单元层发送第一数据处理请求，所述分布单元层根据所述第一数据处理请求生成第二数据处理请求作为所述数据处理请求向所述集中单元层的所述获取单元发送。
  8. 根据权利要求6所述的数据处理装置，其特征在于，所述反馈单元生成所述响应信号返回给所述用户终端包括：所述反馈单元生成第一响应信号发送给分布单元层，所述分布单元层根据所述第一响应信号生成第二响应信号，并通过有源天线单元发送给所述用户终端。
  9. 根据权利要求7所述的数据处理装置，其特征在于，所述第一数据处理请求包括人工智能标识，和/或业务类型标识，和/或指示信息；
    所述第二数据处理请求包括所述用户终端的身份信息，和/或所述人工智能标识，和/或所述业务类型标识，和/或所述指示信息。
  10. 根据权利要求8所述的数据处理装置，其特征在于，所述第一响应信号包括用户终端的身份信息，和/或人工智能标识，和/或业务类型标识，和/或指示信息；
    所述第二响应信号包括所述人工智能标识，和/或所述业务类型标识，和/或所述指示信息。
  11. 一种通信系统架构，包括用户终端、天线单元、分布单元层以及集中单元层，其特征在于，所述集中单元层中设有用于执行人工智能任务的人工智能模型，所述用户终端通过所述集中单元层处理业务数据。
  12. 一种电子设备，包括：
    至少一个处理器；以及
    与所述至少一个处理器通信连接的存储器；其中，
    所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行权利要求1-5中任一项所述的数据处理方法。
  13. 一种存储有计算机指令的非瞬时计算机可读存储介质，其中，所述计算机指令用于使所述计算机执行根据权利要求1-5中任一项所述的数据处理方法。
  14. 一种计算机程序产品，包括计算机程序，所述计算机程序在被处理器执行时实现根据权利要求1-5中任一项所述的数据处理方法。
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