WO2023141887A1 - 语义通信的传输方法、终端设备 - Google Patents

语义通信的传输方法、终端设备 Download PDF

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Publication number
WO2023141887A1
WO2023141887A1 PCT/CN2022/074351 CN2022074351W WO2023141887A1 WO 2023141887 A1 WO2023141887 A1 WO 2023141887A1 CN 2022074351 W CN2022074351 W CN 2022074351W WO 2023141887 A1 WO2023141887 A1 WO 2023141887A1
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Prior art keywords
information
semantic
terminal device
extended
source
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PCT/CN2022/074351
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English (en)
French (fr)
Inventor
田文强
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Oppo广东移动通信有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Application filed by Oppo广东移动通信有限公司 filed Critical Oppo广东移动通信有限公司
Priority to CN202280089885.XA priority Critical patent/CN118715524A/zh
Priority to PCT/CN2022/074351 priority patent/WO2023141887A1/zh
Publication of WO2023141887A1 publication Critical patent/WO2023141887A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/12—Messaging; Mailboxes; Announcements

Definitions

  • the present application relates to the field of communications, and more specifically, to a semantic communication transmission method and a terminal device.
  • the goal of communication transmission is to realize the lossless transmission of original information.
  • the lossless transmission of original information is only a basic requirement, not all requirements for communication transmission. Only the transmission of more information can meet the constantly updated communication needs.
  • the embodiment of the present application provides a semantic communication transmission method and a terminal device, which can realize the transmission of semantic communication and can meet constantly updated communication requirements.
  • An embodiment of the present application provides a transmission method for semantic communication, which is applied to a terminal device, including:
  • the terminal device performs semantic acquisition processing on the information source to obtain semantic information
  • the terminal device obtains the first information to be transmitted according to the semantic information
  • the terminal device sends the first information.
  • An embodiment of the present application provides a transmission method for semantic communication, which is applied to a terminal device, including:
  • the terminal device receives second information
  • the terminal device performs semantic acquisition processing on the information source to obtain semantic information.
  • An embodiment of the present application provides a semantic communication transmission method applied to network devices, including:
  • the network device receives first information
  • the semantic information is information obtained by the terminal device side by performing semantic acquisition processing on the information source.
  • An embodiment of the present application provides a semantic communication transmission method applied to network devices, including:
  • the network device determines the second information to be transmitted according to the information source; wherein, the information source includes semantic information to be executed for semantic acquisition processing;
  • the network device sends the second information.
  • An embodiment of the present application provides a terminal device, including:
  • the first semantic acquisition unit is configured to perform semantic acquisition processing on the information source to obtain semantic information
  • a first processing unit configured to obtain first information to be transmitted according to the semantic information
  • a first sending unit configured to send the first information.
  • An embodiment of the present application provides a terminal device, including:
  • a first receiving unit configured to receive second information
  • a second processing unit configured to recover an information source from the second information
  • the second semantic acquisition unit is configured to perform semantic acquisition processing on the information source to obtain semantic information.
  • An embodiment of the present application provides a network device, and the network device includes:
  • a second receiving unit configured to receive the first information
  • a third processing unit configured to recover semantic information from the first information
  • the semantic information is information obtained by the terminal device side by performing semantic acquisition processing on the information source.
  • An embodiment of the present application provides a network device, and the network device includes:
  • the fourth processing unit is configured to determine the second information to be transmitted according to the information source; wherein the information source includes semantic information to be executed for semantic acquisition processing;
  • a second sending unit configured to send the second information.
  • An embodiment of the present application provides a terminal device, including a processor and a memory.
  • the memory is used to store a computer program
  • the processor is used to call and run the computer program stored in the memory, so that the terminal device executes the method described in the above-mentioned embodiments of the present application.
  • An embodiment of the present application provides a network device, including a processor and a memory.
  • the memory is used to store a computer program
  • the processor is used to call and run the computer program stored in the memory, so that the network device executes the method described in the above-mentioned embodiments of the present application.
  • An embodiment of the present application provides a chip configured to implement the method described in the foregoing embodiments of the present application.
  • the chip includes: a processor, configured to call and run a computer program from the memory, so that the device installed with the chip executes the method described in the above-mentioned embodiments of the present application.
  • An embodiment of the present application provides a computer-readable storage medium, which is used to store a computer program, and when the computer program is run by a device, the device executes the method described in the above-mentioned embodiments of the present application.
  • An embodiment of the present application provides a computer program product, including computer program instructions, where the computer program instruction causes a computer to execute the method described in the foregoing embodiments of the present application.
  • An embodiment of the present application provides a computer program, which, when running on a computer, causes the computer to execute the method described in the foregoing embodiments of the present application.
  • the terminal device can perform semantic acquisition processing on the information source to obtain semantic information, and the terminal device can determine the first information to be transmitted according to the semantic information, and the terminal device, as the sending end, can send the first information to the receiving end , so that the transmission of semantic communication can be realized, which can meet the constantly updated communication requirements.
  • Fig. 1 is a schematic diagram of an application scenario according to an embodiment of the present application.
  • Fig. 2 is a schematic flowchart of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 3 is a schematic flowchart of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 4 is a schematic flowchart of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 5 is a schematic flowchart of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 6 is a schematic flowchart of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 7 is a schematic flowchart of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 8 is a schematic flowchart of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 9 is a schematic flowchart of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 10 is a schematic flowchart of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 11 is a schematic flowchart of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 12 is a schematic codec diagram of an example of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 13 is a schematic neural network diagram of an example of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 14 is a schematic diagram of the relationship between information according to an example of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 15 is a schematic codec schematic diagram of an example of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 16 is a schematic diagram of extended semantic acquisition according to an example of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 17 is a schematic diagram of an extended semantic transmission according to an example of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 18 is a schematic diagram of core semantic acquisition according to an example of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 19 is a schematic diagram of core semantic transmission according to an example of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 20 is a schematic diagram of combined semantic transmission according to an example of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 21 is a schematic codec diagram of an example of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 22 is a schematic diagram of extended semantic transmission according to an example of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 23 is a schematic diagram of core semantic transmission according to an example of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 24 is a schematic diagram of combined semantic transmission according to an example of a semantic communication transmission method according to an embodiment of the present application.
  • Fig. 25 is a schematic block diagram of a terminal device according to an embodiment of the present application.
  • Fig. 26 is a schematic block diagram of a terminal device according to an embodiment of the present application.
  • Fig. 27 is a schematic block diagram of a network device according to an embodiment of the present application.
  • Fig. 28 is a schematic block diagram of a network device according to an embodiment of the present application.
  • Fig. 29 is a schematic block diagram of a communication device according to an embodiment of the present application.
  • FIG. 30 is a schematic block diagram of a chip according to an embodiment of the present application.
  • Fig. 31 is a schematic block diagram of a communication system according to an embodiment of the present application.
  • the technical solution of the embodiment of the present application can be applied to various communication systems, such as: Global System of Mobile communication (Global System of Mobile communication, GSM) system, code division multiple access (Code Division Multiple Access, CDMA) system, broadband code division multiple access (Wideband Code Division Multiple Access, WCDMA) system, General Packet Radio Service (GPRS), Long Term Evolution (LTE) system, Advanced long term evolution (LTE-A) system , New Radio (NR) system, evolution system of NR system, LTE (LTE-based access to unlicensed spectrum, LTE-U) system on unlicensed spectrum, NR (NR-based access to unlicensed spectrum) on unlicensed spectrum unlicensed spectrum (NR-U) system, Non-Terrestrial Networks (NTN) system, Universal Mobile Telecommunications System (UMTS), Wireless Local Area Networks (WLAN), Wireless Fidelity (Wireless Fidelity, WiFi), fifth-generation communication (5th-Generation, 5G) system or other communication systems, etc.
  • GSM Global System of Mobile
  • D2D Device to Device
  • M2M Machine to Machine
  • MTC Machine Type Communication
  • V2V Vehicle to Vehicle
  • V2X Vehicle to everything
  • the communication system in the embodiment of the present application may be applied to a carrier aggregation (Carrier Aggregation, CA) scenario, may also be applied to a dual connectivity (Dual Connectivity, DC) scenario, and may also be applied to an independent (Standalone, SA) deployment Web scene.
  • Carrier Aggregation, CA Carrier Aggregation
  • DC Dual Connectivity
  • SA independent deployment Web scene
  • the communication system in the embodiment of the present application may be applied to an unlicensed spectrum, where the unlicensed spectrum may also be considered as a shared spectrum; or, the communication system in the embodiment of the present application may also be applied to a licensed spectrum, where, Licensed spectrum can also be considered as non-shared spectrum.
  • the embodiments of the present application describe various embodiments in conjunction with network equipment and terminal equipment, wherein the terminal equipment may also be referred to as user equipment (User Equipment, UE), access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent or user device, etc.
  • user equipment User Equipment, UE
  • access terminal user unit
  • user station mobile station
  • mobile station mobile station
  • remote station remote terminal
  • mobile device user terminal
  • terminal wireless communication device
  • wireless communication device user agent or user device
  • the terminal device can be a station (STAION, ST) in the WLAN, a cellular phone, a cordless phone, a session initiation system (Session Initiation Protocol, SIP) phone, a wireless local loop (Wireless Local Loop, WLL) station, a personal digital processing (Personal Digital Assistant, PDA) devices, handheld devices with wireless communication functions, computing devices or other processing devices connected to wireless modems, vehicle-mounted devices, wearable devices, next-generation communication systems such as terminal devices in NR networks, or future Terminal equipment in the evolved public land mobile network (Public Land Mobile Network, PLMN) network, etc.
  • STAION, ST station
  • SIP Session Initiation Protocol
  • WLL Wireless Local Loop
  • PDA Personal Digital Assistant
  • the terminal device can be deployed on land, including indoor or outdoor, handheld, wearable or vehicle-mounted; it can also be deployed on water (such as ships, etc.); it can also be deployed in the air (such as aircraft, balloons and satellites) superior).
  • the terminal device may be a mobile phone (Mobile Phone), a tablet computer (Pad), a computer with a wireless transceiver function, a virtual reality (Virtual Reality, VR) terminal device, an augmented reality (Augmented Reality, AR) terminal Equipment, wireless terminal equipment in industrial control, wireless terminal equipment in self driving, wireless terminal equipment in remote medical, wireless terminal equipment in smart grid , wireless terminal equipment in transportation safety, wireless terminal equipment in smart city, or wireless terminal equipment in smart home.
  • a virtual reality (Virtual Reality, VR) terminal device an augmented reality (Augmented Reality, AR) terminal Equipment
  • wireless terminal equipment in industrial control wireless terminal equipment in self driving
  • wireless terminal equipment in remote medical wireless terminal equipment in smart grid
  • wireless terminal equipment in transportation safety wireless terminal equipment in smart city, or wireless terminal equipment in smart home.
  • the terminal device may also be a wearable device.
  • Wearable devices can also be called wearable smart devices, which is a general term for the application of wearable technology to intelligently design daily wear and develop wearable devices, such as glasses, gloves, watches, clothing and shoes.
  • a wearable device is a portable device that is worn directly on the body or integrated into the user's clothing or accessories. Wearable devices are not only a hardware device, but also achieve powerful functions through software support, data interaction, and cloud interaction.
  • Generalized wearable smart devices include full-featured, large-sized, complete or partial functions without relying on smart phones, such as smart watches or smart glasses, etc., and only focus on a certain type of application functions, and need to cooperate with other devices such as smart phones Use, such as various smart bracelets and smart jewelry for physical sign monitoring.
  • the network device may be a device for communicating with the mobile device, and the network device may be an access point (Access Point, AP) in WLAN, a base station (Base Transceiver Station, BTS) in GSM or CDMA , or a base station (NodeB, NB) in WCDMA, or an evolved base station (Evolutional Node B, eNB or eNodeB) in LTE, or a relay station or access point, or a vehicle-mounted device, a wearable device, and an NR network
  • BTS Base Transceiver Station
  • NodeB, NB base station
  • Evolutional Node B, eNB or eNodeB evolved base station
  • LTE Long Term Evolutional Node B, eNB or eNodeB
  • gNB network equipment in the network or the network equipment in the future evolved PLMN network or the network equipment in the NTN network, etc.
  • the network device may have a mobile feature, for example, the network device may be a mobile device.
  • the network equipment may be a satellite or a balloon station.
  • the satellite can be a low earth orbit (low earth orbit, LEO) satellite, a medium earth orbit (medium earth orbit, MEO) satellite, a geosynchronous earth orbit (geosynchronous earth orbit, GEO) satellite, a high elliptical orbit (High Elliptical Orbit, HEO) satellite. ) Satellite etc.
  • the network device may also be a base station installed on land, water, and other locations.
  • the network device may provide services for a cell, and the terminal device communicates with the network device through the transmission resources (for example, frequency domain resources, or spectrum resources) used by the cell, and the cell may be a network device ( For example, a cell corresponding to a base station), the cell may belong to a macro base station, or may belong to a base station corresponding to a small cell (Small cell), and the small cell here may include: a metro cell (Metro cell), a micro cell (Micro cell), a pico cell ( Pico cell), Femto cell, etc. These small cells have the characteristics of small coverage and low transmission power, and are suitable for providing high-speed data transmission services.
  • the transmission resources for example, frequency domain resources, or spectrum resources
  • the cell may be a network device (
  • the cell may belong to a macro base station, or may belong to a base station corresponding to a small cell (Small cell)
  • the small cell here may include: a metro cell (Metro cell), a micro cell (Micro
  • FIG. 1 exemplarily shows a communication system 100 .
  • the communication system 100 includes a network device 110 and two terminal devices 120 .
  • the communication system 100 may include multiple network devices 110, and the coverage of each network device 110 may include other numbers of terminal devices 120, which is not limited in this embodiment of the present application.
  • the communication system 100 may also include other network entities such as a mobility management entity (Mobility Management Entity, MME), an access and mobility management function (Access and Mobility Management Function, AMF), etc. Not limited.
  • MME Mobility Management Entity
  • AMF Access and Mobility Management Function
  • the network equipment may further include access network equipment and core network equipment. That is, the wireless communication system also includes multiple core networks for communicating with access network devices.
  • the access network device may be a long-term evolution (long-term evolution, LTE) system, a next-generation (mobile communication system) (next radio, NR) system or an authorized auxiliary access long-term evolution (LAA- Evolved base station (evolutional node B, abbreviated as eNB or e-NodeB) macro base station, micro base station (also called “small base station”), pico base station, access point (access point, AP), Transmission point (transmission point, TP) or new generation base station (new generation Node B, gNodeB), etc.
  • LTE long-term evolution
  • NR next-generation
  • LAA- Evolved base station evolutional node B, abbreviated as eNB or e-NodeB
  • eNB next-generation
  • NR next-generation
  • a device with a communication function in the network/system in the embodiment of the present application may be referred to as a communication device.
  • the communication equipment may include network equipment and terminal equipment with communication functions. It may include other devices in the communication system, such as network controllers, mobility management entities and other network entities, which are not limited in this embodiment of the present application.
  • the "indication" mentioned in the embodiments of the present application may be a direct indication, may also be an indirect indication, and may also mean that there is an association relationship.
  • a indicates B which can mean that A directly indicates B, for example, B can be obtained through A; it can also indicate that A indirectly indicates B, for example, A indicates C, and B can be obtained through C; it can also indicate that there is an association between A and B relation.
  • the term "corresponding" may indicate that there is a direct or indirect correspondence between the two, or that there is an association between the two, or that it indicates and is indicated, configuration and is configuration etc.
  • Fig. 2 is a schematic flowchart of a semantic communication transmission method 200 according to an embodiment of the present application.
  • the method can optionally be applied to the system shown in Fig. 1, but is not limited thereto.
  • the method includes at least some of the following:
  • the terminal device performs semantic acquisition processing on the information source to obtain semantic information.
  • the terminal device can also be referred to as the sending end (or coding end), and a semantic acquisition unit for implementing the semantic acquisition process can be added to the terminal equipment, so that the information source can be input into the semantic acquisition unit, and through the semantic The semantic information is obtained as an output after the acquisition process.
  • the semantic acquisition unit can be realized by artificial intelligence technology, such as various neural networks obtained by artificial intelligence technology and not limited to convolutional neural network.
  • the terminal device determines the first information to be transmitted according to the semantic information.
  • the semantic information and the source may also be transmitted (that is, at the terminal device side, in addition to the "source” of the original information, it may also include “semantic information” as additional information, and obtain the first information to be transmitted accordingly).
  • the terminal device sends the first information.
  • the terminal device as the sending end may send the first information as the sending information to be transmitted to the receiving end
  • the receiving end may be a network device (such as a base station), or a terminal device as the receiving end, such as using a mobile phone, Users of portable computers or desktop computers such as tablet computers, in order to realize the communication transmission of human-computer interaction.
  • the terminal device can perform semantic acquisition processing on the information source to obtain semantic information, the terminal device can determine the first information to be transmitted according to the semantic information, and the terminal device sends the first information to the receiving end as the sending end, In this way, the transmission of semantic communication can be realized, which can meet the constantly updated communication needs, that is, not only the transmission of the "information source” as the original information can be realized, but also the transmission of "semantic information" as additional information besides the original information can be realized.
  • the terminal device determines the first information to be transmitted according to the semantic information, including at least one of the following:
  • the terminal device obtains the first information after encoding and modulating the semantic information
  • the terminal device obtains the first information after encoding, modulating and encrypting the semantic information.
  • Fig. 3 is a schematic flowchart of a semantic communication transmission method 300 according to an embodiment of the present application.
  • the method can optionally be applied to the system shown in Fig. 1, but is not limited thereto.
  • the method includes at least some of the following:
  • the terminal device performs extended semantic acquisition processing on the information source to obtain extended semantic information.
  • the terminal device may also be referred to as a sending end (or encoding end), and an extended semantic acquisition unit for implementing the extended semantic acquisition process may be added to the terminal device, so that the information source may be input into the extended semantic acquisition unit,
  • the extended semantic information is output after the extended semantic acquisition processing.
  • the extended semantic acquisition unit can be realized by artificial intelligence technology, such as various neural networks obtained by artificial intelligence technology and not limited to convolutional neural network.
  • the extended semantic information includes: at least one item of emotion information, emphasis information, association information, prediction information, and different task priority information.
  • the terminal device determines the first information to be transmitted according to the extended semantic information.
  • the extended semantic information and the information source can also be transmitted (that is, on the terminal device side, in addition to the "information source” as the original information, the "extended semantic information” as additional information can also be included. Information", and obtain the first information to be transmitted accordingly).
  • the extended semantic information is compared with the "source” of the original information.
  • the extended semantic information is aimed at the semantics that the sender (or encoding end) expects to send.
  • the extended semantic information can be extracted from , which can prevent the receiving end (or decoding end) from being unable to obtain complete information, thereby improving the accuracy and information integrity of transmission.
  • the terminal device sends the first information.
  • the terminal device as the sending end may send the first information as the sending information to be transmitted to the receiving end
  • the receiving end may be a network device (such as a base station), or a terminal device as the receiving end, such as using a mobile phone, Users of portable computers or desktop computers such as tablet computers, in order to realize the communication transmission of human-computer interaction.
  • the terminal device performs extended semantic acquisition processing on the information source to obtain extended semantic information, including at least one of the following:
  • Method 1 Input the information source into the trained first network model (the first network model can be deployed in the above-mentioned extended semantic acquisition unit) to obtain emotional information, emphasis information, association information, prediction information, and different task priority information At least one item of , so as to obtain diversified extended semantic information.
  • Method 2 Input the information source into the trained second network model (the second network model can be deployed in the above-mentioned extended semantic acquisition unit), and obtain different emotional information classifications, different emphasized information classifications, different related information supplements, At least one of different prediction information supplements and different task priority information supplements, so as to obtain further information of diversified extended semantic information (such as information classification or information supplements, etc.).
  • it also includes: classifying and processing each item of information in the extended semantic information based on different classifications, using the corresponding identification information as the classification identification, and establishing a mapping relationship according to the classification identification and the corresponding classification description .
  • classification processing is performed on emotional information and emphasis information, and a mapping relationship is established to obtain a mapping table, wherein the mapping table for emotional information includes: the emotional classification described by the classification identifier and the classification description described by the corresponding classification.
  • the mapping table for the emphasis information includes: the importance category described by the category identifier, and the category description described by the corresponding category.
  • Fig. 4 is a schematic flowchart of a semantic communication transmission method 400 according to an embodiment of the present application.
  • the method can optionally be applied to the system shown in Fig. 1, but is not limited thereto.
  • the method includes at least some of the following:
  • the terminal device performs core semantic acquisition processing on the information source to obtain core semantic information.
  • the terminal device can also be referred to as a sending end (or encoding end), and a core semantics acquisition unit for implementing the core semantics acquisition process can be added to the terminal device, so that the information source can be input into the core semantics acquisition unit,
  • the core semantic information is output after the core semantic acquisition processing.
  • the core semantic acquisition unit can be realized by artificial intelligence technology, such as various neural networks obtained by artificial intelligence technology and not limited to convolutional neural network.
  • the terminal device determines the first information to be transmitted according to the core semantic information.
  • the core semantic information and the information source can also be transmitted (that is, on the terminal device side, in addition to the "information source” as the original information, the "core semantic information” as additional information can also be included. information", and obtain the first information to be transmitted accordingly).
  • the core semantic information is compared with the "source” of the original information.
  • the core semantic information is aimed at the semantics that the receiving end (or decoding end) expects to receive. Through the extraction of the core semantics, it can be extracted from the original information. By extracting the core semantic information, the transmission of unnecessary information at the receiving end (or decoding end) can be avoided, and only the core semantic information can be transmitted, thereby improving the efficiency of transmission.
  • the terminal device sends the first information.
  • the terminal device as the sending end may send the first information as the sending information to be transmitted to the receiving end
  • the receiving end may be a network device (such as a base station), or a terminal device as the receiving end, such as using a mobile phone, Users of portable computers or desktop computers such as tablet computers, in order to realize the communication transmission of human-computer interaction.
  • the terminal device performs core semantic acquisition processing on the information source to obtain core semantic information, including: inputting the information source into the trained third network model (the third network model can be deployed on the above core In the semantic acquisition unit), the core semantic information is obtained.
  • the core semantic information is used to describe the user's operational behavior (or called the user's non-decorative/non-descriptive behavior), such as behavior, action, instruction, data, command, etc., so as to obtain diversified core semantic information.
  • Fig. 5 is a schematic flowchart of a semantic communication transmission method 500 according to an embodiment of the present application.
  • the method can optionally be applied to the system shown in Fig. 1, but is not limited thereto.
  • the method includes at least some of the following:
  • the terminal device performs extended semantic acquisition processing on the information source to obtain extended semantic information.
  • the terminal device performs core semantic acquisition processing on the information source to obtain core semantic information.
  • the terminal device obtains combined semantic information according to the extended semantic information and the core semantic information.
  • the terminal device can also be called the sending end (or encoding end), and a combined semantic acquisition unit for realizing the extended semantics and the core semantics acquisition process can be added to the terminal device (that is, the combined semantics acquisition unit can both realize the extended semantic acquisition processing, and realize the core semantic acquisition processing), so that the information source can be input into the combined semantic acquisition unit, and the extended semantic information and the core semantic information can be obtained by outputting after the extended semantic and core semantic acquisition processing (The extended semantic information and the core semantic information constitute the combined semantic information).
  • the combined semantic acquisition unit can be realized by artificial intelligence technology, such as various neural networks obtained by artificial intelligence technology and not limited to convolutional neural network.
  • the terminal device determines the first information to be transmitted according to the combined semantic information.
  • the extended semantic information, the core semantic information and the information source may also include "the extended semantic information and the core semantic information" as additional information, and obtain the first information to be transmitted accordingly).
  • the extended semantic information is compared with the "source” of the original information.
  • the extended semantic information is aimed at the semantics that the sender (or encoding end) expects to send.
  • the extended semantic information can be extracted from , which can prevent the receiving end (or decoding end) from being unable to obtain complete information, thereby improving the accuracy and information integrity of transmission.
  • the core semantics is compared with the "source" of the original information.
  • the core semantics is the semantics that the receiving end (or decoding end) expects to receive as the target.
  • the terminal device sends the first information.
  • the terminal device as the sending end may send the first information as the sending information to be transmitted to the receiving end
  • the receiving end may be a network device (such as a base station), or a terminal device as the receiving end, such as using a mobile phone, Users of portable computers or desktop computers such as tablet computers, in order to realize the communication transmission of human-computer interaction.
  • Fig. 6 is a schematic flowchart of a semantic communication transmission method 600 according to an embodiment of the present application.
  • the method can optionally be applied to the system shown in Fig. 1, but is not limited thereto.
  • the method includes at least some of the following:
  • the terminal device receives second information.
  • the receiving end in addition to the terminal device as the receiving end (such as a user using a mobile phone, a portable computer such as a tablet computer, or a desktop computer to realize human-computer interaction communication transmission), the receiving end can also be a network device (such as a base station ), the second information may also be the first information in the above-mentioned embodiment, including two scenarios, the first scenario, the sending end and the receiving end all have semantic acquisition units, and the first information includes the source and the carried semantics Information, the receiving end is ready to directly restore the source and semantic information; in the second scenario, the sending end does not need to set up a semantic acquisition unit, only the receiving end has a semantic acquisition unit, and after the receiving end restores the information source, it performs semantic acquisition on the information source. to obtain semantic information.
  • the second information may be the same information as the first information in the above embodiment (for example, both the first information and the second information only include semantic information; or the first information and the second information not only Including semantic information, including information sources, etc.); the second information can also be different information from the first information in the above-mentioned embodiments (for example, the first information not only includes semantic information, but also information sources, and the second information (2) the information only includes the source, etc.), in other words, taking the receiving end as an example of a network device, although both the terminal device and the network device can perform semantic acquisition processing on the source to obtain semantic information, including but not limited to: terminal device and network
  • the devices are combined and used together to complete encoding and decoding processing, and terminal devices and network devices can also perform encoding and decoding processing for semantic acquisition processing.
  • the terminal device recovers the information source from the second information.
  • the terminal device recovers the information source from the second information, which may include at least one of the following:
  • the terminal device obtains the information source after decoding, demodulating and decrypting the second information.
  • the terminal device performs semantic acquisition processing on the information source to obtain semantic information.
  • the terminal device can also be called the receiving end (or decoding end), and a semantic acquisition unit for realizing the semantic acquisition process can be added to the terminal equipment, so that the information source can be input into the semantic acquisition unit, and through the semantic The semantic information is obtained as an output after the acquisition process.
  • the semantic acquisition unit can be realized by artificial intelligence technology, such as various neural networks obtained by artificial intelligence technology and not limited to convolutional neural network.
  • the terminal device after recovering the information source from the second information, the terminal device can perform semantic acquisition processing on the information source to obtain semantic information, thereby realizing the transmission of semantic communication.
  • Fig. 7 is a schematic flowchart of a semantic communication transmission method 700 according to an embodiment of the present application.
  • the method can optionally be applied to the system shown in Fig. 1, but is not limited thereto.
  • the method includes at least some of the following:
  • the terminal device receives the second information.
  • the receiving end in addition to the terminal device as the receiving end (such as a user using a mobile phone, a portable computer such as a tablet computer, or a desktop computer to realize human-computer interaction communication transmission), the receiving end can also be a network device (such as a base station ), the second information may also be the first information in the above-mentioned embodiment, including two scenarios, the first scenario, the sending end and the receiving end all have semantic acquisition units, and the first information includes the source and the carried semantics Information, the receiving end is ready to directly restore the source and semantic information; in the second scenario, the sending end does not need to set up a semantic acquisition unit, only the receiving end has a semantic acquisition unit, and after the receiving end recovers the information source, it performs semantic acquisition on the information source. to obtain semantic information.
  • the second information may be the same information as the first information in the above embodiment (for example, both the first information and the second information only include semantic information; or the first information and the second information not only Including semantic information, including information sources, etc.); the second information can also be different information from the first information in the above-mentioned embodiments (for example, the first information not only includes semantic information, but also information sources, and the second information (2) the information only includes the source, etc.), in other words, taking the receiving end as an example of a network device, although both the terminal device and the network device can perform semantic acquisition processing on the source to obtain semantic information, including but not limited to: terminal device and network
  • the devices are combined and used together to complete encoding and decoding processing, and terminal devices and network devices can also perform encoding and decoding processing for semantic acquisition processing.
  • the terminal device recovers the information source from the second information.
  • the terminal device recovers the information source from the second information, which may include at least one of the following:
  • the terminal device obtains the information source after decoding, demodulating and decrypting the second information.
  • the terminal device performs extended semantic acquisition processing on the information source to obtain extended semantic information.
  • the terminal device can also be called a receiving end (or decoding end), and an extended semantic acquisition unit for implementing the extended semantic acquisition process can be added to the terminal equipment, so that the information source can be input into the extended semantic acquisition unit, The extended semantic information is output after the extended semantic acquisition processing.
  • the extended semantic acquisition unit can be realized by artificial intelligence technology, such as various neural networks obtained by artificial intelligence technology and not limited to convolutional neural network.
  • the extended semantic information includes: at least one item of emotion information, emphasis information, association information, prediction information, and different task priority information.
  • the terminal device performs extended semantic acquisition processing on the information source to obtain extended semantic information, including at least one of the following:
  • Method 1 Input the information source into the trained fourth network model (the fourth network model can be deployed in the above-mentioned extended semantic acquisition unit) to obtain emotional information, emphasis information, association information, prediction information, and different task priority information. At least one item of , so as to obtain diversified extended semantic information.
  • Method 2 Input the information source into the trained fifth network model (the fifth network model can be deployed in the above-mentioned extended semantic acquisition unit), and obtain different emotional information classifications, different emphasized information classifications, different related information supplements, At least one of different prediction information supplements and different task priority information supplements, so as to obtain further information of diversified extended semantic information (such as information classification or information supplements, etc.).
  • it also includes: classifying and processing each item of information in the extended semantic information based on different classifications, using the corresponding identification information as the classification identification, and establishing a mapping relationship according to the classification identification and the corresponding classification description .
  • classification processing is performed on emotional information and emphasis information, and a mapping relationship is established to obtain a mapping table, wherein the mapping table for emotional information includes: the emotional classification described by the classification identifier and the classification description described by the corresponding classification.
  • the mapping table for the emphasis information includes: the importance category described by the category identifier, and the category description described by the corresponding category.
  • Fig. 8 is a schematic flowchart of a semantic communication transmission method 800 according to an embodiment of the present application.
  • the method can optionally be applied to the system shown in Fig. 1, but is not limited thereto.
  • the method includes at least some of the following:
  • the terminal device receives the second information.
  • the receiving end in addition to the terminal device as the receiving end (such as a user using a mobile phone, a portable computer such as a tablet computer, or a desktop computer to realize human-computer interaction communication transmission), the receiving end can also be a network device (such as a base station ), the second information may also be the first information in the above-mentioned embodiment, including two scenarios, the first scenario, the sending end and the receiving end all have semantic acquisition units, and the first information includes the source and the carried semantics Information, the receiving end is ready to directly restore the source and semantic information; in the second scenario, the sending end does not need to set up a semantic acquisition unit, only the receiving end has a semantic acquisition unit, and after the receiving end recovers the information source, it performs semantic acquisition on the information source. to obtain semantic information.
  • the second information may be the same information as the first information in the above embodiment (for example, both the first information and the second information only include semantic information; or the first information and the second information not only Including semantic information, including information sources, etc.); the second information can also be different information from the first information in the above-mentioned embodiments (for example, the first information not only includes semantic information, but also information sources, and the second information (2) the information only includes the source, etc.), in other words, taking the receiving end as an example of a network device, although both the terminal device and the network device can perform semantic acquisition processing on the source to obtain semantic information, including but not limited to: terminal device and network
  • the devices are combined and used together to complete encoding and decoding processing, and terminal devices and network devices can also perform encoding and decoding processing for semantic acquisition processing.
  • the terminal device recovers the information source from the second information.
  • the terminal device recovers the information source from the second information, which may include at least one of the following:
  • the terminal device obtains the information source after decoding, demodulating and decrypting the second information.
  • the terminal device performs core semantic acquisition processing on the information source to obtain core semantic information.
  • the terminal device can also be called a receiving end (or decoding end), and a core semantics acquisition unit for implementing the core semantics acquisition process can be added to the terminal device, so that the information source can be input into the core semantics acquisition unit,
  • the core semantic information is output after the core semantic acquisition processing.
  • the core semantic acquisition unit can be realized by artificial intelligence technology, such as various neural networks obtained by artificial intelligence technology and not limited to convolutional neural network.
  • the core semantic information is used to describe the user's operational behavior (or called the user's non-decorative/non-descriptive behavior), such as behavior, action, instruction, data, command, etc., so as to obtain a variety of core semantic information.
  • the terminal device performs core semantic acquisition processing on the information source to obtain core semantic information, including:
  • Fig. 9 is a schematic flowchart of a semantic communication transmission method 900 according to an embodiment of the present application.
  • the method can optionally be applied to the system shown in Fig. 1, but is not limited thereto.
  • the method includes at least some of the following:
  • the terminal device receives the second information.
  • the receiving end in addition to the terminal device as the receiving end (such as a user using a mobile phone, a portable computer such as a tablet computer, or a desktop computer to realize human-computer interaction communication transmission), the receiving end can also be a network device (such as a base station ), the second information may also be the first information in the above-mentioned embodiment, including two scenarios, the first scenario, the sending end and the receiving end all have semantic acquisition units, and the first information includes the source and the carried semantics Information, the receiving end is ready to directly restore the source and semantic information; in the second scenario, the sending end does not need to set up a semantic acquisition unit, only the receiving end has a semantic acquisition unit, and after the receiving end recovers the information source, it performs semantic acquisition on the information source. to obtain semantic information.
  • the second information may be the same information as the first information in the above embodiment (for example, both the first information and the second information only include semantic information; or the first information and the second information not only Including semantic information, including information sources, etc.); the second information can also be different information from the first information in the above-mentioned embodiments (for example, the first information not only includes semantic information, but also information sources, and the second information (2) the information only includes the source, etc.), in other words, taking the receiving end as an example of a network device, although both the terminal device and the network device can perform semantic acquisition processing on the source to obtain semantic information, including but not limited to: terminal device and network
  • the devices are combined and used together to complete encoding and decoding processing, and terminal devices and network devices can also perform encoding and decoding processing for semantic acquisition processing.
  • the terminal device recovers the information source from the second information.
  • the terminal device recovers the information source from the second information, which may include at least one of the following:
  • the terminal device obtains the information source after decoding, demodulating and decrypting the second information.
  • the terminal device performs extended semantic acquisition processing on the information source to obtain extended semantic information.
  • the terminal device performs core semantic acquisition processing on the information source to obtain core semantic information.
  • the terminal device obtains combined semantic information according to the extended semantic information and the core semantic information.
  • the terminal device can also be referred to as a receiving end (or decoding end), and a combined semantic acquisition unit for realizing the extended semantics and the core semantics acquisition process can be added to the terminal device (the combined semantics acquisition unit can realize both extended Semantic acquisition processing, and core semantic acquisition processing can be realized), so that the information source can be input into the combined semantic acquisition unit, and the extended semantic information and the core semantic information (the core semantic information (the The extended semantic information and the core semantic information constitute the combined semantic information).
  • the combined semantic acquisition unit can be realized by artificial intelligence technology, such as various neural networks obtained by artificial intelligence technology and not limited to convolutional neural network.
  • the extended semantic information includes: at least one item of emotion information, emphasis information, association information, prediction information, and different task priority information.
  • the core semantic information is used to describe the user's operational behavior (or called the user's non-decorative/non-descriptive behavior), such as behavior, action, instruction, data, command, etc., so as to obtain a variety of core semantic information.
  • Fig. 10 is a schematic flow chart of a semantic communication transmission method according to an embodiment of the present application. The method may optionally be applied to the system shown in Fig. 1 , but is not limited thereto. The method includes at least some of the following:
  • the network device receives first information.
  • the network device restores semantic information from the first information, and the semantic information is: information obtained by the terminal device side by performing semantic acquisition processing on the information source.
  • the network device obtains the semantic information after decoding and demodulating the first information; or, the network device obtains the semantic information after decoding, demodulating and decrypting the first information.
  • the semantic information includes: at least one item of extended semantic information and core semantic information.
  • the extended semantic information includes: at least one item of emotion information, emphasis information, association information, prediction information, and task priority information.
  • the extended semantic information further includes: at least one of emotional information classification, emphasis information classification, associated information supplement, prediction information supplement, and task priority information supplement.
  • the core semantic information includes: at least one of behavior, action, instruction, data, and command.
  • the semantic information acquisition process is performed on the terminal device side, that is, the terminal device can perform semantic acquisition processing on the information source to obtain semantic information, and after obtaining the first information to be transmitted according to the semantic information, the terminal device
  • the sender sends the first information to the receiver
  • the receiver is a network device, it receives the first information and restores semantic information from the first information, so that semantics can be realized between the terminal device and the network device
  • the transmission of communication can meet the constantly updated communication needs, that is, it can not only realize the transmission of "information source” as the original information, but also realize the transmission of "semantic information" as additional information besides the original information.
  • Fig. 11 is a schematic flowchart of a semantic communication transmission method according to an embodiment of the present application. The method may optionally be applied to the system shown in Fig. 1 , but is not limited thereto. The method includes at least some of the following:
  • the network device determines the second information to be transmitted according to the information source; the information source includes semantic information to be executed for semantic acquisition processing;
  • the network device determines the second information after encoding and modulating the information source; or, the network device determines the second information after encoding, modulating and encrypting the information source.
  • the network device sends the second information.
  • the semantic information includes: at least one item of extended semantic information and core semantic information.
  • the extended semantic information includes: at least one item of emotion information, emphasis information, association information, prediction information, and task priority information.
  • the extended semantic information includes: at least one of emotional information classification, emphasis information classification, associated information supplement, prediction information supplement, and task priority information supplement.
  • the core semantic information includes: at least one of behavior, action, instruction, data, and command.
  • the network device as the sending end, can determine the second information to be transmitted according to the information source, the information source includes the semantic information to be executed for semantic acquisition processing, and send the second information to the terminal device, on the terminal device side Perform semantic information acquisition processing, that is: after the terminal device as the receiving end recovers the information source from the received second information, it can perform semantic acquisition processing on the information source to obtain semantic information, so that the communication between the terminal device and the network device
  • the transmission of semantic communication can be realized between them, which can meet the constantly updated communication needs, that is, not only the transmission of the "information source” as the original information can be realized, but also the transmission of "semantic information" as additional information besides the original information can be realized.
  • Fig. 12 is a schematic codec diagram of an example of a semantic communication transmission method according to an embodiment of the present application.
  • the basic work flow in a wireless communication system includes: the sender performs a process on the information source at the sending end Coding, modulation, encryption and other operations form the transmission information to be transmitted.
  • the sent information is transmitted to the receiving end through the wireless space, and the receiving end performs operations such as decoding, decryption and demodulation on the received received information, and finally recovers the information source, realizing lossless transmission as the "information source" of the original information to the greatest extent.
  • Fig. 13 is a schematic neural network diagram of an example of a semantic communication transmission method according to an embodiment of the present application.
  • the basic neural network structure includes: an input layer, a hidden layer and an output layer. After the input layer receives data, it processes the received data through the hidden layer, and the final data processing result is generated in the output layer.
  • each node in the neural network represents a processing unit, which can be regarded as simulating a neuron, and multiple neurons form a layer of neural network, and multi-layer information transmission and processing construct a whole neural network.
  • FIG. 14 is a schematic diagram of the relationship between information according to an example of a semantic communication transmission method according to an embodiment of the present application.
  • the original information can be the above-mentioned information source, and can be transmitted based on the wireless communication system architecture shown in Figure 12.
  • the core semantic information and extended semantic information need to be improved after the wireless communication system architecture is perfected. Additional information transmitted.
  • the design goal of the current wireless communication system is to transmit the original information from the sending end to the receiving end losslessly.
  • the wireless communication system architecture needs to be updated to meet the lossless transmission requirements of more information (such as core semantic information and extended semantic information).
  • the neural network shown in Figure 13 is just a basic architecture. With the continuous development of neural network research, more neural network deep learning algorithms and more hidden layers are introduced, which can be trained layer by layer through the multi-hidden layer neural network. Carry out feature learning, thereby greatly improving the learning and processing capabilities of the neural network.
  • the software/hardware of the neural network deployed in various application scenarios naturally language processing, semantic analysis and understanding, pattern recognition, signal processing, optimization combination, anomaly detection, etc.
  • the processing speed and precision of software/hardware can be improved, and the neural network can be applied to at least two types of situations as follows, so as to realize the lossless transmission requirements of semantic information such as core semantic information and extended semantic information.
  • the first type of scenario obtaining and transmitting extended semantic information from original information
  • the contextual information, communication environment, emotion expressed, and emphasis of the same communication content will vary with different statement environments and methods. Different expression effects, different emphasis effects, and different emotional effects. In such cases, the simple transmission of original information cannot carry complete communication information. Even if the receiving end receives the original information without loss, the receiving end cannot accurately confirm the specific context information, communication environment, and expressed emotions. The amount of additional information brought by these, and the emphasis on emphasizing.
  • the receiving end is different from humans in cognition: if both parties to the interaction are humans, because humans have a certain ability to understand emotions compared to machines, even if humans have different degrees of emotional understanding, this
  • the problem can also be relatively weakened, similar to the different communication effects brought about by people-to-people face-to-face communication, voice communication, and text communication for the same communication content in the physical world, but machines lack the ability to understand emotions. Therefore, in the interaction between machines, in addition to meeting the lossless transmission of original information, it is also necessary to update the wireless communication system architecture to meet the lossless transmission of more information.
  • this type of additional information is collectively called extended semantic information, in human-human interaction, human-computer interaction, machine-computer interaction, especially in human-computer interaction
  • extended semantic information in human-human interaction, human-computer interaction, machine-computer interaction, especially in human-computer interaction
  • the second type of scenario extracting and transmitting core semantic information from original information
  • the original information often contains the core information to be expressed and the core information used to modify the core information.
  • the book is the core information expressed, and the description about the book is not the core information of this part of the content. There are a large number of such descriptions in human-to-human interaction, and if the purpose of communication transmission is only to transmit the core information in the original information, then only the core information can be transmitted.
  • this kind of additional information is collectively referred to as core semantic information, in human-human interaction, human-computer interaction, machine-computer interaction, especially in the scene of human-computer interaction, when the interactive
  • core semantic information in human-human interaction, human-computer interaction, machine-computer interaction, especially in the scene of human-computer interaction, when the interactive
  • the first type of scenario needs to obtain additional extended semantic information based on the original information
  • the second type of scenario it is necessary to obtain the refined core semantic information based on the original information.
  • the above process involves The relevant encoding, decoding, and transmission of extended semantic information and core semantic information, as well as the updated design of the entire system are described in detail below.
  • Fig. 15 is a schematic codec schematic diagram of an example of a semantic communication transmission method according to an embodiment of the present application.
  • the workflow of a wireless communication system that mainly implements semantic communication transmission based on the coding end, compared to The workflow shown in Figure 12 requires additionally the introduction of the semantic acquisition unit.
  • it can be specifically extended semantic acquisition unit (for extended semantic acquisition of information), core semantic acquisition unit (for acquisition of core semantic information), combined semantic acquisition unit (for acquisition of extended semantics and core semantic information), so as to realize the function of acquiring semantic information from original information (information source) .
  • Fig. 16 is a schematic diagram of an example of a semantic communication transmission method according to an embodiment of the present application, showing a schematic diagram of extended semantic acquisition.
  • the semantic acquisition unit when the semantic acquisition unit is used to acquire extended semantic information, the semantic acquisition unit may be The extended semantic acquisition unit, whose output information includes the extended semantic information expressed by the original information, the extended semantic information includes multiple types of semantic information, such as emotional information, emphasis information, associated information, prediction information, different task priority information and other extended semantic information one or more of the.
  • For emotional information there can be classifications of emotional information in advance, and different emotional classifications correspond to different labels. As shown in Table 1, the extended semantic information can be represented and transmitted for the classification and identification information of different emotions.
  • emotion classification Category description 1 1st emotion, e.g. joy 2 2nd emotion, e.g. anger 3 3rd emotion, e.g. mourning 4 4th emotion, such as: joy
  • the original information can also be classified, and different categories correspond to different importance marks or weights, or directly output the local original information that needs to be emphasized, as shown in Table 2 and Table 3.
  • Importance classification Category description 1 Emphasis Section 1, eg: Emphasize Characters 2 2nd Emphasis Section, eg: Emphasis Vehicles 3 3rd Emphasis Section, eg: Emphasis Environment 4 4th Emphasis Section, eg: Emphasis Position 5 Section 5 Emphasis, eg: Emphasis text 6 Section 6 Emphasis, eg: Emphasis on Speech 7 Section 7 Emphasis, eg: Emphasis on pictures
  • Fig. 17 is a schematic diagram of an example of a semantic communication transmission method according to an embodiment of the present application, showing a schematic diagram of extended semantic transmission.
  • the UE side performs semantic information acquisition processing on the original information, and after obtaining the extended semantic information, The extended semantic information is transmitted to the base station. Among them, the extended semantic information is compared with the original information. The extended semantic information is obtained from the original information based on the semantics that the sender expects to send. By extracting this part of the extended semantics, it can be avoided that the receiving end cannot obtain complete information. The information that the sender wants to convey, so as to improve the accuracy of transmission.
  • the realization of the above-mentioned semantic acquisition unit can be realized by using a neural network.
  • the input of the neural network is the original information
  • the output is different emotional information or classification, different emphasis on content information or classification, supplement of unrelated information, supplement of different prediction information
  • One or more of the extended semantic information such as the supplement of different task priorities, etc.
  • the structure of the neural network can be a fully connected structure, a convolutional structure, a recurrent neural network (Recurrent Neural Network, RNN) structure, a long short-term memory network ( One or more of the Long-Short Term Memory (LSTM) structure, the self-attention mechanism (self-attention) structure, and the transformer (transformer) structure composed of self-attention and feedforward neural networks.
  • LSTM Long-Short Term Memory
  • self-attention self-attention
  • transformer transformer
  • Fig. 18 is a schematic diagram of core semantic acquisition according to an example of a transmission method of semantic communication according to an embodiment of the present application.
  • the semantic acquisition unit when the semantic acquisition unit is used to acquire core semantic information, the semantic acquisition unit may be The core semantic acquisition unit, whose output information includes the core semantic information expressed by the original information. Comparing the core semantic information with the original information, the core semantic information is based on the semantics that the receiving end expects to receive, and is obtained from the original information. By extracting this part of the core semantics, the transmission of unnecessary information at the receiving end can be avoided , so as to improve the transmission efficiency.
  • FIG. 19 is a schematic schematic diagram of core semantic transmission according to an example of a semantic communication transmission method according to an embodiment of the present application.
  • the UE side performs semantic information acquisition processing on the original information, and after obtaining the core semantic information, The core semantic information is transmitted to the base station.
  • the above-mentioned semantic acquisition unit can be realized by using a neural network, for example, the input of the neural network is original information, and the output is core semantic information.
  • the structure of the neural network can be one or more of the fully connected structure, the convolutional structure, the RNN structure, the LSTM structure, the self-attention structure, and the transformer structure composed of self-attention and feedforward neural networks.
  • Fig. 20 is a schematic diagram of combined semantic transmission according to an example of a semantic communication transmission method according to an embodiment of the present application.
  • the semantic acquisition unit can also be used to acquire extended semantics and core semantics. It belongs to the collection of the above two cases.
  • the original information is acquired and processed with extended semantics and core information.
  • the extended semantics and core semantic information are jointly transmitted to the base station. repeat.
  • Semantic communication transmission on the receiving end (or decoding end) side in the semantic communication system dominated by the decoding end, involves three situations: extended semantic communication, core semantic communication, and extended semantic joint core semantic communication.
  • Fig. 21 is a schematic codec schematic diagram of an example of a semantic communication transmission method according to an embodiment of the present application.
  • the workflow of a wireless communication system that mainly implements semantic communication transmission based on the decoding end, compared to The workflow shown in Figure 12 requires additionally the introduction of the semantic acquisition unit.
  • it can be specifically extended semantic acquisition unit (for extended semantic acquisition of information), core semantic acquisition unit (for acquisition of core semantic information), combined semantic acquisition unit (for acquisition of extended semantics and core semantic information), so as to realize the function of acquiring semantic information from original information (information source) .
  • FIG. 22-24 are schematic diagrams of extended semantic transmission, core semantic transmission, and extended semantic joint core semantic transmission according to an example of a semantic communication transmission method according to an embodiment of the present application.
  • UE The original information is received from the base station, and semantic information is acquired on the original information at the UE side to obtain extended semantic information.
  • the UE receives original information from the base station, and performs core information acquisition processing on the original information at the UE side to obtain core semantic information.
  • the UE receives the original information from the base station, and acquires the extended semantics and core information on the original information at the UE side to obtain the extended semantics and core semantics information.
  • the above-mentioned semantic acquisition unit can be realized by using a neural network, for example, the input of the neural network is original information, and the output is core semantic information.
  • the structure of the neural network can be one or more of the fully connected structure, the convolutional structure, the RNN structure, the LSTM structure, the self-attention structure, and the transformer structure composed of self-attention and feedforward neural networks.
  • the above semantic acquisition unit needs to be deployed at the receiving end, which can obtain the original information expected
  • the extended semantic information expressed such as one or more of the extended semantic information such as emotional information, emphasis information, association information, prediction information, and different task priority information, that is, the input is received by the receiving end (UE) from the base station Original information, the output is the emotional information (or emotional classification), emphasized information (or importance classification), associated information (or classification, such as original information associated with specific additional information other than original information, which can be Historical transmission information, public information that does not need to be transmitted, etc.), forecast information (or classification, such as future time information that can be predicted based on the current original information content, or decision information).
  • Fig. 25 is a schematic block diagram of a terminal device 2500 according to an embodiment of the present application.
  • the terminal device 2500 may include: a first semantic acquisition unit 2510, configured to perform semantic acquisition processing on information sources to obtain semantic information; a first processing unit 2520, configured to determine first information to be transmitted according to the semantic information; The first sending unit 2530 is configured to send the first information.
  • the first processing unit is configured to obtain the first information to be transmitted in a manner including at least one of the following:
  • the first information After encoding and modulating the semantic information, the first information is obtained;
  • the first information After coding, modulating and encrypting the semantic information, the first information is obtained.
  • the first semantic acquisition unit is configured to perform an acquisition process of extended semantics on the information source to obtain extended semantic information.
  • the first semantic acquisition unit is configured to perform core semantic acquisition processing on the information source to obtain core semantic information.
  • the first semantic acquisition unit is configured to acquire extended semantic information on the information source to obtain extended semantic information; perform core semantic acquisition processing on the information source to obtain core semantic information.
  • Semantic information obtain combined semantic information according to the extended semantic information and the core semantic information.
  • the first semantic acquisition unit is configured to obtain the extended semantic information in at least one of the following manners:
  • the extended semantic information includes: at least one item of emotion information, emphasis information, association information, prediction information, and different task priority information.
  • it further includes: classifying each item of information in the extended semantic information based on different classifications, and using the corresponding identification information as the classification identification; according to the classification identification and the corresponding classification Describes the establishment of a mapping relationship.
  • the first semantic acquisition unit is configured to input the information source into a trained third network model to obtain the core semantic information.
  • the terminal device 2500 in the embodiment of the present application can implement the corresponding functions of the terminal device in the foregoing method embodiments.
  • each module (submodule, unit or component, etc.) in the terminal device 2500 refers to the corresponding description in the above method embodiments, and details are not repeated here.
  • the functions described by the modules (submodules, units or components, etc.) in the terminal device 2500 of the embodiment of the application can be realized by different modules (submodules, units or components, etc.), or by the same Module (submodule, unit or component, etc.) implementation.
  • Fig. 26 is a schematic block diagram of a terminal device 2600 according to an embodiment of the present application.
  • the terminal device 2600 may include: a first receiving unit 2610, configured to receive second information; a second processing unit 2620, configured to recover information sources from the second information; a second semantic acquisition unit 2630, configured to The information source performs semantic acquisition processing to obtain semantic information.
  • the second processing unit is configured to recover the information source using at least one of the following methods:
  • the information source After decoding and demodulating the second information, the information source is obtained;
  • the information source After decoding, demodulating and decrypting the second information, the information source is obtained.
  • the second semantic acquisition unit is configured to perform an acquisition process of extended semantics on the information source to obtain extended semantic information.
  • the second semantic acquisition unit is configured to perform core semantic acquisition processing on the information source to obtain core semantic information.
  • the second semantic acquisition unit is configured to acquire extended semantic information on the information source to obtain extended semantic information; perform core semantic acquisition processing on the information source to obtain core semantic information.
  • Semantic information obtain combined semantic information according to the extended semantic information and the core semantic information.
  • the second semantic acquisition unit is configured to obtain the extended semantic information in at least one of the following manners:
  • the extended semantic information includes: at least one item of emotion information, emphasis information, association information, prediction information, and different task priority information.
  • it further includes a third processing unit, configured to classify each item of information in the extended semantic information based on different classifications, and use the corresponding identification information as a classification identifier; according to the The classification identifier and the corresponding classification description establish a mapping relationship.
  • the second semantics acquisition unit is configured to input the information source into a trained sixth network model to obtain the core semantics.
  • the terminal device 2600 in the embodiment of the present application can implement the corresponding functions of the terminal device in the foregoing method embodiments.
  • each module (submodule, unit or component, etc.) in the terminal device 2600 refers to the corresponding description in the above method embodiment, and details are not repeated here.
  • the functions described by the modules (submodules, units or components, etc.) in the terminal device 2600 of the embodiment of the application can be realized by different modules (submodules, units or components, etc.), or by the same Module (submodule, unit or component, etc.) implementation.
  • Fig. 27 is a schematic block diagram of a network device according to an embodiment of the present application.
  • the network device 2700 may include: a second receiving unit 2710, configured to receive the first information; a third processing unit 2720, configured to recover semantic information from the first information; wherein, the semantic information is: a terminal device On the side, the information obtained by semantic acquisition processing of the information source.
  • the third processing unit is configured to restore the semantic information from the first information in at least one of the following manners:
  • the semantic information After decoding, demodulating and decrypting the first information, the semantic information is obtained.
  • the semantic information includes: at least one item of extended semantic information and core semantic information.
  • the extended semantic information includes: at least one item of emotion information, emphasis information, association information, prediction information, and task priority information.
  • the extended semantic information includes: at least one of: emotional information classification, emphasis information classification, associated information supplement, prediction information supplement, and task priority information supplement.
  • the core semantic information includes: at least one of behavior, action, instruction, data, and command.
  • the network device 2700 in the embodiment of the present application can implement the corresponding functions of the terminal device in the foregoing method embodiments.
  • each module (submodule, unit or component, etc.) in the network device 2700 refers to the corresponding description in the above method embodiments, and details are not repeated here.
  • the functions described by the various modules (submodules, units or components, etc.) in the network device 2700 of the embodiment of the application can be realized by different modules (submodules, units or components, etc.), or can be implemented by the same Module (submodule, unit or component, etc.) implementation.
  • Fig. 28 is a schematic block diagram of a network device according to an embodiment of the present application.
  • the network device 2800 includes: a fourth processing unit 2810, configured to determine the second information to be transmitted according to the information source; wherein, the information source includes semantic information to be executed for semantic acquisition processing; a second sending unit 2820, configured to send the second information.
  • the fourth processing unit is configured to determine the second information to be transmitted in at least one of the following manners:
  • the second information is obtained.
  • the semantic information includes: at least one item of extended semantic information and core semantic information.
  • the extended semantic information includes: at least one item of emotion information, emphasis information, association information, prediction information, and task priority information.
  • the extended semantic information includes: at least one of: emotional information classification, emphasis information classification, associated information supplement, prediction information supplement, and task priority information supplement.
  • the core semantic information includes: at least one of behavior, action, instruction, data, and command.
  • the network device 2800 in the embodiment of the present application can implement the corresponding functions of the terminal device in the foregoing method embodiments.
  • each module (submodule, unit or component, etc.) in the network device 2800 refers to the corresponding description in the above method embodiment, and details are not repeated here.
  • the functions described by the modules (submodules, units or components, etc.) in the network device 2800 of the embodiment of the application can be realized by different modules (submodules, units or components, etc.), or by the same Module (submodule, unit or component, etc.) implementation.
  • Fig. 29 is a schematic structural diagram of a communication device 2900 according to an embodiment of the present application.
  • the communication device 2900 includes a processor 2910, and the processor 2910 can invoke and run a computer program from a memory, so that the communication device 2900 implements the method in the embodiment of the present application.
  • the communication device 2900 may further include a memory 2920 .
  • the processor 2910 may call and run a computer program from the memory 2920, so that the communication device 2900 implements the method in the embodiment of the present application.
  • the memory 2920 may be an independent device independent of the processor 2910 , or may be integrated in the processor 2910 .
  • the communication device 2900 may further include a transceiver 2930, and the processor 2910 may control the transceiver 2930 to communicate with other devices, specifically, to send information or data to other devices, or to receive information or data sent by other devices .
  • the transceiver 2930 may include a transmitter and a receiver.
  • the transceiver 2930 may further include antennas, and the number of antennas may be one or more.
  • the communication device 2900 may be the terminal device as the sender in the embodiment of the present application, and the communication device 2900 may implement the corresponding processes implemented by the terminal device in the methods of the embodiment of the present application.
  • the Let me repeat for the sake of brevity, the Let me repeat.
  • the communication device 2900 may be the terminal device serving as the receiving end in the embodiment of the present application, and the communication device 2900 may implement the corresponding processes implemented by the terminal device in each method of the embodiment of the present application.
  • the Let me repeat for the sake of brevity, the Let me repeat.
  • FIG. 30 is a schematic structural diagram of a chip 3000 according to an embodiment of the present application.
  • the chip 3000 includes a processor 3010, and the processor 3010 can call and run a computer program from a memory, so as to implement the method in the embodiment of the present application.
  • the chip 3000 may also include a memory 3026 .
  • the processor 3010 may invoke and run a computer program from the memory 3026, so as to implement the method performed by the terminal device or the terminal device in the embodiment of the present application.
  • the memory 3026 may be an independent device independent of the processor 3010 , or may be integrated in the processor 3010 .
  • the chip 3000 may also include an input interface 3030 .
  • the processor 3010 can control the input interface 3030 to communicate with other devices or chips, specifically, can obtain information or data sent by other devices or chips.
  • the chip 3000 may also include an output interface 3040 .
  • the processor 3010 can control the output interface 3040 to communicate with other devices or chips, specifically, can output information or data to other devices or chips.
  • the chip can be applied to the terminal device as the sending end in the embodiment of the present application, and the chip can implement the corresponding processes implemented by the terminal device in the various methods of the embodiment of the present application. For the sake of brevity, details are not repeated here.
  • the chip can be applied to the terminal device serving as the receiving end in the embodiment of the present application, and the chip can implement the corresponding processes implemented by the terminal device in the methods of the embodiment of the present application.
  • the chip can implement the corresponding processes implemented by the terminal device in the methods of the embodiment of the present application.
  • the chips applied to the terminal device as the sending end and the terminal device as the receiving end may be the same chip or different chips.
  • the chip mentioned in the embodiment of the present application may also be called a system-on-chip, a system-on-chip, a system-on-a-chip, or a system-on-a-chip.
  • the processor mentioned above can be a general-purpose processor, a digital signal processor (DSP), an off-the-shelf programmable gate array (FPGA), an application specific integrated circuit (ASIC) or Other programmable logic devices, transistor logic devices, discrete hardware components, etc.
  • DSP digital signal processor
  • FPGA off-the-shelf programmable gate array
  • ASIC application specific integrated circuit
  • the general-purpose processor mentioned above may be a microprocessor or any conventional processor or the like.
  • the aforementioned memories may be volatile memories or nonvolatile memories, or may include both volatile and nonvolatile memories.
  • the non-volatile memory can be read-only memory (read-only memory, ROM), programmable read-only memory (programmable ROM, PROM), erasable programmable read-only memory (erasable PROM, EPROM), electrically programmable Erases programmable read-only memory (electrically EPROM, EEPROM) or flash memory.
  • the volatile memory may be random access memory (RAM).
  • the memory in the embodiment of the present application may also be a static random access memory (static RAM, SRAM), a dynamic random access memory (dynamic RAM, DRAM), Synchronous dynamic random access memory (synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (double data rate SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (enhanced SDRAM, ESDRAM), synchronous connection Dynamic random access memory (synch link DRAM, SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DR RAM), etc. That is, the memory in the embodiments of the present application is intended to include, but not be limited to, these and any other suitable types of memory.
  • Fig. 31 is a schematic block diagram of a communication system 3100 according to an embodiment of the present application.
  • the communication system 3100 includes a terminal device 3110 as a sending end and a network device 3120 as a receiving end, and the receiving end may also be another terminal device, which will not be described in detail.
  • the 3110 as the sending end may include: a first semantic acquisition unit, configured to perform semantic acquisition processing on the source to obtain semantic information; a first processing unit, configured to obtain the first information to be transmitted according to the semantic information ; A first sending unit, configured to send the first information.
  • the network device 3120 serving as the receiving end may include: a second receiving unit, configured to receive the first information; a third processing unit, configured to recover semantic information from the first information; wherein, the semantic information is: a terminal Information obtained by the device side through semantic acquisition processing of information sources.
  • the 3110 as the sending end can be used to realize the corresponding coding-based semantic communication function realized by the terminal device in the above method
  • the network device 3120 as the receiving end can be used to realize the semantic communication function realized by the network device in the above method Corresponding decoding-based semantic communication functions. For the sake of brevity, details are not repeated here.
  • all or part of them may be implemented by software, hardware, firmware or any combination thereof.
  • software When implemented using software, it may be implemented in whole or in part in the form of a computer program product.
  • the computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the processes or functions according to the embodiments of the present application will be generated in whole or in part.
  • the computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable device.
  • the computer instructions may be stored in or transmitted from one computer-readable storage medium to another computer-readable storage medium, e.g.
  • the computer-readable storage medium may be any available medium that can be accessed by a computer, or a data storage device such as a server or a data center integrated with one or more available media.
  • the available medium may be a magnetic medium (such as a floppy disk, a hard disk, or a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (Solid State Disk, SSD)), etc.
  • sequence numbers of the above-mentioned processes do not mean the order of execution, and the execution order of the processes should be determined by their functions and internal logic, and should not be used in the embodiments of the present application.
  • the implementation process constitutes any limitation.

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Abstract

本申请涉及一种语义通信的传输方法和终端设备，其中，所述方法包括：所述终端设备对信源进行语义获取处理，得到语义信息；所述终端设备根据所述语义信息，确定待传输的第一信息；所述终端设备发送所述第一信息，采用本申请，实现了语义通信的传输。

Description

语义通信的传输方法、终端设备 技术领域
本申请涉及通信领域，更具体地，涉及一种语义通信的传输方法、终端设备。
背景技术
通信传输的目标是：实现原始信息的无损传输。然而，只做原始信息的无损传输只是基本需求，并不是通信传输的全部需求，更多信息的传输才能满足不断更新的通信需求。
发明内容
本申请实施例提供一种语义通信的传输方法、终端设备，可以实现语义通信的传输，能满足不断更新的通信需求。
本申请实施例提供一种语义通信的传输方法，应用于终端设备，包括：
所述终端设备对信源进行语义获取处理，得到语义信息；
所述终端设备根据所述语义信息，得到待传输的第一信息；
所述终端设备发送所述第一信息。
本申请实施例提供一种语义通信的传输方法，应用于终端设备，包括：
所述终端设备接收第二信息；
所述终端设备从所述第二信息中恢复出信源；
所述终端设备对所述信源进行语义获取处理，得到语义信息。
本申请实施例提供一种语义通信的传输方法，应用于网络设备，包括：
所述网络设备接收第一信息；
所述网络设备从所述第一信息中恢复出语义信息；
其中，所述语义信息为：终端设备侧通过对信源进行语义获取处理所得到的信息。
本申请实施例提供一种语义通信的传输方法，应用于网络设备，包括：
所述网络设备根据信源确定待传输的第二信息；其中，所述信源包括待执行语义获取处理的语义信息；
所述网络设备发送所述第二信息。
本申请实施例提供一种终端设备，包括：
第一语义获取单元，用于对信源进行语义获取处理，得到语义信息；
第一处理单元，用于根据所述语义信息，得到待传输的第一信息；
第一发送单元，用于发送所述第一信息。
本申请实施例提供一种终端设备，包括：
第一接收单元，用于接收第二信息；
第二处理单元，用于从所述第二信息中恢复出信源；
第二语义获取单元，用于对所述信源进行语义获取处理，得到语义信息。
本申请实施例提供一种网络设备，所述网络设备包括：
第二接收单元，用于接收第一信息；
第三处理单元，用于从所述第一信息中恢复出语义信息；
其中，所述语义信息为：终端设备侧通过对信源进行语义获取处理所得到的信息。
本申请实施例提供一种网络设备，所述网络设备包括：
第四处理单元，用于根据信源确定待传输的第二信息；其中，所述信源包括待执行语义获取处理的语义信息；
第二发送单元，用于发送所述第二信息。
本申请实施例提供一种终端设备，包括处理器和存储器。该存储器用于存储计算机程序，该处理器用于调用并运行该存储器中存储的计算机程序，以使该终端设备执行上述本申请实施例所述的方法。
本申请实施例提供一种网络设备，包括处理器和存储器。该存储器用于存储计算机程序，该处理器用于调用并运行该存储器中存储的计算机程序，以使该网络设备执行上述本申请实施例所述的方法。
本申请实施例提供一种芯片，用于实现上述本申请实施例所述的方法。
具体地，该芯片包括：处理器，用于从存储器中调用并运行计算机程序，使得安装有该芯片的设备执行上述本申请实施例所述的方法。
本申请实施例提供一种计算机可读存储介质，用于存储计算机程序，当该计算机程序被设备运行时使得该设备执行上述本申请实施例所述的方法。
本申请实施例提供一种计算机程序产品，包括计算机程序指令，该计算机程序指令使得计算机执行上述的本申请实施例所述的方法。
本申请实施例提供一种计算机程序，当其在计算机上运行时，使得计算机执行上述的本申请实施例所述的方法。
本申请实施例，终端设备可以对信源进行语义获取处理，得到语义信息，终端设备可以根据该语义信息确定待传输的第一信息，终端设备作为发送端，可以发送该第一信息给接收端，从而可以实现语义通信的传输，能满足不断更新的通信需求。
附图说明
图1是根据本申请实施例的一应用场景的示意图。
图2是根据本申请一实施例的语义通信的传输方法的示意性流程图。
图3是根据本申请一实施例的语义通信的传输方法的示意性流程图。
图4是根据本申请一实施例的语义通信的传输方法的示意性流程图。
图5是根据本申请一实施例的语义通信的传输方法的示意性流程图。
图6是根据本申请一实施例的语义通信的传输方法的示意性流程图。
图7是根据本申请一实施例的语义通信的传输方法的示意性流程图。
图8是根据本申请一实施例的语义通信的传输方法的示意性流程图。
图9是根据本申请一实施例的语义通信的传输方法的示意性流程图。
图10是根据本申请一实施例的语义通信的传输方法的示意性流程图。
图11是根据本申请一实施例的语义通信的传输方法的示意性流程图。
图12是根据本申请一实施例的语义通信的传输方法一示例的示意性编解码示意图。
图13是根据本申请一实施例的语义通信的传输方法一示例的示意性神经网络示意图。
图14是根据本申请一实施例的语义通信的传输方法一示例的示意性信息间关系示意图。
图15是根据本申请一实施例的语义通信的传输方法一示例的示意性编解码示意图。
图16是根据本申请一实施例的语义通信的传输方法一示例的示意性扩展语义获取示意图。
图17是根据本申请一实施例的语义通信的传输方法一示例的示意性扩展语义传输示意图。
图18是根据本申请一实施例的语义通信的传输方法一示例的示意性核心语义获取示意图。
图19是根据本申请一实施例的语义通信的传输方法一示例的示意性核心语义传输示意图。
图20是根据本申请一实施例的语义通信的传输方法一示例的示意性组合语义传输示意图。
图21是根据本申请一实施例的语义通信的传输方法一示例的示意性编解码示意图。
图22是根据本申请一实施例的语义通信的传输方法一示例的示意性扩展语义传输示意图。
图23是根据本申请一实施例的语义通信的传输方法一示例的示意性核心语义传输示意图。
图24是根据本申请一实施例的语义通信的传输方法一示例的示意性组合语义传输示意图。
图25是根据本申请一实施例的终端设备的示意性框图。
图26是根据本申请一实施例的终端设备的示意性框图。
图27是根据本申请一实施例的网络设备的示意性框图。
图28是根据本申请一实施例的网络设备的示意性框图。
图29是根据本申请实施例的通信设备示意性框图。
图30是根据本申请实施例的芯片的示意性框图。
图31是根据本申请实施例的通信系统的示意性框图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行描述。
本申请实施例的技术方案可以应用于各种通信系统，例如：全球移动通讯(Global System of Mobile communication，GSM)系统、码分多址(Code Division Multiple Access，CDMA)系统、宽带码分多址(Wideband Code Division Multiple Access，WCDMA)系统、通用分组无线业务(General Packet Radio Service，GPRS)、长期演进(Long Term Evolution，LTE)系统、先进的长期演进(Advanced long term evolution，LTE-A)系统、新无线(New Radio，NR)系统、NR系统的演进系统、非授权频谱上的LTE(LTE-based access to unlicensed spectrum，LTE-U)系统、非授权频谱上的NR(NR-based access to unlicensed spectrum，NR-U)系统、非地面通信网络(Non-Terrestrial Networks，NTN)系统、通用移动通信系统(Universal Mobile Telecommunication System，UMTS)、无线局域网(Wireless Local Area Networks，WLAN)、无线保真(Wireless Fidelity，WiFi)、第五代通信(5th-Generation，5G)系统或其他通信系统等。
通常来说，传统的通信系统支持的连接数有限，也易于实现，然而，随着通信技术的发展，移动通信系统将不仅支持传统的通信，还将支持例如，设备到设备(Device to Device，D2D)通信，机器到机器(Machine to Machine，M2M)通信，机器类型通信(Machine Type Communication，MTC)，车辆间(Vehicle to Vehicle，V2V)通信，或车联网(Vehicle to everything，V2X)通信等，本申请实施例也可以应用于这些通信系统。
可选地，本申请实施例中的通信系统可以应用于载波聚合(Carrier Aggregation，CA)场景，也可以应用于双连接(Dual Connectivity，DC)场景，还可以应用于独立(Standalone，SA)布网场景。
可选地，本申请实施例中的通信系统可以应用于非授权频谱，其中，非授权频谱也可以认为是共享频谱；或者，本申请实施例中的通信系统也可以应用于授权频谱，其中，授权频谱也可以认为是非共享频谱。
本申请实施例结合网络设备和终端设备描述了各个实施例，其中，终端设备也可以称为用户设备(User Equipment，UE)、接入终端、用户单元、用户站、移动站、移动台、远方站、远程终端、移动设备、用户终端、终端、无线通信设备、用户代理或用户装置等。
终端设备可以是WLAN中的站点(STAION，ST)，可以是蜂窝电话、无绳电话、会话启动系统(Session Initiation Protocol，SIP)电话、无线本地环路(Wireless Local Loop，WLL)站、个人数字处理(Personal Digital Assistant，PDA)设备、具有无线通信功能的手持设备、计算设备或连接到无线调制解调器的其它处理设备、车载设备、可穿戴设备、下一代通信系统例如NR网络中的终端设备，或者未来演进的公共陆地移动网络(Public Land Mobile Network，PLMN)网 络中的终端设备等。
在本申请实施例中，终端设备可以部署在陆地上，包括室内或室外、手持、穿戴或车载；也可以部署在水面上(如轮船等)；还可以部署在空中(例如飞机、气球和卫星上等)。
在本申请实施例中，终端设备可以是手机(Mobile Phone)、平板电脑(Pad)、带无线收发功能的电脑、虚拟现实(Virtual Reality，VR)终端设备、增强现实(Augmented Reality，AR)终端设备、工业控制(industrial control)中的无线终端设备、无人驾驶(self driving)中的无线终端设备、远程医疗(remote medical)中的无线终端设备、智能电网(smart grid)中的无线终端设备、运输安全(transportation safety)中的无线终端设备、智慧城市(smart city)中的无线终端设备或智慧家庭(smart home)中的无线终端设备等。
作为示例而非限定，在本申请实施例中，该终端设备还可以是可穿戴设备。可穿戴设备也可以称为穿戴式智能设备，是应用穿戴式技术对日常穿戴进行智能化设计、开发出可以穿戴的设备的总称，如眼镜、手套、手表、服饰及鞋等。可穿戴设备即直接穿在身上，或是整合到用户的衣服或配件的一种便携式设备。可穿戴设备不仅仅是一种硬件设备，更是通过软件支持以及数据交互、云端交互来实现强大的功能。广义穿戴式智能设备包括功能全、尺寸大、可不依赖智能手机实现完整或者部分的功能，例如：智能手表或智能眼镜等，以及只专注于某一类应用功能，需要和其它设备如智能手机配合使用，如各类进行体征监测的智能手环、智能首饰等。
在本申请实施例中，网络设备可以是用于与移动设备通信的设备，网络设备可以是WLAN中的接入点(Access Point，AP)，GSM或CDMA中的基站(Base Transceiver Station，BTS)，也可以是WCDMA中的基站(NodeB，NB)，还可以是LTE中的演进型基站(Evolutional Node B，eNB或eNodeB)，或者中继站或接入点，或者车载设备、可穿戴设备以及NR网络中的网络设备(gNB)或者未来演进的PLMN网络中的网络设备或者NTN网络中的网络设备等。
作为示例而非限定，在本申请实施例中，网络设备可以具有移动特性，例如网络设备可以为移动的设备。可选地，网络设备可以为卫星、气球站。例如，卫星可以为低地球轨道(low earth orbit，LEO)卫星、中地球轨道(medium earth orbit，MEO)卫星、地球同步轨道(geostationary earth orbit，GEO)卫星、高椭圆轨道(High Elliptical Orbit，HEO)卫星等。可选地，网络设备还可以为设置在陆地、水域等位置的基站。
在本申请实施例中，网络设备可以为小区提供服务，终端设备通过该小区使用的传输资源(例如，频域资源，或者说，频谱资源)与网络设备进行通信，该小区可以是网络设备(例如基站)对应的小区，小区可以属于宏基站，也可以属于小小区(Small cell)对应的基站，这里的小小区可以包括：城市小区(Metro cell)、微小区(Micro cell)、微微小区(Pico cell)、毫微微小区(Femto cell)等，这些小小区具有覆盖范围小、发射功率低的特点，适用于提供高速率的数据传输服务。
图1示例性地示出了一种通信系统100。该通信系统100包括一个网络设备110和两个终端设备120。可选地，该通信系统100可以包括多个网络设备110，并且每个网络设备110的覆盖范围内可以包括其它数量的终端设备120，本申请实施例对此不做限定。
可选地，该通信系统100还可以包括移动性管理实体(Mobility Management Entity，MME)、接入与移动性管理功能(Access and Mobility Management Function，AMF)等其他网络实体，本申请实施例对此不作限定。
其中，网络设备又可以包括接入网设备和核心网设备。即无线通信系统还包括用于与接入网设备进行通信的多个核心网。接入网设备可以是长期演进(long-term evolution，LTE)系统、下一代(移动通信系统)(next radio，NR)系统或者授权辅助接入长期演进(authorized auxiliary access long-term evolution，LAA-LTE)系统中的演进型基站(evolutional node B，简称可以为eNB或e-NodeB)宏基站、微基站(也称为“小基站”)、微微基站、接入站点(access point，AP)、传输站点(transmission point，TP)或新一代基站(new generation Node B，gNodeB)等。
应理解，本申请实施例中网络/系统中具有通信功能的设备可称为通信设备。以图1示出的通信系统为例，通信设备可包括具有通信功能的网络设备和终端设备，网络设备和终端设备可以为本申请实施例中的具体设备，此处不再赘述；通信设备还可包括通信系统中的其他设备，例如网络控制器、移动管理实体等其他网络实体，本申请实施例中对此不做限定。
应理解，本文中术语“系统”和“网络”在本文中常被可互换使用。本文中术语“和/或”，仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。另外，本文中字符“/”，一般表示前后关联对象是一种“或”的关系。
应理解，在本申请的实施例中提到的“指示”可以是直接指示，也可以是间接指示，还可以是表示具有关联关系。举例说明，A指示B，可以表示A直接指示B，例如B可以通过A获取；也可以表示A间接指示B，例如A指示C，B可以通过C获取；还可以表示A和B之间具有关联关系。
在本申请实施例的描述中，术语“对应”可表示两者之间具有直接对应或间接对应的关系，也可以表示两者之间具有关联关系，也可以是指示与被指示、配置与被配置等关系。
为便于理解本申请实施例的技术方案，以下对本申请实施例的相关技术进行说明，以下相关技术作为可选方案与本申请实施例的技术方案可以进行任意结合，其均属于本申请实施例的保护范围。
图2是根据本申请一实施例的语义通信的传输方法200的示意性流程图。该方法可选地可以应用于图1所示的系统，但并不仅限于此。该方法包括以下内容的至少部分内容：
S210、终端设备对信源进行语义获取处理，得到语义信息。
一些示例中，终端设备还可以称为发送端(或编码端)，在终端设备可以增加用于实现该语义获取处理的语义获取单元，从而可以将该信源输入该语义获取单元，经该语义获取处理后输出得到该语义信息。其中，该语义获取单元可以通过人工智能技术实现，比如通过人工智能技术得到的且不限于卷积神经网络的各种神经网络。
S220、终端设备根据该语义信息，确定待传输的第一信息。
一些示例中，除了传输该语义信息，还可以传输该语义信息和该信源(即：在终端设备侧，除了作为原始信息的“信源”，还可以包括作为额外信息的“语义信息”，并据此得到待传输的该第一信息)。
S230、终端设备发送该第一信息。
一些示例中，终端设备作为发送端可以将该第一信息作为待传输的发送信息发送给接收端，接收端可以是网络设备(如基站)，也可以是作为接收端的终端设备，比如使用手机、如平板电脑等便携电脑或台式机的用户，以实现人-机交互的通信传输。
采用本申请实施例，终端设备可以对信源进行语义获取处理，得到语义信息，终端设备可以根据该语义信息确定待传输的第一信息，终端设备作为发送端发送该第一信息给接收端，从而可以实现语义通信的传输，能满足不断更新的通信需求，即：不仅可以实现作为原始信息的“信源”的传输，还可以实现作为除原始信之外额外信息的“语义信息”的传输。
在一种可能的实现方式中，终端设备根据语义信息，确定待传输的第一信息，包括以下至少之一：
方式1)终端设备对该语义信息进行编码调制后，得到该第一信息；
方式2)终端设备对该语义信息进行编码调制及加密后，得到该第一信息。
图3是根据本申请一实施例的语义通信的传输方法300的示意性流程图。该方法可选地可以应用于图1所示的系统，但并不仅限于此。该方法包括以下内容的至少部分内容：
S310、终端设备对信源进行扩展语义的获取处理，得到扩展语义信息。
一些示例中，终端设备还可以称为发送端(或编码端)，在终端设备可以增加用于实现该扩展语义获取处理的扩展语义获取单元，从而可以将该信源输入该扩展语义获取单元，经该扩展语义获取处理后输出得到该扩展语义信息。其中，该扩展语义获取单元可以通过人工智能技术实现，比如通过人工智能技术得到的且不限于卷积神经网络的各种神经网络。
一些示例中，该扩展语义信息包括：情绪信息、强调信息、关联信息、预测信息、不同任务优先级信息中的至少一项。
S320、终端设备根据该扩展语义信息，确定待传输的第一信息。
一些示例中，除了传输该扩展语义信息，还可以传输该扩展语义信息和该信源(即：在终端设备侧，除了作为原始信息的“信源”，还可以包括作为额外信息的“扩展语义信息”，并据此得到待传输的该第一信息)。其中，该扩展语义信息与作为原始信息的“信源”相比较，该扩展语义信息是以发送端(或编码端)期望发送的语义为目标，通过对该扩展语义的提取，以便从原始信息中提取出该扩展语义信息，可以规避接收端(或解码端)无法获取完整的信息，从而提高传输的准确性和信息完整性。
S330、终端设备发送该第一信息。
一些示例中，终端设备作为发送端可以将该第一信息作为待传输的发送信息发送给接收端，接收端可以是网络设备(如基站)，也可以是作为接收端的终端设备，比如使用手机、如平板电脑等便携电脑或台式机的用户，以实现人-机交互的通信传输。
在一种可能的实现方式中，终端设备对信源进行扩展语义的获取处理，得到扩展语义信息，包括以下至少之一：
方式1)将该信源输入训练好的第一网络模型(第一网络模型可以部署于上述扩展语义获取单元)中，得到情绪信息、强调信息、关联信息、预测信息、不同任务优先级信息中的至少一项，从而得到多样化的扩展语义信息。
方式2)将该信源输入训练好的第二网络模型(第二网络模型可以部署于上述扩展语义获取单元)中，得到不同的情绪信息分类、不同的强调信息分类、不同的关联信息补充、不同的预测信息补充、不同任务优先级信息补充中的至少一项，从而得到多样化的扩展语义信息的进一步信息(如信息分类或信息补充等)。
在一种可能的实现方式中，还包括：将扩展语义信息中的每一项信息基于不同分类进行分类处理，并采用对应的标识信息作为分类标识，根据分类标识和对应的分类描述建立映射关系。比如，针对情绪信息和强调信息分别执行分类处理，建立映射关系得到映射表，其中，针对情绪信息的映射表包括：以该分类标识描述的情绪分类、以及对应分类描述的分类说明。针对强调信息的映射表包括：以该分类标识描述的重要性分类、以及对应分类描述的分类说明。
图4是根据本申请一实施例的语义通信的传输方法400的示意性流程图。该方法可选地可以应用于图1所示的系统，但并不仅限于此。该方法包括以下内容的至少部分内容：
S410、终端设备对信源进行核心语义的获取处理，得到核心语义信息。
一些示例中，终端设备还可以称为发送端(或编码端)，在终端设备可以增加用于实现该核心语义获取处理的核心语义获取单元，从而可以将该信源输入该核心语义获取单元，经该核心语义获取处理后输出得到该核心语义信息。其中，该核心语义获取单元可以通过人工智能技术实现，比如通过人工智能技术得到的且不限于卷积神经网络的各种神经网络。
S420、终端设备根据该核心语义信息，确定待传输的第一信息。
一些示例中，除了传输该核心语义信息，还可以传输该核心语义信息和该信源(即：在终端设备侧，除了作为原始信息的“信源”，还可以包括作为额外信息的“核心语义信息”，并据此得到待传输的该第一信息)。其中，该核心语义信息与作为原始信息的“信源”相比较，核心语义信息是以接收端(或解码端)期望接收的语义为目标，通过对核心语义的提取，以便从原始信息中提取出该核心语义信息，可以规避接收端(或解码端)不需要的信息的传输，只传输该核心语义信息，从而提高传输的效率。
S430、终端设备发送该第一信息。
一些示例中，终端设备作为发送端可以将该第一信息作为待传输的发送信息发送给接收端，接收端可以是网络设备(如基站)，也可以是作为接收端的终端设备，比如使用手机、如平板电脑等便携电脑或台式机的用户，以实现人-机交互的通信传输。
在一种可能的实现方式中，终端设备对信源进行核心语义的获取处理，得到核心语义信息，包括：将该信源输入训练好的第三网络模型(第三网络模型可以部署于上述核心语义获取单元)中，得到核心语义信息。核心语义信息用于描述用户的操作性行为(或称为用户的非修饰性/非描述性行为)，比如，行为、动作、指令、数据、命令等，从而得到多样化的核心语义信息。
图5是根据本申请一实施例的语义通信的传输方法500的示意性流程图。该方法可选地可以应用于图1所示的系统，但并不仅限于此。该方法包括以下内容的至少部分内容：
S510、终端设备对信源进行扩展语义的获取处理，得到扩展语义信息。
S520、终端设备对信源进行核心语义的获取处理，得到核心语义信息。
S530、终端设备根据该扩展语义信息和该核心语义信息，得到组合语义信息。
一些示例中，终端设备还可以称为发送端(或编码端)，在终端设备可以增加用于实现该扩展语义和该核心语义获取处理的组合语义获取单元(即：该组合语义获取单元既能实现扩展语义获取处理，又能实现核心语义获取处理)，从而可以将该信源输入该组合语义获取单元，经该扩展语义和该核心语义获取处理后输出得到该扩展语义信息和该核心语义信息(该扩展语义信息和该核心语义信息构成该组合语义信息)。其中，该组合语义获取单元可以通过人工智能技术实现，比如通过人工智能技术得到的且不限于卷积神经网络的各种神经网络。
S540、终端设备根据该组合语义信息，确定待传输的第一信息。
一些示例中，除了传输该组合语义信息中的该扩展语义信息和该核心语义信息，还可以传输该扩展语义信息、该核心语义信息和该信源(即：在终端设备侧，除了作为原始信息的“信源”，还可以包括作为额外信息的“该扩展语义信息和该核心语义信息”，并据此得到待传输的该第一信息)。其中，该扩展语义信息与作为原始信息的“信源”相比较，该扩展语义信息是以发送端(或编码端)期望发送的语义为目标，通过对该扩展语义的提取，以便从原始信息中提取出该扩展语义信息，可以规避接收端(或解码端)无法获取完整的信息，从而提高传输的准确性和信息完整性。该核心语义与作为原始信息的“信源”相比较，核心语义是以接收端(或解码端)期望接收的语义为目标，在原始信息中获取的该核心语义，通过对核心语义的提取，可以规避接收端(或解码端)不需要的信息的传输，从而提高传输的效率。
S550、终端设备发送该第一信息。
一些示例中，终端设备作为发送端可以将该第一信息作为待传输的发送信息发送给接收端，接收端可以是网络设备(如基站)，也可以是作为接收端的终端设备，比如使用手机、如平板电脑等便携电脑或台式机的用户，以实现人-机交互的通信传输。
图6是根据本申请一实施例的语义通信的传输方法600的示意性流程图。该方法可选地可以应用于图1所示的系统，但并不仅限于此。该方法包括以下内容的至少部分内容：
S610、终端设备接收第二信息。
一些示例中，除了作为接收端的该终端设备(比如使用手机、如平板电脑等便携电脑或台式机的用户，以实现人-机交互的通信传输)，该接收端还可以为网络设备(如基站)，该第二信息也可以是上述实施例中的第一信息，包括两个场景，第一个场景、发送端和接收端都存在语义获取单元，第一信息中包括信源和携带的语义信息，接收端备直接恢复信源及语义信息；第二个场景、发送端可以不设置语义获取单元，只有接收端存在语义获取单元，接收端恢复出信源后， 对信源进行语义获取，从而得到语义信息。
具体的，该第二信息可以与上述实施例中的第一信息为相同的信息(比如，该第一信息和该第二信息都只包括语义信息；或者该第一信息和该第二信息不仅包括语义信息，还包括信源等)；该第二信息还可以与上述实施例中的第一信息为不同的信息(比如，该第一信息不仅包括语义信息，还包括信源，而该第二信息只包括信源等)，换言之，以接收端为网络设备为例，终端设备和网络设备虽然都可以针对信源进行语义获取处理，从而得到语义信息，包括但不限于：终端设备和网络设备结合在一起配套使用，以完成编码及解码处理，终端设备和网络设备也可以各自进行针对语义获取处理的编码和解码处理。
S620、终端设备从该第二信息中恢复出信源。
一些示例中，终端设备从该第二信息中恢复出信源，可以包括以下至少之一：
方式1)终端设备对该第二信息进行解码解调后，得到该信源；
方式2)终端设备对该第二信息进行解码解调及解密后，得到该信源。
S630、终端设备对该信源进行语义获取处理，得到语义信息。
一些示例中，终端设备还可以称为接收端(或解码端)，在终端设备可以增加用于实现该语义获取处理的语义获取单元，从而可以将该信源输入该语义获取单元，经该语义获取处理后输出得到该语义信息。其中，该语义获取单元可以通过人工智能技术实现，比如通过人工智能技术得到的且不限于卷积神经网络的各种神经网络。
采用本申请实施例，终端设备从第二信息中恢复出信源后，可以对信源进行语义获取处理，得到语义信息，从而可以实现语义通信的传输。
图7是根据本申请一实施例的语义通信的传输方法700的示意性流程图。该方法可选地可以应用于图1所示的系统，但并不仅限于此。该方法包括以下内容的至少部分内容：
S710、终端设备接收第二信息。
一些示例中，除了作为接收端的该终端设备(比如使用手机、如平板电脑等便携电脑或台式机的用户，以实现人-机交互的通信传输)，该接收端还可以为网络设备(如基站)，该第二信息也可以是上述实施例中的第一信息，包括两个场景，第一个场景、发送端和接收端都存在语义获取单元，第一信息中包括信源和携带的语义信息，接收端备直接恢复信源及语义信息；第二个场景、发送端可以不设置语义获取单元，只有接收端存在语义获取单元，接收端恢复出信源后，对信源进行语义获取，从而得到语义信息。
具体的，该第二信息可以与上述实施例中的第一信息为相同的信息(比如，该第一信息和该第二信息都只包括语义信息；或者该第一信息和该第二信息不仅包括语义信息，还包括信源等)；该第二信息还可以与上述实施例中的第一信息为不同的信息(比如，该第一信息不仅包括语义信息，还包括信源，而该第二信息只包括信源等)，换言之，以接收端为网络设备为例，终端设备和网络设备虽然都可以针对信源进行语义获取处理，从而得到语义信息，包括但不限于：终端设备和网络设备结合在一起配套使用，以完成编码及解码处理，终端设备和网络设备也可以各自进行针对语义获取处理的编码和解码处理。
S720、终端设备从该第二信息中恢复出信源。
一些示例中，终端设备从该第二信息中恢复出信源，可以包括以下至少之一：
方式1)终端设备对该第二信息进行解码解调后，得到该信源；
方式2)终端设备对该第二信息进行解码解调及解密后，得到该信源。
S730、终端设备对该信源进行扩展语义的获取处理，得到扩展语义信息。
一些示例中，终端设备还可以称为接收端(或解码端)，在终端设备可以增加用于实现该扩展语义获取处理的扩展 语义获取单元，从而可以将该信源输入该扩展语义获取单元，经该扩展语义获取处理后输出得到该扩展语义信息。其中，该扩展语义获取单元可以通过人工智能技术实现，比如通过人工智能技术得到的且不限于卷积神经网络的各种神经网络。
一些示例中，该扩展语义信息包括：情绪信息、强调信息、关联信息、预测信息、不同任务优先级信息中的至少一项。
在一种可能的实现方式中，终端设备对信源进行扩展语义的获取处理，得到扩展语义信息，包括以下至少之一：
方式1)将该信源输入训练好的第四网络模型(第四网络模型可以部署于上述扩展语义获取单元)中，得到情绪信息、强调信息、关联信息、预测信息、不同任务优先级信息中的至少一项，从而得到多样化的扩展语义信息。
方式2)将该信源输入训练好的第五网络模型(第五网络模型可以部署于上述扩展语义获取单元)中，得到不同的情绪信息分类、不同的强调信息分类、不同的关联信息补充、不同的预测信息补充、不同任务优先级信息补充中的至少一项，从而得到多样化的扩展语义信息的进一步信息(如信息分类或信息补充等)。
在一种可能的实现方式中，还包括：将扩展语义信息中的每一项信息基于不同分类进行分类处理，并采用对应的标识信息作为分类标识，根据分类标识和对应的分类描述建立映射关系。比如，针对情绪信息和强调信息分别执行分类处理，建立映射关系得到映射表，其中，针对情绪信息的映射表包括：以该分类标识描述的情绪分类、以及对应分类描述的分类说明。针对强调信息的映射表包括：以该分类标识描述的重要性分类、以及对应分类描述的分类说明。
图8是根据本申请一实施例的语义通信的传输方法800的示意性流程图。该方法可选地可以应用于图1所示的系统，但并不仅限于此。该方法包括以下内容的至少部分内容：
S810、终端设备接收第二信息。
一些示例中，除了作为接收端的该终端设备(比如使用手机、如平板电脑等便携电脑或台式机的用户，以实现人-机交互的通信传输)，该接收端还可以为网络设备(如基站)，该第二信息也可以是上述实施例中的第一信息，包括两个场景，第一个场景、发送端和接收端都存在语义获取单元，第一信息中包括信源和携带的语义信息，接收端备直接恢复信源及语义信息；第二个场景、发送端可以不设置语义获取单元，只有接收端存在语义获取单元，接收端恢复出信源后，对信源进行语义获取，从而得到语义信息。
具体的，该第二信息可以与上述实施例中的第一信息为相同的信息(比如，该第一信息和该第二信息都只包括语义信息；或者该第一信息和该第二信息不仅包括语义信息，还包括信源等)；该第二信息还可以与上述实施例中的第一信息为不同的信息(比如，该第一信息不仅包括语义信息，还包括信源，而该第二信息只包括信源等)，换言之，以接收端为网络设备为例，终端设备和网络设备虽然都可以针对信源进行语义获取处理，从而得到语义信息，包括但不限于：终端设备和网络设备结合在一起配套使用，以完成编码及解码处理，终端设备和网络设备也可以各自进行针对语义获取处理的编码和解码处理。
S820、终端设备从该第二信息中恢复出信源。
一些示例中，终端设备从该第二信息中恢复出信源，可以包括以下至少之一：
方式1)终端设备对该第二信息进行解码解调后，得到该信源；
方式2)终端设备对该第二信息进行解码解调及解密后，得到该信源。
S830、终端设备对该信源进行核心语义的获取处理，得到核心语义信息。
一些示例中，终端设备还可以称为接收端(或解码端)，在终端设备可以增加用于实现该核心语义获取处理的核心语义获取单元，从而可以将该信源输入该核心语义获取单元，经该核心语义获取处理后输出得到该核心语义信息。其中，该核心语义获取单元可以通过人工智能技术实现，比如通过人工智能技术得到的且不限于卷积神经网络的各种神经网络。
一些示例中，该核心语义信息用于描述用户的操作性行为(或称为用户的非修饰性/非描述性行为)，比如，行为、 动作、指令、数据、命令等，从而得到多样化的核心语义信息。
在一种可能的实现方式中，终端设备对信源进行核心语义的获取处理，得到核心语义信息，包括：
将该信源输入训练好的第六网络模型(第六网络模型可以部署于上述核心语义获取单元)中，得到核心语义信息。
图9是根据本申请一实施例的语义通信的传输方法900的示意性流程图。该方法可选地可以应用于图1所示的系统，但并不仅限于此。该方法包括以下内容的至少部分内容：
S910、终端设备接收第二信息。
一些示例中，除了作为接收端的该终端设备(比如使用手机、如平板电脑等便携电脑或台式机的用户，以实现人-机交互的通信传输)，该接收端还可以为网络设备(如基站)，该第二信息也可以是上述实施例中的第一信息，包括两个场景，第一个场景、发送端和接收端都存在语义获取单元，第一信息中包括信源和携带的语义信息，接收端备直接恢复信源及语义信息；第二个场景、发送端可以不设置语义获取单元，只有接收端存在语义获取单元，接收端恢复出信源后，对信源进行语义获取，从而得到语义信息。
具体的，该第二信息可以与上述实施例中的第一信息为相同的信息(比如，该第一信息和该第二信息都只包括语义信息；或者该第一信息和该第二信息不仅包括语义信息，还包括信源等)；该第二信息还可以与上述实施例中的第一信息为不同的信息(比如，该第一信息不仅包括语义信息，还包括信源，而该第二信息只包括信源等)，换言之，以接收端为网络设备为例，终端设备和网络设备虽然都可以针对信源进行语义获取处理，从而得到语义信息，包括但不限于：终端设备和网络设备结合在一起配套使用，以完成编码及解码处理，终端设备和网络设备也可以各自进行针对语义获取处理的编码和解码处理。
S920、终端设备从该第二信息中恢复出信源。
一些示例中，终端设备从该第二信息中恢复出信源，可以包括以下至少之一：
方式1)终端设备对该第二信息进行解码解调后，得到该信源；
方式2)终端设备对该第二信息进行解码解调及解密后，得到该信源。
S930、终端设备对该信源进行扩展语义的获取处理，得到扩展语义信息。
S940、终端设备对该信源进行核心语义的获取处理，得到核心语义信息。
S950、终端设备根据该扩展语义信息和该核心语义信息，得到组合语义信息。
一些示例中，终端设备还可以称为接收端(或解码端)，在终端设备可以增加用于实现该扩展语义和该核心语义获取处理的组合语义获取单元(该组合语义获取单元既能实现扩展语义获取处理，又能实现核心语义获取处理)，从而可以将该信源输入该组合语义获取单元，经该扩展语义和该核心语义获取处理后输出得到该扩展语义信息和该核心语义信息(该扩展语义信息和该核心语义信息构成该组合语义信息)。其中，该组合语义获取单元可以通过人工智能技术实现，比如通过人工智能技术得到的且不限于卷积神经网络的各种神经网络。
一些示例中，该扩展语义信息包括：情绪信息、强调信息、关联信息、预测信息、不同任务优先级信息中的至少一项。
一些示例中，该核心语义信息用于描述用户的操作性行为(或称为用户的非修饰性/非描述性行为)，比如，行为、动作、指令、数据、命令等，从而得到多样化的核心语义信息。
图10是根据本申请一实施例的语义通信的传输方法的示意性流程图，该方法可选地可以应用于图1所示的系统，但并不仅限于此。该方法包括以下内容的至少部分内容：
S1010、网络设备接收第一信息。
S1020、该网络设备从该第一信息中恢复出语义信息，语义信息为：终端设备侧通过对信源进行语义获取处理所得 到的信息。
一些示例中，该网络设备对该第一信息进行解码解调后，得到该语义信息；或者，该网络设备对该第一信息进行解码解调及解密后，得到该语义信息。
一些示例中，该语义信息包括：扩展语义信息、核心语义信息中的至少一项。
一些示例中，该扩展语义信息，包括：情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项。
一些示例中，该扩展语义信息，还包括：情绪信息分类、强调信息分类、关联信息补充、预测信息补充、任务优先级信息补充中的至少一项。
一些示例中，该核心语义信息，包括：行为、动作、指令、数据、命令中的至少一项。
采用本申请实施例，在终端设备侧进行语义信息的获取处理，即：终端设备可以对信源进行语义获取处理，以得到语义信息，根据该语义信息得到待传输的第一信息后，终端设备作为发送端发送该第一信息给接收端，接收端为网络设备的情况下，接收该第一信息，从该第一信息中恢复出语义信息，从而在终端设备与网络设备之间可以实现语义通信的传输，能满足不断更新的通信需求，即：不仅可以实现作为原始信息的“信源”的传输，还可以实现作为除原始信之外额外信息的“语义信息”的传输。
图11是根据本申请一实施例的语义通信的传输方法的示意性流程图，该方法可选地可以应用于图1所示的系统，但并不仅限于此。该方法包括以下内容的至少部分内容：
S1110、网络设备根据信源确定待传输的第二信息；该信源包括待执行语义获取处理的语义信息；
一些示例中，该网络设备对该信源进行编码调制后，确定该第二信息；或者，该网络设备对该信源进行编码调制及加密后，确定该第二信息。
S1120、该网络设备发送该第二信息。
一些示例中，该语义信息包括：扩展语义信息、核心语义信息中的至少一项。
一些示例中，该扩展语义信息，包括：情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项。
一些示例中，该扩展语义信息，包括：情绪信息分类、强调信息分类、关联信息补充、预测信息补充、任务优先级信息补充中的至少一项。
一些示例中，该核心语义信息，包括：行为、动作、指令、数据、命令中的至少一项。
采用本申请实施例，网络设备作为发送端，可以根据信源确定待传输的第二信息，该信源包括待执行语义获取处理的语义信息，发送该第二信息给终端设备，在终端设备侧进行语义信息的获取处理，即：作为接收端的终端设备从接收的该第二信息中恢复出信源后，可以对信源进行语义获取处理，以得到语义信息，从而在终端设备与网络设备之间可以实现语义通信的传输，能满足不断更新的通信需求，即：不仅可以实现作为原始信息的“信源”的传输，还可以实现作为除原始信之外额外信息的“语义信息”的传输。
下面对上述本申请实施例提供的语义通信的传输方法进行详细说明。
图12是根据本申请一实施例的语义通信的传输方法一示例的示意性编解码示意图，如图12所示，在无线通信系统中基本的工作流程包括：发送机在发送端对信源进行编码、调制、加密等操作，形成待传输的发送信息。发送信息通过无线空间传输至接收端，接收端对收到的接收信息进行解码、解密解调等操作，最终恢复出该信源，最大限度的实现作为原始信息的“信源”的无损传输。
图13是根据本申请一实施例的语义通信的传输方法一示例的示意性神经网络示意图，如图13所示，基本的神经网络的结构包括：输入层、隐藏层和输出层。该输入层接收数据后，通过该隐藏层对接收的数据进行处理，最后的数据处理结果在输出层产生。其中，神经网络中的每个节点代表一个处理单元，可以认为是模拟了一个神经元，多个神经元组 成一层神经网络，多层的信息传递与处理构造出一个整体的神经网络。
图14是根据本申请一实施例的语义通信的传输方法一示例的示意性信息间关系示意图，如图14所示，包括核心语义信息、原始信息和扩展语义信息。其中，该原始信息可以是上述信源，可以基于图12所示的无线通信系统架构进行传输，而核心语义信息和扩展语义信息相对于该信源来说，是需要对无线通信系统架构完善后传输的额外信息。换言之，当前的无线通信系统的设计的目标是将原始信息从发送端无损传输至接收端，然而，至少如下至少两类情况(第一类场景和第二类场景)，只做原始信息的无损传输并不是通信传输的全部需求，除了满足原始信息的无损传输，还需要更新无线通信系统架构，以满足更多信息(比如核心语义信息和扩展语义信息等语义信息)的无损传输需求。
如图13所示的神经网络只是一个基本架构，随着神经网络研究的不断发展，更多的神经网络深度学习算法，较多的隐藏层被引入，可以通过多隐层的神经网络逐层训练进行特征学习，从而极大地提升神经网络的学习和处理能力，神经网络部署在各个应用场景(自然语言处理、语义分析理解、模式识别、信号处理、优化组合、异常探测等场景)的软/硬件中，可以提高软/硬件的处理速度和精度，可以将神经网络应用于如下至少两类情况，以实现核心语义信息和扩展语义信息等语义信息的无损传输需求。
第一类场景：从原始信息获取、传输扩展语义信息
以人与人直接交流为例，同样交流内容的上下文信息、交流环境、表达的情感、强调的重点这些会随着不同的陈述环境和方式而不同，即使是完全同样的原始信息传输也会带来不同的表达效果、不同的强调效果、不同的感性效果。在这类情况下，单纯地做原始信息的传输并不能携带完整的交流信息，即使接收端完全无损的接收了原始信息，接收端也无法准确的确认出特定上下文信息、交流环境、表达的情感、强调的重点这些带来的额外信息量。该接收端作为机器，与人在认知上的这种不同，在于：如果交互的双方都是人，因为人相比机器都有一定的情感理解能力，即便人的情感理解能力程度不同，这个问题也是可以被相对弱化一些的，类似于在物理世界中，人和人面对面交流、语音交流、文字交流对于同样的交流内容所带来的不同交流效果，但是机器缺少情感理解能力，需要通过技术手段来弥补情感理解能力不足的问题，因此，在机器与机器间的交互中，除了满足原始信息的无损传输，还需要更新无线通信系统架构，以满足更多信息的无损传输需求，对于第一类场景，原始信息传输以外额外信息的获取与信息传递，将这类额外信息统一称为扩展语义信息，在人-人交互、人-机交互、机-机交互中，特别是在人-机交互、机-机交互的场景中，当交互的至少一方是缺乏对这些扩展语义的主动获取和理解能力时，或者能力比较弱，或者能力不对等时，如何优化通信系统设计来完成原始信息以外额外信息(如扩展语义信息)的获取与传递是需要解决的问题。
第二类场景：从原始信息提炼、传输核心语义信息
原始信息中往往包含所要表述的核心信息和用来修饰核心信息的核心信息，例如当A表述了大量的描述一本书的信息同时又表述希望B能借给A这本书时，希望借这本书是表达的核心信息，而关于书的描述并不是这部分内容的核心信息。在人与人的交互中存在大量的这类描述，而如果通信传输的目的只是做原始信息中核心信息的传输时，则可以只传输核心的信息，对于第二类场景，原始信息传输以外额外信息的获取与信息传递，将这类额外信息统一称为核心语义信息，在人-人交互、人-机交互、机-机交互中，特别是在人-机交互的场景中，当交互的至少一方是在待交互信息中添加了非核心语义，而交互的另一方并不需要这些非核心语义时，如何优化通信系统设计来完成原始信息以外额外信息(如核心语义信息)的获取与传递是需要解决的问题。
综上所述，第一类场景，需要在原始信息的基础上获取额外的扩展语义信息，而对于第二类场景，需要在原始信息的基础上获取提炼的核心语义信息，上述过程所涉及的扩展语义信息、核心语义信息的相关编码、解码、传输，以及整个系统的更新设计如下具体阐述。
一、发送端(或称编码端)一侧的语义通信传输，在编码端为主的语义通信系统中，涉及扩展语义通信、核心语义 通信、以及扩展语义联合核心语义通信三种情况。
图15是根据本申请一实施例的语义通信的传输方法一示例的示意性编解码示意图，如图15所示，以编码端为主实现语义通信传输的无线通信系统的工作流程，相比于图12所示的工作流程，额外需要的是语义获取单元的引入，根据扩展语义通信、核心语义通信、以及扩展语义联合核心语义通信三种情况，可以具体为扩展语义获取单元(用于扩展语义信息的获取)、核心语义获取单元(用于核心语义信息的获取)，组合语义获取单元(用于扩展语义和核心语义信息的获取)，从而实现从原始信息(信源)获取语义信息的功能。
图16是根据本申请一实施例的语义通信的传输方法一示例的示意性扩展语义获取示意图，如图16所示，当语义获取单元用于实现扩展语义信息的获取时，语义获取单元可以为扩展语义获取单元，其输出信息包括了原始信息所表达的扩展语义信息，扩展语义信息包括多类语义信息，比如情绪信息、强调信息、关联信息、预测信息、不同任务优先级信息等扩展语义信息中的一项或者多项。
对于情绪信息，可以预先有情绪信息的分类，不同的情绪分类对应不同的标识，如表1所示，扩展语义信息可以针对不同情绪的分类标识信息来表征并传输。
情绪分类 分类说明
1 第1情绪，例如：喜
2 第2情绪，例如：怒
3 第3情绪，例如：哀
4 第4情绪，例如：乐
表1
对于强调信息，对于要强调的重点信息，也可以对原始信息做分类、不同类对应不同的重要性标识或者权重，或者直接输出需要强调的局部原始信息，例如表2、表3所示。
重要性分类 分类说明
1 第1强调部分，例如：强调主语
2 第2强调部分，例如：强调谓语
3 第3强调部分，例如：强调宾语
4 第4强调部分，例如：强调动词
5 第5强调部分，例如：强调名词
6 第6强调部分，例如：强调修饰成分
表2
重要性分类 分类说明
1 第1强调部分，例如：强调人物
2 第2强调部分，例如：强调车辆
3 第3强调部分，例如：强调环境
4 第4强调部分，例如：强调位置
5 第5强调部分，例如：强调文字
6 第6强调部分，例如：强调语音
7 第7强调部分，例如：强调图片
表3
图17是根据本申请一实施例的语义通信的传输方法一示例的示意性扩展语义传输示意图，如图17所示，在UE侧对原始信息进行语义信息的获取处理，得到扩展语义信息后，传输该扩展语义信息给基站。其中，扩展语义信息与原始信息相比较，该扩展语义信息是以发送端期望发送的语义为目标，在原始信息中获取的，通过对这部分扩展语义的提取，可以规避接收端无法获取完整的发送端希望传递的信息，从而提高传输的准确性。
对于上述语义获取单元的实现可以利用神经网络来实现，例如神经网络的输入是原始信息，输出是不同情绪信息或分类、不同重点强调内容信息或分类、不关联信息的补充、不同预测信息的补充、不同任务优先级的补充等扩展语义信息中的一项或者多项，神经网络的结构可以是全连接结构、卷积结构、循环神经网络(Recurrent Neural Network，RNN)结构、长短期记忆网络(Long-Short Term Memory，LSTM)结构、自注意力机制(self-attention)结构、由自注意力和前馈神经网络组成的转换器(transformer)结构中的一项或者多项。
图18是根据本申请一实施例的语义通信的传输方法一示例的示意性核心语义获取示意图，如图18所示，当语义获取单元用于实现核心语义信息的获取时，语义获取单元可以为核心语义获取单元，其输出信息包括了原始信息所表达的核心语义信息。核心语义信息与原始信息相比较，该核心语义信息是以接收端期望接收的语义为目标，在原始信息中获取的，通过对这部分核心语义的提取，可以规避接收端不需要的信息的传输，从而提高传输的效率。
图19是根据本申请一实施例的语义通信的传输方法一示例的示意性核心语义传输示意图，如图19所示，在UE侧对原始信息进行语义信息的获取处理，得到核心语义信息后，传输该核心语义信息给基站。对于上述语义获取单元的实现可以利用神经网络来实现，例如神经网络的输入是原始信息，输出是核心语义信息。神经网络的结构可以是全连接结构、卷积结构、RNN结构、LSTM结构、self-attention结构、由自注意力和前馈神经网络组成的transformer结构中的一项或者多项。
图20是根据本申请一实施例的语义通信的传输方法一示例的示意性组合语义传输示意图，如图20所示，语义获取单元也可以用于扩展语义的获取和核心语义的获取，实现上属于上述两种情况的合集，在UE侧对原始信息进行扩展语义和核心信息的获取处理，得到扩展语义和核心语义信息后，将该扩展语义和核心语义信息一起联合传输给基站，这里不再赘述。
二、接送端(或称解码端)一侧的语义通信传输，在解码端为主的语义通信系统中，涉及扩展语义通信、核心语义通信、以及扩展语义联合核心语义通信三种情况。
图21是根据本申请一实施例的语义通信的传输方法一示例的示意性编解码示意图，如图21所示，以解码端为主实现语义通信传输的无线通信系统的工作流程，相比于图12所示的工作流程，额外需要的是语义获取单元的引入，根据扩展语义通信、核心语义通信、以及扩展语义联合核心语义通信三种情况，可以具体为扩展语义获取单元(用于扩展语义信息的获取)、核心语义获取单元(用于核心语义信息的获取)，组合语义获取单元(用于扩展语义和核心语义信息的获取)，从而实现从原始信息(信源)获取语义信息的功能。
图22-图24分别是根据本申请一实施例的语义通信的传输方法一示例的示意性扩展语义传输、核心语义传输、及扩展语义联合核心语义传输的各个示意图，如图22所示，UE从基站接收原始信息，在UE侧对原始信息进行语义信息的获取处理，得到扩展语义信息。如图23所示，UE从基站接收原始信息，在UE侧对原始信息进行核心信息的获取处理，得到核心语义信息。如图24所示，UE从基站接收原始信息，在UE侧对原始信息进行扩展语义和核心信息的获取处理，得到扩展语义和核心语义信息。
对于上述语义获取单元的实现可以利用神经网络来实现，例如神经网络的输入是原始信息，输出是核心语义信息。神经网络的结构可以是全连接结构、卷积结构、RNN结构、LSTM结构、self-attention结构、由自注意力和前馈神经网络组成的transformer结构中的一项或者多项。
一些示例中，在人-机交互的场景中，如果在发送端(例如自然语言、物理信息传输)没有做语义信息获取处理，则需要在接收端部署上述语义获取单元，可以获取原始信息所期望表述的扩展语义信息，例如情绪信息、强调信息、关联信息、预测信息、不同任务优先级信息等扩展语义信息中的一项或者多项，即：输入是接收端(UE)从基站接收到的原始信息、输出是需要获取的情绪信息(或者情绪分类)、强调信息(或者重要性分类)、关联信息(或者分类，例如原始信息与特定的原始信息以外的额外信息关联，这些额外信息可以是历史传输信息、不需要传输的公开信息等)、预测信息(或者分类，例如基于当前原始信息内容所能预测的未来时刻信息、或者决策信息)。
采用上述在发送端或接收端部署语义获取单元来完善无线通信系统，相比于如图12所示的无线通信系统主要考虑的是原始信息的传输能满足更多额外信息的通信需求，在通信双方是“人”的前提下，虽然仅传输原始信息是有效的，但是，也会产生对期望传输的内容在交互者之间理解不一致的问题。随着技术发展，更多的物联、智联场景下，当通信的双方开始更新为“物”时，“人-物”、“物-物”传输(即：当信息传递者或者获取者至少有一方是“物”，甚至是在比较复杂的“人-物”、“物-物”交互)的场景中，即使无损的原始信息传输也并非最佳传输方案。一方面，当交互的至少一方是缺乏对原始信息本身以外的扩展语义(扩展语义是指发送端期望发送的完整信息)的主动获取和理解能力时，或者这部分能力比较弱，或者能力不对等时，会导致信息传输不完整、不准确的问题，通过扩展语义的获取处理，可以避免这类问题，使得接收端获取发送端希望传递的完整信息，从而更好地支持物联、智联场景下信息传输过程中信息完整性和传输准确性的通信需求；另一方面，当交互的至少一方是在待交互信息中添加了核心语义信息以外的冗余信息(核心语义信息即为接收端期望接收的关键信息，冗余信息即为非核心语义信息)，而交互的另一方并不需要这些冗余信息时，会导致信息传输冗余、不准确的问题，通过核心语义的获取处理，可以避免这类问题，使得接收端无需获取发送端发送的冗余信息，更好地支持物联、智联场景下信息传输过程中传输准确性的通信需求，提高传输效率。
需要指出的是，上面这些示例可以结合上述本申请实施例中的各种可能性，此处不做赘述。
图25是根据本申请一实施例的终端设备2500的示意性框图。该终端设备2500可以包括：第一语义获取单元2510，用于对信源进行语义获取处理，得到语义信息；第一处理单元2520，用于根据所述语义信息，确定待传输的第一信息；第一发送单元2530，用于发送所述第一信息。
在一种可能的实现方式中，所述第一处理单元，用于采用包括以下至少之一的方式得到所述待传输的第一信息：
对所述语义信息进行编码调制后，得到所述第一信息；
对所述语义信息进行编码调制及加密后，得到所述第一信息。
在一种可能的实现方式中，所述第一语义获取单元，用于对所述信源进行扩展语义的获取处理，得到扩展语义信息。
在一种可能的实现方式中，所述第一语义获取单元，用于对所述信源进行核心语义的获取处理，得到核心语义信息。
在一种可能的实现方式中，所述第一语义获取单元，用于对所述信源进行扩展语义的获取处理，得到扩展语义信息；对所述信源进行核心语义的获取处理，得到核心语义信息；根据所述扩展语义信息和所述核心语义信息，得到组合语义信息。
在一种可能的实现方式中，所述第一语义获取单元，用于采用包括以下至少之一方式得到所述扩展语义信息：
将所述信源输入训练好的第一网络模型中，得到情绪信息、强调信息、关联信息、预测信息、不同任务优先级信息中的至少一项；
将所述信源输入训练好的第二网络模型中，得到不同的情绪信息分类、不同的强调信息分类、不同的关联信息补充、不同的预测信息补充、不同任务优先级信息补充中的至少一项。
在一种可能的实现方式中，所述扩展语义信息包括：情绪信息、强调信息、关联信息、预测信息、不同任务优先级信息中的至少一项。
在一种可能的实现方式中，还包括：将所述扩展语义信息中的每一项信息基于不同分类进行分类处理，并采用对应的标识信息作为分类标识；根据所述分类标识和对应的分类描述建立映射关系。
在一种可能的实现方式中，所述第一语义获取单元，用于将所述信源输入训练好的第三网络模型中，得到所述核心语义信息。
本申请实施例的终端设备2500能够实现前述的方法实施例中的终端设备的对应功能。该终端设备2500中的各个模块(子模块、单元或组件等)对应的流程、功能、实现方式以及有益效果，可参见上述方法实施例中的对应描述，在此不再赘述。需要说明，关于申请实施例的终端设备2500中的各个模块(子模块、单元或组件等)所描述的功能，可以由不同的模块(子模块、单元或组件等)实现，也可以由同一个模块(子模块、单元或组件等)实现。
图26是根据本申请一实施例的终端设备2600的示意性框图。该终端设备2600可以包括：第一接收单元2610，用于接收第二信息；第二处理单元2620，用于从所述第二信息中恢复出信源；第二语义获取单元2630，用于对所述信源进行语义获取处理，得到语义信息。
在一种可能的实现方式中，所述第二处理单元，用于采用包括以下至少之一恢复出所述信源：
对所述第二信息进行解码解调后，得到所述信源；
对所述第二信息进行解码解调及解密后，得到所述信源。
在一种可能的实现方式中，所述第二语义获取单元，用于对所述信源进行扩展语义的获取处理，得到扩展语义信息。
在一种可能的实现方式中，所述第二语义获取单元，用于对所述信源进行核心语义的获取处理，得到核心语义信息。
在一种可能的实现方式中，所述第二语义获取单元，用于对所述信源进行扩展语义的获取处理，得到扩展语义信息；对所述信源进行核心语义的获取处理，得到核心语义信息；根据所述扩展语义信息和所述核心语义信息，得到组合语义信息。
在一种可能的实现方式中，所述第二语义获取单元，用于采用包括以下至少之一方式得到所述扩展语义信息：
将所述信源输入训练好的第四网络模型中，得到情绪信息、强调信息、关联信息、预测信息、不同任务优先级信息中的至少一项；
将所述信源输入训练好的第五网络模型中，得到不同的情绪信息分类、不同的强调信息分类、不同的关联信息补充、不同的预测信息补充、不同任务优先级信息补充中的至少一项。
在一种可能的实现方式中，所述扩展语义信息包括：情绪信息、强调信息、关联信息、预测信息、不同任务优先级信息中的至少一项。
在一种可能的实现方式中，还包括第三处理单元，用于将所述扩展语义信息中的每一项信息基于不同分类进行分类处理，并采用对应的标识信息作为分类标识；根据所述分类标识和对应的分类描述建立映射关系。
在一种可能的实现方式中，所述第二语义获取单元，用于将所述信源输入训练好的第六网络模型中，得到所述核心语义。
本申请实施例的终端设备2600能够实现前述的方法实施例中的终端设备的对应功能。该终端设备2600中的各个模块(子模块、单元或组件等)对应的流程、功能、实现方式以及有益效果，可参见上述方法实施例中的对应描述，在此不再赘述。需要说明，关于申请实施例的终端设备2600中的各个模块(子模块、单元或组件等)所描述的功能，可以由不同的模块(子模块、单元或组件等)实现，也可以由同一个模块(子模块、单元或组件等)实现。
图27是根据本申请一实施例的网络设备的示意性框图。该网络设备2700可以包括：第二接收单元2710，用于接收第一信息；第三处理单元2720，用于从所述第一信息中恢复出语义信息；其中，所述语义信息为：终端设备侧通过对信源进行语义获取处理所得到的信息。
在一种可能的实现方式中，所述第三处理单元，用于采用包括以下至少之一方式从所述第一信息中恢复出语义信息：
对所述第一信息进行解码解调后，得到所述语义信息；
对所述第一信息进行解码解调及解密后，得到所述语义信息。
在一种可能的实现方式中，所述语义信息包括：扩展语义信息、核心语义信息中的至少一项。
在一种可能的实现方式中，所述扩展语义信息，包括：情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项。
在一种可能的实现方式中，所述扩展语义信息，包括：情绪信息分类、强调信息分类、关联信息补充、预测信息补充、任务优先级信息补充中的至少一项。
在一种可能的实现方式中，所述核心语义信息，包括：行为、动作、指令、数据、命令中的至少一项。
本申请实施例的网络设备2700能够实现前述的方法实施例中的终端设备的对应功能。该网络设备2700中的各个模块(子模块、单元或组件等)对应的流程、功能、实现方式以及有益效果，可参见上述方法实施例中的对应描述，在此不再赘述。需要说明，关于申请实施例的网络设备2700中的各个模块(子模块、单元或组件等)所描述的功能，可以由不同的模块(子模块、单元或组件等)实现，也可以由同一个模块(子模块、单元或组件等)实现。
图28是根据本申请一实施例的网络设备的示意性框图。该网络设备2800包括：第四处理单元2810，用于根据信源确定待传输的第二信息；其中，所述信源包括待执行语义获取处理的语义信息；第二发送单元2820，用于发送所述第二信息。
在一种可能的实现方式中，所述第四处理单元，用于采用包括以下至少之一方式确定待传输的第二信息：
对所述信源进行编码调制后，得到所述第二信息；
对所述信源进行编码调制及加密后，得到所述第二信息。
在一种可能的实现方式中，所述语义信息包括：扩展语义信息、核心语义信息中的至少一项。
在一种可能的实现方式中，所述扩展语义信息，包括：情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项。
在一种可能的实现方式中，所述扩展语义信息，包括：情绪信息分类、强调信息分类、关联信息补充、预测信息补充、任务优先级信息补充中的至少一项。
在一种可能的实现方式中，所述核心语义信息，包括：行为、动作、指令、数据、命令中的至少一项。
本申请实施例的网络设备2800能够实现前述的方法实施例中的终端设备的对应功能。该网络设备2800中的各个模块(子模块、单元或组件等)对应的流程、功能、实现方式以及有益效果，可参见上述方法实施例中的对应描述，在此不再赘述。需要说明，关于申请实施例的网络设备2800中的各个模块(子模块、单元或组件等)所描述的功能，可以由不同的模块(子模块、单元或组件等)实现，也可以由同一个模块(子模块、单元或组件等)实现。
图29是根据本申请实施例的通信设备2900示意性结构图。该通信设备2900包括处理器2910，处理器2910可以从存储器中调用并运行计算机程序，以使通信设备2900实现本申请实施例中的方法。
可选地，通信设备2900还可以包括存储器2920。其中，处理器2910可以从存储器2920中调用并运行计算机程序，以使通信设备2900实现本申请实施例中的方法。
其中，存储器2920可以是独立于处理器2910的一个单独的器件，也可以集成在处理器2910中。
可选地，通信设备2900还可以包括收发器2930，处理器2910可以控制该收发器2930与其他设备进行通信，具体地，可以向其他设备发送信息或数据，或接收其他设备发送的信息或数据。
其中，收发器2930可以包括发射机和接收机。收发器2930还可以进一步包括天线，天线的数量可以为一个或多个。
可选地，该通信设备2900可为本申请实施例的作为发送端的终端设备，并且该通信设备2900可以实现本申请实施例的各个方法中由终端设备实现的相应流程，为了简洁，在此不再赘述。
可选地，该通信设备2900可为本申请实施例的作为接收端的终端设备，并且该通信设备2900可以实现本申请实施例的各个方法中由终端设备实现的相应流程，为了简洁，在此不再赘述。
图30是根据本申请实施例的芯片3000的示意性结构图。该芯片3000包括处理器3010，处理器3010可以从存储器中调用并运行计算机程序，以实现本申请实施例中的方法。
可选地，芯片3000还可以包括存储器3026。其中，处理器3010可以从存储器3026中调用并运行计算机程序，以实现本申请实施例中由终端设备或者终端设备执行的方法。
其中，存储器3026可以是独立于处理器3010的一个单独的器件，也可以集成在处理器3010中。
可选地，该芯片3000还可以包括输入接口3030。其中，处理器3010可以控制该输入接口3030与其他设备或芯片进行通信，具体地，可以获取其他设备或芯片发送的信息或数据。
可选地，该芯片3000还可以包括输出接口3040。其中，处理器3010可以控制该输出接口3040与其他设备或芯片进行通信，具体地，可以向其他设备或芯片输出信息或数据。
可选地，该芯片可应用于本申请实施例中作为发送端的终端设备，并且该芯片可以实现本申请实施例的各个方法中由终端设备实现的相应流程，为了简洁，在此不再赘述。
可选地，该芯片可应用于本申请实施例中作为接收端的终端设备，并且该芯片可以实现本申请实施例的各个方法中由终端设备实现的相应流程，为了简洁，在此不再赘述。
应用于作为发送端的终端设备和作为接收端的终端设备的芯片可以是相同的芯片或不同的芯片。
应理解，本申请实施例提到的芯片还可以称为系统级芯片，系统芯片，芯片系统或片上系统芯片等。
上述提及的处理器可以是通用处理器、数字信号处理器(digital signal processor，DSP)、现成可编程门阵列(field programmable gate array，FPGA)、专用集成电路(application specific integrated circuit，ASIC)或者其他可编程逻辑器件、晶体管逻辑器件、分立硬件组件等。其中，上述提到的通用处理器可以是微处理器或者也可以是任何常规的处理器等。
上述提及的存储器可以是易失性存储器或非易失性存储器，或可包括易失性和非易失性存储器两者。其中，非易失性存储器可以是只读存储器(read-only memory，ROM)、可编程只读存储器(programmable ROM，PROM)、可擦除可编程只读存储器(erasable PROM，EPROM)、电可擦除可编程只读存储器(electrically EPROM，EEPROM)或闪存。易失性存储器可以是随机存取存储器(random access memory，RAM)。
应理解，上述存储器为示例性但不是限制性说明，例如，本申请实施例中的存储器还可以是静态随机存取存储器(static RAM，SRAM)、动态随机存取存储器(dynamic RAM，DRAM)、同步动态随机存取存储器(synchronous DRAM，SDRAM)、双倍数据速率同步动态随机存取存储器(double data rate SDRAM，DDR SDRAM)、增强型同步动态随机存取存储器(enhanced SDRAM，ESDRAM)、同步连接动态随机存取存储器(synch link DRAM，SLDRAM)以及直接内存总线随机存取存储器(Direct Rambus RAM，DR RAM)等等。也就是说，本申请实施例中的存储器旨在包括但不限于这些和任意其它适合类型的存储器。
图31是根据本申请实施例的通信系统3100的示意性框图。该通信系统3100包括作为发送端的终端设备3110和作为接收端的网络设备3120，接收端还可以是另一个终端设备，不做赘述。其中，该作为发送端的3110可以包括：第一语义获取单元，用于对信源进行语义获取处理，得到语义信息；第一处理单元，用于根据所述语义信息，得到待传输的第一信息；第一发送单元，用于发送所述第一信息。该作为接收端的网络设备3120可以包括：第二接收单元，用于接收第一信息；第三处理单元，用于从所述第一信息中恢复出语义信息；其中，所述语义信息为：终端设备侧通过对信源 进行语义获取处理所得到的信息。其中，该作为发送端的3110可以用于实现上述方法中由终端设备实现的相应的以编码为主的语义通信功能，以及该作为接收端的网络设备3120可以用于实现上述方法中由网络设备实现的相应的解码为主的语义通信功能。为了简洁，在此不再赘述。
在上述实施例中，可以全部或部分地通过软件、硬件、固件或者其任意组合来实现。当使用软件实现时，可以全部或部分地以计算机程序产品的形式实现。该计算机程序产品包括一个或多个计算机指令。在计算机上加载和执行该计算机程序指令时，全部或部分地产生按照本申请实施例中的流程或功能。该计算机可以是通用计算机、专用计算机、计算机网络、或者其他可编程装置。该计算机指令可以存储在计算机可读存储介质中，或者从一个计算机可读存储介质向另一个计算机可读存储介质传输，例如，该计算机指令可以从一个网站站点、计算机、服务器或数据中心通过有线(例如同轴电缆、光纤、数字用户线(Digital Subscriber Line，DSL))或无线(例如红外、无线、微波等)方式向另一个网站站点、计算机、服务器或数据中心进行传输。该计算机可读存储介质可以是计算机能够存取的任何可用介质或者是包含一个或多个可用介质集成的服务器、数据中心等数据存储设备。该可用介质可以是磁性介质，(例如，软盘、硬盘、磁带)、光介质(例如，DVD)、或者半导体介质(例如固态硬盘(Solid State Disk，SSD))等。
应理解，在本申请的各种实施例中，上述各过程的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请实施例的实施过程构成任何限定。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
以上所述仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以该权利要求的保护范围为准。

Claims (71)

  1. 一种语义通信的传输方法，应用于终端设备，所述方法包括：
    所述终端设备对信源进行语义获取处理，得到语义信息；
    所述终端设备根据所述语义信息，确定待传输的第一信息；
    所述终端设备发送所述第一信息。
  2. 根据权利要求1所述的方法，其中，所述终端设备根据所述语义信息，确定待传输的第一信息，包括以下至少之一：
    所述终端设备对所述语义信息进行编码调制后，得到所述第一信息；
    所述终端设备对所述语义信息进行编码调制及加密后，得到所述第一信息。
  3. 根据权利要求1或2所述的方法，其中，所述终端设备对信源进行语义获取处理，得到语义信息，包括：
    所述终端设备对所述信源进行扩展语义的获取处理，得到扩展语义信息。
  4. 根据权利要求1或2所述的方法，其中，所述终端设备对信源进行语义获取处理，得到语义信息，包括：
    所述终端设备对所述信源进行核心语义的获取处理，得到核心语义信息。
  5. 根据权利要求1或2所述的方法，其中，所述终端设备对信源进行语义获取处理，得到语义信息，包括：
    所述终端设备对所述信源进行扩展语义的获取处理，得到扩展语义信息；
    所述终端设备对所述信源进行核心语义的获取处理，得到核心语义信息；
    所述终端设备根据所述扩展语义信息和所述核心语义信息，得到组合语义信息。
  6. 根据权利要求3或5所述的方法，其中，所述终端设备对所述信源进行扩展语义的获取处理，得到扩展语义信息，包括以下至少之一：
    将所述信源输入训练好的第一网络模型中，得到情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项；
    将所述信源输入训练好的第二网络模型中，得到情绪信息分类、强调信息分类、关联信息补充、预测信息补充、任务优先级信息补充中的至少一项。
  7. 根据权利要求3或5所述的方法，其中，所述扩展语义信息包括：情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项。
  8. 根据权利要求7所述的方法，还包括：
    将所述扩展语义信息中的每一项信息进行分类，并采用对应的标识信息作为分类标识；
    根据所述分类标识和对应的分类描述建立映射关系。
  9. 根据权利要求4或5所述的方法，其中，所述终端设备对所述信源进行核心语义的获取处理，得到核心语义信息，包括：
    将所述信源输入训练好的第三网络模型中，得到所述核心语义信息。
  10. 一种语义通信的传输方法，应用于终端设备，所述方法包括：
    所述终端设备接收第二信息；
    所述终端设备从所述第二信息中恢复出信源；
    所述终端设备对所述信源进行语义获取处理，得到语义信息。
  11. 根据权利要求10所述的方法，所述终端设备从所述第二信息中恢复出信源，包括以下至少之一：
    所述终端设备对所述第二信息进行解码解调后，得到所述信源；
    所述终端设备对所述第二信息进行解码解调及解密后，得到所述信源。
  12. 根据权利要求10或11所述的方法，其中，所述终端设备对所述信源进行语义获取处理，得到语义信息，包括：
    所述终端设备对所述信源进行扩展语义的获取处理，得到扩展语义信息。
  13. 根据权利要求10或11所述的方法，其中，所述终端设备对所述信源进行语义获取处理，得到语义信息，包括：
    所述终端设备对所述信源进行核心语义的获取处理，得到核心语义信息。
  14. 根据权利要求10或11所述的方法，其中，所述终端设备对所述信源进行语义获取处理，得到语义信息，包括：
    所述终端设备对所述信源进行扩展语义的获取处理，得到扩展语义信息；
    所述终端设备对所述信源进行核心语义的获取处理，得到核心语义信息；
    所述终端设备根据所述扩展语义信息和所述核心语义信息，得到组合语义信息。
  15. 根据权利要求12或14所述的方法，其中，所述终端设备对所述信源进行扩展语义的获取处理，得到扩展语义信息，包括以下至少之一：
    将所述信源输入训练好的第四网络模型中，得到情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项；
    将所述信源输入训练好的第五网络模型中，得到情绪信息分类、强调信息分类、关联信息补充、预测信息补充、任务优先级信息补充中的至少一项。
  16. 根据权利要求12或14所述的方法，其中，所述扩展语义信息包括：情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项。
  17. 根据权利要求16所述的方法，还包括：
    将所述扩展语义信息中的每一项信息进行分类，并采用对应的标识信息作为分类标识；
    根据所述分类标识和对应的分类描述建立映射关系。
  18. 根据权利要求13或14所述的方法，其中，所述终端设备对所述信源进行核心语义的获取处理，得到核心语义信息，包括：
    将所述信源输入训练好的第六网络模型中，得到所述核心语义。
  19. 一种语义通信的传输方法，应用于网络设备，所述方法包括：
    所述网络设备接收第一信息；
    所述网络设备从所述第一信息中恢复出语义信息；
    其中，所述语义信息为：终端设备侧通过对信源进行语义获取处理所得到的信息。
  20. 根据权利要求19所述的方法，所述网络设备从所述第一信息中恢复出语义信息，包括以下至少之一：
    所述网络设备对所述第一信息进行解码解调后，得到所述语义信息；
    所述网络设备对所述第一信息进行解码解调及解密后，得到所述语义信息。
  21. 根据权利要求19或20所述的方法，其中，所述语义信息包括：扩展语义信息、核心语义信息中的至少一项。
  22. 根据权利要求21所述的方法，其中，所述扩展语义信息，包括：情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项。
  23. 根据权利要求21所述的方法，其中，所述扩展语义信息，包括：情绪信息分类、强调信息分类、关联信息补充、预测信息补充、任务优先级信息补充中的至少一项。
  24. 根据权利要求21所述的方法，其中，所述核心语义信息，包括：行为、动作、指令、数据、命令中的至少一项。
  25. 一种语义通信的传输方法，应用于网络设备，所述方法包括：
    所述网络设备根据信源确定待传输的第二信息；其中，所述信源包括待执行语义获取处理的语义信息；
    所述网络设备发送所述第二信息。
  26. 根据权利要求25所述的方法，其中，所述网络设备根据信源确定待传输的第二信息，包括以下至少之一：
    所述网络设备对所述信源进行编码调制后，得到所述第二信息；
    所述网络设备对所述信源进行编码调制及加密后，得到所述第二信息。
  27. 根据权利要求25或26所述的方法，其中，所述语义信息包括：扩展语义信息、核心语义信息中的至少一项。
  28. 根据权利要求27所述的方法，其中，所述扩展语义信息，包括：情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项。
  29. 根据权利要求27所述的方法，其中，所述扩展语义信息，包括：情绪信息分类、强调信息分类、关联信息补充、预测信息补充、任务优先级信息补充中的至少一项。
  30. 根据权利要求27所述的方法，其中，所述核心语义信息，包括：行为、动作、指令、数据、命令中的至少一项。
  31. 一种终端设备，包括：
    第一语义获取单元，用于对信源进行语义获取处理，得到语义信息；
    第一处理单元，用于根据所述语义信息，确定待传输的第一信息；
    第一发送单元，用于发送所述第一信息。
  32. 根据权利要求31所述的终端设备，其中，所述第一处理单元，用于采用包括以下至少之一的方式确定所述待传输的第一信息：
    对所述语义信息进行编码调制后，得到所述第一信息；
    对所述语义信息进行编码调制及加密后，得到所述第一信息。
  33. 根据权利要求31或32所述的终端设备，其中，所述第一语义获取单元，用于：
    对所述信源进行扩展语义的获取处理，得到扩展语义信息。
  34. 根据权利要求31或32所述的终端设备，其中，所述第一语义获取单元，用于：
    对所述信源进行核心语义的获取处理，得到核心语义信息。
  35. 根据权利要求31或32所述的终端设备，其中，所述第一语义获取单元，用于：
    对所述信源进行扩展语义的获取处理，得到扩展语义信息；
    对所述信源进行核心语义的获取处理，得到核心语义信息；
    根据所述扩展语义信息和所述核心语义信息，得到组合语义信息。
  36. 根据权利要求33或35所述的终端设备，其中，所述第一语义获取单元，用于采用包括以下至少之一方式得到所述扩展语义信息：
    将所述信源输入训练好的第一网络模型中，得到情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项；
    将所述信源输入训练好的第二网络模型中，得到情绪信息分类、强调信息分类、关联信息补充、预测信息补充、任务优先级信息补充中的至少一项。
  37. 根据权利要求33或35所述的终端设备，其中，所述扩展语义信息包括：情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项。
  38. 根据权利要求37所述的终端设备，还包括：
    将所述扩展语义信息中的每一项信息进行分类，并采用对应的标识信息作为分类标识；
    根据所述分类标识和对应的分类描述建立映射关系。
  39. 根据权利要求34或35所述的终端设备，其中，所述第一语义获取单元，用于：
    将所述信源输入训练好的第三网络模型中，得到所述核心语义信息。
  40. 一种终端设备，包括：
    第一接收单元，用于接收第二信息；
    第二处理单元，用于从所述第二信息中恢复出信源；
    第二语义获取单元，用于对所述信源进行语义获取处理，得到语义信息。
  41. 根据权利要求40所述的终端设备，所述第二处理单元，用于采用包括以下至少之一恢复出所述信源：
    对所述第二信息进行解码解调后，得到所述信源；
    对所述第二信息进行解码解调及解密后，得到所述信源。
  42. 根据权利要求40或41所述的终端设备，其中，所述第二语义获取单元，用于：
    所述终端设备对所述信源进行扩展语义的获取处理，得到扩展语义信息。
  43. 根据权利要求40或41所述的终端设备，其中，所述第二语义获取单元，用于：
    所述终端设备对所述信源进行核心语义的获取处理，得到核心语义信息。
  44. 根据权利要求40或41所述的终端设备，其中，所述第二语义获取单元，用于：
    所述终端设备对所述信源进行扩展语义的获取处理，得到扩展语义信息；
    所述终端设备对所述信源进行核心语义的获取处理，得到核心语义信息；
    所述终端设备根据所述扩展语义信息和所述核心语义信息，得到组合语义信息。
  45. 根据权利要求42或44所述的终端设备，其中，所述第二语义获取单元，用于采用包括以下至少之一方式得到所述扩展语义信息：
    将所述信源输入训练好的第四网络模型中，得到情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项；
    将所述信源输入训练好的第五网络模型中，得到情绪信息分类、强调信息分类、关联信息补充、预测信息补充、任务优先级信息补充中的至少一项。
  46. 根据权利要求42或44所述的终端设备，其中，所述扩展语义信息包括：情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项。
  47. 根据权利要求46所述的终端设备，还包括第三处理单元，用于：
    将所述扩展语义信息中的每一项信息进行分类，并采用对应的标识信息作为分类标识；
    根据所述分类标识和对应的分类描述建立映射关系。
  48. 根据权利要求43或44所述的终端设备，其中，所述第二语义获取单元，用于：
    将所述信源输入训练好的第六网络模型中，得到所述核心语义。
  49. 一种网络设备，所述网络设备包括：
    第二接收单元，用于接收第一信息；
    第三处理单元，用于从所述第一信息中恢复出语义信息；
    其中，所述语义信息为：终端设备侧通过对信源进行语义获取处理所得到的信息。
  50. 根据权利要求49所述的网络设备，其中，所述第三处理单元，用于采用包括以下至少之一方式从所述第一信息中恢复出语义信息：
    对所述第一信息进行解码解调后，得到所述语义信息；
    对所述第一信息进行解码解调及解密后，得到所述语义信息。
  51. 根据权利要求49或50所述的网络设备，其中，所述语义信息包括：扩展语义信息、核心语义信息中的至少一项。
  52. 根据权利要求51所述的网络设备，其中，所述扩展语义信息，包括：情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项。
  53. 根据权利要求51所述的网络设备，其中，所述扩展语义信息，包括：情绪信息分类、强调信息分类、关联信息补充、预测信息补充、任务优先级信息补充中的至少一项。
  54. 根据权利要求51所述的网络设备，其中，所述核心语义信息，包括：行为、动作、指令、数据、命令中的至少一项。
  55. 一种网络设备，所述网络设备包括：
    第四处理单元，用于根据信源确定待传输的第二信息；其中，所述信源包括待执行语义获取处理的语义信息；
    第二发送单元，用于发送所述第二信息。
  56. 根据权利要求55所述的网络设备，其中，所述第四处理单元，用于采用包括以下至少之一方式确定待传输的第二信息：
    对所述信源进行编码调制后，得到所述第二信息；
    对所述信源进行编码调制及加密后，得到所述第二信息。
  57. 根据权利要求55或56所述的网络设备，其中，所述语义信息包括：扩展语义信息、核心语义信息中的至少一项。
  58. 根据权利要求57所述的网络设备，其中，所述扩展语义信息，包括：情绪信息、强调信息、关联信息、预测信息、任务优先级信息中的至少一项。
  59. 根据权利要求57所述的网络设备，其中，所述扩展语义信息，包括：情绪信息分类、强调信息分类、关联信息补充、预测信息补充、任务优先级信息补充中的至少一项。
  60. 根据权利要求57所述的网络设备，其中，所述核心语义信息，包括：行为、动作、指令、数据、命令中的至少一项。
  61. 一种终端设备，包括：处理器和存储器，该存储器用于存储计算机程序，所述处理器用于调用并运行所述存储器中存储的计算机程序，以使所述终端设备执行如权利要求1至18中任一项所述的方法。
  62. 一种网络设备，包括：处理器和存储器，该存储器用于存储计算机程序，所述处理器用于调用并运行所述存储器中存储的计算机程序，以使所述终端设备执行如权利要求19至30中任一项所述的方法。
  63. 一种芯片，包括：处理器，用于从存储器中调用并运行计算机程序，使得安装有所述芯片的设备执行如权利要求1至18中任一项所述的方法。
  64. 一种芯片，包括：处理器，用于从存储器中调用并运行计算机程序，使得安装有所述芯片的设备执行如权利要求19至30中任一项所述的方法。
  65. 一种计算机可读存储介质，用于存储计算机程序，当所述计算机程序被设备运行时使得所述设备执行如权利要求1至18中任一项所述的方法。
  66. 一种计算机可读存储介质，用于存储计算机程序，当所述计算机程序被设备运行时使得所述设备执行如权利要求19至30中任一项所述的方法。
  67. 一种计算机程序产品，包括计算机程序指令，该计算机程序指令使得计算机执行如权利要求1至18中任一项所述的方法。
  68. 一种计算机程序产品，包括计算机程序指令，该计算机程序指令使得计算机执行如权利要求19至30中任一项所述的方法。
  69. 一种计算机程序，所述计算机程序使得计算机执行如权利要求1至18中任一项所述的方法。
  70. 一种计算机程序，所述计算机程序使得计算机执行如权利要求19至30中任一项所述的方法。
  71. 一种通信系统，包括：
    终端设备，用于执行如权利要求1至18中任一项所述的方法；
    网络设备，用于执行如权利要求19至30中任一项所述的方法。
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