CN117914445A

CN117914445A - Semantic importance-based semantic communication method and system

Info

Publication number: CN117914445A
Application number: CN202311783085.0A
Authority: CN
Inventors: 董辰; 刘昱成; 鲍智成; 徐茗; 许晓东
Original assignee: Beijing University of Posts and Telecommunications
Current assignee: Beijing University of Posts and Telecommunications
Priority date: 2023-12-22
Filing date: 2023-12-22
Publication date: 2024-04-19

Abstract

The application provides a semantic communication method and a semantic communication system based on semantic importance, wherein the method comprises the following steps: obtaining target semantic information of the communication data according to the semantic encoder; carrying out importance ranking on each semantic symbol in the target semantic information; according to the importance sequencing result, arranging the semantic symbols at the time points of pilot frequency inserted in OFDM in sequence to obtain an arranged semantic symbol sequence; transmitting the semantic symbol sequence to a receiving end through a wireless channel, so that the receiving end carries out channel estimation on the wireless channel based on a channel estimation algorithm and pilot frequency inserted in OFDM (orthogonal frequency division multiplexing) to obtain a channel estimation value; equalizing the semantic symbol sequence based on the channel estimation value and a channel equalization algorithm to obtain an equalized semantic symbol sequence; and recovering the balanced semantic symbol sequence into target communication data corresponding to the communication data based on a semantic decoder. The application can effectively improve the reliability and accuracy of semantic communication.

Description

Semantic importance-based semantic communication method and system

Technical Field

The application relates to the field of semantic communication, in particular to a semantic communication method and system based on semantic importance.

Background

A time-varying channel refers to a situation in which the channel characteristics change over time in a communication system. In time-varying channels, the characteristics of the transmitted signal, such as attenuation, phase change, multipath effects, interference, etc., in the channel may change over time. We often encounter time-varying channels in daily life, where the channel gain varies over time. In the face of a time-varying channel, a time-varying channel gain is obtained by inserting multiple pilots. Under time-varying channels, the channel variation is not too large in a short time because the characteristics of the wireless channel are typically smoothly varying. Therefore, the channel estimation under the time-varying channel has a key characteristic, the closer the data channel estimation value at the pilot frequency is to the true value in the time domain, the higher the accuracy of the channel estimation is, and the better the corresponding recovery effect is. Semantic communication is a new paradigm for the development of next-generation communication. The importance degree of semantic information is different in semantic communication, wherein important semantic information determines the original appearance of the information to a great extent, and unimportant semantic information has little influence on information recovery, so that the reliability of the important semantic information is particularly important in the transmission process.

The existing semantic communication method does not consider semantic importance, so that communication reliability is poor and accuracy is low.

Disclosure of Invention

In view of this, embodiments of the present application provide a semantic communication method and system based on semantic importance, so as to eliminate or improve one or more drawbacks existing in the prior art.

A first aspect of the present application provides a semantic communication method based on semantic importance, the method comprising:

obtaining target semantic information of the communication data according to the semantic encoder;

Carrying out importance ranking on each semantic symbol in the target semantic information;

according to the importance sequencing result, arranging the semantic symbols at the time points of pilot frequency inserted in OFDM in sequence to obtain an arranged semantic symbol sequence;

Transmitting the semantic symbol sequence to a receiving end through a wireless channel, so that the receiving end carries out channel estimation on the wireless channel based on a channel estimation algorithm and pilot frequency inserted in OFDM (orthogonal frequency division multiplexing) to obtain a channel estimation value; equalizing the semantic symbol sequence based on the channel estimation value and a channel equalization algorithm to obtain an equalized semantic symbol sequence; and recovering the balanced semantic symbol sequence into target communication data corresponding to the communication data based on a semantic decoder.

In some embodiments of the present application, the ranking the importance of each semantic symbol in the target semantic information includes:

Inputting the semantic symbols into a pre-acquired importance ranking model to obtain entropy values corresponding to the semantic symbols, and ranking the entropy values based on a preset threshold value.

In some embodiments of the application, the communication data comprises: at least one of text data, image data, and video data.

In some embodiments of the application, the importance ranking model comprises: neural network models or entropy models.

A third aspect of the present application provides a semantic communication method based on semantic importance, the method comprising:

receiving a semantic symbol sequence sent by a sending end; the semantic symbol sequence is obtained by the sending end according to the target semantic information of the communication data obtained by the semantic encoder, importance sorting is carried out on each semantic symbol in the target semantic information, and each semantic symbol is orderly arranged at the time point of pilot frequency inserted in OFDM according to the importance sorting result;

Performing channel estimation on the wireless channel based on a channel estimation algorithm and the inserted pilot frequency in OFDM to obtain a channel estimation value;

equalizing the semantic symbol sequence based on the channel estimation value and a channel equalization algorithm to obtain an equalized semantic symbol sequence;

and recovering the balanced semantic symbol sequence into target communication data corresponding to the communication data based on a semantic decoder.

In some embodiments of the application, the channel estimation algorithm comprises: LS algorithm, MMSE algorithm or LMMSE algorithm.

In some embodiments of the application, the channel equalization method comprises a ZF algorithm or an MMSE algorithm.

A third aspect of the present application provides a semantic communication system based on semantic importance, the apparatus comprising:

a transmitting end and a receiving end which are in communication connection;

the sending end is used for executing the semantic importance-based semantic communication method according to the first aspect;

the receiving end is configured to execute the semantic importance-based semantic communication method according to the second aspect.

A fourth aspect of the present application provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the semantic importance based semantic communication method according to the first aspect described above when executing the computer program.

A fifth aspect of the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the semantic significance based semantic communication method of the first aspect described above.

Additional advantages, objects, and features of the application will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and drawings.

It will be appreciated by those skilled in the art that the objects and advantages that can be achieved with the present application are not limited to the above-described specific ones, and that the above and other objects that can be achieved with the present application will be more clearly understood from the following detailed description.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate and together with the description serve to explain the application. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the application. Corresponding parts in the drawings may be exaggerated, i.e. made larger relative to other parts in an exemplary device actually manufactured according to the present application, for convenience in showing and describing some parts of the present application. In the drawings:

Fig. 1 is a flow chart of a semantic importance based semantic communication method executed by a sender according to an embodiment of the present application.

Fig. 2 is a schematic structural diagram of a semantic communication system based on semantic importance according to another embodiment of the present application.

Fig. 3 is a flow chart of a semantic importance based semantic communication method performed by a receiving end according to another embodiment of the present application.

Detailed Description

The present application will be described in further detail with reference to the following embodiments and the accompanying drawings, in order to make the objects, technical solutions and advantages of the present application more apparent. The exemplary embodiments of the present application and the descriptions thereof are used herein to explain the present application, but are not intended to limit the application.

It should be noted here that, in order to avoid obscuring the present application due to unnecessary details, only structures and/or processing steps closely related to the solution according to the present application are shown in the drawings, while other details not greatly related to the present application are omitted.

It should be emphasized that the term "comprises/comprising" when used herein is taken to specify the presence of stated features, elements, steps or components, but does not preclude the presence or addition of one or more other features, elements, steps or components.

It is also noted herein that the term "coupled" may refer to not only a direct connection, but also an indirect connection in which an intermediate is present, unless otherwise specified.

Hereinafter, embodiments of the present application will be described with reference to the accompanying drawings. In the drawings, the same reference numerals represent the same or similar components, or the same or similar steps.

The following examples are provided to illustrate the invention in more detail.

The embodiment of the application provides a first semantic communication method based on semantic importance, which can be executed by a sending end, and referring to fig. 1, the semantic communication method based on semantic importance specifically comprises the following contents:

step 110: and obtaining target semantic information of the communication data according to the semantic encoder.

Step 120: and carrying out importance ranking on each semantic symbol in the target semantic information.

Step 130: and according to the importance sequencing result, arranging the semantic symbols at the time points of which pilot frequencies are inserted in the OFDM in sequence to obtain an arranged semantic symbol sequence.

Step 140: transmitting the semantic symbol sequence to a receiving end through a wireless channel, so that the receiving end carries out channel estimation on the wireless channel based on a channel estimation algorithm and pilot frequency inserted in OFDM (orthogonal frequency division multiplexing) to obtain a channel estimation value; equalizing the semantic symbol sequence based on the channel estimation value and a channel equalization algorithm to obtain an equalized semantic symbol sequence; and recovering the balanced semantic symbol sequence into target communication data corresponding to the communication data based on a semantic decoder.

Specifically, the sender (which may be a client device or an electronic device) first inputs communication data into a semantic encoder to output resultant target semantic information. And then, carrying out importance ranking on each semantic symbol in the target semantic information. And according to the importance sequencing result, arranging each semantic symbol in sequence at the time point of pilot frequency inserted in an OFDM (Orthogonal Frequency Division Multiplexing ) system to obtain an arranged semantic symbol sequence. Finally, the semantic symbol sequence is sent to a receiving end through a wireless channel, so that the receiving end carries out channel estimation on the wireless channel based on a channel estimation algorithm and pilot frequency inserted into OFDM to obtain a channel estimation value; equalizing the semantic symbol sequence based on the channel estimation value and a channel equalization algorithm to obtain an equalized semantic symbol sequence; and recovering the balanced semantic symbol sequence into target communication data corresponding to the communication data based on the semantic decoder, so that the reliability and accuracy of semantic communication can be effectively improved.

Wherein the communication data includes: text data, image data, video data, voice data, point cloud data, and the like.

To further improve the reliability and accuracy of communication with semantics, step 120 includes:

Specifically, the sending end inputs each semantic symbol into a pre-acquired importance sorting model to obtain entropy values corresponding to each semantic symbol, and sorts the entropy values based on a preset threshold value, so that reliability and accuracy of semantic communication can be further effectively improved.

Wherein the importance ranking model comprises: neural network models or entropy models.

The embodiment of the application provides a second semantic communication method based on semantic importance, which can be executed by a receiving end, and referring to fig. 3, the semantic communication method based on semantic importance specifically comprises the following contents:

Step 210: receiving a semantic symbol sequence sent by a sending end; the semantic symbol sequence is obtained by the sending end according to the target semantic information of the communication data obtained by the semantic encoder, importance ranking is carried out on each semantic symbol in the target semantic information, and each semantic symbol is orderly arranged at the time point of pilot frequency inserted in OFDM according to the importance ranking result.

Step 220: and carrying out channel estimation on the wireless channel based on a channel estimation algorithm and the inserted pilot frequency in OFDM to obtain a channel estimation value.

Step 230: and carrying out equalization on the semantic symbol sequence based on the channel estimation value and a channel equalization algorithm to obtain an equalized semantic symbol sequence.

Step 240: and recovering the balanced semantic symbol sequence into target communication data corresponding to the communication data based on a semantic decoder.

Specifically, a receiving end firstly receives a semantic symbol sequence sent by a sending end; and then carrying out channel estimation on the wireless channel based on a channel estimation algorithm and the pilot frequency inserted in the OFDM to obtain a channel estimation value. And then, balancing the semantic symbol sequence based on the channel estimation value and a channel balancing algorithm to obtain a balanced semantic symbol sequence. And finally, recovering the balanced semantic symbol sequence into target communication data corresponding to the communication data based on the semantic decoder.

The semantic symbol sequence is obtained by inputting communication data into a semantic encoder by a transmitting end to output target semantic information, carrying out importance sorting on each semantic symbol in the target semantic information, and arranging time points, in which pilot frequency is inserted, of each semantic symbol in the OFDM according to an importance sorting result; the channel estimation algorithm includes: channel estimation algorithms such as LS algorithm (least square), MMSE algorithm (Minimum Mean Square Error, minimum mean square error algorithm), LMMSE algorithm (linear minimum mean square error, linear minimum mean square error algorithm), DFT algorithm (Discrete Fourier Transform ) and SVD algorithm (Singular Value Decomposition, singular value decomposition); the channel equalization method includes a ZF algorithm (zero forcing) or an MMSE algorithm (Minimum Mean Square Error, minimum mean square error algorithm), and a MLSE algorithm (Maximum Likelihood Sequence Estimation ) and the like. The number of subcarriers in OFDM may be set, for example, the OFDM size may be designed to be 64 subcarriers, and 7 OFDM symbols are in the form of one OFDM symbol.

From the software aspect, the present application further provides a semantic communication system based on semantic importance, for executing all or part of the semantic importance-based semantic communication method, referring to fig. 2, where the semantic importance-based semantic communication system specifically includes the following contents:

a transmitting end and a receiving end which are in communication connection;

The sending end is used for executing the first semantic communication method based on semantic importance;

the receiving end is configured to execute the foregoing second semantic communication method based on semantic importance.

The embodiment of the semantic importance based semantic communication system provided by the application can be particularly used for executing the processing flow of the embodiment of the semantic importance based semantic communication method in the embodiment, and the functions of the embodiment of the semantic importance based semantic communication method are not repeated herein, and reference can be made to the detailed description of the embodiment of the semantic importance based semantic communication method.

The embodiment of the application also provides an electronic device, such as a central server, which may include a processor, a memory, a receiver and a transmitter, where the processor is configured to execute the first semantic communication method or the second semantic communication method based on the semantic importance mentioned in the foregoing embodiment, and the processor and the memory may be connected by a bus or other manners, for example, by a bus connection. The receiver may be connected to the processor, memory, by wire or wirelessly.

The processor may be a central processing unit (Central Processing Unit, CPU). The Processor may also be other general purpose processors, digital Signal Processors (DSP), application SPECIFIC INTEGRATED Circuits (ASIC), field-Programmable gate arrays (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above.

The memory, as a non-transitory computer readable storage medium, may be used to store a non-transitory software program, a non-transitory computer executable program, and a module, such as program instructions/modules corresponding to the first semantic communication method or the second semantic communication method based on semantic importance in the embodiments of the present application. The processor executes various functional applications of the processor and data processing by running non-transitory software programs, instructions and modules stored in the memory, i.e. implementing the first semantic communication method or the second semantic communication method based on semantic importance in the above-described method embodiments.

The memory may include a memory program area and a memory data area, wherein the memory program area may store an operating system, at least one application program required for a function; the storage data area may store data created by the processor, etc. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory may optionally include memory located remotely from the processor, the remote memory being connectable to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The one or more modules are stored in the memory that, when executed by the processor, perform the first semantic communication method or the second semantic communication method based on semantic importance in embodiments.

In some embodiments of the present application, a user equipment may include a processor, a memory, and a transceiver unit, which may include a receiver and a transmitter, the processor, the memory, the receiver, and the transmitter may be connected by a bus system, the memory being configured to store computer instructions, the processor being configured to execute the computer instructions stored in the memory to control the transceiver unit to transmit and receive signals.

As an implementation manner, the functions of the receiver and the transmitter in the present application may be considered to be implemented by a transceiver circuit or a dedicated chip for transceiver, and the processor may be considered to be implemented by a dedicated processing chip, a processing circuit or a general-purpose chip.

As another implementation manner, a manner of using a general-purpose computer may be considered to implement the server provided by the embodiment of the present application. I.e. program code for implementing the functions of the processor, the receiver and the transmitter are stored in the memory, and the general purpose processor implements the functions of the processor, the receiver and the transmitter by executing the code in the memory.

The embodiment of the application also provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, implements the steps of the aforementioned first semantic communication method or second semantic communication method based on semantic importance. The computer readable storage medium may be a tangible storage medium such as Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, floppy disks, hard disk, a removable memory disk, a CD-ROM, or any other form of storage medium known in the art.

Those of ordinary skill in the art will appreciate that the various illustrative components, systems, and methods described in connection with the embodiments disclosed herein can be implemented as hardware, software, or a combination of both. The particular implementation is hardware or software dependent on the specific application of the solution and the design constraints. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave.

It should be understood that the application is not limited to the particular arrangements and instrumentality described above and shown in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. The method processes of the present application are not limited to the specific steps described and shown, but various changes, modifications and additions, or the order between steps may be made by those skilled in the art after appreciating the spirit of the present application.

In this disclosure, features that are described and/or illustrated with respect to one embodiment may be used in the same way or in a similar way in one or more other embodiments and/or in combination with or instead of the features of the other embodiments.

The above description is only of the preferred embodiments of the present application and is not intended to limit the present application, and various modifications and variations can be made to the embodiments of the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A semantic communication method based on semantic importance, characterized by comprising:

Sorting the importance of each semantic symbol in the target semantic information;

Arrange the semantic symbols in sequence at the time points where the pilots have been inserted in the OFDM according to the results of the importance sorting, to obtain an arranged semantic symbol sequence;

The semantic symbol sequence is sent to a receiving end via a wireless channel, so that the receiving end performs channel estimation on the wireless channel based on a channel estimation algorithm and a pilot inserted in OFDM to obtain a channel estimation value; the semantic symbol sequence is equalized based on the channel estimation value and a channel equalization algorithm to obtain an equalized semantic symbol sequence; and the equalized semantic symbol sequence is restored to target communication data corresponding to the communication data based on a semantic decoder.

2. The semantic communication method based on semantic importance according to claim 1, characterized in that the importance ranking of each semantic symbol in the target semantic information comprises:

Each of the semantic symbols is input into a pre-acquired importance ranking model to obtain an entropy value corresponding to each of the semantic symbols, and each of the entropy values is ranked based on a preset threshold.

3. The semantic communication method based on semantic importance according to claim 1 is characterized in that the communication data includes: at least one of text data, image data and video data.

4. The semantic communication method based on semantic importance according to claim 2 is characterized in that the importance ranking model includes: a neural network model or an entropy model.

5. A semantic communication method based on semantic importance, characterized by comprising:

Receive a semantic symbol sequence sent by a transmitting end; wherein the semantic symbol sequence is obtained by the transmitting end obtaining target semantic information of communication data according to a semantic encoder, sorting the importance of each semantic symbol in the target semantic information, and arranging each semantic symbol in sequence at a time point where a pilot has been inserted in OFDM according to the result of the importance sorting;

Perform channel estimation on the wireless channel based on a channel estimation algorithm and the inserted pilot in OFDM to obtain a channel estimation value;

The equalized semantic symbol sequence is restored to target communication data corresponding to the communication data based on a semantic decoder.

6. The semantic communication method based on semantic importance according to claim 5 is characterized in that the channel estimation algorithm includes: LS algorithm, MMSE algorithm or LMMSE algorithm.

7. The semantic communication method based on semantic importance according to claim 5, characterized in that the channel equalization method includes a ZF algorithm or an MMSE algorithm.

8. A semantic communication system based on semantic importance, characterized by comprising: a sending end and a receiving end of a communication connection;

The sending end is used to execute the semantic communication method based on semantic importance according to any one of claims 1 to 4;

The receiving end is used to execute the semantic communication method based on semantic importance as described in any one of claims 5-7.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the processor implements the semantic communication method based on semantic importance as described in any one of claims 1 to 4, or executes the semantic communication method based on semantic importance as described in any one of claims 5 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, it implements the semantic communication method based on semantic importance as described in any one of claims 1 to 4, or executes the semantic communication method based on semantic importance as described in any one of claims 5-7.