CN115314086B - Precoding method, device, medium and equipment of communication perception integrated system - Google Patents
Precoding method, device, medium and equipment of communication perception integrated system Download PDFInfo
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- H04B7/00—Radio transmission systems, i.e. using radiation field
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Abstract
The embodiment of the application provides a precoding method, device, medium and equipment of a communication perception integrated system. The method comprises the following steps: according to the received sensing service request, determining a sensing demand parameter corresponding to the sensing service request; allocating non-overlapping sub-carriers for a plurality of target users to generate multi-user baseband signals; taking the mean square error between the minimum user side received signal and the actual transmitted signal as a basic criterion, taking the sensing demand parameter and the maximum transmitting power as constraints, and solving by using an iterative optimization algorithm to determine a target precoding matrix; precoding the multi-user baseband signal according to the target precoding matrix for transmission; and receiving echo signals corresponding to the precoded multi-user baseband signals, and extracting target perception parameters from the echo signals. The technical scheme of the embodiment of the application can improve the precoding processing efficiency and ensure the communication performance of the system.
Description
Technical Field
The present application relates to the field of computers and communications technologies, and in particular, to a precoding method, device, medium and apparatus for a communication perception integrated system.
Background
The goal of communication and perception integration (Integrated Sensing and Communication, ISAC) is to support communication and perception functions on the same frequency spectrum and the same device, so that the frequency spectrum utilization rate can be improved, the device cost can be reduced, and the efficient cooperation and reciprocal reciprocity of the communication and perception functions can be realized.
In the current technical scheme, the communication perception integrated system aiming at multiple carriers needs to perform precoding for multiple times, the calculation difficulty is high, and the communication performance of the system cannot be guaranteed, so that the processing efficiency of precoding is improved, and the communication performance of the system is guaranteed, which is often a technical problem to be solved urgently.
Disclosure of Invention
The embodiment of the application provides a precoding method, a device, a medium and equipment of a communication perception integrated system, which can further improve the precoding processing efficiency at least to a certain extent and ensure the communication performance of the system.
Other features and advantages of the application will be apparent from the following detailed description, or may be learned by the practice of the application.
According to an aspect of the embodiment of the present application, there is provided a precoding method of a communication awareness integrated system, including:
according to the received perception service request, determining a perception demand parameter corresponding to the perception service request, wherein the perception demand parameter is used for describing the maximum deviation degree between the actual perception performance and the ideal perception performance;
allocating non-overlapping sub-carriers for a plurality of target users to generate multi-user baseband signals;
taking the minimum mean square error between the received signal and the actual transmitted signal of the user side as a basic criterion, taking the sensing demand parameter and the maximum transmitting power as constraints, and solving by using an iterative optimization algorithm to determine a target precoding matrix;
precoding the multi-user baseband signal according to the target precoding matrix for transmission;
and receiving echo signals corresponding to the precoded multi-user baseband signals, and extracting target perception parameters from the echo signals.
According to an aspect of an embodiment of the present application, there is provided a precoding apparatus of a communication awareness integrated system, including:
the receiving module is used for determining a perception demand parameter corresponding to the perception service request according to the received perception service request, wherein the perception demand parameter is used for describing the maximum deviation degree between the actual perception performance and the ideal perception performance;
An allocation module, configured to allocate subcarriers that are not overlapped with each other for a plurality of target users, so as to generate a multi-user baseband signal;
the calculation module is used for solving by using an iterative optimization algorithm to determine a target precoding matrix by taking a mean square error between a minimum user side received signal and an actual transmitted signal as a basic criterion and taking the perception demand parameter and the maximum transmitting power as constraints;
the transmitting module is used for precoding the multi-user baseband signals according to the target precoding matrix so as to transmit the multi-user baseband signals;
and the processing module is used for receiving echo signals corresponding to the precoded multi-user baseband signals and extracting target perception parameters from the echo signals.
According to an aspect of the embodiments of the present application, there is provided a computer readable medium having stored thereon a computer program which, when executed by a processor, implements a precoding method of a communication awareness integrated system as described in the above embodiments.
According to an aspect of an embodiment of the present application, there is provided an electronic apparatus including: one or more processors; and a storage device for storing one or more programs, which when executed by the one or more processors, cause the one or more processors to implement the precoding method of the communication awareness integrated system as described in the above embodiments.
According to an aspect of embodiments of the present application, there is provided a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the precoding method of the communication awareness integrated system provided in the above embodiment.
In the technical solutions provided in some embodiments of the present application, according to a received perceived service request, a perceived demand parameter corresponding to the perceived service request is determined, where the perceived demand parameter is used to describe a maximum deviation degree between an actual perceived performance and an ideal perceived performance, and subcarriers that do not overlap each other are allocated to multiple target users, so as to generate a multi-user baseband signal, so that there will be no mutual interference between users, and thus, the pressure of mutual interference suppression on the user side is reduced. And solving by using an iterative optimization algorithm with a minimum mean square error between a user side received signal and an actual transmitted signal as a basic criterion and with a perception demand parameter and a maximum transmitting power as constraints, so as to determine a target precoding matrix, and precoding and transmitting the multi-user baseband signal according to the target precoding matrix. And receiving the corresponding echo signals, and extracting target perception parameters from the echo signals. Therefore, the communication perception integrated system of the multi-carrier only needs to perform precoding once, so that the processing efficiency of precoding is improved, and meanwhile, the communication performance of the system is ensured.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application. It is evident that the drawings in the following description are only some embodiments of the present application and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art. In the drawings:
FIG. 1 shows a schematic diagram of an exemplary system architecture to which the technical solution of an embodiment of the application may be applied;
FIG. 2 shows a schematic diagram of another exemplary system architecture to which the technical solution of an embodiment of the present application may be applied;
FIG. 3 illustrates a flow diagram of a precoding method of a communication awareness integrated system in accordance with an embodiment of the present application;
FIG. 4 illustrates an emission schematic of a communication awareness integrated system in accordance with one embodiment of the present application;
fig. 5 shows a block diagram of a precoding device of a communication awareness integrated system according to an embodiment of the present application;
Fig. 6 shows a schematic diagram of a computer system suitable for use in implementing an embodiment of the application.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the application may be practiced without one or more of the specific details, or with other methods, components, devices, steps, etc. In other instances, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the application.
The block diagrams depicted in the figures are merely functional entities and do not necessarily correspond to physically separate entities. That is, the functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
The flow diagrams depicted in the figures are exemplary only, and do not necessarily include all of the elements and operations/steps, nor must they be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the order of actual execution may be changed according to actual situations.
Fig. 1 shows a schematic diagram of an exemplary system architecture to which the technical solution of an embodiment of the present application may be applied.
As shown in fig. 1, the system architecture may be applied to a scene of internet of vehicles, specifically, the system architecture includes at least one base station, at least one communication user and at least one vehicle to be detected, in this scene, an agent may monitor road traffic conditions in real time, and send a sensing task to the base station (MC-ISAC system, multi-carrier communication sensing integrated system) according to a self-sensing service request, so that the base station senses the traffic scene, and the base station may extract sensing parameters (such as speed, distance, etc.) in the scene according to echo information and send the sensing parameters to the agent, and in consideration of an original communication function of the base station, when the base station is equipped with sensing performance, a part of communication performance may be sacrificed, and a precoding matrix design needs to be performed on a sending baseband signal, so that the sending baseband signal may meet sensing service and maximize communication performance.
Fig. 2 shows a schematic diagram of another exemplary system architecture to which the technical solution of an embodiment of the present application may be applied.
As shown in fig. 2, the system architecture may be applied to a smart factory scenario, and the system architecture may include at least one indoor subsystem, at least one communication user, and at least one probe target composition. It should be understood that the indoor subsystem needs to have both communication and sensing functions, and maximize communication performance by the precoding method on the premise of meeting sensing requirements. In an example, because the indoor subsystem generally has the characteristics of small volume, low power consumption, insufficient computing power and the like, the formation of the precoding matrix and the echo signal processing generally need to consume a large amount of computing power resources, and the indoor subsystem can offload the two computing tasks to a cloud with stronger computing power for processing, so that the computing resources of the indoor subsystem are saved.
Fig. 3 shows a flow diagram of a precoding method of a communication awareness integrated system according to an embodiment of the present application. Referring to fig. 3, the precoding method of the communication perception integrated system at least includes steps S310 to S350, and is described in detail as follows:
in step S310, according to the received perceived service request, a perceived demand parameter corresponding to the perceived service request is determined, where the perceived demand parameter is used to describe a maximum degree of deviation between the actual perceived performance and the ideal perceived performance.
In this embodiment, the agent is capable of generating and sending a sensing service request to the communication sensing integrated system according to the self-sensing service request, where the sensing service request may be used to request the system to start a sensing function, so as to meet the sensing requirement of the agent. In an example, the sensing service request may include identification information of a required sensing parameter, for example, the speed and distance of the sensing target required by the agent, the sensing service request may include identification information corresponding to the speed and distance, and so on. So that the system can extract parameters of the echo signals later.
In another example, a person skilled in the art may set target sensing parameters of an agent in advance, and after the system receives a sensing service request sent by an agent, the target sensing parameters corresponding to the agent may be determined according to identification information (e.g. a device number, a unique identifier, etc.) of the agent included in the sensing service request.
After receiving the perceived service request, the system may determine a perceived need parameter corresponding to the perceived service request, where the perceived need parameter is used to describe a maximum degree of deviation between the actual perceived performance and the ideal perceived performance. It should be appreciated that the smaller the perceived need parameter, the greater the communication performance that the system requires to be sacrificed, and conversely, the greater the perceived need parameter, the less the communication performance that the system requires to be sacrificed.
In an exemplary embodiment, determining, according to a received perceived service request, a perceived demand parameter corresponding to the perceived service request includes:
acquiring a first identifier corresponding to a perceived service request from the received perceived service request, wherein the first identifier is used for representing the importance degree corresponding to the perceived service;
and determining a perception requirement parameter corresponding to the first identifier.
In this embodiment, the perceived service request may include a first identifier for characterizing the importance level corresponding to the perceived service, where it should be understood that the higher the importance level, the smaller the corresponding perceived-demand parameter. The intelligent agent can determine a corresponding first identifier according to the requirement of self-perception service, and adds the first identifier to the perception service request, so that the communication perception integrated system can determine the importance degree of the perception service request according to the first identifier.
Specifically, the communication perception integrated system may store the correspondence between the first identifier and the perception requirement parameter in advance, so that the perception requirement parameter corresponding to the first identifier may be queried and determined based on the first identifier obtained from the perception service request.
In another exemplary embodiment, determining, according to a received perceived service request, a perceived demand parameter corresponding to the perceived service request includes:
and acquiring corresponding sensing demand parameters from the received sensing service request.
In this embodiment, the agent can directly add the perceived-demand parameter to the perceived-service request and send it to the communication-perceived-integration system. After receiving the sensing service request, the system can acquire the corresponding sensing demand parameters without searching, so that the determination efficiency of the sensing demand parameters is improved, and meanwhile, the intelligent body determines the corresponding sensing demand parameters according to actual needs, so that the accuracy of the determination of the sensing demand parameters can be ensured.
With continued reference to fig. 3, in step S320, a plurality of target users are allocated with subcarriers that do not overlap with each other to generate a multi-user baseband signal.
In this embodiment, in response to a received perceived service request, the system may allocate subcarriers that do not overlap with each other to a plurality of target users, and generate corresponding multi-user baseband signals according to the subcarriers allocated to each target user.
Taking U users as an example, the baseband signal allocated to the U-th user by the system is phi u (t) combining baseband signals transmitted to the U users into a vector form:
Φ(t)＝[Φ 1 (t),...,Φ u (t)] T ；
the subcarriers are not overlapped, so that the mutual interference between users is hardly generated, and the pressure of the mutual interference suppression at the user side is relieved.
In an exemplary embodiment of the present application, allocating subcarriers that do not overlap each other to a plurality of target users to generate a multi-user baseband signal includes:
multiple target users are allocated with non-overlapping subcarriers by using orthogonal frequency division multiple access to generate multi-user baseband signals.
In this embodiment, users are distinguished by an orthogonal frequency division multiple access technique, each occupying one subcarrier, and because different subcarriers do not overlap each other, interference between different users can be reduced. The baseband signal sent to user u can be expressed as:
Φ u (t)＝s u e j2πuΔft ；
wherein s is u For actually transmitting signals.
In step S330, the target precoding matrix is determined by solving the base criterion of minimizing the mean square error between the user side received signal and the actual transmitted signal and the constraint of the perceived-required parameter and the maximum transmission power using an iterative optimization algorithm.
Referring now to fig. 4, fig. 4 illustrates a transmission of a multi-carrier communication awareness integrated system in accordance with one embodiment of the present application A jet schematic diagram. As shown in fig. 4, the received signal on the user u side is represented asThe beam pattern G (θ) represents the distribution of transmit power over the discrete azimuth planes, depending mainly on the precoding matrix F.
In this embodiment, the precoding matrix F satisfies the maximum transmit power P constraint, namely:
Tr(FF H )≤P；
the maximum deviation degree of the actual perception performance and the ideal perception performance meets the constraint of the perception demand parameter eta, namely:
wherein F is rad For a precoding matrix corresponding to an ideal beam pattern,representing the Euclidean distance between the precoding matrix corresponding to the actual beam pattern and the precoding matrix corresponding to the ideal beam pattern for perception;
under the condition that the constraint is met, the target precoding matrix is determined by minimizing the mean square error between the received signal and the actual transmitted signal at the user side, so that the aim of maximizing the communication performance is fulfilled.
It should be noted that, the above optimization problem to be solved is a typical non-homogeneous quadratic programming problem (qqp), and in the embodiment of the present application, an iterative optimization algorithm is adopted to obtain the precoding matrix F, so as to maximize the communication performance under the condition of meeting the maximum power constraint P and the requirements of the perceived performance.
In particular, the communication performance uses e u Measurement, representing received signal at user u sideAnd actually transmitted signal s u Mean Square Error (MSE) between:
in the above expression of the mean square error, the actual transmission signal s on the communication perception integrated system side u With the actual received signal at the user sideAll are complex signals under digital modulation;
w u a combining matrix representing the receiver side of user u, the combining matrix being used to decode (decode) the received signal at the user side to obtain the actual received signal;
H u representing a complex baseband equivalent channel response matrix between the communication perception integrated system and the user u;
f is a precoding matrix of the communication perception integrated system side to be solved;
u u is a special column vector that contains a total of U elements, with only the U element being 1 and the remaining elements being 0;
representing the variance of the complex Additive White Gaussian Noise (AWGN).
Then, the iterative optimization algorithm can be described as:
s.t.Tr(FF H )≤P
further, based on the above embodiment, the method for solving the iterative optimization algorithm may include the following steps:
the system collects channel state information in the current environment, which may include path gain and phase shift, expressed in complex form. Initializing a precoding matrix F to be solved, and combining matrices w at the sides of users 1-u 1 ～w u Analog precoding matrix F corresponding to ideal beam pattern rad The matrix F is vectorized, yielding a supplementary column vector f=vec (F).
Fixing a precoding matrix F, and solving an optimal combining matrix w of the user 1-u sides 1 ～w u ：
According to F and w 1 ～w u Calculating MSE of the user 1-u sides: e, e 1 ～e u Obtaining the weight of each user: ωu=1/eu.
Combining matrix w for fixed user 1-u sides 1 ～w u And weight omega 1 ～ω u The original non-homogeneous qqp problem is rewritten to the following form:
s.t.||f|| 2 ≤P
||f-vec(F rad )|| 2 ≤η
where f=vec (F), operator vec () represents vectorizing the matrix F, i.e. stacking all columns of matrix F as vector F,
is a unitary matrix, N r Representing the number of receiving antennas at the user side; />Representing the kronecker product operation.
f old And f is obtained for the last iteration. The auxiliary vector f can now be solved directly using a convex optimization tool.
Rearranging the column vector F obtained by solving into a matrix F, and obtaining a precoding matrix F and a combining matrix w according to the iterative solution of the round 1 ～w u The downlink Rate (Rate) of the present round of iterations is calculated.
If Rate > Rate old The next iteration is performed. Rate (Rate) old Representing the downlink rate obtained by the last iterative computation. If Rate < Rate old And ending the iteration and outputting the target precoding matrix F.
Therefore, the multi-carrier communication perception integrated system meets the perception requirement by sacrificing certain communication performance, and the iterative optimization algorithm is adopted on the basis to maximize the downlink communication performance, so that the system can realize self communication service and simultaneously give consideration to the perception requirement of the system.
With continued reference to fig. 3, in step S340, the multi-user baseband signal is precoded for transmission according to the target precoding matrix.
In this embodiment, after determining the target precoding matrix, the system may precode the multi-user baseband signal according to the target precoding matrix and transmit via the radio frequency circuitry. Therefore, only one-time precoding is needed, the complexity of system calculation is effectively reduced, and the precoding processing efficiency is further improved.
In step S350, an echo signal corresponding to the precoded multi-user baseband signal is received, and a target perceptual parameter is extracted from the echo signal.
In this embodiment, the communication perception integrated system is capable of receiving an echo signal and extracting a target perception parameter from the echo signal, and the system may send the target perception parameter to the agent to satisfy the perception task of the agent.
In one example, the system can extract the target perception parameters from the echo signals using existing high resolution estimation methods, such as algorithms MUSIC, capon, ESPRIT, based on the received echo signals.
Thus, in the embodiment shown in fig. 1, according to the received perceived service request, a perceived demand parameter corresponding to the perceived service request is determined, where the perceived demand parameter is used to describe the maximum deviation degree between the actual perceived performance and the ideal perceived performance, and a plurality of target users are allocated with sub-carriers that do not overlap with each other, so as to generate a multi-user baseband signal, so that there will be no mutual interference between the users, and further the pressure of the mutual interference suppression on the user side is reduced. And solving by using an iterative optimization algorithm with a minimum mean square error between a user side received signal and an actual transmitted signal as a basic criterion and with a perception demand parameter and a maximum transmitting power as constraints, so as to determine a target precoding matrix, and precoding and transmitting the multi-user baseband signal according to the target precoding matrix. And receiving the corresponding echo signals, and extracting target perception parameters from the echo signals. Therefore, the communication perception integrated system of the multi-carrier only needs to perform precoding once, so that the processing efficiency of precoding is improved, and meanwhile, the communication performance of the system is ensured.
Based on the above embodiments, in one embodiment of the present application, extracting the target perception parameter from the echo signal includes:
generating corresponding parameter extraction task information according to the echo signals;
transmitting the parameter extraction task information to a third-party computing device, so that the third-party computing device extracts target perception parameters from the echo signals according to the parameter extraction task information;
the target awareness parameters fed back by the third-party computing device are received.
In this embodiment, the system may generate corresponding parameter extraction task information based on the received echo signals, which may be used to instruct a third party computing device to extract target perception parameters from the echo signals according to the parameter extraction task information.
The system can send the parameter extraction task information to the third party computing device to cause the third party computing device to extract the target perceived parameter from the echo signal based on the parameter extraction task information. It should be noted that the third party computing device may be one or more of a cloud computing, an edge computing, or a fog computing technology. When the third-party computing device finishes the extraction, the extracted target perception parameters can be fed back into the system.
Therefore, the computing task with higher computing complexity is unloaded to the computing equipment with strong computing capability to be executed, and scarce computing resources are replaced at the cost of surplus communication resources, so that timeliness of system task processing is guaranteed.
Based on the above embodiments, in one embodiment of the present application, based on a criterion of minimizing a mean square error between a user side received signal and an actual transmitted signal, the perceived demand parameter and the maximum transmission power are constraint, and an iterative optimization algorithm is used to perform a solution to determine a target precoding matrix, which includes:
generating corresponding precoding matrix calculation task information according to the perception demand parameters;
transmitting the precoding matrix calculation task information to a third party computing device, so that the third party computing device calculates the task information according to the precoding matrix, takes a minimum mean square error between a user side received signal and an actual transmitted signal as a basic criterion, takes the sensing requirement parameter and the maximum transmitting power as constraints, and uses an iterative optimization algorithm to solve so as to determine a target precoding matrix;
the target precoding matrix fed back by the third party computing device is received.
In the embodiment, the precoding matrix generation with higher calculation difficulty is unloaded to the third-party computing equipment for calculation, so that the target precoding matrix fed back by the third-party computing equipment is received, and the generation efficiency of target precoding is improved.
The following describes an embodiment of the apparatus of the present application, which may be used to perform the precoding method of the communication awareness integrated system in the above embodiment of the present application. For details not disclosed in the embodiments of the apparatus of the present application, please refer to an embodiment of the precoding method of the communication awareness integrated system of the present application.
Fig. 5 shows a block diagram of a precoding device of a communication awareness integrated system according to an embodiment of the present application.
Referring to fig. 5, a precoding apparatus of a communication awareness integrated system according to an embodiment of the present application includes:
a receiving module 510, configured to determine, according to a received perceived service request, a perceived demand parameter corresponding to the perceived service request, where the perceived demand parameter is used to describe a maximum degree of deviation between an actual perceived performance and an ideal perceived performance;
an allocation module 520, configured to allocate subcarriers that are not overlapped with each other to a plurality of target users, so as to generate a multi-user baseband signal;
A calculation module 530, configured to solve, using an iterative optimization algorithm, with the perceived-demand parameter and the maximum transmit power as constraints, based on a criterion of minimizing a mean square error between the user-side received signal and the actual transmitted signal, so as to determine a target precoding matrix;
a transmitting module 540, configured to precode the multi-user baseband signal according to the target precoding matrix for transmission;
a processing module 550, configured to receive an echo signal corresponding to the precoded multi-user baseband signal, and extract a target perceptual parameter from the echo signal.
In one embodiment of the present application, the receiving module 510 is configured to: acquiring a first identifier corresponding to a perceived service request from the received perceived service request, wherein the first identifier is used for representing the importance degree corresponding to the perceived service; and determining a perception requirement parameter corresponding to the first identifier.
In one embodiment of the present application, the receiving module 510 is configured to: and acquiring corresponding sensing demand parameters from the received sensing service request.
In one embodiment of the application, the processing module 550 is configured to: generating corresponding parameter extraction task information according to the echo signals; transmitting the parameter extraction task information to a third-party computing device, so that the third-party computing device extracts target perception parameters from the echo signals according to the parameter extraction task information; the target awareness parameters fed back by the third-party computing device are received.
In one embodiment of the application, the computing module 530 is configured to: generating corresponding precoding matrix calculation task information according to the perception demand parameters; transmitting the precoding matrix calculation task information to a third party computing device, so that the third party computing device calculates the task information according to the precoding matrix, takes a minimum mean square error between a user side received signal and an actual transmitted signal as a basic criterion, takes the sensing requirement parameter and the maximum transmitting power as constraints, and uses an iterative optimization algorithm to solve so as to determine a target precoding matrix; the target precoding matrix fed back by the third party computing device is received.
In one embodiment of the application, the allocation module 520 is configured to: multiple target users are allocated with non-overlapping subcarriers by using orthogonal frequency division multiple access to generate multi-user baseband signals.
In one embodiment of the application, the computing module 530 is configured to:
the precoding matrix F satisfies the maximum transmit power P constraint, namely:
Tr(FF H )≤P；
the maximum deviation degree of the actual perception performance and the ideal perception performance meets the constraint of the perception demand parameter eta, namely:
wherein F is rad For a precoding matrix corresponding to an ideal beam pattern, Representing the Euclidean distance between the precoding matrix corresponding to the actual beam pattern and the precoding matrix corresponding to the ideal beam pattern for perception;
under the condition that the constraint is met, an iterative optimization algorithm is used to determine a target precoding matrix by minimizing the mean square error between a user side received signal and an actual transmitted signal.
According to another embodiment of the present application, a precoding apparatus of a communication awareness integrated system includes:
the perception service initiating module is used for intelligently identifying a perception task through the service requirement of the system and sending the perception task to the communication transmitter;
the precoding module is used for converting the baseband signals into a scene suitable for communication perception integration, is positioned in the communication transmitter and has the functions of channel estimation, subcarrier allocation, precoding matrix generation, baseband signal processing and the like;
the computing power auxiliary module is formed by combining one or more computing resources in cloud computing, fog computing or edge computing, has strong computing performance, and can assist in precoding matrix design and extraction of perception parameters of echo signals;
the radio frequency processing module consists of a DAC, an ADC, a radio frequency link unit and the like, and realizes the interconversion of the processed baseband signal and the radio frequency signal;
The echo processing module is used for processing the receiving end baseband signal after radio frequency processing, extracting the perception parameters corresponding to the perception tasks from the receiving end baseband signal, and meeting the perception tasks corresponding to the perception service initiating module.
Fig. 6 shows a schematic diagram of a computer system suitable for use in implementing an embodiment of the application.
It should be noted that, the computer system of the electronic device shown in fig. 6 is only an example, and should not impose any limitation on the functions and the application scope of the embodiments of the present application.
As shown in fig. 6, the computer system includes a central processing unit (Central Processing Unit, CPU) 601 which can perform various appropriate actions and processes according to a program stored in a Read-Only Memory (ROM) 602 or a program loaded from a storage section 608 into a random access Memory (Random Access Memory, RAM) 603, for example, performing the method described in the above embodiment. In the RAM 603, various programs and data required for system operation are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other through a bus 604. An Input/Output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, mouse, etc.; an output portion 607 including a Cathode Ray Tube (CRT), a liquid crystal display (Liquid Crystal Display, LCD), and a speaker, etc.; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN (Local Area Network ) card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The drive 610 is also connected to the I/O interface 605 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on drive 610 so that a computer program read therefrom is installed as needed into storage section 608.
In particular, according to embodiments of the present application, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 609, and/or installed from the removable medium 611. When executed by a Central Processing Unit (CPU) 601, performs the various functions defined in the system of the present application.
It should be noted that, the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-Only Memory (ROM), an erasable programmable read-Only Memory (Erasable Programmable Read Only Memory, EPROM), flash Memory, an optical fiber, a portable compact disc read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with a computer-readable computer program embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Where each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be provided in a processor. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.
As another aspect, the present application also provides a computer-readable medium that may be contained in the electronic device described in the above embodiment; or may exist alone without being incorporated into the electronic device. The computer-readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to implement the methods described in the above embodiments.
It should be noted that although in the above detailed description several modules or units of a device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functions of two or more modules or units described above may be embodied in one module or unit in accordance with embodiments of the application. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, and includes several instructions to cause a computing device (may be a personal computer, a server, a touch terminal, or a network device, etc.) to perform the method according to the embodiments of the present application.
Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains.
It is to be understood that the application is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (8)
1. A precoding method of a communication perception integrated system, comprising:
according to the received perception service request, determining a perception demand parameter corresponding to the perception service request, wherein the perception demand parameter is used for describing the maximum deviation degree between the actual perception performance and the ideal perception performance;
allocating non-overlapping sub-carriers for a plurality of target users to generate multi-user baseband signals;
taking the mean square error between the minimum user side received signal and the actual transmitted signal as a basic criterion, taking the sensing demand parameter and the maximum transmitting power as constraints, and solving by using an iterative optimization algorithm to determine a target precoding matrix;
Precoding the multi-user baseband signal according to the target precoding matrix for transmission;
receiving echo signals corresponding to the precoded multi-user baseband signals, and extracting target perception parameters from the echo signals;
according to the received perceived service request, determining a perceived demand parameter corresponding to the perceived service request, including:
acquiring a first identifier corresponding to a perceived service request from the received perceived service request, wherein the first identifier is used for representing the importance degree corresponding to the perceived service, and the higher the importance degree is, the smaller the perceived demand parameter is;
determining a perceived-demand parameter corresponding to the first identifier;
based on a criterion of minimizing a mean square error between a user side received signal and an actual transmitted signal, the perceptual demand parameter and the maximum transmitting power are used as constraints, and an iterative optimization algorithm is used for solving to determine a target precoding matrix, which comprises the following steps:
the precoding matrix F corresponding to the actual beam pattern satisfies the maximum transmit power P constraint, namely:
Tr(FF H )≤P；
the maximum deviation degree of the actual perception performance and the ideal perception performance meets the constraint of the perception demand parameter eta, namely:
Wherein F is rad For a precoding matrix corresponding to an ideal beam pattern,representing the Euclidean distance between the precoding matrix corresponding to the actual beam pattern and the precoding matrix corresponding to the ideal beam pattern for perception;
under the condition that the maximum transmitting power P constraint and the perception requirement parameter eta constraint are met, an iterative optimization algorithm is used for determining a target precoding matrix by minimizing the mean square error between a user side receiving signal and an actual transmitting signal.
2. The method of claim 1, wherein determining a perceived need parameter corresponding to a perceived service request based on the received perceived service request comprises:
and acquiring corresponding sensing demand parameters from the received sensing service request.
3. The method according to any of claims 1-2, wherein extracting target perception parameters from the echo signals comprises:
generating corresponding parameter extraction task information according to the echo signals;
transmitting the parameter extraction task information to a third-party computing device, so that the third-party computing device extracts target perception parameters from the echo signals according to the parameter extraction task information;
The target awareness parameters fed back by the third-party computing device are received.
4. The method according to any of claims 1-2, wherein the perceived need parameter and the maximum transmit power are constrained based on a criterion of minimizing a mean square error between the user side received signal and the actual transmitted signal, and wherein the solving using an iterative optimization algorithm to determine the target precoding matrix comprises:
generating corresponding precoding matrix calculation task information according to the perception demand parameters;
transmitting the precoding matrix calculation task information to a third party computing device, so that the third party computing device calculates the task information according to the precoding matrix, takes a minimum mean square error between a user side received signal and an actual transmitted signal as a basic criterion, takes the sensing requirement parameter and the maximum transmitting power as constraints, and uses an iterative optimization algorithm to solve so as to determine a target precoding matrix;
the target precoding matrix fed back by the third party computing device is received.
5. The method according to any of claims 1-2, wherein allocating subcarriers that do not overlap each other to a plurality of target users to generate a multi-user baseband signal comprises:
Multiple target users are allocated with non-overlapping subcarriers by using orthogonal frequency division multiple access to generate multi-user baseband signals.
6. A precoding device of a communication perception integrated system, comprising:
the receiving module is used for determining a perception demand parameter corresponding to the perception service request according to the received perception service request, wherein the perception demand parameter is used for describing the maximum deviation degree between the actual perception performance and the ideal perception performance;
an allocation module, configured to allocate subcarriers that are not overlapped with each other for a plurality of target users, so as to generate a multi-user baseband signal;
the calculation module is used for solving by using an iterative optimization algorithm to determine a target precoding matrix by taking a mean square error between a minimum user side received signal and an actual transmitted signal as a basic criterion and taking the perception demand parameter and the maximum transmitting power as constraints;
the transmitting module is used for precoding the multi-user baseband signals according to the target precoding matrix so as to transmit the multi-user baseband signals;
the processing module is used for receiving echo signals corresponding to the precoded multi-user baseband signals and extracting target perception parameters from the echo signals;
The receiving module is used for:
acquiring a first identifier corresponding to a perceived service request from the received perceived service request, wherein the first identifier is used for representing the importance degree corresponding to the perceived service, and the higher the importance degree is, the smaller the perceived demand parameter is;
determining a perceived-demand parameter corresponding to the first identifier;
the computing module is used for:
the precoding matrix F corresponding to the actual beam pattern direction satisfies the maximum transmit power P constraint, that is:
Tr(FF H )≤P；
the maximum deviation degree of the actual perception performance and the ideal perception performance meets the constraint of the perception demand parameter eta, namely:
wherein F is rad For a precoding matrix corresponding to an ideal beam pattern,representing the Euclidean distance between the precoding matrix corresponding to the actual beam pattern and the precoding matrix corresponding to the ideal beam pattern for perception;
under the condition that the maximum transmitting power P constraint and the perception requirement parameter eta constraint are met, an iterative optimization algorithm is used for determining a target precoding matrix by minimizing the mean square error between a user side receiving signal and an actual transmitting signal.
7. A computer readable medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements a precoding method of a communication awareness integration system according to any one of claims 1 to 5.
8. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the precoding method of the communication awareness integration system of any one of claims 1-5.
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