CN116743222A

CN116743222A - Multiplexing beam forming method, communication perception calculation integrated system and related device

Info

Publication number: CN116743222A
Application number: CN202310557982.3A
Authority: CN
Inventors: 李晓阳; 周梓钦; 朱光旭; 李航; 史清江; 崔原豪
Original assignee: Shenzhen Research Institute of Big Data SRIBD
Current assignee: Shenzhen Research Institute of Big Data SRIBD
Priority date: 2023-05-17
Filing date: 2023-05-17
Publication date: 2023-09-12

Abstract

The embodiment of the invention provides a multiplexing beam forming method, a communication perception calculation integrated system and a related device, and relates to the technical field of communication. Comprising the following steps: constructing a first result constraint condition related to a received result, a first sensing matrix constraint condition related to sensing performance and a first power constraint condition related to transmitting power by using multiplexing signals capable of simultaneously carrying out communication, sensing and calculation; and constructing a first constraint condition set by using the first result constraint condition, the first perception matrix constraint condition and the first power constraint condition, and then solving the first constraint condition set to obtain the optimized values of the receiving end beam shaper and the transmitting end beam shaper. The method comprises the steps of designing beam forming of a transmitting end and beam forming of a receiving end, simultaneously adjusting antennas of the receiving end and transmitting end, minimizing air calculation errors on the premise of ensuring sensing accuracy, and improving air calculation performance and data processing efficiency, thereby improving resource utilization efficiency.

Description

Multiplexing beam forming method, communication perception calculation integrated system and related device

Technical Field

The present application relates to the field of communications technologies, and in particular, to a multiplexing beamforming method, a communication perception computing integrated system, and a related device.

Background

Along with the development of the internet of things, massive data are required to be collected from the environment by radar equipment and transmitted to a server for subsequent processing, and in a data processing scheme, data sensing, transmitting and calculating links are independently designed. This mechanism may cause the perceived signal and the communication signal to compete for radio spectrum resources, burdening the radio channel, and causing the communication link to be more congested.

In the related art, in order to improve spectrum efficiency, a radar communication and sensing multiplexing signal is designed, and a communication sensing integrated technology is utilized to realize simultaneous data sensing and transmission of a physical layer. The calculation performance of the communication perception calculation integrated system is limited by the parameter design of the wave beam shaper, but the design performance of the wave beam shaper in the related technology has low resource utilization efficiency.

Disclosure of Invention

The embodiment of the application mainly aims to provide a multiplexing beam forming method, a communication perception calculation integrated system and a related device, and improves the optimization performance and the optimization efficiency of a beam forming matrix.

To achieve the above object, a first aspect of an embodiment of the present application provides an antenna multiplexing beamforming method, which is applied to a communication perception computing integrated system, where the communication perception computing integrated system includes: the system comprises a transmitting end beam shaper, a receiving end beam shaper and at least one radar device, wherein a transmitting signal of the radar device is a multiplexing signal obtained by performing beam shaping on an initial multiplexing signal by utilizing the transmitting end beam shaper; the radar equipment is also used for receiving a target reflection signal obtained by reflecting the emission signal by a perception target; the method comprises the following steps:

Obtaining the target reflection signals received by the radar equipment to obtain processing signals, calculating according to the processing signals to obtain a statistical result matrix, obtaining the mean square error of the target reflection matrix of each radar equipment according to the statistical result matrix, and constructing a first perception matrix constraint condition based on an error tolerance value;

based on the receiving end beam shaper, obtaining a receiving vector according to the multiplexing signal, calculating a result mean square error between the receiving vector and a real data value, and constructing a first result constraint condition by minimizing the result mean square error;

acquiring the transmitting power of the radar equipment to construct a first power constraint condition;

and constructing a first constraint condition set according to the first result constraint condition, the first perception matrix constraint condition and the first power constraint condition, and solving the first constraint condition set to obtain a first beamforming weight optimization value of the receiving end beamformer and a second beamforming weight optimization value of the transmitting end beamformer.

In an embodiment, the obtaining, based on the receiving-end beam shaper, a receiving vector according to the multiplexing signal, and calculating a mean square error of a result between the receiving vector and a real data value, and minimizing the mean square error of the result to construct a first result constraint condition includes:

Calculating to obtain the real data value according to the initial multiplexing signal of each radar device;

calculating to obtain a transmission total signal according to the transmission signal of each radar device;

obtaining the receiving vector according to the receiving end beam shaper and the total transmission signal;

and calculating the mean square error of the receiving vector and the real data value to obtain the result mean square error, and carrying out minimization constraint on the result mean square error to obtain the first result constraint condition.

In an embodiment, the obtaining the target reflection signals received by the radar devices to obtain processing signals, calculating according to the processing signals to obtain a statistical result matrix, obtaining a mean square error of the target reflection matrix of each radar device according to the statistical result matrix, and constructing a first perception matrix constraint condition based on an error tolerance value, including:

calculating a target reflection signal according to the target reflection matrix of the radar equipment, the multiplexing signal and the interference signal; the interference signal is obtained by calculation according to the transmitting end beam shaper;

obtaining all target reflected signals of the radar equipment to obtain the processing signals, and optimizing the results of the processing signals according to the law of large numbers to obtain the statistical result matrix;

Acquiring an estimated value of the target reflection matrix according to the statistical result matrix;

and calculating the mean square error of the target reflection matrix and the estimated value to obtain the mean square error of the target reflection matrix, so that the mean square error of the target reflection matrix is smaller than the error tolerance value, and constructing the first perception matrix constraint condition.

In an embodiment, the obtaining the transmission power of the radar apparatus constructs a first power constraint condition, including:

obtaining power information according to the transmitting end beam shaper;

and setting the power information to be smaller than or equal to the transmitting power, and constructing the first power constraint condition.

In an embodiment, the solving the first constraint condition set to obtain a first beamforming weight optimization value of the receiving end beamformer and a second beamforming weight optimization value of the transmitting end beamformer includes:

obtaining a first conversion relation between the transmitting end beam shaper and the receiving end beam shaper by zero forcing design;

converting the first set of constraints into a second set of constraints based on the first conversion relationship;

the receiving end beam shaper is expressed as a semi-positive definite matrix by utilizing semi-positive scaling, and the second constraint condition set is converted into a third constraint condition set according to the semi-positive definite matrix;

And performing convex optimization solution on the third constraint condition set to obtain the first beamforming weight optimization value of the receiving end beamforming device, and obtaining the second beamforming weight optimization value of the transmitting end beamforming device based on the first conversion relation.

In an embodiment, the converting the first set of constraints into a second set of constraints based on the first conversion relationship includes:

based on the first conversion relation, replacing the transmitting end beam shaper by the receiving end beam shaper in the first result constraint condition to obtain a second result constraint condition;

based on the first conversion relation, replacing the transmitting end beam shaper by the receiving end beam shaper in the first power constraint condition to obtain a second power constraint condition;

based on the first conversion relation, replacing the transmitting end beam shaper by the receiving end beam shaper in the first sensing matrix constraint condition to obtain a second sensing matrix constraint condition;

and generating the second constraint condition set according to the second result constraint condition, the second perception matrix constraint condition and the second power constraint condition.

In an embodiment, the representing the receiving end beamformer as a semi-positive definite matrix by the semi-positive scaling, converting the second constraint set into a third constraint set according to the semi-positive definite matrix includes:

converting the second result constraint condition into a third result constraint condition according to the semi-positive definite matrix;

converting the second power constraint condition into a third power constraint condition according to the semi-positive definite matrix;

converting the second sensing matrix constraint condition into a third sensing matrix constraint condition according to the semi-positive definite matrix;

and generating the third constraint condition set according to the third result constraint condition, the third perception matrix constraint condition, the third power constraint condition and the semi-positive definite matrix.

In an embodiment, the performing convex optimization solution on the third constraint condition set to obtain the first beamforming weight optimization value of the receiving end beamformer includes:

performing convex optimization solving on the third constraint condition set to obtain the semi-positive definite matrix;

and solving the semi-positive matrix optimization problem to obtain the first beamforming weight optimization value of the receiving end beamformer.

To achieve the above object, a second aspect of the embodiments of the present application provides an antenna multiplexing beamforming device, which is applied to a communication perception calculation integrated system, where the communication perception calculation integrated system includes: the system comprises a transmitting end beam shaper, a receiving end beam shaper and at least one radar device, wherein a transmitting signal of the radar device is a multiplexing signal obtained by performing beam shaping on an initial multiplexing signal by utilizing the transmitting end beam shaper; the radar equipment is also used for receiving a target reflection signal obtained by reflecting the emission signal by a perception target; the device comprises:

the sensing matrix constraint condition construction module is used for acquiring the target reflection signals received by the radar equipment to obtain processing signals, calculating to obtain a statistical result matrix according to the processing signals, acquiring the mean square error of the target reflection matrix of each radar equipment according to the statistical result matrix, and constructing a first sensing matrix constraint condition based on an error tolerance value;

the result constraint condition construction module is used for obtaining a receiving vector according to the multiplexing signal based on the receiving end beam shaper, calculating a result mean square error between the receiving vector and a real data value, and minimizing the result mean square error to construct a first result constraint condition;

The power constraint condition construction module is used for acquiring the transmitting power of the radar equipment to construct a first power constraint condition;

the weight optimization value calculation module is used for constructing a first constraint condition set according to the first result constraint condition, the first perception matrix constraint condition and the first power constraint condition, and solving the first constraint condition set to obtain a first beamforming weight optimization value of the receiving end beamformer and a second beamforming weight optimization value of the transmitting end beamformer.

To achieve the above objective, a third aspect of the embodiments of the present application provides a communication perception calculation integrated system, where the system includes a transmitting end beam shaper and a receiving end beam shaper, and a first beam shaping weight optimization value of the receiving end beam shaper and a second beam shaping weight optimization value of the transmitting end beam shaper are calculated according to any one of the antenna multiplexing beam shaping methods of the first aspect.

To achieve the above object, a fourth aspect of the embodiments of the present application proposes an electronic device, including a memory storing a computer program and a processor implementing the method according to the first aspect when the processor executes the computer program.

To achieve the above object, a fifth aspect of the embodiments of the present application proposes a storage medium, which is a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method according to the first aspect.

The multiplexing beam forming method, the communication perception calculation integrated system and the related device provided by the embodiment of the application construct a first result constraint condition related to a receiving result, a first perception matrix constraint condition related to perception performance and a first power constraint condition related to transmitting power by utilizing multiplexing signals capable of simultaneously carrying out communication, perception and calculation; and constructing a first constraint condition set by using the first result constraint condition, the first perception matrix constraint condition and the first power constraint condition, and then solving the first constraint condition set to obtain the optimized values of the receiving end beam shaper and the transmitting end beam shaper. The embodiment of the application designs the beam forming of the transmitting end and the beam forming of the receiving end, simultaneously adjusts the antennas of the receiving and transmitting ends, minimizes the air calculation error on the premise of ensuring the sensing accuracy, and improves the air calculation performance and the data processing efficiency, thereby improving the resource utilization efficiency.

Drawings

Fig. 1 is a schematic diagram of a communication awareness and computation integrated system according to an embodiment of the present invention.

Fig. 2 is a flowchart of an antenna multiplexing beamforming method according to another embodiment of the present invention.

Fig. 3 is a flowchart of step S110 in fig. 2.

Fig. 4 is a flowchart of step S120 in fig. 2.

Fig. 5 is a flowchart of step S130 in fig. 2.

Fig. 6 is a flowchart of step S140 in fig. 2.

Fig. 7 is a flowchart of step S142 in fig. 6.

Fig. 8 is a flowchart of step S144 in fig. 6.

Fig. 9 is a flowchart of step S145 in fig. 6.

Fig. 10 is a signal processing flow chart of a communication perception calculation integrated system according to still another embodiment of the present invention.

Fig. 11 is a schematic diagram of an application scenario of target positioning in an application scenario of an antenna multiplexing beamforming method according to another embodiment of the present invention.

Fig. 12 is a schematic view of the calculation result in fig. 11.

Fig. 13 is a block diagram of an antenna multiplexing beamforming apparatus according to another embodiment of the present invention.

Fig. 14 is a schematic hardware structure of an electronic device according to an embodiment of the present invention.

Detailed Description

The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.

It should be noted that although functional block division is performed in a device diagram and a logic sequence is shown in a flowchart, in some cases, the steps shown or described may be performed in a different order than the block division in the device, or in the flowchart.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein is for the purpose of describing embodiments of the invention only and is not intended to be limiting of the invention.

First, several nouns involved in the present invention are parsed:

beamforming): is a signal processing technique that improves the transmission quality of a signal by adjusting the direction in which the signal is transmitted (or received). It can reduce interference in transmission, improve coverage and reliability of signals, etc. In a communication system, beamforming generally refers to using multiple antennas or arrays to control the direction and shape of a signal in a certain manner, so that the signal is more intensively transmitted to a target location, thereby improving communication quality. Unlike conventional omni-directional transmission or reception, beamforming can focus signal energy on an area to be covered, reduces transmission of signals in an area not to be covered, and has higher efficiency and capacity. Beamforming is widely used in new generation wireless communication technologies such as 5G and millimeter wave communication. Besides communication systems, the beam forming can be used in the fields of radar, sonar, medical imaging and the like, and the detection range and the accuracy of signals can be improved.

Along with the development of the internet of things, massive data are required to be collected from the environment by radar equipment and transmitted to a server for subsequent processing, and in a data processing scheme, data sensing, transmitting and calculating links are independently designed. This mechanism results in the data sensing and transmission links competing for spectrum resources, while the computation links compete for time resources with the other two.

To achieve simultaneous communication and perception, the target reflected signal is projected into a transmission space orthogonal to the communication signal. In order to further improve the communication and sensing efficiency, a multi-antenna system is developed to realize multiple-input multiple-output radar sensing and communication, and the radar sensing and communication coexisting system needs to sense and communicate a real-time feedback state of a receiving and transmitting end, which causes a serious information interaction burden. Therefore, in order to improve the spectrum efficiency in the related art, the radar communication and sensing multiplexing signal is designed, the communication sensing integrated technology is utilized to realize the simultaneous data sensing and transmission of the physical layer, namely, the dual-function signal which can be simultaneously used for target sensing and data transmission is designed, and in practical application, the dual-function waveform design which can be simultaneously used for target sensing and data transmission is further expanded to a multi-antenna multiple-transmitting-multiple-receiving system, wherein the data information is embedded into the side lobe of the target reflection signal.

However, since the computing link is often located at the network layer or the application layer, it is difficult to combine with the communication perception integration technology of the physical layer, and the occurrence of air computing makes data computation of the physical layer possible. By utilizing the superposition properties of analog signals during multiple access channel propagation, over-the-air computing techniques may enable function computation during signal propagation. Unlike conventional multiple access schemes, over-the-air computation aims to reduce the error between the collected statistics and the true value. Based on air calculation, the technology integrating the perception communication calculation can be realized on the air interface of the physical layer. The air computing performance of the communication perception computing integrated system is limited by the parameter design of the wave beam shaper, but the design performance of the wave beam shaper in the related technology does not fully consider the computing link, the resource utilization efficiency is low, and the computing performance of the air computing is poor.

Based on this, the embodiment of the invention provides a multiplexing beam forming method, a communication perception calculation integrated system and a related device, which are used for designing beam forming of a transmitting end and beam forming of a receiving end, simultaneously adjusting antennas of a receiving end and a transmitting end, minimizing an air calculation error on the premise of ensuring perception accuracy, and improving air calculation performance and data processing efficiency, thereby improving resource utilization efficiency.

The embodiment of the application provides an antenna beam forming method and a communication perception calculation integrated system, which are specifically described by the following embodiment, and the antenna beam forming method in the embodiment of the application is described first.

First, a communication perception calculation integrated system in an embodiment of the present application is described.

Referring to fig. 1, a communication awareness computing integration system 10 includes: 1 perception target 110, M radar devices 120 with Ns antennas, M radar devices 120 forming a device clusterAnd a server 130 for performing aerial calculations, the server 130 having Na antennas. In an embodiment, ns antennas of each radar device 120 sense a sensing target at the same time, and send the obtained multiple sensing data to the server 130, and the data is overlapped in a waveform manner in the signal transmission process to implement aerial calculation, and finally the server 130 demodulates a required calculation result. In one embodiment, server 130 may be a wireless router with data processing functionality.

The whole signal transceiving time is divided into T time periods, and in each time period, each radar device 120 transmits a multiplexed signal, and each multiplexed signal carries data to be calculated in the air and is also used as a radar sensing pulse for sensing the sensing target 110 and for data communication. The multiplexed signal can be perceived, communicated and calculated simultaneously. Wherein the multiplexed signal is reflected by the perception target 110 to obtain a target reflected signal, and the target reflected signal is received by the corresponding radar device 120, and the multiplexed signal is received by the server 130 after air calculation. Wherein the target reflection matrix of each radar device 120 to the perceived target 110 in the radar sensing phase is Gii, and the data transmission channel matrix of each radar device 120 to the server 130 in the data communication phase is Hi, wherein 1.ltoreq.i.ltoreq.m.

In one embodiment, N is on each radar device 120 _tx Root antenna for multiplexing signal transmission, N _rx Root is used for receiving target reflected signal, wherein N _tx +N _rx ＝N _s . The transmitted signals of the devices follow independent co-distributions with a mean of 0 and a variance of 1.

In one embodiment, during the t-th time period, the mth radar device 120 transmitsCan be represented as a K-dimensional vector s _m [t]Where K represents the number of functions that need to be computed over the air, and can be obtained in the actual computing scenario. In an embodiment, the initial multiplexing signal may be a sensing signal or a data transmission signal, and the multiplexing signal obtained according to the initial multiplexing signal may have the functions of radar sensing and data communication at the same time by using the antenna multiplexing beam forming method of the embodiment of the present application.

For different radar devices 120, the signal s is initially multiplexed _m [t]It is required to satisfy independent co-distribution with mean 0 and variance 1, i.eIn addition, the initial multiplexing signals of all the radar devices 120 of i+.m need to satisfy the condition:

in an embodiment, the communication perception computing integrated system 10 further includes a beam shaper, where the beam shaper is a device for implementing beam shaping and spatial filtering by using an antenna sensor array, is a signal processing technology for directional transmission or reception, is implemented by combining elements in the antenna array, and implements beam shaping by using a principle that signals with a specific angle are subject to relevant interference, and other signals are subject to interference cancellation, so as to implement spatial selectivity. The beam shaper of the present embodiment includes: the system comprises a transmitting end beam shaper and a receiving end beam shaper, wherein the transmitting end beam shaper is used for carrying out beam shaping on a multiplexing signal. It will be appreciated that the beamformer may be in a matrix form. The embodiment of the application improves the signal-to-noise ratio of the received signal by utilizing the wave beam forming, eliminates the bad interference source and focuses the transmitted signal to a specific position.

The following describes an antenna multiplexing beamforming method in an embodiment of the present invention.

Fig. 2 is an optional flowchart of an antenna multiplexing beamforming method according to an embodiment of the present invention, where the method in fig. 2 may include, but is not limited to, steps S110 to S140. It should be understood that the order of steps S110 to S140 in fig. 2 is not particularly limited, and the order of steps may be adjusted, or some steps may be reduced or added according to actual requirements.

Step S110: obtaining target reflection signals received by radar equipment to obtain processing signals, calculating according to the processing signals to obtain a statistical result matrix, obtaining the mean square error of the target reflection matrix of each radar equipment according to the statistical result matrix, and constructing a first perception matrix constraint condition based on an error tolerance value.

In one embodiment, referring to fig. 3, the process of constructing the first perceptual matrix constraint in step S110 includes the steps of:

step S111: and calculating according to the target reflection matrix, the multiplexing signal and the interference signal of the radar equipment to obtain a target reflection signal.

In one embodiment, for the mth radar apparatus, a transmit-side beamformer W is used _m For the initial multiplex signal s _m [t]Beamforming to obtain multiplexed signal, i.e. transmitting signal x _m (t) expressed as:

x _m [t]＝W _m s _m [t]

wherein, the transmitting end beam shaper W _m Is N _tx A matrix of order x K.

For the mth radar equipment, obtaining a target reflection signal y after sensing target to reflect the multiplexing signal _m (t) expressed as:

y _m [t]＝G _mm W _m s _m [t]+Ω _m [t]+n _r [t]

wherein G is _mn Representing the target reflection matrix of the mth radar device. G for the mth and ith radar apparatuses _im Target reflection matrix representing Nrx×Ntx order, Q _im Direct interference matrix, n, representing Nrx x Ntx order _r (t) an additive Gaussian white noise direction of Nrx orderThe mean value of the quantity is 0, and the variance isIt will be appreciated that Q _im Obtained from parameters of the actual communication system.

Omega above _m And (t) representing an interference signal, and calculating according to the target reflection matrix, the transmitting end beam shaper, the direct interference matrix and the initial multiplexing signal.

Step S112: and obtaining a target reflected signal of the radar equipment to obtain a processed signal, and optimizing the result of the processed signal according to the law of large numbers to obtain a statistical result matrix.

In an embodiment, in order to eliminate the interference in the radar sensing process as much as possible, the statistical result matrix is obtained by matched filtering. By reflecting the signal y on a target for T time periods _m (t) performing matched filtering to obtain signal statistics of the mth radar device, and recording the signal statistics as processed signalsThis is a matrix of order Nrx x K, specifically:

in one embodiment, the following approximate expression can be established when the period T is sufficiently long, according to the law of large numbers:

according to the above approximate expression, the signal will be processedPerforming result optimization to obtain a statistical result matrix +.>Expressed as:

wherein N is _m Is an Nrx x K order statistical noise matrix.

Step S113: and obtaining an estimated value of the target reflection matrix according to the statistical result matrix.

In one embodiment, a statistical noise matrix N is calculated _m Is expressed as:

according to the probability density function p (N _m ) Maximum likelihood estimation is carried out on the target reflection matrix, and the method can obtain

Estimation of target reflection matrixExpressed as:

step S114: and calculating the mean square error of the target reflection matrix and the estimated value to obtain the mean square error of the target reflection matrix, so that the mean square error of the target reflection matrix is smaller than the error tolerance value, and constructing a first perception matrix constraint condition.

In one embodiment, the target reflection matrix mean square error is expressed as:

given an error tolerance value η of an mth radar device _m The first perceptual matrix constraint is expressed as:

Thereby obtaining a first perceptual matrix constraint.

Step S120: based on a receiving end beam shaper, a receiving vector is obtained according to the multiplexing signal, the result mean square error between the receiving vector and a real data value is calculated, and a first result constraint condition is constructed by minimizing the result mean square error.

In one embodiment, referring to fig. 4, the process of constructing the first result constraint in step S120 includes the steps of:

step S121: and calculating a real data value according to the initial multiplexing signal of each radar device.

In one embodiment, the true data value is an initial multiplexed signal for each radar device, represented as

Step S122: and calculating a transmission total signal according to the multiplexing signal of each radar device.

In one embodiment, the transmission signal is based on the multiplexed signal W _m s _m [t]And a data transmission channel matrix H _m Calculated, expressed as: h _m W _m s _m [t]。

The transmission signal of each radar device is calculated to obtain a transmission total signal, which is the result of superposition of signal waveforms of each radar device in the air calculation process, and is expressed as follows:

step S123: and obtaining a receiving vector according to the wave beam shaper at the receiving end and the total transmission signal.

In one embodiment, for the server, the received signal is a total transmission signal obtained by air calculation and superposition of the transmission signals of the radar devices, and after receiving, the total transmission signal is beamformed by a receiving end beam forming device to obtain a received vector Receive vector->A vector of dimension K, expressed as:

wherein A represents a receiving end beam shaper and H _m Representing N between an mth radar device and a server _a ×N _tx Order data transmission channel matrix, n _c (t) is N _a Additive Gaussian white noise vector with a mean of 0 and a variance ofIt will be appreciated that H _m Obtained from parameters of the actual communication system.

Step S124: and calculating the mean square error of the received vector and the real data value to obtain a result mean square error, and carrying out minimization constraint on the result mean square error to obtain a first result constraint condition.

In one embodiment, the error of the over-the-air calculation is typically measured as the resulting mean square error between the received signal and the true data value, expressed as:

in one embodiment, minimizing the resulting mean square error, the first resulting constraint is expressed as:

thereby yielding a first outcome constraint.

Step S130: and acquiring the transmitting power of the radar equipment to construct a first power constraint condition.

In one embodiment, referring to fig. 5, the process of constructing the first perceptual matrix constraint of step S130 includes the steps of:

step S131: and obtaining power information according to a transmitting end beam shaper.

In one embodiment, the power information is expressed as:

Step S132: setting the power information to be smaller than or equal to the transmitting power, and constructing a first power constraint condition.

In an embodiment, since the transmit power P of each radar apparatus is limited, the first power constraint needs to be satisfied in the beamforming design, expressed as:

thereby yielding a first power constraint.

Step S140: and constructing a first constraint condition set according to the first result constraint condition, the first perception matrix constraint condition and the first power constraint condition, and solving the first constraint condition set to obtain a first beamforming weight optimization value of the receiving end beamformer and a second beamforming weight optimization value of the transmitting end beamformer.

In one embodiment, the first set of constraints is expressed as:

in an embodiment, the conversion is required because the first constraint set is a non-convex optimization problem due to the coupling relationship of the receiving end beamformers between the transmitting end beamformers. Referring to fig. 6, step S140 includes the steps of:

step S141: and obtaining a first conversion relation between the transmitting end beam shaper and the receiving end beam shaper by using zero forcing design.

In one embodiment, zero forcing design (null) is a technique for suppressing signal interference. By introducing specific structures and parameters into the system, the response of the interference signal to specific output is zero, so that the interference signal is restrained. In this embodiment, in order to align signal amplitudes of the same type of data transmitted by each device as much as possible, a transmitting-end beamformer of the radar device adopts a zero-forcing design, and a coupling relationship between the transmitting-end beamformer and a receiving-end beamformer is removed by using the zero-forcing design, where a first conversion relationship between the transmitting-end beamformer and the receiving-end beamformer is expressed as:

Step S142: the first set of constraints is converted to a second set of constraints based on the first conversion relationship.

In one embodiment, referring to fig. 7, step S142 includes the steps of:

step S1421: and based on the first conversion relation, replacing the transmitting end beam shaper by the receiving end beam shaper in the first result constraint condition to obtain a second result constraint condition.

In one embodiment, substituting the first transformation relationship into the first result constraint yields a second result constraint expressed as:

step S1422: and based on the first conversion relation, replacing the transmitting end beam shaper by the receiving end beam shaper in the first power constraint condition to obtain a second power constraint condition.

In one embodiment, the second power constraint is expressed as:

step S1423: based on the first conversion relation, the receiving end beam shaper is used for replacing the transmitting end beam shaper in the first sensing matrix constraint condition, and a second sensing matrix constraint condition is obtained.

In one embodiment, the second perceptual matrix constraint is expressed as:

step S1424: and generating a second constraint condition set according to the second result constraint condition, the second perception matrix constraint condition and the second power constraint condition.

In one embodiment, the second set of constraints is expressed as:

through the above process, the coupling relation between the transmitting end beam shaper and the receiving end beam shaper is removed, and the variables in the second constraint condition set include the receiving end beam shaper a.

Step S143: and expressing the receiving end beam shaper as a semi-positive definite matrix by utilizing semi-positive scaling, and converting the second constraint condition set into a third constraint condition set according to the semi-positive definite matrix.

In one embodiment, the receiver beamformer is represented as a semi-positive definite matrix using semi-positive definite scalingThe semi-positive definite matrix is expressed as: />Referring to fig. 8, step S143 includes the steps of:

step S1431: and converting the second result constraint condition into a third result constraint condition according to the semi-positive definite matrix. In one embodiment, the third result constraint leaves only the noise-related termsThe third outcome constraint is expressed as:

step S1432: the second power constraint is converted to a third power constraint according to the semi-positive definite matrix. In one embodiment, the third power constraint is expressed as:

step S1433: and converting the second sensing matrix constraint condition into a third sensing matrix constraint condition according to the semi-positive definite matrix. In one embodiment, the third perceptual matrix constraint is expressed as:

Step S1434: and generating a third constraint condition set according to the third result constraint condition, the third perception matrix constraint condition, the third power constraint condition and the semi-positive definite matrix.

In one embodiment, the third set of constraints is expressed as:

wherein ≡gtoreq represents a semi-positive determination of the matrix, i.e. each element in the matrix is not less than zero.

To this end, the transmitting end beam shaper W _m And the optimization of the receiving end beam shaper A is converted into a pair of semi-positive definite matrixesThe optimization of (a) that is, the objective function of the third constraint set is a semi-positive definite matrix ++>Is a solution to (c).

Step S144: and performing convex optimization solution on the third constraint condition set to obtain a first beamforming weight optimization value of the receiving end beamforming device, and obtaining a second beamforming weight optimization value of the transmitting end beamforming device based on the first conversion relation.

In one embodiment, referring to fig. 9, step S144 includes the steps of:

step S1441: and carrying out convex optimization solution on the third constraint condition set to obtain a semi-positive definite matrix.

In an embodiment, since the objective function in the third constraint set is linear and all the constraint conditions are convex constraints, the third constraint set is converted into a convex problem, and the fourth constraint set is subjected to convex optimization solution to obtain the semi-positive definite matrix Is a value of (2).

In an embodiment, the convex optimization solution is performed by using a convex optimization tool kit (for example, matlab CVX tool kit, etc.), and the solution mode is not specifically limited in this embodiment.

Step S1442: and solving the optimization problem of the semi-positive definite matrix to obtain a first beamforming weight optimization value of the receiving end beamforming device.

In one embodiment, due toThe first beamforming weight optimization value of the receiving end beamformer a can be obtained by solving through a gaussian loop algorithm, and then the first beamforming weight optimization value of the receiving end beamformer a is obtained according to the first conversion relation.

In one embodiment, a gaussian loop solution process is used to solve a system of linear equations, which can be converted into a linear trapezoidal matrix with arbitrary complexity, thereby simplifying the solution process. The basic idea of Gaussian loop solution is as follows: the system of equations is simplified by a series of linear transformations and ultimately converted into a row-stepped trapezoidal matrix such that the coefficients of each unknown only appear on the main diagonal of the row in which it resides. Specifically, the algorithm is divided into the following steps:

and performing primary equal-line transformation on the coefficient matrix, and converting the coefficient matrix into an upper triangular matrix. I.e. elements of the triangular region under the coefficient matrix are eliminated. This step may be achieved by multiplying the first row by the inverse of the first column of the coefficient matrix's first coefficient and then adding it to the following row (i.e. gaussian elimination), or using the first equal row transform of the matrix (e.g. exchanging two rows, adding one row to a multiple of the other).

Then, starting from the last row, the corresponding unknowns are solved in turn. For the i-th unknown, the value of the i-th unknown can be found by multiplying all coefficients to the left of the i-th line (i-1 line and above) by their corresponding unknown values and then subtracting them from the right-hand term of the equation.

The above process is repeated until all unknowns are solved.

It should be noted that in performing a gaussian cycle solution, if all elements in a column of the coefficient matrix are 0, the column cannot be used as a main diagonal, and a non-zero element needs to be shifted onto the main diagonal of the column by way of a swap row.

In one embodiment, the gaussian random solution may generate the first beamforming weight optimization value by: extracting a random number from a Gaussian distribution with a mean value of 0 and a variance of 1; converting the random number into a required mean value and variance through linear transformation and translation operation; repeating the steps until the total number of the needed random variables is generated.

The embodiment of the application obtains the first beamforming weight optimization value of the receiving end beamforming device A and the transmitting end beamforming devices W of M radar devices _m The second beamforming weight optimization value of the antenna is used for realizing the simultaneous adjustment of the antennas of the receiving and transmitting ends.

In one embodiment, referring to fig. 10, a signal processing flow diagram of a communication awareness and computing integrated system is provided.

Referring to fig. 10, for the mth radar apparatus, a transmitting-end beamformer W is first utilized _m For the initial multiplex signal s _m [t]Beamforming is carried out to obtain multiplexingSignal W _m s _m [t]. The multiplexed signal then propagates in the channel using the data transmission channel matrix H _m And performing gain to obtain a transmission signal of the mth radar device. At the same time, the signal s is initially multiplexed _m [t]Through the target reflection matrix G _mm After adjustment of (2) and then overlap omega _m An interference signal represented by (t) and an additive white gaussian noise vector n _r (t) obtaining the target reflected signal y _m (t) reflecting the signal y according to the target _m (t) obtaining an estimate of the target reflection matrixThereby obtaining the mean square error MSE (G) _mm ). Then, the receiving vector of the server is calculated, for the server, the received signal is the total transmission signal of the transmission signals of all radar devices after being subjected to air calculation and superposition, and after being received, the receiving vector is obtained by carrying out wave beam forming through a wave beam forming device A at the receiving end>

It can be understood that after the joint design of the radar sensing and the beamforming of the antenna of the receiving and transmitting end is performed on the communication signal, the calculation performance of the aerial calculation is improved.

In the application scene of communication perception calculation integration, a plurality of multi-antenna radar devices simultaneously transmit a perception signal for target detection and a communication signal for transmitting data, wherein the perception signal is received by the radar devices after being reflected by a target, and the communication signal is received by a server after being calculated in the air. The sensor extracts the target information according to the received signals, and the server presumes the statistical information of the data of each radar device according to the received air calculation result. In the related art, sensing, communication and calculation are often regarded as independent links, and lack of global consideration leads to limited data processing efficiency. For example, the bearing capacity of the communication channel and the computing capacity of the server are not considered in the design process of the data sensing link, and excessive sensing data is wasted because subsequent transmission and computation cannot be performed. In addition, for radar devices employing radar sensing, the radar sensing signal and the data transmission signal compete for wireless spectrum resources, burdening the wireless channel, and resulting in more congestion of the communication link. Therefore, in order to combine the air calculation and communication perception fusion technology, the embodiment of the application minimizes the air calculation error on the premise of ensuring the perception accuracy, and improves the air calculation performance and the data processing efficiency, thereby improving the resource utilization efficiency.

The communication perception calculation integrated antenna multiplexing beam forming technology can be used for target positioning. As shown in fig. 10, a plurality of radar devices in the target positioning application scene detect the same perceived target, estimate the relative angle and distance of the perceived target from the received target reflection signal, estimate the position of the perceived target according to the coordinates of the perceived target, and send the position information of the perceived target to the server. Referring to fig. 10, the radar apparatus i measures the target position as:the radar apparatus m measures the target position as: />And carrying out air calculation on the information sent by all radar equipment in a waveform superposition mode in the transmission process, and finally receiving the average value of the estimated target positions of all radar equipment by the server.

Referring to fig. 10, in an embodiment, assuming that an actual target position is at (5, 30) meters, 10 radar devices are equally spaced at y-axis 0 to 20 meters for estimating the target position and transmitting the estimated result to a server. The method can see that the estimated target position of each radar device deviates from the actual position, and the estimated target position after being averaged by the aerial calculation is more accurate, so that the design concept of minimizing the aerial calculation error on the premise of ensuring the perception accuracy is embodied. Compared with the arrival angle method adopted by the related art target positioning, the effect of the embodiment of the application is better than that of the arrival angle method.

The technical scheme provided by the embodiment of the application is that a multiplexing signal capable of simultaneously carrying out communication perception calculation is utilized to construct a first result constraint condition related to a receiving result, a first perception matrix constraint condition related to perception performance and a first power constraint condition related to transmitting power; and constructing a first constraint condition set by using the first result constraint condition, the first perception matrix constraint condition and the first power constraint condition, and then solving the first constraint condition set to obtain the optimized values of the receiving end beam shaper and the transmitting end beam shaper. The embodiment of the application designs the beam forming of the transmitting end and the beam forming of the receiving end, simultaneously adjusts the antennas of the receiving and transmitting ends, minimizes the air calculation error on the premise of ensuring the sensing accuracy, and improves the air calculation performance and the data processing efficiency, thereby improving the resource utilization efficiency.

The embodiment of the application also provides an antenna multiplexing beamforming device, which can realize the antenna multiplexing beamforming method, and referring to fig. 13, the antenna multiplexing beamforming device is applied to the communication perception calculation integrated system as shown in fig. 1, and the communication perception calculation integrated system comprises: the system comprises a transmitting end beam shaper, a receiving end beam shaper and at least one radar device, wherein the transmitting signals of the radar device are obtained by carrying out beam shaping on an initial multiplexing signal by utilizing the transmitting end beam shaper, and the multiplexing signal is a data communication signal or a multiplexing signal; the radar equipment is also used for receiving a target reflection signal obtained by sensing a target reflection emission signal; the device comprises:

The sensing matrix constraint condition construction module 1310 is configured to obtain a target reflection signal received by the radar device, obtain a processing signal, calculate according to the processing signal to obtain a statistical result matrix, obtain a mean square error of the target reflection matrix of each radar device according to the statistical result matrix, and construct a first sensing matrix constraint condition based on an error tolerance value.

The result constraint condition construction module 1320 is configured to obtain a received vector from the multiplexed signal based on the receiving end beamformer, calculate a result mean square error between the received vector and the real data value, and construct a first result constraint condition by minimizing the result mean square error.

The power constraint condition construction module 1330 is configured to acquire a transmit power of the radar device to construct a first power constraint condition.

The weight optimization value calculation module 1340 is configured to construct a first constraint condition set according to the first result constraint condition, the first perception matrix constraint condition and the first power constraint condition, and solve the first constraint condition set to obtain a first beamforming weight optimization value of the receiving-end beamformer and a second beamforming weight optimization value of the transmitting-end beamformer.

The specific implementation manner of the antenna multiplexing beamforming device in this embodiment is substantially identical to the specific implementation manner of the antenna multiplexing beamforming method described above, and will not be described herein.

The embodiment of the invention also provides electronic equipment, which comprises:

at least one memory;

at least one processor;

at least one program;

the program is stored in the memory, and the processor executes the at least one program to implement the antenna multiplexing beamforming method according to the present invention. The electronic equipment can be any intelligent terminal including a mobile phone, a tablet personal computer, a personal digital assistant (Personal Digital Assistant, PDA for short), a vehicle-mounted computer and the like.

Referring to fig. 14, fig. 14 illustrates a hardware structure of an electronic device according to another embodiment, the electronic device includes:

the processor 1401 may be implemented by a general purpose CPU (central processing unit), a microprocessor, an application specific integrated circuit (ApplicationSpecificIntegratedCircuit, ASIC), or one or more integrated circuits, etc. for executing related programs, so as to implement the technical solution provided by the embodiments of the present invention;

the memory 1402 may be implemented in the form of a ROM (read only memory), a static storage device, a dynamic storage device, or a RAM (random access memory). Memory 1402 may store an operating system and other application programs, and when the technical solutions provided in the embodiments of the present disclosure are implemented in software or firmware, relevant program codes are stored in memory 1402, and the processor 1401 invokes an antenna multiplexing beamforming method for performing the embodiments of the present disclosure;

An input/output interface 1403 for implementing information input and output;

the communication interface 1404 is configured to implement communication interaction between the device and other devices, and may implement communication in a wired manner (e.g. USB, network cable, etc.), or may implement communication in a wireless manner (e.g. mobile network, WIFI, bluetooth, etc.); and

bus 1405) for transferring information between components of the device (e.g., processor 1401, memory 1402, input/output interface 1403, and communication interface 1404);

wherein processor 1401, memory 1402, input/output interface 1403 and communication interface 1404 enable communication connections between each other within the device via bus 1405.

The embodiment of the application also provides a storage medium, which is a computer readable storage medium, and the storage medium stores a computer program, and the computer program realizes the antenna multiplexing beam forming method when being executed by a processor.

The memory, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as non-transitory computer executable programs. 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 optionally includes memory remotely located relative to 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 multiplexing beam forming method, the communication perception calculation integrated system and the related device provided by the embodiment of the application construct a first result constraint condition related to a receiving result, a first perception matrix constraint condition related to perception performance and a first power constraint condition related to transmitting power by using multiplexing signals capable of simultaneously carrying out communication perception calculation; and constructing a first constraint condition set by using the first result constraint condition, the first perception matrix constraint condition and the first power constraint condition, and then solving the first constraint condition set to obtain the optimized values of the receiving end beam shaper and the transmitting end beam shaper. The embodiment of the application designs the beam forming of the transmitting end and the beam forming of the receiving end, simultaneously adjusts the antennas of the receiving and transmitting ends, minimizes the air calculation error on the premise of ensuring the sensing accuracy, and improves the air calculation performance and the data processing efficiency, thereby improving the resource utilization efficiency.

The embodiments described in the embodiments of the present application are for more clearly describing the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application, and those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.

It will be appreciated by persons skilled in the art that the embodiments of the application are not limited by the illustrations, and that more or fewer steps than those shown may be included, or certain steps may be combined, or different steps may be included.

The above described apparatus embodiments are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

Those of ordinary skill in the art will appreciate that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof.

The terms "first," "second," "third," "fourth," and the like in the description of the application and in the above figures, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

It should be understood that in the present application, "at least one (item)" means one or more, and "a plurality" means two or more. "and/or" for describing the association relationship of the association object, the representation may have three relationships, for example, "a and/or B" may represent: only a, only B and both a and B are present, wherein a, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b or c may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the above-described division of units is merely a logical function division, and there may be another division manner in actual implementation, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, including multiple instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method of the various embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing a program.

The preferred embodiments of the present application have been described above with reference to the accompanying drawings, and are not thereby limiting the scope of the claims of the embodiments of the present application. Any modifications, equivalent substitutions and improvements made by those skilled in the art without departing from the scope and spirit of the embodiments of the present application shall fall within the scope of the claims of the embodiments of the present application.

Claims

1. The antenna multiplexing beam forming method is characterized by being applied to a communication perception and calculation integrated system, and the communication perception and calculation integrated system comprises the following steps: the system comprises a transmitting end beam shaper, a receiving end beam shaper and at least one radar device, wherein a transmitting signal of the radar device is a multiplexing signal obtained by performing beam shaping on an initial multiplexing signal by utilizing the transmitting end beam shaper; the radar equipment is also used for receiving a target reflection signal obtained by reflecting the emission signal by a perception target; the method comprises the following steps:

2. The method of antenna multiplexing beamforming according to claim 1, wherein said obtaining a received vector from the multiplexed signal based on the receiving-side beamformer, and calculating a resulting mean square error between the received vector and a real data value, and minimizing the resulting mean square error to construct a first resulting constraint, comprises:

3. The method of antenna multiplexing beamforming according to claim 1, wherein said obtaining the target reflected signals received by the radar devices to obtain a processed signal, calculating a statistical result matrix according to the processed signal, obtaining a mean square error of the target reflected matrix of each of the radar devices according to the statistical result matrix, and constructing a first sensing matrix constraint condition based on an error tolerance value, includes:

calculating a target reflection signal according to the target reflection matrix of the radar equipment, the multiplexing signal and the interference signal;

4. The method of antenna multiplexing beamforming according to claim 1, wherein said obtaining the transmit power of the radar device constructs a first power constraint, comprising:

obtaining power information according to the transmitting end beam shaper;

5. The method of antenna multiplexing beamforming according to claim 1, wherein said solving the first constraint set to obtain a first beamforming weight optimization value of the receiving end beamformer and a second beamforming weight optimization value of the transmitting end beamformer comprises:

6. The method of antenna multiplexing beamforming according to claim 5, wherein said converting said first set of constraints into a second set of constraints based on said first conversion relationship comprises:

7. The method of antenna multiplexing beamforming according to claim 5, wherein said representing said receiving-side beamformer as a semi-positive definite matrix using semi-positive definite scaling, converting said second set of constraints into a third set of constraints based on said semi-positive definite matrix, comprises:

8. The method of antenna multiplexing beamforming according to claim 7, wherein said performing convex optimization solution on said third constraint condition set to obtain said first beamforming weight optimization value of said receiving end beamformer comprises:

and solving the optimization problem of the semi-positive definite matrix to obtain the first beamforming weight optimization value of the receiving end beamforming device.

9. An antenna multiplexing beam forming device, which is characterized by being applied to a communication perception calculation integrated system, wherein the communication perception calculation integrated system comprises: the system comprises a transmitting end beam shaper, a receiving end beam shaper and at least one radar device, wherein a transmitting signal of the radar device is a multiplexing signal obtained by performing beam shaping on an initial multiplexing signal by utilizing the transmitting end beam shaper; the radar equipment is also used for receiving a target reflection signal obtained by reflecting the emission signal by a perception target; the device comprises:

10. A communication perception calculation integrated system, characterized in that the system comprises a transmitting end beam shaper and a receiving end beam shaper, wherein a first beam shaping weight optimization value of the receiving end beam shaper and a second beam shaping weight optimization value of the transmitting end beam shaper are calculated according to the antenna multiplexing beam shaping method of any one of claims 1 to 8.

11. An electronic device comprising a memory storing a computer program and a processor implementing the antenna multiplexing beamforming method according to any of claims 1 to 8 when the computer program is executed by the processor.

12. A computer readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the antenna multiplexing beamforming method of any of claims 1 to 8.