CN116846439A

CN116846439A - Clustering beam forming method, communication perception calculation integrated system and related device

Info

Publication number: CN116846439A
Application number: CN202310558367.4A
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: 2023-10-03

Abstract

The embodiment of the application provides a clustering beam forming method, a communication perception calculation integrated system and a related device, and relates to the technical field of communication. The method comprises the following steps: constructing a first result constraint condition related to a received 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 wave beam forming of the transmitting end to ensure the radar perception performance, designs the wave beam forming of the receiving end to improve the aerial calculation performance, and simultaneously adjusts the antenna of the receiving end, thereby further improving the resource utilization efficiency.

Description

Clustering 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 clustered beam forming method, a communication perception computing integrated system, and a related device.

Background

Along with the development of the internet of things, mass data needs to be collected from the environment by sensing 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.

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 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 clustering 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 cluster 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, a radar sensing beam shaper and at least one sensing device, wherein a transmitting signal of the sensing device comprises: the transmitting end beam forming is utilized to beam-form the initial data transmission signal to obtain a data transmission signal, the radar sensing beam forming is utilized to beam-form the initial radar sensing signal to obtain a radar sensing signal, and the sensing equipment is also used for receiving a target reflection signal obtained by reflecting the transmitting signal by a sensing target; the method comprises the following steps:

Obtaining the target reflection signals received by the sensing 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 sensing 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, a receiving vector is obtained according to the data transmission signal and the radar sensing 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;

acquiring the transmitting power of the sensing 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 some embodiments, the constructing a first result constraint condition based on the receiving end beamformer, obtaining a receiving vector according to the data transmission signal and the radar sensing signal, and calculating a result mean square error between the receiving vector and a real data value, and minimizing the result mean square error includes:

Calculating to obtain the real data value according to the initial data transmission signal of each sensing device;

calculating a transmission total signal according to the transmission signal of each sensing device, wherein the transmission signal consists of a first transmission signal and a second transmission signal, the first transmission signal is calculated according to the data transmission signal and a data transmission channel matrix, and the second transmission signal is calculated according to the radar sensing signal and the target reflection signal channel matrix;

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 some embodiments, the obtaining the target reflection signals received by the sensing 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 sensing device according to the statistical result matrix, and constructing a first sensing matrix constraint condition based on an error tolerance value, including:

Calculating to obtain a target reflection signal according to the target reflection matrix of the sensing equipment, the radar sensing signal and the interference signal;

obtaining all target reflected signals of the sensing 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 some embodiments, the obtaining the transmit power of the sensing device constructs a first power constraint, including:

calculating the trace of the data transmission signal to obtain first power information, and calculating the trace of the radar sensing signal to obtain second power information;

calculating power information according to the first power information and the second power information, enabling the power information to be smaller than or equal to the transmitting power, and constructing the first power constraint condition.

In some embodiments, 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;

obtaining a result update of the radar sensing beam shaper according to unitary matrixes and scale factors by utilizing an orthogonal matrix principle, and converting the second constraint condition set into a third constraint condition set based on the result update;

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

and performing convex optimization solving on the fourth 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 some embodiments, the converting the first set of constraints into a second set of constraints based on the first conversion relationship comprises:

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;

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

In some embodiments, the obtaining a result update of the radar-aware beamformer based on unitary matrices and scale factors using orthogonal matrix principles and converting the second set of constraints to a third set of constraints based on the result update comprises:

replacing the radar sensing beam shaper in the second result constraint condition by using the result update to obtain a third result constraint condition;

replacing the radar sensing beam shaper in the first sensing matrix constraint condition by using the result update to obtain a second sensing matrix constraint condition;

replacing the radar sensing beam shaper in the second power constraint condition by using the result update to obtain a third power constraint condition;

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

In some embodiments, the representing the receiving end beamformer as a semi-positive definite matrix using semi-positive scaling, converting the third set of constraints into a fourth set of constraints according to the semi-positive definite matrix includes:

obtaining the minimum factor value of the scale factor;

converting the third result constraint condition into a fourth result constraint condition according to the minimum factor value and the semi-positive definite matrix;

converting the third power constraint condition into a fourth power constraint condition according to the minimum factor value and the semi-positive definite matrix;

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

In some embodiments, performing convex optimization solution on the fourth constraint condition set to obtain the first beamforming weight optimization value of the receiving end beamformer includes:

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

and carrying out Gaussian cycle solution on the semi-positive definite matrix to obtain the first beamforming weight optimization value of the receiving end beamforming device.

To achieve the above object, a second aspect of the embodiments of the present application provides an antenna cluster 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, a radar sensing beam shaper and at least one sensing device, wherein a transmitting signal of the sensing device comprises: the transmitting end beam shaper is utilized to beam-shape the initial data transmission signal to obtain a data transmission signal, the radar sensing beam shaper is utilized to beam-shape the initial radar sensing signal to obtain a radar sensing signal, and the sensing equipment is also used for receiving a target reflection signal obtained by reflecting the transmitting signal by a sensing target; the device comprises:

The sensing matrix constraint condition construction module is used for acquiring the target reflection signals received by the sensing devices 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 sensing device 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 data transmission signal and the radar sensing 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 sensing 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 clustering 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 clustering beam forming method, the communication perception calculation integrated system and the related device provided by the embodiment of the application are characterized in that 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 are constructed; 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 wave beam forming of the transmitting end to ensure the radar perception performance, designs the wave beam forming of the receiving end to improve the aerial calculation performance, and simultaneously adjusts the antenna of the receiving end, thereby further 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 cluster 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 S143 in fig. 6.

Fig. 9 is a flowchart of step S144 in fig. 6.

Fig. 10 is a flowchart of step S145 in fig. 6.

Fig. 11 is a signal processing flow chart of a communication perception calculation integrated system according to still another embodiment of the present invention.

Fig. 12 is a schematic diagram of a variation curve of a mean square error of a result of a uniform air calculation with the number of antennas of a server in an application scenario of an antenna clustering beamforming method according to another embodiment of the present invention.

Fig. 13 is a schematic diagram of a variation curve of a mean square error of a result of a uniform air calculation with the number of antennas of a sensing device in an application scenario of an antenna clustering beam forming method according to another embodiment of the present invention.

Fig. 14 is a block diagram of an antenna cluster beamforming apparatus according to another embodiment of the present invention.

Fig. 15 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.

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 the above, the embodiment of the invention provides a clustering beam forming method, a communication perception calculation integrated system and a related device, which are used for designing the beam forming of a transmitting end to ensure radar perception performance, and designing the beam forming of a receiving end to improve aerial calculation performance and simultaneously adjust an antenna of a receiving end so as to further improve 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 with Ns antennasSensing device 120, M sensing devices 120 forming a device clusterAnd a server 130 for performing aerial calculations, the server 130 having Na antennas. In one embodiment, server 130 may be a wireless router with data processing functionality.

The entire signal transceiving time is divided into T time periods, and each sensing device 120 may simultaneously transmit a radar sensing signal for sensing the sensing target 110 and a data transmission signal for data communication during each time period. Wherein the radar sensing signal is reflected by the sensing target 110 to obtain a target reflected signal, the target reflected signal is received by the corresponding sensing device 120, and the data transmission signal is received by the server 130 after air calculation. Wherein the target reflection matrix of each sensing device 120 to the sensing target 110 in the radar sensing phase is Gii, and the data transmission channel matrix of each sensing device 120 to the server 130 in the data communication phase is Hi, wherein 1.ltoreq.i.ltoreq.m.

In one embodiment, the antennas of each sensing device 120 are divided into two parts, one part is a sensing antenna for sensing radar, the number of which is Nr, and the other part is a sensing antenna for transmitting data, the number of which is Nc, and the number of antennas satisfies: ns=nr+nc.

In the mth sensing device, ntx antennas in Nr sensing antennas are used for transmitting radar sensing signals, and Nrx antennas are used for receiving target reflected signals y when radar sensing is performed _m (t) the number of antennas satisfies: nr=ntx+nrx.

In the t-th time period, the initial data transmission signal sent by the mth sensing device 120 can be expressed as a K-dimensional vector d _m (t), wherein K represents the number of functions needed to perform aerial computation, which can be obtained in an actual computing scene.

For different sensing devices 120, an initial data transmission signal d _m (t) the mean is required to be 0 variance

Similarly, the initial radar sense signal generated by the mth sensing device 120 during the t-th time period may also be represented as a K-dimensional vector s _m (t) the radar sensing signal needs to meet the requirement that the mean value is 0 and the variance is 1

In addition, the data transmission signal is orthogonal to the radar sensing signal, and the data transmission signal and the radar sensing signal are statistically independent, namely, for all i and m, the conditions are satisfied:

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: a transmitting end beam shaper, a receiving end beam shaper and a radar sensing beam shaper. 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 cluster beamforming method in an embodiment of the present application.

Fig. 2 is an optional flowchart of an antenna cluster beamforming method according to an embodiment of the present application, 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 all sensing devices 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 sensing device 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 to obtain a target reflection signal according to the target reflection matrix, the radar sensing signal and the interference signal of the sensing equipment.

In an embodiment, for the mth sensing device, a transmitting-end beamformer W is utilized _m For initial data transmission signal d _m (t) performing beamforming to obtain a data transmission signal, which is expressed as: w (W) _m d _m (t) sensing the beamformer F with radar _m For the initial radar sense signal s _m (t) performing beamforming to obtain radar sensing signals, denoted as F _m s _m (t), so that the mth sensing device transmits a signal x in the t-th period _m (t) is expressed as:

wherein, the transmitting end beam shaper W _m Is N _c X K-order matrix, radar sensing beamformer F _m Is N _tx A matrix of order x K.

For the mth sensing equipment, a target reflection signal y is obtained after the radar sensing signal is reflected by the sensing target _m (t) expressed as:

y _m (t)＝G _mm F _m s _m (t)+Ω _m (t)+n _r (t)

wherein G is _mmm Representing the target reflection matrix of the mth sensing device. For the mth and ith sensing devices,G _imm target reflection matrix representing Nrx×Ntx order, Q _im Direct channel matrix of radar signal representing Nrx x Ntx order, C _im Data signal reflection channel matrix representing Nrx Nc order, O _imm Direct channel matrix of data signal representing Nrx XNc order, n _r (t) is an Nrx-dimensional additive Gaussian white noise vector which follows Rayleigh distributionIt will be appreciated that Q _im And o _im Obtained from parameters of the actual communication system.

Omega above _m And (t) representing an interference signal, which is calculated according to a transmitting end beam shaper, a data signal reflection channel matrix, a data signal direct channel matrix, an initial data transmission signal and an initial radar sensing signal.

Step S112: and obtaining a target reflected signal of the sensing 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 one embodiment, the signal y is reflected by the target for T time periods _m (t) performing matched filtering to obtain the signal statistical result of the mth sensing device, and recording the signal statistical result as a processed signalThis 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 matrix that obeys the rayleigh distribution:

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

In one embodiment, a statistical result matrix is calculatedProbability density function +.>Expressed as:

the probability density functionFor describing a statistical result matrix->At the target reflection matrix G _mm Is a probability density of (c).

G is then found by minimizing the log-likelihood function _mm Maximum likelihood value of (2)Expressed as:

deriving the maximum likelihood value, expressed as:

setting the maximum likelihood value and the corresponding derivative to zero to obtain the estimated value of the 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 eta of an mth sensing 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 a data transmission signal and a radar sensing signal, and a 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 data transmission signal of each sensing device.

In one embodiment, the actual data value is the initial data transmission signal for each sensing device, expressed as:

step S122: and calculating a transmission total signal according to the transmission signal of each sensing device.

In one embodiment, the transmission signal is composed of a first transmission signal and a second transmission signal, wherein the first transmission signal is based on the data transmission signal W _m d _m (t) data transmission channel matrix H _m Calculated, expressed as: h _m W _m d _m (t). The second transmission signal is based on the radar sensing signal F _m s _m (t) and target reflected signal channel matrix R _m Calculated, expressed as: r is R _m F _m s _m (t)。

From the topThe transmission signals of the mth sensing device obtained by the first transmission signal and the second transmission signal are expressed as follows: h _m W _m d _m (t)+R _m F _m s _m (t) calculating a transmission signal of each sensing device to obtain a transmission total signal, which is expressed as:

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 sensing devices, and after receiving, the total transmission signal is beamformed by a receiving end beam forming device to obtain a receiving vectorReceive vector->A vector of dimension K, expressed as:

wherein A represents a receiving end beam shaper and H _m N representing the mth sensing device _a ×N _c Data transmission channel matrix of order, R _m N representing the mth sensing device _a ×N _tx Radar sensing signal channel matrix of order, n _c (t) is N _a Additive gaussian white noise vector of dimension, which obeys distributionAnd is connected with d _m (t) and s _m (t) statistical independence. It will be appreciated that R _m And 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 resulting mean square error from the received vector and the true data value is 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: the method comprises the steps of obtaining the transmitting power of the sensing 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: calculating the trace of the data transmission signal to obtain first power information, and calculating the trace of the radar sensing signal to obtain second power information.

In one embodiment, the first power information is expressed as:the second power information is expressed as:

step S132: calculating power information according to the first power information and the second power information, enabling 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 sensing device is limited, the first power constraint needs to be met 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 problem of non-convex optimization due to the coupling relationship between the transmitting end beamformer, the receiving end beamformer and the radar-aware beamformer. 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, the coupling relationship between the transmitting-end beamformer and the receiving-end beamformer is removed by zero-forcing design, and the 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: and generating a second constraint condition set according to the second result constraint condition, the first perception matrix constraint condition and the second power constraint condition.

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

through the 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 comprise the receiving end beam shaper A and the radar sensing beam shaper F _m Receiving end beam shaper A and radar sensing beam shaper F _m There is still a coupling relationship and therefore the second set of constraints remains a non-convex optimization problem.

Step S143: and obtaining a result update of the radar sensing beam shaper according to the unitary matrix and the scale factor by utilizing an orthogonal matrix principle, and converting the second constraint condition set into a third constraint condition set based on the result update.

In one embodiment, unitary matrix refers to a complex matrix in linear algebra whose conjugate transpose is equal to the inverse matrix. In short, a unitary matrix is a complex matrix satisfying a specific condition, and is called a real orthogonal matrix if a defined matrix definition field is only in a real number field, where the unitary matrix is equivalent to an orthogonal matrix. In this embodiment, the radar-aware beamformer F is designed in a multi-antenna system for further decoupling _m Limiting to orthogonal matrix, let D _m The representation satisfiesCan be updated as a result, expressed as: f (F) _m ＝α _m D _m Wherein alpha is _m Is a positive scaling factor.

In one embodiment, referring to fig. 8, step S143 includes the steps of:

step S1431: and replacing the radar sensing beam shaper in the second result constraint condition by using the result update to obtain a third result constraint condition.

In one embodiment, the third result constraint is expressed as:

step S1432: and replacing the radar sensing beam shaper in the first sensing matrix constraint condition by using the result update to obtain a second sensing matrix constraint condition.

In an embodiment, the result update is substituted into the first perceptual matrix constraint to obtain a second perceptual matrix constraint, where the second perceptual matrix constraint is expressed as:

step S1433: and replacing the radar sensing beam shaper in the second power constraint condition by using the updated result to obtain a third power constraint condition.

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

step S1434: and generating a third constraint condition set according to the third result constraint condition, the second perception matrix constraint condition and the third power constraint condition.

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

from the above, it can be seen that the third set of constraints has been receivedEnd beamformer A and radar sensing beamformer F _m Is removed.

Step S144: representing a receiving end beamformer as a semi-positive definite matrix using semi-positive scalingThe third set of constraints is converted into a fourth set of constraints 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. 9, step S144 includes the steps of:

step S1441: the minimum factor value of the scale factor is obtained.

From the second perceptual matrix constraint, it can be seen that increasing α _m The error of the air calculation will be increased, so in order to minimize the air calculation error, the present embodiment takes α _m The minimum value of the second sensing matrix constraint condition is left and right equal to obtain the minimum factor valueExpressed as:

step S1442: and converting the third result constraint condition into a fourth result constraint condition according to the minimum factor value and the semi-positive definite matrix.

In one embodiment, the fourth result constraint is expressed as:

step S1443: and converting the third power constraint condition into a fourth power constraint condition according to the minimum factor value and the semi-positive definite matrix.

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

step S1444: and generating a fourth constraint condition set according to the fourth result constraint condition, the fourth power constraint condition and the semi-positive definite matrix.

In one embodiment, the fourth 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 fourth constraint set is a semi-positive definite matrix ++ >Is a solution to (c).

Step S145: and performing convex optimization solution on the fourth 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. 10, step S145 includes the steps of:

step S1451: and carrying out convex optimization solution on the fourth constraint condition set to obtain a semi-positive definite matrix.

In an embodiment, since the objective function in the fourth constraint set is linear and all the constraint conditions are convex constraints, the fourth 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 matrixIs 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 S1452: and carrying out Gaussian cycle solution on the semi-positive definite matrix to obtain a first beamforming weight optimization value of the receiving end beamforming device.

In one embodiment, due toAnd solving by using a Gaussian cycle algorithm to obtain a first beamforming weight optimization value of the receiving end beamformer A, and further obtaining the first beamforming weight optimization value of the receiving end beamformer A 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.

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 sensing 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. 11, a signal processing flow diagram of a communication awareness and computing integrated system is provided.

Referring to fig. 11, for the mth sensing device, a transmitting-end beamformer W is first utilized _m For initial data transmission signal d _m (t) beamforming to obtain data transmission signal W _m d _m (t) sensing the beamformer F with radar _m For the initial radar sense signal s _m (t) performing beam forming to obtain a radar sensing signal F _m s _m (t). The radar sensing signal and the data transmission signal are then propagated in the channel using the data transmission channel matrix H _m And performing gain to obtain a transmission signal of the mth sensing device. At the same time, radar sense signal F _m s _m (t) pass through the target reflection momentArray 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 matrixAnd then obtaining the mean square error MSE (Gmm) of the target reflection matrix. 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 the sensing devices after being subjected to air calculation and superposition, and the receiving vector is obtained by carrying out wave beam forming through a wave beam forming device at the receiving end after receiving>

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 sensing devices simultaneously transmit radar perception signals for target detection and communication signals for data transmission, wherein the radar perception signals are received by the sensing devices after being reflected by targets, and the communication signals are received by a server after aerial calculation. The sensor extracts target information according to the received radar sensing signals, and the server presumes the statistical information of the data of each sensing device according to the received air calculation result. In the related art, the antenna selection scheme superimposes the channel gains of all users, and selects a plurality of receiving antennas with the largest channel gains from the superimposed results as the receiving end. The standard for measuring radar perception performance by the antenna clustering beamforming technology of the communication perception and calculation integrated system is the target reflection matrix mean square error, the standard for measuring aerial calculation performance is the result mean square error between a received vector and a real data value, and the two have a competitive relationship, so that the aerial calculation performance is improved as much as possible while the radar perception performance is ensured.

Fig. 12 is a plot of the resulting mean square error of the homogenized air calculation as a function of the number of antennas at the server. It can be seen that as the number of antennas of the server increases, the resulting mean square error gradually decreases. This is because more receive antennas will increase the optimization dimension of the receive end beamformer, thereby reducing errors with hierarchical gain. Compared with the antenna selection scheme in the related art, the antenna clustering beam forming method provided by the embodiment of the application can obviously reduce the mean square error of the result of air calculation.

Fig. 13 is a plot of the resulting mean square error of the homogenized air calculation as a function of the number of antennas of the sensing device. It can be seen that the air calculated mean square error gradually increases as the number of antennas of the sensing device increases. This is because adding an antenna to the sensing device will result in an increase in the dimension of the target reflection matrix of the perceived target, making radar perception performance limitations more stringent. Compared with the antenna selection scheme in the related art, the antenna clustering beam forming method provided by the embodiment of the application can obviously reduce the mean square error of the result of air calculation.

According to the technical scheme provided by the embodiment of the application, 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 are constructed; 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 wave beam forming of the transmitting end to ensure the radar perception performance, designs the wave beam forming of the receiving end to improve the aerial calculation performance, and simultaneously adjusts the antenna of the receiving end, thereby further improving the resource utilization efficiency.

The embodiment of the invention also provides an antenna clustering beam forming device, which can realize the antenna clustering beam forming method, and referring to fig. 14, the antenna clustering beam forming 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, a radar sensing beam shaper and at least one sensing device, wherein the transmitting signals of the sensing device comprise: the method comprises the steps of carrying out beam forming on an initial data transmission signal by using a transmitting end beam forming device to obtain a data transmission signal, carrying out beam forming on an initial radar sensing signal by using a radar sensing beam forming device to obtain a radar sensing signal, and receiving a target reflection signal obtained by sensing a target reflection transmitting signal by using sensing equipment; the device comprises:

the sensing matrix constraint condition construction module 1410 is configured to obtain a target reflection signal received by a sensing device, obtain a processing signal, calculate a statistical result matrix according to the processing signal, obtain a mean square error of the target reflection matrix of each sensing 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 1420 is configured to obtain a reception vector from the data transmission signal and the radar sensing signal based on the receiving end beamformer, calculate a result mean square error between the reception 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 1430 is configured to acquire a transmit power of the sensing device to construct a first power constraint condition.

The weight optimization value calculation module 1440 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 cluster beam forming device in this embodiment is substantially identical to the specific implementation manner of the antenna cluster beam forming 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 cluster beam forming 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. 15, fig. 15 illustrates a hardware structure of an electronic device according to another embodiment, the electronic device includes:

the processor 1501 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 to implement the technical solution provided by the embodiments of the present invention;

the memory 1502 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). The memory 1502 may store an operating system and other application programs, and when the technical solutions provided in the embodiments of the present disclosure are implemented by software or firmware, relevant program codes are stored in the memory 1502, and the processor 1501 invokes an antenna cluster beamforming method for executing the embodiments of the present disclosure;

an input/output interface 1503 for inputting and outputting information;

the communication interface 1504 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 1505) for transferring information between components of the device (e.g., processor 1501, memory 1502, input/output interface 1503, and communication interface 1504);

wherein the processor 1501, the memory 1502, the input/output interface 1503 and the communication interface 1504 enable communication connection between each other within the device via the bus 1505.

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 clustering 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 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 clustering beam forming method is characterized by being applied to a communication perception calculation integrated system, and the communication perception calculation integrated system comprises the following steps: the system comprises a transmitting end beam shaper, a receiving end beam shaper, a radar sensing beam shaper and at least one sensing device, wherein a transmitting signal of the sensing device comprises: the transmitting end beam forming is utilized to beam-form the initial data transmission signal to obtain a data transmission signal, the radar sensing beam forming is utilized to beam-form the initial radar sensing signal to obtain a radar sensing signal, and the sensing equipment is also used for receiving a target reflection signal obtained by reflecting the transmitting signal by a sensing target; the method comprises the following steps:

2. The method of antenna cluster beamforming according to claim 1, wherein said constructing a first result constraint based on said receiving-side beamformer, obtaining a received vector from said data transmission signal and said radar-aware signal, and calculating a resulting mean square error between said received vector and a true data value, minimizing said resulting mean square error, comprises:

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

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

5. The method of antenna cluster 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 cluster 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 cluster beamforming according to claim 6, wherein said obtaining a result update of said radar-aware beamformer based on unitary matrices and scale factors using orthogonal matrix principles and converting said second set of constraints to a third set of constraints based on said result update comprises:

8. The method of antenna cluster beamforming according to claim 7, wherein said representing said receiving-side beamformer as a semi-positive definite matrix with semi-positive definite scaling, converting said third set of constraints into a fourth set of constraints according to said semi-positive definite matrix, comprises:

obtaining the minimum factor value of the scale factor;

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

10. An antenna clustering 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, a radar sensing beam shaper and at least one sensing device, wherein a transmitting signal of the sensing device comprises: the transmitting end beam shaper is utilized to beam-shape the initial data transmission signal to obtain a data transmission signal, the radar sensing beam shaper is utilized to beam-shape the initial radar sensing signal to obtain a radar sensing signal, and the sensing equipment is also used for receiving a target reflection signal obtained by reflecting the transmitting signal by a sensing target; the device comprises:

11. 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 clustering beam shaping method of any one of claims 1 to 9.

12. An electronic device comprising a memory storing a computer program and a processor implementing the antenna cluster beamforming method of any of claims 1 to 9 when the computer program is executed by the processor.

13. A computer readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the antenna cluster beamforming method of any of claims 1 to 9.