Sensing integrated beamforming transmission method, network device, apparatus and medium

Abstract

The application provides a sensing-integrated beamforming transmission method, a network device, an apparatus and a medium. The method comprises: a network device receiving communication pilot signals respectively transmitted by M terminals and sensing pilot signals respectively reflected or scattered by N sensing targets and then arriving at the network device; performing communication channel estimation based on the communication pilot signals to obtain a communication estimation channel matrix corresponding to each terminal; performing sensing channel estimation based on the sensing pilot signals to obtain a sensing estimation channel matrix corresponding to each sensing target; determining a hybrid precoding matrix based on the communication estimation channel matrix corresponding to each terminal and the sensing estimation channel matrix corresponding to each sensing target; and transmitting communication data streams and sensing sequences to each terminal and each sensing target after beamforming using the hybrid precoding matrix.

Description

Technical Field

[0001] This application relates to the field of wireless communication technology, and in particular to a method, network equipment, apparatus and medium for integrated inductive beamforming transmission. Background Technology

[0002] In a sensor-communication integrated system, communication and sensing functions need to be implemented simultaneously. The communication object is a traditional terminal (User Equipment, UE) or base station, while the sensing object is a passive object in the environment. There may be significant interference between the communication object and the sensing object, which can affect the performance of the sensor-communication integrated system. Summary of the Invention

[0003] This application provides a method, network device, apparatus, and medium for integrated sensing beamforming transmission, which solves the mutual interference problem that exists when communication and sensing are integrated into beamforming, and improves the performance of the integrated sensing system.

[0004] In a first aspect, this application provides a sensing-integrated beamforming transmission method, applied to network devices, comprising: It receives communication pilot signals sent by M terminals, and sensing pilot signals that arrive at the network device after being reflected or scattered by N sensing targets; M is an integer greater than or equal to 1, and N is an integer greater than or equal to 1. Communication channel estimation is performed based on communication pilot signals to obtain the communication estimation channel matrix corresponding to each terminal; sensing channel estimation is performed based on sensing pilot signals to obtain the sensing estimation channel matrix corresponding to each sensing target. Based on the communication estimation channel matrix corresponding to each terminal and the perception estimation channel matrix corresponding to each sensing target, the hybrid precoding matrix is ​​determined; After beamforming the communication data stream and sensing sequence using a hybrid precoding matrix, they are transmitted to each terminal and each sensing target.

[0005] In some embodiments, a hybrid precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal and the perception estimation channel matrix corresponding to each sensing target, including: Based on the communication estimation channel matrix and beam set corresponding to each terminal, the communication beam corresponding to each terminal is determined; based on the sensing estimation channel matrix and beam set corresponding to each sensing target, the sensing beam corresponding to each sensing target is determined. The hybrid precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each sensing target, the communication beam corresponding to each terminal, and the perception beam corresponding to each sensing target.

[0006] In some embodiments, determining the communication beam corresponding to each terminal based on the communication estimation channel matrix and beam set corresponding to each terminal includes: For each terminal, the communication estimation channel matrix corresponding to the terminal is multiplied with the beam matrix corresponding to the beam set, and the communication beam corresponding to the terminal is selected from the beam set based on the multiplication result. The beam matrix is ​​a matrix composed of the direction vectors of each beam in the beam set.

[0007] In some embodiments, determining the sensing beam corresponding to each sensing target based on the sensing estimation channel matrix and beam set corresponding to each sensing target includes: For each sensing target, the sensing estimation channel matrix corresponding to the sensing target is multiplied with the beam matrix corresponding to the beam set, and the sensing beam corresponding to the sensing target is selected from the beam set based on the multiplication result. The beam matrix is ​​a matrix composed of the direction vectors of each beam in the beam set.

[0008] In some embodiments, a hybrid precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, the communication beam corresponding to each terminal, and the sensing beam corresponding to each sensing target, including: The analog precoding matrix is ​​determined based on the direction vector of the communication beam corresponding to each terminal and the direction vector of the sensing beam corresponding to each sensing target. The digital precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, and the analog precoding matrix. The hybrid precoding matrix is ​​determined based on the analog precoding matrix and the digital precoding matrix.

[0009] In some embodiments, the digital precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, and the analog precoding matrix, including: The equivalent channel matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each sensing target, and the analog precoding matrix. The digital precoding matrix is ​​determined based on the equivalent channel matrix and the precoding algorithm.

[0010] In some embodiments, the digital precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, and the analog precoding matrix, including: Based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each perception target, and the analog precoding matrix, the sub-equivalent channel matrix corresponding to each terminal and each perception target is determined respectively. For each sub-equivalent channel matrix, the corresponding sub-digital precoding matrix is ​​determined based on the sub-equivalent channel matrix and the precoding algorithm; The digital precoding matrix is ​​determined based on all the sub-digital precoding matrices.

[0011] Secondly, this application also provides a network device, including a memory, a transceiver, and a processor; A memory for storing computer programs; a transceiver for sending and receiving data under the control of the processor; and a processor for reading the computer programs from the memory and performing the following operations: It receives communication pilot signals sent by M terminals, and sensing pilot signals that arrive at the network device after being reflected or scattered by N sensing targets; M is an integer greater than or equal to 1, and N is an integer greater than or equal to 1. Communication channel estimation is performed based on communication pilot signals to obtain the communication estimation channel matrix corresponding to each terminal; sensing channel estimation is performed based on sensing pilot signals to obtain the sensing estimation channel matrix corresponding to each sensing target. Based on the communication estimation channel matrix corresponding to each terminal and the perception estimation channel matrix corresponding to each sensing target, the hybrid precoding matrix is ​​determined; After beamforming the communication data stream and sensing sequence using a hybrid precoding matrix, they are transmitted to each terminal and each sensing target.

[0012] In some embodiments, a hybrid precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal and the perception estimation channel matrix corresponding to each sensing target, including: Based on the communication estimation channel matrix and beam set corresponding to each terminal, the communication beam corresponding to each terminal is determined; based on the sensing estimation channel matrix and beam set corresponding to each sensing target, the sensing beam corresponding to each sensing target is determined. The hybrid precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each sensing target, the communication beam corresponding to each terminal, and the perception beam corresponding to each sensing target.

[0013] In some embodiments, determining the communication beam corresponding to each terminal based on the communication estimation channel matrix and beam set corresponding to each terminal includes: For each terminal, the communication estimation channel matrix corresponding to the terminal is multiplied with the beam matrix corresponding to the beam set, and the communication beam corresponding to the terminal is selected from the beam set based on the multiplication result. The beam matrix is ​​a matrix composed of the direction vectors of each beam in the beam set.

[0014] In some embodiments, determining the sensing beam corresponding to each sensing target based on the sensing estimation channel matrix and beam set corresponding to each sensing target includes: For each sensing target, the sensing estimation channel matrix corresponding to the sensing target is multiplied with the beam matrix corresponding to the beam set, and the sensing beam corresponding to the sensing target is selected from the beam set based on the multiplication result. The beam matrix is ​​a matrix composed of the direction vectors of each beam in the beam set.

[0015] In some embodiments, a hybrid precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, the communication beam corresponding to each terminal, and the sensing beam corresponding to each sensing target, including: The analog precoding matrix is ​​determined based on the direction vector of the communication beam corresponding to each terminal and the direction vector of the sensing beam corresponding to each sensing target. The digital precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, and the analog precoding matrix. The hybrid precoding matrix is ​​determined based on the analog precoding matrix and the digital precoding matrix.

[0016] In some embodiments, the digital precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, and the analog precoding matrix, including: The equivalent channel matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each sensing target, and the analog precoding matrix. The digital precoding matrix is ​​determined based on the equivalent channel matrix and the precoding algorithm.

[0017] In some embodiments, the digital precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, and the analog precoding matrix, including: Based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each perception target, and the analog precoding matrix, the sub-equivalent channel matrix corresponding to each terminal and each perception target is determined respectively. For each sub-equivalent channel matrix, the corresponding sub-digital precoding matrix is ​​determined based on the sub-equivalent channel matrix and the precoding algorithm; The digital precoding matrix is ​​determined based on all the sub-digital precoding matrices.

[0018] Thirdly, this application also provides a sensing-integrated beamforming transmission device, comprising: The receiving unit is used to receive communication pilot signals sent by M terminals respectively, and sensing pilot signals that arrive at the network device after being reflected or scattered by N sensing targets respectively; M is an integer greater than or equal to 1, and N is an integer greater than or equal to 1. The estimation unit is used to perform communication channel estimation based on communication pilot signals to obtain the communication estimation channel matrix corresponding to each terminal; and to perform sensing channel estimation based on sensing pilot signals to obtain the sensing estimation channel matrix corresponding to each sensing target. The determining unit is used to determine the hybrid precoding matrix based on the communication estimation channel matrix corresponding to each terminal and the perception estimation channel matrix corresponding to each perception target; The beamforming transmission unit is used to beamform the communication data stream and sensing sequence using a hybrid precoding matrix and then transmit them to each terminal and each sensing target.

[0019] Fourthly, this application also provides a non-transiently readable storage medium storing a program for causing a processor to execute the inductive beamforming transmission method described in the first aspect above.

[0020] Fifthly, this application also provides a communication device, wherein the communication device stores a program for causing the communication device to execute the inductive beamforming transmission method described in the first aspect above.

[0021] In a sixth aspect, this application also provides a processor-readable storage medium storing a program for causing a processor to execute the inductive beamforming transmission method described in the first aspect above.

[0022] In a seventh aspect, this application also provides a chip product, wherein the chip product stores a program for causing the chip product to execute the inductive beamforming transmission method described in the first aspect above.

[0023] The integrated sensing beamforming transmission method, network equipment, apparatus, and medium provided in this application estimate the communication channel using communication pilot signals and estimate the sensing channel using sensing pilot signals. By estimating the channel information rather than the ideal channel information, a hybrid precoding matrix is ​​determined, making the determined hybrid precoding matrix more suitable for practical application scenarios. This effectively solves the mutual interference problem that exists when communication and sensing are integrated in beamforming in practical applications of integrated sensing systems, and improves the performance of integrated sensing systems. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a flowchart illustrating the inductive beamforming transmission method provided in an embodiment of this application.

[0026] Figure 2 A flowchart illustrating the integrated inductive hybrid precoding beamforming process provided in this application embodiment.

[0027] Figure 3 The waveform diagram provided in the embodiments of this application is for inductive analog beam selection.

[0028] Figure 4 The above is a hybrid precoding waveform diagram provided for an embodiment of this application.

[0029] Figure 5 This is a schematic diagram of the network device provided in an embodiment of this application.

[0030] Figure 6 This is a schematic diagram of the structure of the inductive beamforming transmission device provided in the embodiments of this application. Detailed Implementation

[0031] In the embodiments of this application, the term "and / or" describes the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following associated objects have an "or" relationship.

[0032] In the embodiments of this application, the term "multiple" refers to two or more, and other quantifiers are similar.

[0033] In the embodiments of this application, the terms "first," "second," etc., are used to distinguish similar objects, and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same class, and the number of objects is not limited; for example, the first object can be one or more.

[0034] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0035] To facilitate a clearer understanding of the technical solutions of the various embodiments of this application, some technical content related to the various embodiments of this application will be introduced first.

[0036] Precoding is a technique used in traditional Multi-Input Multi-Output (MIMO) communication systems to preprocess transmitted signals using channel information obtained in advance by the transmitter. It can reduce interference between multiple users and improve system transmission rate and reliability. It is commonly divided into linear precoding and nonlinear precoding. Linear precoding is more suitable for practical applications due to its lower complexity and ease of hardware implementation. Common linear precoding methods include Zero Forcing (ZF) precoding, Minimum Mean Squared Error (MMSE) precoding, and Block Diagonalization (BD) precoding. Furthermore, the method by which the transmitter obtains channel information in advance typically involves the user (UE) sending an uplink pilot signal to the base station. The base station performs channel estimation to obtain uplink channel information, and then uses channel reciprocity to convert the uplink channel information into downlink channel information between the base station and the UE.

[0037] From another perspective, precoding can be categorized into all-digital precoding, all-analog precoding, and hybrid digital-analog precoding. All-digital precoding can simultaneously modulate amplitude and phase, but requires each antenna to be connected to a separate RF chain, resulting in higher costs and making it particularly unsuitable for MIMO systems with a large number of antennas. All-analog precoding connects all antennas to only one RF chain via phase shifters, offering lower costs, but only allows phase modulation, limiting spectral efficiency. Hybrid digital-analog precoding combines the advantages of both, achieving higher antenna gain with fewer RF chains, making it the preferred choice for future 6th Generation (6G) massive MIMO antennas. Furthermore, hybrid digital-analog precoding is further divided into fully connected and sub-connected models; the latter, due to its lower cost and simpler structure, is more suitable for practical implementation.

[0038] In a sensor-integrated system, communication and sensing functions need to be implemented simultaneously. The communication object is a traditional UE or base station, while the sensing object is a passive object in the environment. The two are generally different, so it can be regarded as a multi-user system of sensor-integrated system. There may be a large interference problem between the two.

[0039] The design of integrated sensing beamforming transmitters mainly follows two directions: one is antenna segmentation, dividing the antenna panel into two parts, one for communication and the other for sensing; the other is directly designing an integrated antenna with dual functions, i.e., using a single antenna array to achieve dual-beam or multi-beam operation. Related designs often employ mathematical optimization algorithms, such as Semi-Definite Relaxation (SDR), Alternating Direction Method of Multipliers (ADMM), and Deep Learning (DL). While these optimization algorithms offer good performance, they often have high computational complexity, requiring significant hardware and computing power, which substantially increases the construction and maintenance costs of integrated sensing systems, making them unsuitable for practical applications. Furthermore, these algorithms require prior assumptions of ideal channel estimation information, but in practical applications, only estimated channel information is typically available. There is often a discrepancy between the estimated and ideal channel information, leading to actual application results that may not meet the predicted performance. Furthermore, these algorithms often assume that the transmitter can generate beams pointing in any direction. However, in practical applications, due to hardware constraints such as phase shifters, the beams can only point in a few directions, for example, only eight beam directions are provided. Therefore, the deviation between the actual beam direction and the ideal beam direction will also lead to a decrease in algorithm performance.

[0040] Figure 1 This is a flowchart illustrating the inductive beamforming transmission method provided in an embodiment of this application. The method is applied to network devices (e.g., base stations). Figure 1 As shown, the method includes the following steps 101, 102, 103 and 104.

[0041] Step 101: Receive communication pilot signals sent by M terminals respectively, and sensing pilot signals that arrive at the network device after being reflected or scattered by N sensing targets respectively; M is an integer greater than or equal to 1, and N is an integer greater than or equal to 1.

[0042] Specifically, the M terminals are terminals communicating with the network device, and can also be referred to as communication users. In order for the network device to obtain communication channel information, each of the M terminals can send a communication pilot signal to the network device. This communication pilot signal is a pilot signal used for communication channel estimation, and can be agreed upon in advance by the network device and the terminals. For ease of understanding, the communication pilot signal sent by the terminal can be denoted as communication pilot 1. Communication pilot 1 reaches the network device through the communication channel between the terminal and the network device, and the communication pilot signal received by the network device can be denoted as communication pilot 2.

[0043] In addition to communicating with the M terminals, the network device can also sense the target. The sensing mode can be either single-base sensing mode or dual-base sensing mode. In single-base sensing mode, the network device transmits and receives data independently, meaning that the sensing nodes at both ends (sensing sending node and sensing receiving node) are both the network device. In dual-base sensing mode, the sensing node at one end is the network device, while the sensing node at the other end (peer sensing node) can be other network devices or terminals.

[0044] In order for network devices to acquire sensing channel information, either the network device (in single-base sensing mode) or the peer sensing node (in dual-base sensing mode) can transmit sensing pilot signals within the sensing area. These sensing pilot signals are used for sensing channel estimation. In dual-base sensing mode, the sensing pilot signals can be pre-agreed upon by the network device and the peer sensing node. For ease of understanding, the transmitted sensing pilot signal can be denoted as Sensing Pilot 1. Sensing Pilot 1 reaches the network device after being reflected or scattered by the sensing target, and the sensing pilot signal received by the network device can be denoted as Sensing Pilot 2.

[0045] Step 102: Perform communication channel estimation based on communication pilot signals to obtain the communication estimation channel matrix corresponding to each terminal; perform sensing channel estimation based on sensing pilot signals to obtain the sensing estimation channel matrix corresponding to each sensing target.

[0046] Specifically, after receiving communication pilot 2, the network device performs channel estimation based on communication pilot 2 and the known communication pilot 1 (which can be pre-agreed upon by the network device and the terminal). Then, based on the principle of channel reciprocity, it obtains the estimated channel matrix corresponding to each terminal, that is, the estimated channel matrix of the communication channel from the network device to each terminal. The estimated channel matrix of the communication channel from the network device to the m-th terminal can be denoted as... m = 1, 2, ..., M.

[0047] Channel reciprocity refers to the phenomenon in a communication system where uplink and downlink signals transmit on different time slots of the same frequency resource. Within a relatively short period (i.e., the coherence time of channel propagation), the channel fading experienced by the transmitted signals in the uplink and downlink can be considered the same. According to the principle of channel reciprocity, the uplink estimated channel matrix and the downlink estimated channel matrix are conjugate transposes. Therefore, after obtaining the uplink estimated channel matrix based on communication pilot 2 and communication pilot 1, the corresponding downlink estimated channel matrix can be obtained according to the principle of channel reciprocity; that is, the estimated channel matrix of the communication channels from the network device to each terminal.

[0048] After receiving sensing pilot 2, the network device performs channel estimation based on sensing pilot 2 and the known sensing pilot 1 (in dual-base sensing mode, sensing pilot 1 can be pre-agreed upon by the network device and the peer sensing node). Then, based on the principle of channel reciprocity, it obtains the estimated sensing channel matrix corresponding to each sensing target, that is, the estimated channel matrix of the sensing channel from the network device to each sensing target and then to the peer sensing node (or the network device). The estimated channel matrix of the sensing channel from the network device to the nth sensing target and then to the peer sensing node (or the network device) can be denoted as... n = 1, 2, ..., N.

[0049] Step 103: Determine the hybrid precoding matrix based on the communication estimation channel matrix corresponding to each terminal and the perception estimation channel matrix corresponding to each perception target.

[0050] Specifically, obtain the corresponding data for each terminal. and corresponding to each sensing target Then, the network device can determine the hybrid precoding matrix based on these estimated channel matrices. The hybrid precoding matrix refers to the digital-analog hybrid precoding matrix, that is, the precoding method used for integrated sensing beamforming in the various embodiments of this application is digital-analog hybrid precoding.

[0051] Step 104: After beamforming the communication data stream and sensing sequence using a hybrid precoding matrix, send them to each terminal and each sensing target.

[0052] Specifically, integrated sensing beamforming involves precoding beamforming to treat the sensing target and communication users together as multiple users in an integrated sensing system. Precoding reduces interference between multiple users and improves the performance of the integrated sensing system.

[0053] After determining the hybrid precoding matrix, the network device performs integrated beamforming on the communication data streams to be sent to each communication user and the sensing sequences for sensing, and then sends them out, thereby realizing spatial division multiplexing of communication and sensing.

[0054] The sensing-integrated beamforming transmission method provided in this application estimates the communication channel using communication pilot signals and estimates the sensing channel using sensing pilot signals. By estimating the channel information rather than the ideal channel information, a hybrid precoding matrix is ​​determined, making the determined hybrid precoding matrix more suitable for practical application scenarios. This effectively solves the mutual interference problem that exists when communication and sensing are integrated into beamforming in practical applications of sensing-integrated systems, and improves the performance of sensing-integrated systems.

[0055] In some embodiments, a hybrid precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal and the perception estimation channel matrix corresponding to each sensing target, including: Based on the communication estimation channel matrix and beam set corresponding to each terminal, the communication beam corresponding to each terminal is determined; based on the sensing estimation channel matrix and beam set corresponding to each sensing target, the sensing beam corresponding to each sensing target is determined. The hybrid precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each sensing target, the communication beam corresponding to each terminal, and the perception beam corresponding to each sensing target.

[0056] Specifically, in practical applications, due to hardware constraints such as phase shifters, the transmitting end can only provide a limited number of beam directions. By selecting appropriate communication beams and sensing beams, the performance of the integrated sensing system can be better improved.

[0057] Obtain the corresponding terminal Then, the network device can select the communication beam corresponding to each terminal from the beam set based on these estimated channel matrices. For the sensing target, the network device can select the corresponding communication beam based on the target. The sensing beam corresponding to each sensing target is selected from the beam set. This beam set is a finite set of beams that the network device can provide.

[0058] Then, the network device, based on the selected communication beams and sensing beams, and in conjunction with the corresponding terminals... and corresponding to each sensing target This allows us to determine the hybrid precoding matrix, thereby enabling integrated inductive beamforming.

[0059] In some embodiments, determining the communication beam corresponding to each terminal based on the communication estimation channel matrix and beam set corresponding to each terminal includes: For each terminal, the communication estimation channel matrix corresponding to the terminal is multiplied with the beam matrix corresponding to the beam set, and the communication beam corresponding to the terminal is selected from the beam set based on the multiplication result. The beam matrix is ​​a matrix composed of the direction vectors of each beam in the beam set.

[0060] For example, the direction vector of each beam in a beam set can be represented as: in, This represents the direction vector of beam k, where k = 1, 2, ..., K, and K represents the number of beams in the beam set. Indicates amplitude, , Indicates the number of transmit antennas of a network device. Indicates the spacing between antenna elements. This indicates the azimuth angle corresponding to beam k. This indicates the wavelength, and the superscript T indicates transpose. For each beam in the beamset, except... Apart from the differences, all other parameters in the direction vector of each beam are the same.

[0061] In some embodiments, the beam matrix can be represented as: For the m-th terminal, we can With beam matrix Multiply, The dimension of the matrix is , This represents the number of receiving antennas for the m-th terminal. With beam matrix The dimension obtained after multiplication is The matrix is ​​denoted as matrix. .matrix It can be represented as: Will Take the absolute values ​​of the elements in the same column and add them together to get K sums, denoted as K. , , ..., .For example: , , ..., Then, these K values ​​( , , ..., The beam corresponding to the maximum value in the value is taken as the communication beam for the m-th terminal. For example: if If the value is the maximum among these K values, then beam 1 will be used as the communication beam corresponding to the m-th terminal; if If the value is the maximum among these K values, then beam 2 will be used as the communication beam corresponding to the m-th terminal; and so on. If the value is the maximum among these K values, then beam k will be used as the communication beam corresponding to the m-th terminal.

[0062] It is understood that by selecting the communication beam in this way, the communication beams corresponding to different terminals can be the same or different, and this application does not limit this.

[0063] By selecting the communication beam in the above manner, a beam that is more compatible with the communication channel corresponding to each terminal can be selected from the limited beam set provided by the network device, thereby improving the performance of the integrated sensing system.

[0064] In some embodiments, determining the sensing beam corresponding to each sensing target based on the sensing estimation channel matrix and beam set corresponding to each sensing target includes: For each sensing target, the sensing estimation channel matrix corresponding to the sensing target is multiplied with the beam matrix corresponding to the beam set, and the sensing beam corresponding to the sensing target is selected from the beam set based on the multiplication result. The beam matrix is ​​a matrix composed of the direction vectors of each beam in the beam set.

[0065] For example, for the nth perceived target, it can be With beam matrix Multiply, The dimension of the matrix is , This indicates the number of receiving antennas at the peer sensing node. With beam matrix The dimension obtained after multiplication is The matrix is ​​denoted as matrix. .matrix It can be represented as: Will Take the absolute values ​​of the elements in the same column and add them together to get K sums, denoted as K. , , ..., .For example: , , ..., Then, these K values ​​( , , ..., The beam corresponding to the maximum value in the range is used as the sensing beam for the nth sensing target. For example: if If it is the maximum value among these K values, then beam 1 will be used as the sensing beam corresponding to the nth sensing target; if If the value is the maximum among these K values, then beam 2 will be used as the sensing beam corresponding to the nth sensing target; and so on. If the value is the maximum among these K values, then beam k will be used as the sensing beam corresponding to the nth sensing target.

[0066] It is understood that by selecting the sensing beam in this way, the sensing beams corresponding to different sensing targets can be the same or different, and this application does not limit this.

[0067] By selecting sensing beams in the above manner, the beams that are more compatible with the sensing channels corresponding to each sensing target can be selected from the limited beam set provided by the network device, thereby improving the performance of the integrated sensing system.

[0068] In some embodiments, a hybrid precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, the communication beam corresponding to each terminal, and the sensing beam corresponding to each sensing target, including: The analog precoding matrix is ​​determined based on the direction vector of the communication beam corresponding to each terminal and the direction vector of the sensing beam corresponding to each sensing target. The digital precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, and the analog precoding matrix. The hybrid precoding matrix is ​​determined based on the analog precoding matrix and the digital precoding matrix.

[0069] Specifically, the hybrid precoding matrix can be calculated based on the analog precoding matrix and the digital precoding matrix. For example, assuming the analog precoding matrix is... The digital precoding matrix is Hybrid precoding matrix .

[0070] The digital precoding matrix can be determined based on the direction vector of the communication beam corresponding to each terminal and the direction vector of the sensing beam corresponding to each sensing target. For example, assuming that the number of transmit antennas corresponding to each transmit port of the network device is... The direction vectors used to determine the individual communication beams or sensing beams of the digital precoding matrix can be... The column vectors and the expression for the beam direction vector can be found in the previous text. Less than or equal to In the case of beam k, truncation The first 1 to Each element serves as the direction vector of beam k.

[0071] In some embodiments, the network device employs an integrated antenna design that combines communication and sensing functions, assuming... This represents the direction vector of the communication beam corresponding to each terminal. Let represent the direction vector of the sensing beam corresponding to each sensing target. Then, the analog precoding matrix can be represented as: Where, diag[·] represents transforming the vector within the brackets into a diagonal matrix, and the number of diagonal elements (i.e., ...) represents the number of elements within the diagonal matrix. The number of repetitions) is the number of ports for hybrid precoding (or the number of transmit ports of the network device).

[0072] In some embodiments, the network device employs a segmented antenna design, assuming This represents the direction vector of the communication beam corresponding to each terminal. Let represent the direction vector of the sensing beam corresponding to each sensing target. Then, the analog precoding matrix can be represented as: . Let represent the sub-simulation precoding matrix corresponding to object i, where i = 1, 2, ..., (M+N). The objects here include M terminals and N sensing targets.

[0073] For terminal i, Number of diagonal elements (i.e.) The number of repetitions is the number of transmit ports corresponding to terminal i.

[0074] For the perceived target i, Number of diagonal elements (i.e.) The number of repetitions is the number of transmission ports corresponding to the sensing target i.

[0075] In some embodiments, the digital precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, and the analog precoding matrix, including: The equivalent channel matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each sensing target, and the analog precoding matrix. The digital precoding matrix is ​​determined based on the equivalent channel matrix and the precoding algorithm.

[0076] For example, network devices employ an integrated antenna design that combines communication and sensing functions, assuming... Represents the equivalent channel matrix. ,in, The superscript T of the matrix indicates transpose.

[0077] It should be noted that, The order of the submatrices in the matrix is ​​not restricted, for example... Alternatively, other sorting methods can be used, as long as the sorting method of each related matrix is ​​consistent during the determination of the hybrid precoding matrix. The sorting method of the sub-matrices in other related matrices will also be the same, and will not be elaborated further.

[0078] After determining the equivalent channel matrix, the digital precoding matrix can be determined based on the equivalent channel matrix and the precoding algorithm. The specific method for determining the digital precoding matrix depends on the precoding algorithm used, and can be found in the relevant precoding algorithm documentation, which will not be elaborated here.

[0079] The precoding algorithm can be selected according to the needs of the scenario, and this application does not impose any restrictions. For example, precoding algorithms such as ZF, MMSE or BD can be used.

[0080] For example, assuming the ZF precoding algorithm is used, the digital precoding matrix... ,in, To meet the power constraints of network devices The normalization factor, The sum of all sensing and communication data streams, where the superscript H of the matrix denotes the conjugate transpose. This represents the square of the norm.

[0081] In some embodiments, the digital precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, and the analog precoding matrix, including: Based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each perception target, and the analog precoding matrix, the sub-equivalent channel matrix corresponding to each terminal and each perception target is determined respectively. For each sub-equivalent channel matrix, the corresponding sub-digital precoding matrix is ​​determined based on the sub-equivalent channel matrix and the precoding algorithm; The digital precoding matrix is ​​determined based on all the sub-digital precoding matrices.

[0082] For example, network devices using a segmented antenna design can be configured based on the number of antenna segments. Write it in the following block format: Each row is a or ,Right now , Each column is denoted as one. ,Right now = .Should The dimension of the matrix is , The dimension of the matrix is , This indicates the number of receiving antennas at the peer sensing node. This represents the number of receiving antennas for the m-th terminal. Indicates the number of transmit antennas of a network device. This indicates the number of transmit antennas corresponding to each transmit port of the network device. This represents the number of transmission ports corresponding to each object i, where i = 1, 2, ..., (M+N). The objects here include M terminals and N sensing targets.

[0083] Assumption This represents the sub-equivalent channel matrix corresponding to object i. After determining the sub-equivalent channel matrix, the sub-digital precoding matrix can be determined based on the sub-equivalent channel matrix and the precoding algorithm. The specific method for determining the sub-digital precoding matrix depends on the precoding algorithm used, and can be found in the relevant precoding algorithm documentation, which will not be elaborated here.

[0084] For example, assuming the ZF precoding algorithm is used, for the sub-equivalent channel matrix... Its corresponding sub-digital precoding matrix ,in, To satisfy the power constraint of object i The normalization factor, This is the number of data streams corresponding to object i.

[0085] After obtaining each sub-digital precoding matrix, arrange the (M+N) sub-digital precoding matrices column-wise to obtain the digital precoding matrix. .

[0086] Figure 2 This is a flowchart of the integrated sensing and communication hybrid precoding beamforming process provided in an embodiment of this application. In this scenario, base station A performs sensing and communication simultaneously. M communication users (UEs) and N sensing targets are located in different directions from base station A. The estimated channel matrices for each UE and each sensing target are as follows: and Sensing can be bi-base sensing, where the sensing node at the other end is base station B; or it can be uni-base sensing, in which case it can be denoted as base station B, but is essentially still base station A. For example... Figure 2 As shown, its main processes include: 1. Communication users send communication pilots, and base station B sends sensing pilots.

[0087] 1.1 The UE sends communication pilot 1 to base station A. Base station A performs uplink channel estimation based on the received communication pilot 2 carrying channel information and the prior communication pilot 1. Then, it obtains the downlink communication estimation channel matrix based on the channel reciprocity principle. .

[0088] 1.2. During the target detection phase, base station B transmits a periodic scanning beam, i.e., transmits the pre-agreed sensing pilot 1. After being reflected and scattered by the target, it reaches base station A and becomes sensing pilot 2 carrying channel information. Base station A performs uplink sensing channel estimation based on sensing pilot 2 and sensing pilot 1, and then obtains the complete downlink sensing estimation channel matrix according to the principle of signal reciprocity. In the case of single-base sensing, base station B is equivalent to base station A, and the uplink sensing channel estimation is the same as the downlink sensing channel matrix estimation. Here, the uplink direction refers to the direction from base station B to the sensing target and then back to base station A, while the downlink direction refers to the direction from base station A to the sensing target and then back to base station B. If the focus is more on communication users, sensing target detection can be performed only around the communication users.

[0089] During the target tracking phase, base station B can estimate the approximate direction of the target based on target detection and then perform beam scanning around the target. Assuming the number of beam scans is P (P is less than the number of beams in a full scan), P downlink sensing estimation channel matrices can be obtained from the scan. The channel containing the target of interest is then selected, also denoted as... .

[0090] 2. Base station A obtains the beam direction based on the communication user and the sensing target.

[0091] For each Base station A will Multiply by the beam matrix corresponding to the finite set of beams it can provide, and select the beam based on the multiplication result. The corresponding communication beam, and thus the direction vector of the communication beam. .

[0092] For each Base station A will Multiply by the beam matrix corresponding to the finite set of beams it can provide, and select the beam based on the multiplication result. The corresponding sensing beam, and thus the direction vector of the sensing beam is determined. .

[0093] Then, base station A according to , And the antenna deployment method determines the analog precoding matrix, based on , The digital precoding matrix is ​​determined by factors such as the analog precoding matrix, antenna deployment method, and precoding algorithm. Then, a hybrid precoding matrix is ​​obtained based on the analog and digital precoding matrices. The precoding algorithm can be selected from ZF, MMSE, or BD algorithms depending on the scenario requirements.

[0094] 3. Base station A performs precoding services for sensing users and communication users.

[0095] Base station A is configured with communication data stream and sensing sequence. After integrated beamforming through a hybrid precoding matrix, it sends out the integrated signal to communicate with communication users and simultaneously perform sensing measurements on the sensing target.

[0096] In addition, the integrated synergistic hybrid precoding beamforming update process includes: Based on the real-time communication and sensing results after integrated hybrid precoding beamforming, base station A re-performs channel estimation. Specifically, communication users perform channel estimation according to the precoding matrix. After sending communication pilot signals, base station A performs uplink channel estimation and then obtains the downlink real-time communication estimation channel matrix based on the channel reciprocity principle. Base station B follows the precoding matrix (Instead of the full or partial scan in step 1.2) A sensing pilot is sent to base station A. Base station A performs uplink sensing channel estimation and then obtains the downlink real-time sensing estimation channel matrix based on the channel reciprocity principle. Channel matrix estimated based on downlink real-time communication. and downlink real-time sensing estimation channel matrix Then, perform a new integrated synesthetic hybrid precoding beamforming, that is, repeat steps 2 and 3 above. The precoding matrix... for The corresponding communication user's transmit precoding matrix, precoding matrix The channel where the sensing target of interest is located The corresponding base station B's transmit precoding matrix.

[0097] The following examples illustrate two different antenna deployment methods for integrated inductive and sensing hybrid precoding beamforming schemes.

[0098] Example 1: An integrated antenna design that combines communication and sensing functions.

[0099] Base station A and base station B perform sensing and downlink communication with the UE. The sensing and communication functions share the antenna panel of base station A to simultaneously generate sensing and communication beams pointing in different directions. Furthermore, sensing and communication use different sequences. A hybrid ZF precoding scheme is employed at base station A to suppress interference between communication and sensing. It is assumed that there is only one communication user and one sensing target, located in different directions.

[0100] Some simulation parameters are shown in Table 1. The UE sends a pre-agreed communication pilot to base station A, and base station B sends a pre-agreed sensing pilot. After being reflected and scattered by the sensing target, the pilot reaches base station A. Base station A obtains the communication estimation channel matrix based on the received communication pilot and sensing pilot. and sensing estimation of channel matrix .

[0101] Table 1. Relevant configuration parameters for space division multiplexing

[0102] Assuming base station A provides 8 beam directions, when the ideal transmission directions corresponding to the actual channel are 20° (UE) and 40° (sensing target), base station A will... , Multiply by the beam matrices corresponding to the beam set respectively to select the communication beam and the sensing beam, such as... Figure 3 As shown, the actual beam direction of the communication beam is 22.02° (for the UE, the direction vector is denoted as...). The actual beam direction of the sensing beam is 38.68° (the direction vector of the sensing target is denoted as...). In the figure, DFT refers to the Discrete Fourier Transform (DFT). The solid line corresponds to the actual beam direction. It can be seen that there is a slight difference between the actual beam direction and the ideal beam direction (the peak of the solid line and the horizontal axis corresponding to the dashed line are in different positions), but this deviation is more consistent with reality. Because an integrated sub-connected hybrid precoding is used, the actual obtained analog precoding matrix... The number of diagonal elements represents the number of ports in the hybrid precoding. The corresponding equivalent channel matrix... .

[0103] according to The digital precoding matrix is ​​obtained using the ZF precoding algorithm. To eliminate interference between sensing and communication, a hybrid precoding matrix is ​​used. The waveform diagram after separating communication and sensing in hybrid precoding is shown below. Figure 4 As shown, it can be seen that the beam amplitude of the communication and sensing sidelobes, represented by the solid line, is further reduced in the direction of the other party compared to the beam of the analog precoding, forming two large dips, indicating that effective interference suppression processing has been performed.

[0104] Next, base station A configures the communication data stream and sensing sequence, performs integrated beamforming through a hybrid precoding matrix, and sends out the integrated signal to communicate with the communication user. At the same time, it performs sensing measurements on the sensing target, thus realizing spatial multiplexing of communication and sensing.

[0105] A more general example of an integrated antenna design that combines communication and sensing functions is described below: If there are M communication users (UEs) and N sensing targets, the number of transmission ports of base station A is: The number of transmitting antennas of base station A is The number of transmit antennas corresponding to each transmit port is .

[0106] M UEs send pre-agreed communication pilots to base station A. Base station A obtains M downlink communication estimation channel matrices based on the received communication pilots. , ..., Base station B periodically transmits pre-agreed sensing pilot signals, which are reflected and scattered by the sensing target before reaching base station A. Base station A then obtains N downlink sensing estimation channel matrices based on the received sensing pilot signals. , ..., The total downlink estimated channel matrix is: .

[0107] Base station A multiplies the (M+N) estimated channel matrices with the beam matrices corresponding to the beam set, respectively, to select the communication beam and the sensing beam. The beam direction vectors of each communication beam and each sensing beam are denoted as follows: , ..., , , ..., (There may be cases where the selected beams are essentially the same). and All Column vectors.

[0108] Since an integrated sub-connection hybrid precoding is used, the actual obtained analog precoding matrix is: Where the number of diagonal elements is the number of ports for hybrid precoding. The corresponding equivalent channel is .

[0109] Base station A according to Digital precoding is obtained using the ZF precoding algorithm. To eliminate interference between all sensing targets and communication users (all sensing targets and all UEs are considered as users of base station A, and interference between any users is eliminated, including between sensing and communication, between sensing and sensing, and between communication and communication). ,in, To meet the power constraints of base station A The normalization factor, This is the sum of the number of data streams for all sensing and communication.

[0110] Total hybrid precoding matrix .

[0111] Next, base station A configures the communication data stream and sensing sequence, performs integrated beamforming through a hybrid precoding matrix, and sends out the integrated signal to communicate with the communication user. At the same time, it performs sensing measurements on the sensing target, thus realizing spatial multiplexing of communication and sensing.

[0112] Example 2: Segmented antenna hybrid precoding design.

[0113] Base station A and base station B perform sensing operations and downlink communication with the UE. Base station A acts as the transmitter, dividing its antenna panel into two sections to form sensing and communication beams pointing in different directions. The sensing receiving antenna panel is physically isolated from the two transmitting antenna panels to avoid interference. Furthermore, sensing uses a Zadoff-Chu (ZC) sequence, and communication uses Quadrature Phase Shift Keying (QPSK) modulation. It is assumed that there is only one sensing target and one communication user, located in opposite directions.

[0114] Base station A obtains the communication estimation channel matrix according to the aforementioned process. and sensing estimation of channel matrix Similar to Example 1, base station A will... , Multiply by the beam set respectively to select the communication beam and the sensing beam. The beam direction vectors of the communication beam and the sensing beam are denoted as follows: and Unlike Example 1, due to the use of segmented antennas, assumed to be 2 ports, the total analog precoding matrix... Meanwhile, to improve the interference suppression effect, , The segmented antennas are written as follows: , For communication, the sub-equivalent channel matrix is: Based on the sub-equivalent channel matrix and the ZF precoding algorithm, the sub-digital precoding matrix corresponding to the communication user is obtained. Similarly, the sub-digital precoding matrix corresponding to the perceived target can be obtained. Total digital precoding matrix The overall hybrid precoding matrix Next, base station A configures the communication data stream and sensing sequence, performs integrated beamforming through a hybrid precoding matrix, and sends out the integrated signal to communicate with the communication user. At the same time, it performs sensing measurements on the sensing target, thus realizing spatial division multiplexing of communication and sensing.

[0115] A more general example of a block antenna hybrid precoding design is described below: If there are M communication users (UEs) and N sensing targets, the number of transmission ports of base station A is: The number of transmitting antennas of base station A is The number of transmit antennas corresponding to each transmit port is Each UE or sensing target may correspond to one or more transmission ports of base station A, denoted as . Accordingly, the number of transmit antennas of base station A corresponding to each UE or sensing target is: That is, the transmitting antenna of base station A is also divided into (M+N) blocks.

[0116] M UEs send pre-agreed communication pilots to base station A. Base station A obtains M downlink communication estimation channel matrices based on the received communication pilots. , ..., Base station B periodically transmits pre-agreed sensing pilot signals, which are reflected and scattered by the sensing target before reaching base station A. Base station A then obtains N downlink sensing estimation channel matrices based on the received sensing pilot signals. , ..., The total downlink estimated channel matrix is: , dimension The antenna is divided into (M+N) sub-matrices according to the number of antenna blocks. , The dimension is .

[0117] Base station A multiplies the (M+N) estimated channel matrices with the beam matrices corresponding to the beam set, respectively, to select the communication beam and the sensing beam. The beam direction vectors of each communication beam and each sensing beam are denoted as follows: , ..., , , ..., (There may be cases where the selected beams are essentially the same). and All Column vectors.

[0118] For object i (where the object includes M terminals and N sensing targets), its corresponding sub-simulation precoding matrix is: (Object i is UE) or (Object i is the perceived target). or The number of repetitions equals The total analog precoding matrix The sub-equivalent channel matrix corresponding to object i is: .

[0119] According to the sub-equivalent channel The corresponding sub-digital precoding matrix is ​​obtained using the ZF precoding algorithm. . ,in, To satisfy the power constraint of object i The normalization factor, This is the number of data streams corresponding to object i.

[0120] (M+N) Arranged column by column, the total digital precoding matrix is ​​obtained as follows: ,Right now .

[0121] Total hybrid precoding matrix .

[0122] Next, base station A configures the communication data stream and sensing sequence, performs integrated beamforming through a hybrid precoding matrix, and sends out the integrated signal to communicate with the communication user. At the same time, it performs sensing measurements on the sensing target, thus realizing spatial multiplexing of communication and sensing.

[0123] The hybrid precoding beamforming scheme for integrated sensing and communication systems proposed in this application can effectively solve the problems of the inability to obtain the ideal channel a priori and the limited resolution of the simulated beam in practical applications of integrated sensing and communication systems. At the same time, it adopts a low-complexity precoding algorithm to solve the problem of mutual interference between communication and sensing, which can effectively suppress the interference between communication and sensing, improve system reliability, increase system spectrum utilization, and effectively reduce hardware costs, making it convenient for future practical applications.

[0124] Figure 5 This is a schematic diagram of the network device provided in the embodiments of this application, such as... Figure 5 As shown, the network device includes a memory 520, a transceiver 510, and a processor 500; wherein the processor 500 and the memory 520 can also be physically arranged separately.

[0125] The memory 520 is used to store computer programs; the transceiver 510 is used to send and receive data under the control of the processor 500.

[0126] Among them, Figure 5 In this application, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits of one or more processors represented by processor 500 and memory represented by memory 520 together. The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be further described herein. The bus interface provides an interface. The transceiver 510 can be multiple elements, including a transmitter and a receiver, providing a unit for communicating with various other devices over a transmission medium, including wireless channels, wired channels, optical fibers, and other transmission media.

[0127] The processor 500 is responsible for managing the bus architecture and general processing, while the memory 520 can store the data used by the processor 500 when performing operations.

[0128] The processor 500 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD). The processor can also adopt a multi-core architecture.

[0129] The processor 500 executes any of the methods described in the embodiments of this application by calling a computer program stored in the memory 520 in accordance with the obtained executable instructions.

[0130] It should be noted that the network device provided in this application embodiment can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0131] The following describes the inductive beamforming transmission device provided in the embodiments of this application. The inductive beamforming transmission device described below can be referred to in correspondence with the inductive beamforming transmission method described above.

[0132] Figure 6 This is a schematic diagram of the structure of the inductively integrated beamforming transmission device provided in the embodiments of this application, as shown below. Figure 6 As shown, the device includes: The receiving unit 610 is used to receive communication pilot signals sent by M terminals respectively, and sensing pilot signals that arrive at the network device after being reflected or scattered by N sensing targets respectively; M is an integer greater than or equal to 1, and N is an integer greater than or equal to 1. The estimation unit 620 is used to perform communication channel estimation based on communication pilot signals to obtain the communication estimation channel matrix corresponding to each terminal; and to perform sensing channel estimation based on sensing pilot signals to obtain the sensing estimation channel matrix corresponding to each sensing target. The determining unit 630 is used to determine the hybrid precoding matrix based on the communication estimation channel matrix corresponding to each terminal and the perception estimation channel matrix corresponding to each perception target; The beamforming and transmitting unit 640 is used to beamform the communication data stream and the sensing sequence using a hybrid precoding matrix and then transmit them to each terminal and each sensing target.

[0133] In some embodiments, a hybrid precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal and the perception estimation channel matrix corresponding to each sensing target, including: Based on the communication estimation channel matrix and beam set corresponding to each terminal, the communication beam corresponding to each terminal is determined; based on the sensing estimation channel matrix and beam set corresponding to each sensing target, the sensing beam corresponding to each sensing target is determined. The hybrid precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each sensing target, the communication beam corresponding to each terminal, and the perception beam corresponding to each sensing target.

[0134] In some embodiments, determining the communication beam corresponding to each terminal based on the communication estimation channel matrix and beam set corresponding to each terminal includes: For each terminal, the communication estimation channel matrix corresponding to the terminal is multiplied with the beam matrix corresponding to the beam set, and the communication beam corresponding to the terminal is selected from the beam set based on the multiplication result. The beam matrix is ​​a matrix composed of the direction vectors of each beam in the beam set.

[0135] In some embodiments, determining the sensing beam corresponding to each sensing target based on the sensing estimation channel matrix and beam set corresponding to each sensing target includes: For each sensing target, the sensing estimation channel matrix corresponding to the sensing target is multiplied with the beam matrix corresponding to the beam set, and the sensing beam corresponding to the sensing target is selected from the beam set based on the multiplication result. The beam matrix is ​​a matrix composed of the direction vectors of each beam in the beam set.

[0136] In some embodiments, a hybrid precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, the communication beam corresponding to each terminal, and the sensing beam corresponding to each sensing target, including: The analog precoding matrix is ​​determined based on the direction vector of the communication beam corresponding to each terminal and the direction vector of the sensing beam corresponding to each sensing target. The digital precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, and the analog precoding matrix. The hybrid precoding matrix is ​​determined based on the analog precoding matrix and the digital precoding matrix.

[0137] In some embodiments, the digital precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, and the analog precoding matrix, including: The equivalent channel matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each sensing target, and the analog precoding matrix. The digital precoding matrix is ​​determined based on the equivalent channel matrix and the precoding algorithm.

[0138] In some embodiments, the digital precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the sensing estimation channel matrix corresponding to each sensing target, and the analog precoding matrix, including: Based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each perception target, and the analog precoding matrix, the sub-equivalent channel matrix corresponding to each terminal and each perception target is determined respectively. For each sub-equivalent channel matrix, the corresponding sub-digital precoding matrix is ​​determined based on the sub-equivalent channel matrix and the precoding algorithm; The digital precoding matrix is ​​determined based on all the sub-digital precoding matrices.

[0139] It should be noted that the inductive beamforming transmission device provided in this application embodiment can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0140] It should be noted that the division of units in the embodiments of this application is illustrative and only represents one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units.

[0141] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0142] On the other hand, embodiments of this application also provide a processor-readable storage medium storing a program for causing a processor to execute the inductive beamforming transmission method provided in the above embodiments.

[0143] It should be noted that the processor-readable storage medium provided in this application embodiment can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0144] The processor-readable storage medium can be any available medium or data storage device that the processor can access, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO)), optical memory (e.g., CD, DVD, BD, HVD), and semiconductor memory (e.g., ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)).

[0145] The technical solutions provided in this application can be applied to a variety of systems. For example, applicable systems may include Long Term Evolution (LTE) systems, LTE Frequency Division Duplex (FDD) systems, LTE Time Division Duplex (TDD) systems, Long Term Evolution Advanced (LTE-A) systems, Universal Mobile Telecommunications System (UMTS), Worldwide Interoperability for Microwave Access (WiMAX) systems, 5G New Radio (NR) systems and their evolved communication systems, and 6G (sixth generation mobile communication technology) systems. These systems may include terminal equipment and network equipment. The systems may also include a core network component, such as an Evolved Packet Core (EPC), a 5G core network (5GC), or a 6G core network.

[0146] The terminal involved in the embodiments of this application can be a device that provides voice and / or data connectivity to a user, a handheld device with wireless connectivity, or other processing devices connected to a wireless modem. The name of the terminal may differ in different systems; for example, in a 5G system, the terminal can be called a User Equipment (UE). Wireless terminal devices can communicate with one or more core networks (CNs) via a Radio Access Network (RAN). Wireless terminal devices can be mobile terminal devices, such as mobile phones (or "cellular" phones) and computers with mobile terminal devices, for example, portable, pocket-sized, handheld, computer-embedded, or vehicle-mounted mobile devices that exchange voice and / or data with the RAN. Examples include Personal Communication Service (PCS) phones, cordless phones, Session Initiated Protocol (SIP) phones, Wireless Local Loop (WLL) stations, and Personal Digital Assistants (PDAs). Wireless terminal equipment can also be referred to as a system, subscriber unit, subscriber station, mobile station, mobile station, remote station, access point, remote terminal, access terminal, user terminal, user agent, or user device, but this application does not limit the terminology.

[0147] The network device involved in this application embodiment can be a base station, which may include multiple cells providing services to terminals. Depending on the specific application, a base station may also be called an access point, or a device in an access network that communicates with a wireless terminal device through one or more sectors on the air interface, or other names. The network device can be used to exchange received air frames with Internet Protocol (IP) packets, acting as a router between the wireless terminal device and the rest of the access network, where the rest of the access network may include an Internet Protocol (IP) communication network. The network device can also coordinate the attribute management of the air interface. For example, the network equipment involved in the embodiments of this application can be a Base Transceiver Station (BTS) in a Global System for Mobile communications (GSM) or Code Division Multiple Access (CDMA), a base station (NodeB) in Wide-band Code Division Multiple Access (WCDMA), an evolved Node B (eNB or e-NodeB) in a long term evolution (LTE) system, a 5G base station (gNB) in a next generation system, a Home evolved Node B (HeNB), a relay node, a femto, a pico, etc., and is not limited in the embodiments of this application. In some network structures, the network equipment may include centralized unit (CU) nodes and distributed unit (DU) nodes, and the centralized unit and distributed unit may also be geographically separated.

[0148] Network devices and terminals can each use one or more antennas for multiple-input multiple-output (MIMO) transmission. MIMO transmission can be single-user MIMO (SU-MIMO) or multiple-user MIMO (MU-MIMO). Depending on the configuration and number of antenna combinations, MIMO transmission can be 2D-MIMO, 3D-MIMO, FD-MIMO, or massive-MIMO, and can also be diversity transmission, precoding transmission, or beamforming transmission, etc.

[0149] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0150] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-executable instructions. These computer-executable instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0151] These processor-executable instructions may also be stored in a processor-readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the processor-readable memory produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0152] These processors can execute instructions that can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable device for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0153] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for integrated inductive beamforming transmission, characterized in that, Applied to network devices, including: The network device receives communication pilot signals sent by M terminals and sensing pilot signals that arrive at the network device after being reflected or scattered by N sensing targets; M is an integer greater than or equal to 1 and N is an integer greater than or equal to 1. Based on the communication pilot signals, communication channel estimation is performed to obtain the communication estimation channel matrix corresponding to each terminal; based on the sensing pilot signals, sensing channel estimation is performed to obtain the sensing estimation channel matrix corresponding to each sensing target. Based on the communication estimation channel matrix corresponding to each terminal and the perception estimation channel matrix corresponding to each perception target, a hybrid precoding matrix is ​​determined; After beamforming the communication data stream and sensing sequence using the hybrid precoding matrix, they are sent to each of the terminals and each of the sensing targets.

2. The inductive beamforming transmission method according to claim 1, characterized in that, The determination of the hybrid precoding matrix based on the communication estimation channel matrix corresponding to each of the terminals and the perception estimation channel matrix corresponding to each of the sensing targets includes: Based on the communication estimation channel matrix and beam set corresponding to each terminal, the communication beam corresponding to each terminal is determined; based on the perception estimation channel matrix and beam set corresponding to each perception target, the perception beam corresponding to each perception target is determined. A hybrid precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each perception target, the communication beam corresponding to each terminal, and the perception beam corresponding to each perception target.

3. The inductive beamforming transmission method according to claim 2, characterized in that, The step of determining the communication beam corresponding to each terminal based on the communication estimation channel matrix and beam set corresponding to each terminal includes: For each terminal, the communication estimation channel matrix corresponding to the terminal is multiplied with the beam matrix corresponding to the beam set, and the communication beam corresponding to the terminal is selected from the beam set based on the multiplication result. The beam matrix is ​​a matrix composed of the direction vectors of each beam in the beam set.

4. The inductive beamforming transmission method according to claim 2, characterized in that, The step of determining the sensing beam corresponding to each of the sensing targets based on the sensing estimation channel matrix corresponding to each of the sensing targets and the beam set includes: For each of the sensing targets, the sensing estimation channel matrix corresponding to the sensing target is multiplied with the beam matrix corresponding to the beam set, and the sensing beam corresponding to the sensing target is selected from the beam set based on the multiplication result; The beam matrix is ​​a matrix composed of the direction vectors of each beam in the beam set.

5. The inductive beamforming transmission method according to any one of claims 2 to 4, characterized in that, The step of determining the hybrid precoding matrix based on the communication estimation channel matrix corresponding to each of the terminals, the perception estimation channel matrix corresponding to each of the sensing targets, the communication beam corresponding to each of the terminals, and the perception beam corresponding to each of the sensing targets includes: The analog precoding matrix is ​​determined based on the direction vector of the communication beam corresponding to each terminal and the direction vector of the sensing beam corresponding to each sensing target. The digital precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each perception target, and the analog precoding matrix. Based on the analog precoding matrix and the digital precoding matrix, a hybrid precoding matrix is ​​determined.

6. The inductive beamforming transmission method according to claim 5, characterized in that, The step of determining the digital precoding matrix based on the communication estimation channel matrix corresponding to each of the terminals, the perception estimation channel matrix corresponding to each of the sensing targets, and the analog precoding matrix includes: Based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each perception target, and the analog precoding matrix, the equivalent channel matrix is ​​determined; The digital precoding matrix is ​​determined based on the equivalent channel matrix and the precoding algorithm.

7. The inductive beamforming transmission method according to claim 5, characterized in that, The step of determining the digital precoding matrix based on the communication estimation channel matrix corresponding to each of the terminals, the perception estimation channel matrix corresponding to each of the sensing targets, and the analog precoding matrix includes: Based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each perception target, and the analog precoding matrix, a sub-equivalent channel matrix corresponding to each terminal and each perception target is determined respectively. For each of the sub-equivalent channel matrices, a sub-digital precoding matrix corresponding to the sub-equivalent channel matrix is ​​determined based on the sub-equivalent channel matrix and the precoding algorithm; The digital precoding matrix is ​​determined based on all the aforementioned sub-digital precoding matrices.

8. A network device, characterized in that, Includes memory, transceiver, and processor; Memory, used to store computer programs; The transceiver is used to send and receive data under the control of the processor; the processor is used to read the computer program in the memory and perform the following operations: The network device receives communication pilot signals sent by M terminals and sensing pilot signals that arrive at the network device after being reflected or scattered by N sensing targets; M is an integer greater than or equal to 1 and N is an integer greater than or equal to 1. Based on the communication pilot signal, a communication channel estimation is performed to obtain the communication estimation channel matrix corresponding to each terminal; Based on the sensing pilot signal, sensing channel estimation is performed to obtain the sensing estimation channel matrix corresponding to each sensing target; Based on the communication estimation channel matrix corresponding to each terminal and the perception estimation channel matrix corresponding to each perception target, a hybrid precoding matrix is ​​determined; After beamforming the communication data stream and sensing sequence using the hybrid precoding matrix, they are sent to each of the terminals and each of the sensing targets.

9. The network device according to claim 8, characterized in that, The determination of the hybrid precoding matrix based on the communication estimation channel matrix corresponding to each of the terminals and the perception estimation channel matrix corresponding to each of the sensing targets includes: Based on the communication estimation channel matrix and beam set corresponding to each terminal, the communication beam corresponding to each terminal is determined; based on the perception estimation channel matrix and beam set corresponding to each perception target, the perception beam corresponding to each perception target is determined. A hybrid precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each perception target, the communication beam corresponding to each terminal, and the perception beam corresponding to each perception target.

10. The network device according to claim 9, characterized in that, The step of determining the communication beam corresponding to each terminal based on the communication estimation channel matrix and beam set corresponding to each terminal includes: For each terminal, the communication estimation channel matrix corresponding to the terminal is multiplied with the beam matrix corresponding to the beam set, and the communication beam corresponding to the terminal is selected from the beam set based on the multiplication result. The beam matrix is ​​a matrix composed of the direction vectors of each beam in the beam set.

11. The network device according to claim 9, characterized in that, The step of determining the sensing beam corresponding to each of the sensing targets based on the sensing estimation channel matrix corresponding to each of the sensing targets and the beam set includes: For each of the sensing targets, the sensing estimation channel matrix corresponding to the sensing target is multiplied with the beam matrix corresponding to the beam set, and the sensing beam corresponding to the sensing target is selected from the beam set based on the multiplication result; The beam matrix is ​​a matrix composed of the direction vectors of each beam in the beam set.

12. The network device according to any one of claims 9 to 11, characterized in that, The step of determining the hybrid precoding matrix based on the communication estimation channel matrix corresponding to each of the terminals, the perception estimation channel matrix corresponding to each of the sensing targets, the communication beam corresponding to each of the terminals, and the perception beam corresponding to each of the sensing targets includes: The analog precoding matrix is ​​determined based on the direction vector of the communication beam corresponding to each terminal and the direction vector of the sensing beam corresponding to each sensing target. The digital precoding matrix is ​​determined based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each perception target, and the analog precoding matrix. Based on the analog precoding matrix and the digital precoding matrix, a hybrid precoding matrix is ​​determined.

13. The network device according to claim 12, characterized in that, The step of determining the digital precoding matrix based on the communication estimation channel matrix corresponding to each of the terminals, the perception estimation channel matrix corresponding to each of the sensing targets, and the analog precoding matrix includes: Based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each perception target, and the analog precoding matrix, the equivalent channel matrix is ​​determined; The digital precoding matrix is ​​determined based on the equivalent channel matrix and the precoding algorithm.

14. The network device according to claim 12, characterized in that, The step of determining the digital precoding matrix based on the communication estimation channel matrix corresponding to each of the terminals, the perception estimation channel matrix corresponding to each of the sensing targets, and the analog precoding matrix includes: Based on the communication estimation channel matrix corresponding to each terminal, the perception estimation channel matrix corresponding to each perception target, and the analog precoding matrix, a sub-equivalent channel matrix corresponding to each terminal and each perception target is determined respectively. For each of the sub-equivalent channel matrices, a sub-digital precoding matrix corresponding to the sub-equivalent channel matrix is ​​determined based on the sub-equivalent channel matrix and the precoding algorithm; The digital precoding matrix is ​​determined based on all the aforementioned sub-digital precoding matrices.

15. A sensor-integrated beamforming transmission device, characterized in that, include: The receiving unit is used to receive communication pilot signals sent by M terminals respectively, and sensing pilot signals that arrive at the network device after being reflected or scattered by N sensing targets respectively; M is an integer greater than or equal to 1, and N is an integer greater than or equal to 1. The estimation unit is used to perform communication channel estimation based on the communication pilot signal and obtain the communication estimation channel matrix corresponding to each terminal. Based on the sensing pilot signal, sensing channel estimation is performed to obtain the sensing estimation channel matrix corresponding to each sensing target; The determining unit is configured to determine the hybrid precoding matrix based on the communication estimation channel matrix corresponding to each of the terminals and the perception estimation channel matrix corresponding to each of the sensing targets; The beamforming transmission unit is used to beamform the communication data stream and the sensing sequence using the hybrid precoding matrix, and then transmit them to each of the terminals and each of the sensing targets.

16. A processor-readable storage medium, characterized in that, The processor-readable storage medium stores a program for causing the processor to perform the method according to any one of claims 1 to 7.

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