Intelligent reflecting surface assisted non-line-of-sight integration method and system

Abstract

The application provides an intelligent reflecting surface assisted non-orthogonal communication and sensing integration method and system, wherein the method comprises the following steps: activating the intelligent reflecting surface to make the intelligent reflecting surface in an activated mode; receiving a pilot signal sent by a user equipment; estimating an uplink cascade channel and constructing a downlink cascade channel according to the reciprocity of the channel; sending a communication signal to the user equipment according to preset beamforming parameters through the downlink cascade channel, so that the user equipment demodulates the received communication signal, estimates the angle of arrival of the intelligent reflecting surface to the user equipment, and estimates the current position based on the angle of arrival in a coherent time block, wherein the coherent time block is divided by the communication signal, the coherent time block contains a time slot and is divided into at least one sub-coherent time block. Based on the above, the user equipment realizes communication and position sensing of the user equipment according to the signals sent by the base station in a continuous mode, so as to save the pilot overhead of the signals, effectively improve the spectrum efficiency of the system, and solve the problem of large time-frequency resource overhead of the system.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication, and in particular to a smart reflecting surface assisted non-orthogonal communication and sensing integration method and system. BACKGROUND

[0002] The smart reflecting surface can intelligently control the wireless transmission environment and is considered as an innovative technology for the sixth generation mobile communication system. Specifically, the smart reflecting surface is a digital controllable super surface composed of a large number of low-cost reflecting elements, which can reconstruct the wireless transmission environment by actively adjusting the amplitude and phase of the incident signal.

[0003] At present, the smart reflecting surface has been widely studied for use in the field of communication and the field of position sensing. In the field of communication, through active and passive joint beamforming, the smart reflecting surface can greatly improve the signal-to-noise ratio, transmission rate and spectral efficiency of the system, and realize high-rate communication. In the field of position sensing, the deployment of the smart reflecting surface can construct a virtual line-of-sight link between the base station and the terminal, and realize high-precision positioning of the terminal by extracting position parameter information such as received signal strength, angle of arrival and time of arrival in the link. Based on the advantages of applying the smart reflecting surface to communication and position sensing, in order to simultaneously realize high-rate communication and high-precision position sensing in one system, in related technologies, a smart reflecting surface assisted time division communication and position sensing integration system has appeared, which realizes the two functions of communication and position sensing in the same system through time division based on a set of hardware devices.

[0004] However, in related technologies, the communication process and the position sensing process are carried out in a time division manner, occupying orthogonal time-frequency resources, so that the smart reflecting surface assisted time division communication and position sensing integration system has the problems of low spectral efficiency and large time-frequency resource overhead. SUMMARY

[0005] The present application aims to at least solve one of the technical problems in the related art to some extent.

[0006] To this end, a first object of the present application is to propose a smart reflecting surface assisted non-orthogonal communication and sensing integration method to realize communication and position sensing of user equipment, save pilot overhead of signals, effectively improve spectral efficiency of the system, and solve the problem of large system time-frequency resource overhead.

[0007] A second object of the present application is to propose a smart reflecting surface assisted non-orthogonal communication and sensing integration system.

[0008] A third object of the present application is to propose a storage medium.

[0009] To achieve the above objects, an embodiment of the first aspect of the present application proposes a smart reflecting surface assisted non-orthogonal communication and sensing integration method, comprising:

[0010] activating the smart reflecting surface to make the smart reflecting surface in an activated mode, receiving a pilot signal sent by the user equipment, estimating an uplink cascade channel and constructing a downlink cascade channel according to channel reciprocity;

[0011] sending a communication signal to the user equipment according to preset beamforming parameters through the downlink cascade channel, so that the user equipment demodulates the received communication signal, estimates an angle of arrival of the smart reflecting surface to the user equipment, and estimates a current position based on the angle of arrival within a coherence time block;

[0012] The coherence time block is divided by the communication signal, the coherence time block contains time slots and is divided into at least one sub-coherence time block, in the sub-coherence time block, the plurality of smart reflecting surfaces are in the activated mode in turn and work according to the preset beamforming parameters in different sub-coherence time blocks, when any smart reflecting surface is in the activated mode, other smart reflecting surfaces are in the inactivated mode, and the smart reflecting surface is configured with a plurality of reflecting elements.

[0013] Optionally, in the embodiment of the present application, the user equipment equipped with at least two antennas comprises:

[0014] M=M y *M z a uniform rectangular array antenna, wherein M y and M z respectively represent the number of antennas along the y-axis and z-axis directions.

[0015] Optionally, in the embodiment of the present application, the method of estimating an uplink cascade channel and constructing a downlink cascade channel according to channel reciprocity comprises:

[0016] switching array element training technology, least square technology, least mean square error technology, compressed sensing technology and deep learning technology.

[0017] Optionally, in the embodiment of the present application, the method that the coherence time block contains time slots and is divided into at least one sub-coherence time block is:

[0018] equal length division method;

[0019] unequal length division method.

[0020] Optionally, in the embodiment of the present application, when the smart reflecting surface is in the activated mode, the incident signal is reflected according to a preset phase offset, and when the smart reflecting surface is in the inactivated mode, the signal is not reflected.

[0021] Optionally, in an embodiment of the present invention, sending a signal to the user equipment according to preset beamforming parameters includes the following steps:

[0022] Calculate synesthetic CRLB;

[0023] The beamforming algorithm based on the aforementioned inductive CRLB is used to perform beamforming on the base station and the smart reflector.

[0024] Optionally, in an embodiment of the present invention, the method for calculating synesthetic CRLB includes:

[0025]

[0026] Where ζ represents the weighting coefficient, which ranges from 0 to 1, and J represents the parameter vector to be estimated. The Fisher information matrix, where x(t) represents the information symbol transmitted by the base station in the t-th time slot of the subcoherent time block. and These represent the elevation angle and azimuth angle of arrival along the path from the base station to the user, respectively.

[0027] The Fisher information matrix J of the parameter vector θ to be estimated is calculated according to the following formula.

[0028]

[0029] in, Let p(x) represent the variance of the noise signal, and let p(x) represent the base station transmitted signal vector x = [x(1), ..., x(T)]. T The probability density function, This represents the operation of taking the real part, β x β represents the bias of the received signal with respect to the transmitted signal. γ，t Indicates the received signal pair The biased directional quantity, Indicates the received signal pair The biased directional quantity.

[0030] The bias β of the received signal to the transmitted signal x The received signal pair biased directional β γ，t and the received signal pair biased directional quantity Calculate using the following formula:

[0031] β x =H I2U ΘH B2I w

[0032]

[0033]

[0034] where w denotes the base station beamforming vector, H B2I denotes the channel from the base station to the intelligent reflecting surface, Θ denotes the phase shift matrix of the reflecting surface, defined as H I2U denotes the channel from the reflecting surface to the user, D γ denotes the partial derivative matrix of H I2U with respect to denotes the partial derivative matrix of H I2U with respect to denotes the Hadamard product operation.

[0035] The H I2U denotes the partial derivative matrix of D with respect to γ and H I2U denotes the partial derivative matrix of with respect to is calculated according to the following formula:

[0036]

[0037]

[0038] where m∈{1,…,M},l∈{1,…,L}.

[0039] Optionally, in the embodiments of the present application, the beamforming algorithm based on the CRLB of the common sense performs beamforming on the base station and the intelligent reflecting surface, comprising:

[0040] C phase shift matrix samples are randomly generated according to the probability distribution function Ξ(Θ;P) of Θ where P denotes the probability matrix of the phase shift matrix Θ, initialized as where 1 N×M denotes an all-one matrix of N rows and M columns.

[0041] The probability distribution function Ξ(Θ;P) of the phase shift matrix Θ is expressed as

[0042]

[0043] where denotes the value set of the phase shift θ l of the intelligent reflecting surface array element, b denotes the number of quantization bits, denotes the s-th element of , the decision function is expressed as

[0044] ​​

[0045] C phase offset matrix samples are generated corresponding common CRLB values are calculated and C elite phase offset matrices corresponding to C elite minimum common CRLB values are selected The elements of the probability matrix P of the phase offset matrix Θ are updated as follows:

[0046]

[0047] The above process is repeated according to the probability distribution function Ξ(Θ;P) of the updated Θ until the difference between the maximum and minimum of the common CRLB values corresponding to the C generated phase offset matrix samples is less than a threshold value κ, at which time the phase offset matrix generated by the probability matrix is the optimized result.

[0048] To achieve the above object, the second aspect of the present application proposes an intelligent reflecting surface assisted non-orthogonal integrated sensing system, comprising: a base station equipped with at least one antenna, a user equipment equipped with at least two antennas, and a plurality of intelligent reflecting surfaces, wherein,

[0049] The base station is configured to receive a pilot signal sent by the user equipment, activate the intelligent reflecting surface to make the intelligent reflecting surface in an active mode, estimate an uplink cascade channel, and construct a downlink cascade channel according to the reciprocity of the channel.

[0050] The user equipment is configured to receive a communication signal sent by the base station through the downlink cascade channel according to a preset beamforming parameter, demodulate the received communication signal, estimate an angle of arrival of the intelligent reflecting surface to the user equipment, estimate a current position based on the angle of arrival within a coherence time block.

[0051] The coherence time block is divided by the communication signal, the coherence time block contains a time slot and is divided into at least one sub-coherence time block, within the sub-coherence time block, the plurality of intelligent reflecting surfaces are in the active mode in turn and work according to the preset beamforming parameter, when any intelligent reflecting surface is in the active mode, other intelligent reflecting surfaces are in the inactive mode, and the intelligent reflecting surface is configured with a plurality of reflecting elements.

[0052] To achieve the above object, the third aspect of the present application proposes a storage medium, wherein the computer program is stored, when the computer program is executed by the processor, the intelligent reflecting surface assisted non-orthogonal integrated sensing method proposed in the first aspect of the present application is realized.

[0053] Additional aspects and advantages of the present application will be set forth in part in the description that follows, and in part will become apparent to those having ordinary skill in the art upon examination of the following or can be learned from practice of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0054] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, taken in conjunction with the accompanying drawings, in which:

[0055] Figure 1 An application diagram of a smart reflector assisted non-orthogonal co-sensing integrated system provided by an embodiment of the present application is shown in FIG. 1.

[0056] Figure 2 A flow diagram of a smart reflector assisted non-orthogonal co-sensing integrated method provided by an embodiment of the present application is shown in FIG. 2.

[0057] Figure 3 A coherent time block equal length division diagram provided by an embodiment of the present application is shown in FIG. 3.

[0058] Figure 4 A co-sensing performance comparison diagram between a beamforming scheme based on CRLB and a beamforming scheme based on SNR provided by an embodiment of the present application is shown in FIG. 4.

[0059] Figure 5 A communication performance and location sensing performance comparison diagram between a smart reflector assisted non-orthogonal co-sensing integrated system and a smart reflector assisted time division orthogonal co-sensing integrated system in an embodiment of the present application is shown in FIG. 5.

[0060] Figure 6 A communication performance and location sensing performance comparison diagram between a smart reflector assisted non-orthogonal co-sensing integrated system and a smart reflector assisted time division orthogonal co-sensing integrated system in an embodiment of the present application is shown in FIG. 5. DETAILED DESCRIPTION

[0061] Embodiments of the present application are described in detail below with reference to the attached drawings, which show by way of example, embodiments in which like reference numerals refer to like elements or elements having similar functions. The embodiments described below are illustrative, and are not meant to be limiting to the scope of the application as defined by the claims.

[0062] A smart reflector assisted non-orthogonal co-sensing integrated method of an embodiment of the present application is described below with reference to the accompanying drawings.

[0063] Figure 1 An application diagram of a smart reflector assisted non-orthogonal co-sensing integrated system provided by an embodiment of the present application is shown in FIG. 1.

[0064] As Figure 1It is illustrated that the method is applied to an intelligent reflecting surface assisted non-orthogonal communication integrated system, the intelligent reflecting surface assisted non-orthogonal communication integrated system comprising: a base station equipped with at least one antenna, a user equipment equipped with at least two antennas, and a plurality of intelligent reflecting surfaces. In an embodiment of the present application, the user equipment equipped with at least two antennas comprises:

[0065] M = M y *M z a uniform rectangular array antenna, wherein M y and M z respectively represent the number of antennas along the y-axis and z-axis directions.

[0066] For example, in an embodiment of the present application, the number of base station antennas can be 8, the number of reflecting surfaces can be 2, the number of user antennas can be 16, and the number of reflecting surface elements on the reflecting surface can be 16. The distance from the base station to the intelligent reflecting surface is 30 meters, the distance from the user to the intelligent reflecting surface is 10 meters, and the user receives a signal-to-noise ratio of 0 decibels.

[0067] Figure 2 A flowchart of a smart reflecting surface assisted non-orthogonal communication integrated method provided by an embodiment of the present application.

[0068] As Figure 2 illustrated, the method comprises the following steps:

[0069] Step S1: activating the intelligent reflecting surface to place the intelligent reflecting surface in an activated mode, receiving a pilot signal sent by the user equipment, estimating an uplink cascade channel, and constructing a downlink cascade channel according to the reciprocity of the channel.

[0070] It should be noted that only when the intelligent super surface is in the activated mode can the signal be reflected. Since the user equipment can be in a blind area, the base station can only receive the signal after the signal is reflected by the intelligent super surface in the activated mode after the signal is sent by the user equipment. In addition, when the signal propagates in the channel, the amplitude and phase of the signal will change due to the influence of the channel. Therefore, after receiving the signal, the base station can calculate the change amount of the signal caused by the influence of the channel during the propagation process according to the change of the received signal relative to the transmitted signal (pilot signal), and then estimate the information of the channel.

[0071] In an embodiment of the present disclosure, the method of estimating the uplink cascade channel and constructing the downlink cascade channel according to the reciprocity of the channel comprises:

[0072] switch array training technology, least square technology, least mean square error technology, compressed sensing technology, and deep learning technology.

[0073] Step S2: sending a signal to the user equipment through a downlink cascaded channel according to preset beamforming parameters, so that the user equipment demodulates the received signal, estimates the angle of arrival of the intelligent reflecting surface to the user equipment, and estimates the current position based on the angle of arrival in the coherent time block.

[0074] In one embodiment of the present disclosure, the coherent time block is divided by a communication signal, the coherent time block contains time slots and is divided into at least one sub-coherent time block, in the sub-coherent time block, a plurality of intelligent reflecting surfaces are in an active mode in different sub-coherent times in turn and work according to preset beamforming parameters, when any intelligent reflecting surface is in the active mode, other intelligent reflecting surfaces are in a non-active mode, and the intelligent reflecting surface is configured with a plurality of reflecting elements.

[0075] In one embodiment of the present disclosure, the coherent time block contains time slots and is divided into at least one sub-coherent time block by the following methods:

[0076] equal-length division method;

[0077] unequal-length division method.

[0078] For example, in one embodiment of the present disclosure, Figure 3 A schematic diagram of equal-length division of a coherent time block is provided in an embodiment of the present disclosure. As shown in the figure, Figure 3 each coherent time block is equally divided into N coherent sub-time blocks of the same length by the equal-length division method, and the number of time slots in each coherent sub-time block is 2.

[0079] In one embodiment of the present disclosure, the intelligent reflecting surface reflects the incident signal according to the preset phase offset when it is in the active mode, and does not reflect the signal when it is in the non-active mode.

[0080] In one embodiment of the present disclosure, the step of sending a signal to the user equipment according to preset beamforming parameters includes the following steps:

[0081] calculating the common CRLB (Cramer-rao lower bound);

[0082] performing beamforming on the base station and the intelligent reflecting surface based on the beamforming algorithm of the common CRLB.

[0083] Further, in one embodiment of the present disclosure, the method for calculating the common CRLB includes:

[0084]

[0085] wherein ζ represents a weight coefficient, the value range of which is 0 to 1, and J represents a to-be-estimated parameter vector Fisher information matrix of the unknown parameter vector θ, where x(t) denotes the information symbol transmitted by the base station at the t-th time slot of the sub-coherent time block. and denote the arrival elevation and azimuth of the base station-to-user path, respectively.

[0086] The Fisher information matrix J of the unknown parameter vector θ is computed as

[0087]

[0088] where, denotes the variance of the noise signal, p(x) denotes the probability density function of the base station transmitted signal vector x = [x(1),..., x(T)] T denotes the operation of taking the real part, β x denotes the partial derivative of the received signal with respect to the transmitted signal, β γ，t denotes the partial derivative of the received signal with respect to denotes the partial derivative of the received signal with respect to

[0089] The partial derivative of the received signal with respect to the transmitted signal β x , the partial derivative of the received signal with respect to β γ，t , and the partial derivative of the received signal with respect to are computed according to

[0090] β x = H I2U ΘH B2I w

[0091]

[0092]

[0093] where w denotes the base station beamforming vector, H B2I denotes the base station-to-intelligent reflecting surface channel, Θ denotes the phase offset matrix of the reflecting surface, defined as H I2U denotes the reflecting surface-to-user channel, D γ denotes the partial derivative matrix of H I2U with respect to denotes the partial derivative matrix of H I2U with respect to denotes the Hadamard product operation.

[0094] H I2U with respect to​​​​​​ The partial derivative coefficient matrix D γ and H I2U right The partial derivative coefficient matrix Calculate using the following formula:

[0095]

[0096]

[0097] Where m∈{1,…,M}, l∈{1,…,L}.

[0098] Furthermore, in one embodiment of this disclosure, the method for beamforming a base station and a smart reflector based on the inductive CRLB-based beamforming algorithm includes:

[0099] C phase offset matrix samples are randomly generated based on the probability distribution function Ξ(Θ;P) of Θ. Where P represents the probability matrix of the phase offset matrix Θ, initialized to... Among them 1 N×M This represents an N-row, M-column matrix of all 1s.

[0100] The probability distribution function Ξ(Θ;P) of the phase offset matrix Θ is expressed as:

[0101]

[0102] in, The phase offset θ of the intelligent reflector array element l The set of possible values ​​for , where b represents the number of quantization bits. express The s-th element, the decision function Represented as

[0103]

[0104] For the generated C phase offset matrix samples Calculate the corresponding synesthesia CRLB value And select C elit The C corresponding to the e minimum synesthesia CRLB values elite Phase offset matrix Update the elements of the probability matrix P of the phase offset matrix Θ to:

[0105]

[0106] The above process is repeated according to the probability distribution function Ξ(Θ;P) of the updated Θ until the difference between the maximum value and the minimum value of the generated C phase offset matrix samples corresponding to the mutual sensing CRLB value is less than the threshold value κ, and at this time, the phase offset matrix generated by the probability matrix is the optimized result.

[0107] Figure 4 A mutual sensing performance comparison chart of the beamforming scheme based on the mutual sensing CRLB and the beamforming scheme based on the SNR in the embodiment of the application. Figure 5 and Figure 6 A communication performance and location sensing performance comparison of the intelligent reflecting surface assisted non-orthogonal integrated sensing system and the intelligent reflecting surface assisted time division orthogonal integrated sensing system in the embodiment of the application.

[0108] It should be noted that based on the above calculation and in combination with Figure 4 , Figure 5 and Figure 6 , the following conclusions can be drawn, as shown in Figure 4 , in the beamforming scheme based on the mutual sensing CRLB joint performance bound, the communication mutual information is improved with the increase of the sensing CRLB (i.e., the increase of the sensing error), proving that there is a trade-off relationship between the communication and sensing performance. For example, sacrificing the communication performance to improve the sensing performance. Therefore, by adjusting the mutual sensing weight coefficient, the communication and location sensing performance can be flexibly balanced to achieve any mutual sensing performance combination on the joint performance bound in Figure 4 . In contrast, the beamforming scheme based on the SNR not only cannot achieve the optimal joint performance bound, but also can only achieve fixed communication and sensing performance (represented as a point in the figure). In terms of sensing performance, the beamforming scheme based on the mutual sensing CRLB is much better than the beamforming scheme based on the SNR, and in terms of communication performance, the former is slightly better than the latter. In addition, both of them are much better than the random phase beamforming scheme in terms of mutual sensing performance. And as shown in Figure 5 and Figure 6 , the non-orthogonal integrated sensing system can simultaneously achieve better communication performance and location sensing performance. In addition, as the number of intelligent reflecting surface elements increases, the performance gap between the two becomes more obvious. It is proved that the proposed intelligent reflecting surface assisted non-orthogonal integrated sensing system can achieve better mutual sensing performance under the same time-frequency resources, and the spectrum efficiency is significantly improved.

[0109] Based on this, the intelligent reflecting surface assisted non-orthogonal integrated sensing system proposed in the application can simultaneously realize communication and location sensing under non-orthogonal time-frequency resources, effectively improving the spectrum efficiency of the intelligent reflecting surface assisted mutual sensing integrated system, and the proposed beamforming method based on the mutual sensing CRLB can effectively adjust and balance the communication performance and sensing performance.

[0110] In addition, in the field of communication, the evaluation index in the prior art can only represent the communication performance or the sensing performance of the system (for example, the communication performance is measured by the transmission rate, and the sensing performance is measured by the positioning accuracy). However, in the integrated communication and sensing system, the communication performance and the sensing performance are closely coupled, and there is a certain trade-off relationship between the two, and the change of one performance will also affect the other performance, so the traditional single evaluation index of one performance cannot be used to realize the trade-off between the two performances. Based on this, by using the integrated communication and sensing CRLB, the communication performance and the sensing performance of the system can be represented at the same time, and the trade-off of the integrated communication and sensing performance can be realized by adjusting the weight coefficient ζ. For example, when ζ is increased, the system will sacrifice part of the sensing performance to improve the communication performance of the system, so as to realize the replacement and trade-off between the communication performance and the sensing performance.

[0111] In an embodiment of the present application, the method for user equipment to demodulate information symbols according to signal comprises:

[0112] least square method;

[0113] least mean square error method.

[0114] Specifically, in an embodiment of the present application, the signal is received by the user equipment after propagating through the path of base station-intelligent metasurface-user equipment, and the information symbols demodulated by the user equipment according to the received signal are used as data to estimate the angle of arrival of the intelligent reflecting surface to the user equipment. Wherein, the angle of arrival refers to the measure of the direction of wave radiation propagation to the observation point

[0115] In an embodiment of the present application, the method for user equipment to estimate the position of the angle of arrival in the coherent time block comprises:

[0116] multi-station cross-direction finding positioning algorithm.

[0117] It should be noted that in the embodiments of the present application, estimating the self-position, that is, realizing the positioning function of the user, is a common requirement in communication and sensing integration. In the traditional time division communication and sensing method, when the base station sends the pilot signal to the user equipment, the user equipment performs signal processing operation on the received pilot signal to estimate the self-position (i.e., position sensing); when the base station sends the communication signal to the user equipment, the user can realize data transmission (i.e., communication) by demodulating the communication signal. In order to realize the integration of communication and sensing, the base station can only alternately send the pilot signal and the communication signal, so the communication function and the position sensing function occupy different time-frequency resources. However, in the present method, the base station sends the communication signal to the user equipment, and the user realizes communication by demodulating the received communication signal, at the same time, the user can estimate the angle of arrival of the smart surface to the user equipment link according to the received signal by using the total least squares-rotation invariant vector technology and the multiple signal classification technology, since the position of the smart surface is known, the self-position can be estimated by using the multi-station cross direction finding positioning algorithm. Therefore, the base station can always send the communication signal to the user equipment, and the user equipment can realize communication and self-position sensing at the same time according to the received signal, that is, the two functions of communication and position sensing can be realized at the same time in the non-orthogonal time-frequency resources.

[0118] In summary, the method provided by the embodiments of the present application can activate the smart reflective surface to make the smart reflective surface in the activated mode, receive the pilot signal sent by the user equipment, estimate the uplink cascade channel and construct the downlink cascade channel according to the reciprocity of the channel; then send the signal to the user equipment according to the preset beamforming parameters through the downlink cascade channel, so that the user equipment demodulates the received signal, estimates the angle of arrival of the smart reflective surface to the user equipment, and estimates the current position based on the angle of arrival in the coherent time block. Based on this, the method can always send the communication signal to the user equipment, and the user equipment can realize communication and self-position sensing at the same time according to the received signal, that is, the two functions of communication and position sensing can be realized at the same time in the non-orthogonal time-frequency resources, realizing communication and position sensing of the user equipment, saving the pilot cost of the signal, effectively improving the spectrum efficiency of the system, and solving the problem of large time-frequency resource overhead of the system.

[0119] Reference Figure 1 The system provided by the embodiments of the present application also includes a base station equipped with at least one antenna, a user equipment equipped with at least two antennas, and a plurality of smart reflective surfaces.

[0120] The base station is used to receive the pilot signal sent by the user equipment, activate the smart reflective surface to make the smart reflective surface in the activated mode, estimate the uplink cascade channel and construct the downlink cascade channel according to the reciprocity of the channel;

[0121] The user equipment is configured to receive a base station transmitting a signal through a downlink cascaded channel according to preset beamforming parameters, demodulate the received signal, estimate an angle of arrival of the intelligent reflecting surface to the user equipment, and estimate a current position based on the angle of arrival within a coherent time block.

[0122] The signal includes a coherent time block, the coherent time block includes a time slot and is divided into at least one sub-coherent time block, in the sub-coherent time block, the last intelligent reflecting surface in the plurality of intelligent reflecting surfaces is in an active mode and works according to preset beamforming parameters, and the other intelligent reflecting surfaces are in an inactive mode.

[0123] It should be noted that the foregoing explanation of the embodiment of the intelligent reflecting surface assisted non-orthogonal communication and sensing integration method provided by the embodiment of the application is also applicable to the system of the embodiment, and reference can be made to the related description of the above embodiment, which will not be described here again.

[0124] In summary, the intelligent reflecting surface assisted non-orthogonal communication and sensing integration system provided by the embodiment of the application first activates the intelligent reflecting surface to make the intelligent reflecting surface in an active mode, receives a pilot signal sent by the user equipment, estimates an uplink cascaded channel and constructs a downlink cascaded channel according to the reciprocity of the channel, then transmits a signal to the user equipment through the downlink cascaded channel according to preset beamforming parameters, so that the user equipment demodulates the received signal, estimates an angle of arrival of the intelligent reflecting surface to the user equipment, and estimates a current position based on the angle of arrival within a coherent time block. Based on this, the method can always transmit a communication signal to the user equipment, and the user equipment can simultaneously realize communication and position sensing according to the received signal, that is, the two functions of communication and position sensing are realized in non-orthogonal time-frequency resources, the position of the user equipment is sensed, the pilot overhead of the signal is saved, the spectral efficiency of the system is effectively improved, and the problem of large system time-frequency resource overhead is solved.

[0125] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction.

[0126] Moreover, the terms "first", "second", "third", etc. are used herein only to describe different steps or categories of steps in a claim for patent purposes, and are not to be construed as implying or implying relative importance or a number of indicated technical features. Thus, features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality" is at least two, for example, two, three, etc., unless otherwise explicitly specified.

[0127] Any process or method descriptions or descriptions of the flow diagrams described herein or otherwise described herein can be understood as representing modules, segments, or portions of code that include one or more executable instructions for implementing specific logical functions or steps in the process, and the preferred embodiments of the present application include additional implementations that can not be described in detail in the description of the flow diagrams or otherwise described herein, and that can include the implementation of the functions according to the involved functions in a substantially simultaneous manner or in reverse order, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0128] The logic and / or steps represented in the flow diagrams or otherwise described herein, for example, can be considered as a list of executable instructions for implementing logical functions, which can be specifically implemented in any computer readable medium for use by or in conjunction with an instruction execution system, device or apparatus, such as a computer-based system, a system including a processor, or other system that can take instructions from an instruction execution system, device or apparatus and execute them. For the purposes of this specification, a "computer readable medium" can be any device that can contain, store, communicate, propagate or transport a program for use by or in conjunction with an instruction execution system, device or apparatus. More specific examples (non-exhaustive list) of computer readable medium include the following: electrical connections having one or more wires (electronic devices), portable computer diskette (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable compact disc read-only memory (CD ROM). In addition, a computer readable medium can even be paper or other suitable medium on which the program can be printed, as the program can be electronically obtained, for example, by optical scanning of the paper or other medium, followed by electronic conversion, interpretation or processing, if necessary, in other suitable manner, and then stored in a computer memory.

[0129] It should be understood that each part of the present application can be realized by hardware, software, firmware or their combination. In the above-mentioned embodiments, a plurality of steps or methods can be realized by software or firmware stored in a memory and executed by a suitable instruction execution system. As in another embodiment, if realized by hardware, any one or their combination of the following technologies known in the art can be used: discrete logic circuit with logic gate circuit for implementing logic function on data signal, application specific integrated circuit with suitable combination logic gate circuit, programmable gate array (PGA), field programmable gate array (FPGA) and the like.

[0130] Those skilled in the art of the present technology can understand that all or part of the steps carried out by the above-mentioned embodiment method can be completed by a program instructing the relevant hardware, and the program can be stored in a computer readable storage medium. When the program is executed, it includes one of the steps of the method embodiment or a combination thereof.

[0131] In addition, each functional unit in each embodiment of the present application can be integrated in one processing module, or each unit can exist physically, or two or more units can be integrated in one module. The above-mentioned integrated module can be realized in the form of hardware or in the form of software functional module. The integrated module, if realized in the form of software functional module and sold or used as an independent product, can also be stored in a computer readable storage medium.

[0132] The above-mentioned storage medium can be read-only memory, disk or optical disk, etc. Although the embodiments of the present application have been shown and described above, it should be understood that the above-mentioned embodiments are exemplary and cannot be understood as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above-mentioned embodiments within the scope of the present application.

Claims

1. A method for integrating intelligent reflective surface-assisted non-positive traffic sensing, characterized in that, An application is made to an integrated system of intelligent reflectors-assisted non-orthogonal traffic sensors, the integrated system comprising: a base station equipped with at least one antenna, a user equipment equipped with at least two antennas, and multiple intelligent reflectors, the method comprising: Activating the smart reflector puts it into an active mode. The base station receives the pilot signal sent by the user equipment, estimates the uplink concatenated channel, and constructs the downlink concatenated channel based on the reciprocity of the channel. Through the downlink concatenated channel, a communication signal is sent to the user equipment according to a preset beamforming parameter, so that the user equipment demodulates the received communication signal, estimates the angle of arrival from the smart reflector to the user equipment, and estimates the current position based on the angle of arrival within the coherent time block; The coherent time block is divided by the communication signal. The coherent time block includes time slots and is divided into at least one sub-coherent time block. Within the sub-coherent time block, the multiple smart reflectors are sequentially in active mode and operate according to the preset beamforming parameters in different sub-coherent time periods. When any smart reflector is in active mode, the other smart reflectors are in inactive mode. The smart reflector is configured with multiple reflective elements. When the smart reflector is in active mode, it reflects the incident signal according to a preset phase offset. When the smart reflector is in inactive mode, it does not reflect the signal.

2. The integrated method according to claim 1, characterized in that, The user equipment equipped with at least two antennas includes: M=M y *M z A uniform rectangular array antenna, wherein M y and M z They represent along shaft and The number of antennas along the axial direction.

3. The integrated method according to claim 1, characterized in that, The method for estimating the uplink concatenated channel and constructing the downlink concatenated channel based on the reciprocity of the channel includes: Switching array element training technology, least squares technology, minimum mean square error technology, compressed sensing technology, and deep learning technology.

4. The integrated method according to claim 1, characterized in that, The method for dividing the coherent time block, which includes time slots, into at least one sub-coherent time block is as follows: Equal-length division method; Non-equal length partitioning method.

5. The integrated method according to claim 1, characterized in that, Sending communication signals to the user equipment according to preset beamforming parameters includes the following steps: Calculate synesthetic CRLB; The beamforming algorithm based on the aforementioned inductive CRLB is used to perform beamforming on the base station and the smart reflector.

6. The integrated method according to claim 5, characterized in that, The method for calculating synesthetic CRLB includes: in, This represents the weighting coefficient, which ranges from 0 to 1. Represents the vector of parameters to be estimated The Fisher information matrix, in which Indicates the base station in the sub-coherence time block at the 1st Information symbols transmitted in each time slot and These represent the elevation angle and azimuth angle of arrival along the path from the base station to the user, respectively. The parameter vector to be estimated Fisher information matrix Calculate using the following formula: in, The variance of the noise signal is represented. Represents the base station transmit signal vector The probability density function, This indicates the operation of taking the real part. This represents the bias of the received signal relative to the transmitted signal. Indicates the received signal pair The biased directional quantity, Indicates the received signal pair The biased directional quantity; The bias of the received signal to the transmitted signal The received signal pair biased directional quantity and the received signal pair biased directional quantity Calculate using the following formula: in, Represents the base station beamforming vector. This represents the channel from the base station to the smart reflector. The phase offset matrix of the reflecting surface is defined as follows: , This represents the channel from the reflector to the user. express right The partial derivative coefficient matrix, express right The partial derivative coefficient matrix, This represents the Hadamard product operation; The right The partial derivative coefficient matrix and right The partial derivative coefficient matrix Calculate using the following formula: in, , .

7. The integrated method according to claim 5, characterized in that, The method for beamforming a base station and a smart reflector based on the inductive CRLB-based beamforming algorithm includes: according to probability distribution function Randomly generated Phase offset matrix samples ,in Represents the phase offset matrix The probability matrix is ​​initialized to ,in express OK A matrix of all 1s in each column; The phase offset matrix probability distribution function Represented as in, Indicates the phase shift of the intelligent reflector array element The set of possible values, Indicates the number of quantization bits. express The 1 element, decision function Represented as For the generated Phase offset matrix samples Calculate the corresponding synesthesia CRLB value , and select The minimum synesthesia CRLB value corresponds to Phase offset matrix , phase offset matrix probability matrix The elements are updated as follows: According to the updated probability distribution function Repeat the above process until the product is generated. The difference between the maximum and minimum values ​​of the synesthetic CRLB values ​​corresponding to each phase offset matrix sample is less than the threshold value. Then, the phase offset matrix generated by the probability matrix is ​​the result of optimization.

8. A smart reflective surface-assisted non-positive traffic sensing integrated system, characterized in that, include: A base station equipped with at least one antenna, user equipment equipped with at least two antennas, and multiple smart reflectors, among which, The base station is used to receive pilot signals sent by user equipment, activate the smart reflector to put the smart reflector in active mode, estimate the uplink concatenated channel and construct the downlink concatenated channel according to the reciprocity of the channel; The user equipment is used to receive communication signals transmitted by the base station through the downlink concatenated channel according to preset beamforming parameters, demodulate the received communication signals, estimate the angle of arrival from the smart reflector to the user equipment, and estimate the current position based on the angle of arrival within the coherent time block; The coherent time block is divided by the communication signal. The coherent time block includes time slots and is divided into at least one sub-coherent time block. Within the sub-coherent time block, the multiple smart reflectors are sequentially in active mode and operate according to the preset beamforming parameters in different sub-coherent time periods. When any smart reflector is in active mode, the other smart reflectors are in inactive mode. The smart reflector is configured with multiple reflective elements. When the smart reflector is in active mode, it reflects the incident signal according to a preset phase offset. When the smart reflector is in inactive mode, it does not reflect the signal.

9. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-7.

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