Integrated Communication and Positioning System and Method Based on Intelligent Reflective Surface

Abstract

This invention discloses an integrated communication and positioning system and method based on an intelligent reflector. In the communication subframe, the transmitter maps communication information onto the control signal of the intelligent reflector. The intelligent reflector's phase modulation capability for spatial electromagnetic waves is used to modulate the phase of a single-frequency carrier, avoiding the high cost, complexity, and energy consumption of traditional mixer modulation. In the sensing and positioning subframe, the reflector reflects electromagnetic waves of different beam patterns according to a preset codebook. The receiver performs frame synchronization and frequency offset correction according to the protocol's communication subframes. Based on the positioning codebook of the positioning subframe, it calculates the cascaded channel state information of the base station-reflector-user, thereby calculating the user's positioning information and feeding it back via the uplink. The reflector performs narrow beamforming and positioning codebook optimization design for the user based on the feedback information, thereby improving the signal-to-noise ratio of communication and reducing the Cramer-Rao lower bound of positioning errors, achieving synergistic enhancement of communication and sensing.

Description

Technical Field

[0001] This invention relates to the fields of wireless communication and sensing positioning technology, and in particular to an integrated communication and positioning system and method based on an intelligent reflective surface. Background Technology

[0002] Thanks to key technologies such as ultra-dense networks (UDNs), massive MIMO (Multiple Input Multiple Output), and millimeter wave (mmWave) communication, fifth-generation (5G) wireless networks have achieved a 1000-fold increase in network capacity and ubiquitous wireless connectivity for at least 400 million devices. However, high complexity, hardware costs, and increased energy consumption remain critical unresolved issues. For example, densely deploying base stations or access points in UDNs not only increases hardware overhead and maintenance costs but also exacerbates network interference. Providing reliable and scalable backhaul transmission is a challenging task, especially in indoor deployments without full optical coverage. Furthermore, extending massive MIMO from below 6 GHz to the mmWave band typically requires more complex signal processing and more expensive and energy-intensive hardware. Therefore, researching innovative, spectrum-efficient, and cost-effective solutions for future wireless networks beyond 5G remains imperative.

[0003] Intelligent Reflectors (RIS) actively modify the wireless channel between reflective links through highly controllable intelligent signals. By appropriately adjusting 3D passive beamforming, the signals reflected by the reflector can constructively add to signals from other paths to enhance the desired signal power at the receiver, or destructively eliminate unwanted signals such as co-channel interference, thus improving energy efficiency. RIS-based communication systems operate over short distances, allowing for dense deployment, scalability, and low power consumption. They address the pain points of current communication systems, such as high complexity, high energy consumption, high hardware and maintenance costs, and increased network interference, offering an innovative, energy-efficient, and cost-effective solution.

[0004] Smart reflectors can reconfigure the wireless propagation environment through software-controlled reflection, revolutionizing the traditional method of baseband signal modulation by the transmitter. In smart reflector systems, the incident excitation wave and reflection coefficient function are very similar to the carrier and baseband signals of traditional communication systems. Guided by modulation techniques in modern wireless communication, TDCIM-based systems have implemented various modulation schemes. Existing work has achieved system-level designs including Frequency Shift Keying (FSK), Phase Shift Keying (PSK), and Quadrature Amplitude Modulation (QAM) by controlling the physical characteristics of smart reflectors through software coding. Recently, more advanced systems combining Multiple-Input Multiple-Output (MIMO) technology have also been proposed.

[0005] In terms of positioning, the receiver in the RIS-based system is equipped with a hybrid architecture employing quantized beamforming. Unlike traditional multiple-input multiple-output (MIMO) systems, channel estimation design for RIS-based systems is challenging because RIS are typically passive arrays with limited signal processing capabilities. The application of smart metasurface-assisted wireless communication systems still faces numerous challenges. A method is needed to obtain accurate user location information to assist in optimizing the smart metasurface reflection coefficient, thereby improving the performance of the wireless communication system and achieving the integrated fusion of smart metasurface-assisted wireless communication and sensing / positioning. Summary of the Invention

[0006] This invention provides an integrated communication and positioning system and method based on an intelligent reflective surface to address the problems of low accuracy, high power consumption and cost, high hardware and algorithm complexity, and low functional reusability of communication and positioning in hardware architecture and algorithm system of current indoor positioning systems.

[0007] A first aspect of this invention provides a communication and positioning integrated system based on an intelligent reflective surface. The communication protocol of the integrated communication and positioning system is divided into communication subframes and positioning sensing subframes according to time. The integrated communication and positioning system includes:

[0008] A signal generator used to transmit a single-frequency carrier wave;

[0009] Includes M×N reflective units U m,n The intelligent reflective surface is used to perform time-division reflection phase modulation according to the frame structure of the protocol and reflect the signal to the air interface channel. When the frame structure is a communication subframe, the reflection phase coefficient of the reflection unit is adjusted synchronously. When the frame structure is a positioning sensing subframe, the reflection phase coefficient of different reflection units is adjusted according to a preset codebook.

[0010] The receiving end is used to perform frame synchronization and frequency offset correction based on the reflected signal and the communication subframe of the protocol. It calculates the cascaded channel state information of the integrated communication and positioning system based on the preset codebook of the positioning sensing subframe, obtains the positioning information of the receiving end, and feeds it back to the intelligent reflector through the uplink. This enables the intelligent reflector to perform narrow beamforming and precoding in the communication subframe based on the feedback information, and optimizes the reflection phase coefficient of the intelligent reflector in the positioning sensing subframe.

[0011] Optionally, in one embodiment of the present invention, the reflection phase coefficient of the smart reflective surface is Γ. m,n (t), the transmitting antenna of the signal generator transmits a single-frequency carrier wave. Distance to Reflection unit U m,n The light is reflected by the intelligent reflective surface to the air interface channel and is then reflected by the reflection unit U. m,n Distance is The receiving antenna at the receiving end receives the cascaded channel status information of the integrated communication and positioning system as follows:

[0012]

[0013] Where E represents the energy of the received signal. It is the transmitting antenna and the reflecting unit U. m,n The combined normalized power radiation mode of the receiving antenna at the receiving end, where λ is the carrier wavelength and f c For carrier frequency.

[0014] Optionally, in one embodiment of the present invention, the phase sign of the smart reflective surface is... Where N loc N com These represent the number of symbols in the sensing and positioning subframe and the communication subframe, respectively. These represent the reflection phase coefficient vectors at the k-th time.

[0015] Optionally, in one embodiment of the present invention, in the communication subframe, the phase coefficients of all reflective elements of the intelligent reflective surface are kept consistent, the communication subframe includes communication pilot symbols, and the receiving end is further used to perform local correlation on the received signal according to the preset pilot, realize the synchronization of the frame start point, and confirm the position of the sensing and positioning subframe by the synchronization point, and perform frequency offset estimation and phase correction according to the preset pilot.

[0016] Optionally, in one embodiment of the present invention, the reflection phase coefficient Γ of the reflecting unit is synchronously adjusted in the communication subframe. m,n (t) is:

[0017]

[0018] Among them, Γ k Let T be the k-th reflection phase coefficient. s R(t) represents the symbol duration, and R(t) represents the rectangular pulse shaping signal.

[0019] Optionally, in one embodiment of the present invention, the combination of all reflection unit phase coefficients at each moment in the positioning sensing subframe is the positioning sensing symbol codebook for the current moment. In the positioning sensing subframe, the reflection unit phase coefficient Γ of each reflection unit of the reflecting surface is set according to the preset codebook. m,n (t) is:

[0020]

[0021] Optionally, in one embodiment of the present invention, the sampling symbol of the positioning-aware subframe received by the receiving end is:

[0022]

[0023] Where w[k] is the Gaussian noise at the k-th sampling time, Γ k H is the diagonal matrix of the current localization-aware symbol codebook. BR and H RU These are the channel state information vectors of the base station-smart reflector and the smart reflector-receiver, characterized by the incident angle and the exit angle, respectively, and H BR The static channel vector is known.

[0024]

[0025]

[0026] in, θ t , θ r These are the azimuth and elevation angles from the smart reflector to the signal generator, and the azimuth and elevation angles from the smart reflector to the receiver, respectively.

[0027] Optionally, in one embodiment of the present invention, the relationship between the received signal vector of the receiving end and the channel state information vector of the unknown smart reflector-receiver, and the calculation method of the channel state information vector of the smart reflector-receiver, are as follows:

[0028]

[0029]

[0030] Among them, H combine It is H BR and all sampling times Γk Cascaded channel representation, W represents the Gaussian white noise of the receiver. It is a least-squares estimation of the smart reflector-receiver channel, and the receiver bases it on... Given the coordinates of the base station, the system uses the MUSIC algorithm based on feature space to calculate its own location.

[0031] Optionally, in one embodiment of the present invention, the intelligent reflector performs narrow beamforming and precoding in the communication subframe based on feedback information, and optimizes the reflection phase coefficient of the intelligent reflector in the positioning sensing subframe, including:

[0032] The receiving end will use its own location coordinates and the channel state information vector of the smart reflector-receiver. The information is reported to the base station via the uplink carrier channel, enabling the base station to use the channel state information vector of the smart reflector-receiver. The reflection phase coefficients of the smart reflector are pre-coded and narrow-beamformed. The pre-coded phase coefficients of the smart reflector's reflective elements are then represented as follows:

[0033]

[0034] Where Q{·} represents the quantization of the ideal precoded value by the reflective unit of the smart reflective surface;

[0035] Applying semidefinite programming to the autocorrelation matrix of the observation matrix To optimize the solution, a frequency optimization algorithm based on a complete set of observation matrices is used to decompose A. opt The optimized phase of the positioning and sensing subframe for the intelligent reflective surface is calculated as follows:

[0036]

[0037] A second aspect of the present invention provides a collaborative optimization method for a communication and positioning integrated system based on an intelligent reflector. Utilizing the communication and positioning integrated system based on an intelligent reflector described in the above embodiments, the collaborative optimization method includes the following steps:

[0038] A single-frequency carrier is transmitted via a signal generator;

[0039] According to the frame structure of the protocol, the intelligent reflector is subjected to reflection phase modulation and the reflected signal is sent to the air interface channel. When the frame structure is a communication subframe, the reflection phase coefficient of the reflection unit is adjusted synchronously. When the frame structure is a positioning and sensing subframe, the reflection phase coefficient of different reflection units is adjusted according to a preset codebook.

[0040] Frame synchronization and frequency offset correction are performed based on the communication subframes of the reflected signal and protocol. The cascaded channel state information of the integrated communication and positioning system is calculated based on the preset codebook of the positioning sensing subframe to obtain the positioning information of the receiving end. This information is then fed back to the intelligent reflector through the uplink, enabling the intelligent reflector to perform narrow beamforming and precoding in the communication subframe based on the feedback information. The reflection phase coefficient of the intelligent reflector is optimized in the positioning sensing subframe.

[0041] The communication and positioning integrated system and method based on intelligent reflectors of this invention, in the communication subframe, the transmitting end maps communication information onto the control signal of the intelligent reflector, utilizing the phase modulation capability of the intelligent reflector to modulate the phase of a single-frequency carrier wave, thus avoiding the high cost, high complexity, and high energy consumption of traditional mixer modulation. In the sensing and positioning subframe, the reflector reflects electromagnetic waves of different beam patterns according to a preset codebook. The receiving end achieves frame synchronization and frequency offset correction according to the communication subframe of the protocol, and calculates the cascaded channel state information of the base station-reflector-user based on the positioning codebook of the positioning subframe, thereby calculating the user's positioning information and feeding it back through the uplink. The reflector performs narrow beamforming and precoding on the user based on the feedback information, thereby improving the signal-to-noise ratio of communication and reducing the Cramer-Rao lower bound of positioning error, achieving synergistic enhancement of communication and sensing integration.

[0042] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0043] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0044] Figure 1 This is a schematic diagram of a communication and positioning integrated system structure based on an intelligent reflective surface according to an embodiment of the present invention;

[0045] Figure 2 This is a schematic diagram illustrating an application scenario of an integrated communication and sensing system based on an intelligent reflective surface, according to an embodiment of the present invention.

[0046] Figure 3 A schematic diagram of the cascaded channel and geometric position under two-dimensional far-field conditions for a communication and sensing integrated system based on an intelligent reflective surface provided in an embodiment of the present invention;

[0047] Figure 4 This is a flowchart of a base station-user information exchange process provided according to an embodiment of the present invention;

[0048] Figure 5A schematic diagram of the phase setting frame structure of the base station-side intelligent reflector provided in an embodiment of the present invention;

[0049] Figure 6 This is a comparison of estimation errors before and after single RIS phase optimization according to an embodiment of the present invention;

[0050] Figure 7 The following are SNR curves of the achievable communication rate of the system after beamforming according to different schemes provided in the embodiments of the present invention;

[0051] Figure 8 A flowchart illustrating a collaborative optimization method for a communication and positioning integrated system based on an intelligent reflective surface, according to an embodiment of the present invention. Detailed Implementation

[0052] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0053] The following description, with reference to the accompanying drawings, describes an integrated communication and positioning system and method based on an intelligent reflective surface, according to embodiments of the present invention. Addressing the problems mentioned in the background section regarding the low accuracy, high power consumption and cost, high hardware and algorithm complexity, and low functional reusability of communication and positioning in hardware architecture and algorithm systems of current indoor positioning systems, the present invention provides an integrated communication and positioning system based on an intelligent reflective surface. This system utilizes the phase modulation capability of the intelligent reflective surface for spatial electromagnetic waves to achieve high-precision channel estimation and user-aware positioning. Furthermore, it optimizes the reflection coefficient of the intelligent reflective surface to improve channel communication quality and reduces the Cramer-Rao lower bound of positioning errors, achieving synergistic enhancement through integrated sensing.

[0054] Specifically, Figure 1 This is a schematic diagram of a communication and positioning integrated system structure based on an intelligent reflective surface according to an embodiment of the present invention.

[0055] like Figure 1 As shown, the communication protocol of the integrated communication and positioning system is divided into communication subframes and positioning sensing subframes according to time. The integrated communication and positioning system based on intelligent reflective surfaces includes: a signal generator 100 on the base station side and a system comprising M×N reflective units U. m,n The intelligent reflective surface 200 and the receiver on the user side 300.

[0056] Signal generator 100 is used to transmit a single-frequency carrier.

[0057] Includes M×N reflective units U m,nThe intelligent reflector 200 is used to perform time-division reflection phase modulation according to the frame structure of the protocol and reflect the signal to the air interface channel. When the frame structure is a communication subframe, the reflection phase coefficient of the reflection unit is adjusted synchronously. When the frame structure is a positioning sensing subframe, the reflection phase coefficient of different reflection units is adjusted according to a preset codebook.

[0058] The receiver 300 is used to perform frame synchronization and frequency offset correction based on the reflected signal and the communication subframe of the protocol. It calculates the cascaded channel state information of the integrated communication and positioning system based on the preset codebook of the positioning sensing subframe, obtains the positioning information of the receiver, and feeds it back to the intelligent reflector through the uplink. The intelligent reflector then performs narrow beamforming and precoding in the communication subframe based on the feedback information and optimizes the reflection phase coefficient of the intelligent reflector in the positioning sensing subframe.

[0059] In embodiments of the present invention, a smart reflector design is used to achieve user terminal sensing and positioning, as well as enhance downlink communication quality. The system's communication protocol is divided into communication subframes (Fcom) and positioning sensing subframes (Floc) based on time. In the communication subframe, the smart reflector synchronously modifies the reflection phase Γ of all reflector elements. mn (t) is used to achieve signal modulation. In the positioning and sensing subframe, the intelligent reflective surface modulates the reflection phase Γ of different reflective units according to a preset codebook. mn (t) is controlled to reflect electromagnetic waves of different beam patterns, which are then received and processed by the receiver. The receiver performs frame synchronization and frequency offset correction according to the communication subframe Fcom of the protocol. Based on the positioning codebook of the positioning subframe Floc, it calculates the cascaded channel state information of the base station-reflector-user (BS-RIS-UE), thereby calculating the user's positioning information and feeding it back via the uplink. The reflector performs narrow beamforming and precoding on the user based on the feedback information, thereby improving the signal-to-noise ratio of communication and reducing the Cramer-Rao lower bound of the positioning error, achieving integrated sensing and communication enhancement.

[0060] In this integrated sensing system, the base station transmits a single-frequency signal, and the intelligent reflector performs time-division phase modulation of the reflected signal according to the frame structure, sending the reflected signal to the air interface channel. The receiver performs positioning sensing calculations and communication demodulation based on the reflected signal and the frame structure.

[0061] The channel model of the integrated sensing and communication system is as follows: the base station transmitter consists of a signal generator and a smart reflector, and the smart reflector has M×N reflecting units U. m,n Its reflection coefficient signal is Γ m,n (t), where both the base station transmitter (BS) and the user receiver (UE) have a single antenna. The base station BS is used as the origin p. BS =[0,0,0] T The coordinates of RIS and UE are p RIS =[xRIS ,y RIS ,z RIS ] T p UE =[x UE ,y UE ,z UE ] T The transmitting antenna transmits a single-frequency carrier wave. Distance to Reflective surface unit U m,n Reflected by RIS to the air interface channel, and then by a distance U m,n Distance is The user-end antenna receives the signal. The entire channel is a cascaded channel of BS-RIS-UE, specifically determined by the following formula:

[0062]

[0063] Among them, the transmit antenna energy, transmitter gain, receiver gain, and RIS gain are respectively P t G t G r G. From U m,n From the transmitter's azimuth and elevation angles, from U m,n The azimuth and elevation angles to the receiver. x d y , λ, f c These are the horizontal and vertical dimensions, carrier wavelength, and carrier frequency of the RIS unit, respectively. It is a transmitting antenna, U m,n The combined normalized power radiation mode of the receiving antenna is as follows:

[0064]

[0065] In the far-field scenario of this system, the equivalent baseband signal at the receiver is determined by the following formula:

[0066]

[0067] Where r t r r These are the distances from the transmitter and receiver to the center point of the RIS, respectively. U m,n Compared to the distance deviation from the center point to the transmitter and receiver, that is:

[0068]

[0069]

[0070] θ t , θ r Let be the azimuth and elevation angles from the RIS to the transmitter and receiver, respectively. Let E represent the energy of the received signal. This can be simply expressed as:

[0071]

[0072] The integrated sensing frame structure is time-division based, divided into a communication subframe (Fcom) and a positioning and sensing subframe (Floc) based on time. Specifically, the phase symbol of the intelligent reflector is designed as follows: Where N loc N com These represent the number of symbols in the sensing and positioning subframe and the communication subframe, respectively. These represent the reflection phase coefficient vectors at the k-th time.

[0073] In the communication subframe Fcom, all reflective elements on the reflector maintain a consistent change at every moment to achieve phase modulation and broadcast transmission of the single-frequency carrier. The receiver performs time-domain timing synchronization, frequency offset calculation, and correction based on the communication subframe.

[0074] In the communication subframe Fcom, all elements of the reflector maintain a consistent phase change to achieve phase modulation of the carrier and broadcast reflection into the air interface channel. The communication subframe Fcom contains communication pilot symbols. The receiver performs local correlation on the received signal based on the preset pilot to synchronize with the frame start point. The synchronization point confirms the position of the sensing and positioning subframe Floc, and frequency offset estimation and phase correction are performed based on the pilot. Specifically, the reflection coefficient Γ of the reflector in the communication subframe Fcom... m,n The setting of (t) is determined by the following formula:

[0075]

[0076] Where Γ k Let T be the k-th reflection phase coefficient. s Let R(t) be the symbol duration, and R(t) be the rectangular pulse shaping signal, specifically including...

[0077] In the positioning and sensing subframe Floc, different reflecting elements on the reflector are set to different reflection phases at each moment to transmit electromagnetic waves with different beam patterns according to a preset codebook. The receiving user determines the Floc position based on the frame timing synchronization result, calculates the channel state information based on Floc and the codebook, and infers the positioning and sensing result.

[0078] In the location-aware subframe Floc, the reflector elements are configured with reflection coefficients according to a preset codebook, and the coefficients differ between elements to transmit electromagnetic waves in different beam patterns. Specifically, the reflection coefficient Γ of the reflector in the location-aware subframe Floc is... m,n The setting of (t) is determined by the following formula:

[0079]

[0080] All reflection units at each time step in Floc The combination of these elements constitutes the current location-aware symbol codebook.

[0081] The sampling symbols of the Floc subframe received by the user receiver are determined by the following formula:

[0082]

[0083] Where w[k] is the Gaussian noise at the k-th sampling time, Γ k It is the diagonal matrix of the current codebook, that is:

[0084]

[0085] Where H BR H RU These are the BS-RIS and RIS-UE channel state information vectors characterized by the incident angle and the exit angle, respectively, and H BR Given the static channel vector, under the far-field assumption of this system, H BR and H RU Both can be represented as containing parameters and θ t , and θ r The form of the Kronecker product, θ t , θ r These represent the azimuth and elevation angles from the RIS to the transmitter, and the azimuth and elevation angles from the RIS to the receiver. Specifically, H... BR H RU Determined by the following formula:

[0086]

[0087]

[0088] The user receiver's time signal is represented using a vector: Then the received signal vector and the unknown channel H RU Relationship and H RU The calculation is determined by the following formula:

[0089]

[0090]

[0091] Among them, H combine It is H BR and all sampling times Γ k The cascaded channel representation, that is, has W is the Gaussian white noise of the receiver. This is a least-squares estimate of the RIS-UE channel. The user terminal, based on... Given the coordinates of the base station, the system uses the MUSIC algorithm based on feature space to calculate its own location.

[0092] Users use uplink carrier frequencies to feed back channel state information. Based on the feedback results, the base station performs narrow beamforming and precoding on the user's communication in Fcom to improve the signal-to-noise ratio and channel capacity. In Floc, the positioning codebook is optimized and designed, and high-precision positioning is achieved through subsequent feedback iterations.

[0093] The user terminal will calculate its own coordinates and channel status information. The information is reported to the base station via the uplink carrier channel. The base station then... The reflection phase of the RIS is pre-coded and narrow-beamformed. Specifically, the sign of the reflection coefficient of the RIS cell after precoding is determined by the following formula:

[0094]

[0095] The RIS reflection unit, limited by hardware conditions, can only achieve partially discrete reflection phases. Q{·} represents the quantization of the ideal precoded value by the RIS reflection unit. Beamforming is applied to both Fcom and Floc to improve the signal-to-noise ratio and channel capacity. Beamforming is applied to Fcom to improve the signal-to-noise ratio and channel capacity, while the RIS phase coefficients in Floc are optimized to reduce positioning error. High-precision positioning is achieved through subsequent feedback iterations.

[0096] In the localization-aware subframe Floc, high-precision localization is achieved through subsequent feedback iterations. Since the location is already known... To improve positioning accuracy and enable real-time tracking of user (UE) position changes, the lower bound of the estimation error in the Floc codebook is optimized using the estimation error as the target. The design has been optimized.

[0097] Consider a RIS communication system model: β represents the signal amplitude and path loss. Since the actual environment is quite complex, β cannot be accurately calculated from the path loss, so it is set as an unknown to be measured. The unknown phase introduced by carrier recovery at the receiving end; H combine It is H BR and all sampling times Γ k The known concatenated channels can be accessed via codebook Γ. k Dynamic adjustment can be considered as H RU The observation matrix is ​​simplified below by A; H RU It is an unknown RIS-UE channel, which can be accessed via This means, that is:

[0098]

[0099] H RU The simplified representation below is denoted by h. All unknown parameter vectors are... The Fisher information matrix for estimating Θ is:

[0100]

[0101] Specifically, it is determined using the following formula:

[0102]

[0103] Where W = A H A is the autocorrelation matrix of the observation matrix A. The lower bound of the positioning error can be expressed as:

[0104]

[0105] Then we have:

[0106]

[0107] In the initial estimate After that, it is known. Then, the location codebook Γ k Optimization is performed, and then the observation matrix A is adjusted to reduce the impact on The Cramé-Rao bound is estimated in subsequent iterations. From the above derivation, the optimization variable is... Due to hardware limitations, the RIS unit symbol in the positioning subframe is a QPSK symbol, therefore |W ij |≤N loc If 0 ≤ i, j ≤ MN-1, then the optimization problem can be expressed as:

[0108]

[0109] st|Wij |≤N loc

[0110] This problem is similar to a semi-definite programming (SDP) problem and can be solved by optimization using the CVX toolbox.

[0111] Furthermore, after obtaining the optimized autocorrelation matrix W opt =A H After A, W needs to be... opt The observation matrix A is decomposed and solved. Due to the constant modulus and discrete phase characteristics of the QPSK symbols in A, a frequency optimization algorithm based on the complete set of observation matrices is used to solve A.

[0112] W opt It is N loc A at any given moment t =The sum of the autocorrelation matrices of A(t,:), that is, Consider all possible phases of observation matrix A Each observation vector A i =A all (i,:) all correspond to an autocorrelation matrix Then W opt The complete set R can be used all Each element in the array and its corresponding frequency p i Let's represent this. Then there's an optimization problem:

[0113]

[0114] st0≤p(i)≤N loc

[0115] The frequency vector p is obtained by solving using the CVX toolbox. p is then sorted, and the largest frequency vector is selected whose sum does not exceed N. loc The optimized observation matrix A can be obtained by indexing the frequency of observations. opt In the known BS-RIS static channel H BR In this case, the optimized phase of the positioning subframe RIS can be further calculated:

[0116]

[0117] The following describes the integrated communication and positioning system based on an intelligent reflective surface according to the present invention through a specific embodiment.

[0118] (I) Design of an integrated communication and positioning system based on intelligent reflective surfaces

[0119] Design and application scenarios of integrated communication and positioning system based on intelligent reflective surface, such as Figure 2As shown. The system includes a base station (BS), a smart reflector (RIS), and a user terminal (UE). The line-of-sight link between the UE and the BS is blocked by an obstacle. The AP transmits a single-tone signal, which is reflected and modulated by the RIS and fed back to the air interface channel, where it is received by the UE. The overall channel is a cascaded channel consisting of AP-RIS-UE. The phase control signal of each reflection unit of the RIS can be changed as a whole to achieve communication modulation, or it can be set to different reflection phases to transmit electromagnetic waves with different beam patterns for positioning and sensing. The two reflection phase setting signals are distributed in a time-division manner, forming the frame structure for the phase signal setting at the RIS end.

[0120] With base station BS as the origin p BS =[0,0,0] T The coordinates of RIS and UE are p RIS =[x RIS ,y RIS ,z RIS ] T p UE =[x UE ,y UE ,z UE ] T The intelligent reflective surface has M×N reflective units U m,n Its reflection coefficient signal is Γ m,n (t), both the base station transmitter (BS) and the user receiver (UE) have a single antenna. In this embodiment, both the BS-RIS and RIS-UE channels consider the far field. From U m,n From the transmitter's azimuth and elevation angles, from U m,n The azimuth and elevation angles to the receiver. The transmitting antenna transmits a single-frequency carrier wave. Distance to Reflective surface unit U m,n Reflected by RIS to the air interface channel, and then by a distance U m,n Distance is User-end antenna reception. For example... Figure 3 As shown, the entire channel is a cascaded channel of BS-RIS-UE, specifically determined by the following formula:

[0121]

[0122] The transmit antenna energy, transmitter gain, receiver gain, and RIS gain are respectively P t G t G r G. d x d y λ and λ represent the horizontal and vertical dimensions of the RIS cell, and the carrier wavelength, respectively. It is a transmitting antenna, Um,n The combined normalized power radiation mode of the receiving antenna is as follows:

[0123]

[0124] In the far-field scenario of this system, the equivalent baseband signal at the receiver is determined by the following formula:

[0125]

[0126] Where r t r r These are the distances from the transmitter and receiver to the center point of the RIS, respectively. U m,n Compared to the distance deviation from the center point to the transmitter and receiver, that is:

[0127]

[0128]

[0129] θ t , θ r Let be the azimuth and elevation angles from the RIS to the transmitter and receiver, respectively. Let E represent the energy of the received signal. This can be simply expressed as:

[0130]

[0131] like Figure 4 As shown, the integrated sensing frame structure is time-division based, divided into a communication subframe Fcom and a positioning sensing subframe Floc. Specifically, the phase symbol design of the intelligent reflector is as follows:

[0132]

[0133] Where N loc N com These represent the number of symbols in the sensing and positioning subframe and the communication subframe, respectively. These represent the reflection phase coefficient vectors at the k-th time.

[0134] (II) Communication modulation schemes and receiving algorithms applicable to intelligent reflective surface scenarios

[0135] like Figure 5 As shown, in the communication subframe Fcom, all elements of the reflector maintain a consistent phase change to achieve phase modulation of the carrier and broadcast reflection into the air interface channel. Specifically, the reflection coefficient Γ of the reflector in the communication subframe Fcom... m,nThe setting of (t) is determined by the following formula:

[0136]

[0137] Where Γ k Let T be the k-th reflection phase coefficient. s Where R is the symbol duration, and R(t) is the rectangular pulse shaping signal, specifically:

[0138] The communication subframe Fcom contains communication pilot symbols, consisting of two segments of length N. PN A random sequence (Pseudo-Noise, PN) with a value of 15 is used. Specifically, the reflection coefficient corresponding to the PN sequence is set as follows:

[0139]

[0140] The receiver performs a sliding window cross-correlation on the down-converted sampling symbols sym of the received signal according to a preset pilot signal to achieve synchronization of the frame start point. The position of the sensing and positioning subframe Floc is confirmed by the Fcom synchronization point, and frequency offset estimation and phase correction are performed based on the pilot signal. Specifically, the synchronization of the Fcom and Floc start point positions is determined by the following formula:

[0141]

[0142] ind loc =ind com -N loc

[0143] Under normal hardware conditions, a certain frequency deviation exists between the carrier waves of the receiver and transmitter, which can cause phase rotation in the received symbols, degrading communication and positioning performance. This scheme corrects the frequency deviation based on the PN sequences at both ends of the pilot signal. Specifically, the frequency deviation calculation and phase correction are determined by the following formula:

[0144]

[0145] sym_adj[n] = sym[n]·e j2πΔf·(n-1)

[0146] (III) Channel estimation and user-aware positioning algorithm based on intelligent reflector multi-beam transmission

[0147] like Figure 5 As shown, in the positioning-aware subframe Floc, the reflector elements are configured with reflection coefficients according to a preset codebook, and the coefficients differ between elements to transmit electromagnetic waves in different beam patterns. Specifically, the reflection coefficient Γ of the reflector in the positioning-aware subframe Floc... m,n The setting of (t) is determined by the following formula:

[0148]

[0149] All reflection units at each time step in Floc The combination of these elements constitutes the current location-aware symbol codebook.

[0150] Furthermore, the sampling symbols of the Floc subframe received by the user receiver are specifically determined by the following formula:

[0151]

[0152] Where w[k] is the Gaussian noise at the k-th sampling time, Γ k It is the diagonal matrix of the current codebook, that is:

[0153]

[0154] Where H BR H RU These are the BS-RIS and RIS-UE channel state information vectors characterized by the incident angle and the exit angle, respectively, and H BR Given the static channel vector, under the far-field assumption of this system, H BR and H RU Both can be represented as containing parameters and θ t , and θ r The form of the Kronecker product, θ t , θ r These represent the azimuth and elevation angles from the RIS to the transmitter, and the azimuth and elevation angles from the RIS to the receiver. Specifically, H... BR H RU Determined by the following formula:

[0155]

[0156]

[0157] The user's receiving time signal is represented in vector form: Then the received signal vector and the unknown channel H RU Relationship and H RU The calculation is determined by the following formula:

[0158]

[0159]

[0160] Where H combineIt is H BR and all sampling times Γ k The cascaded channel representation, that is, has W is the Gaussian white noise of the receiver. This is a least-squares estimate of the RIS-UE channel. The user terminal, based on... Given the base station coordinates, the self-positioning orientation is calculated using the feature space-based MUSIC algorithm. Specifically, firstly, based on the RIS-UE channel estimation vector... Calculate the autocorrelation matrix:

[0161] Eigenvalue decomposition is performed on the autocorrelation matrix R to calculate the eigenvalues ​​and eigenvectors of R. The larger K eigenvalues ​​and the smaller MK eigenvalues ​​correspond to the signal subspace and noise subspace, respectively.

[0162]

[0163] R = U S Σ S U S H +U N Σ N U N H

[0164] Make two-dimensional parameters Change, according to To calculate the spectral function, where Peak corresponding That is The estimated value.

[0165] (iv) Iterative optimization scheme for RIS coefficients based on Cramer-Rao bound and signal-to-noise ratio:

[0166] The user terminal will calculate its own coordinates and channel status information. The data is reported to the base station via the uplink carrier frequency channel. In the communication frame Fcom, the base station, based on... The reflection phase of the RIS is pre-coded and narrow-beamformed to maximize the communication signal-to-noise ratio and achievable data rate. Specifically, the sign of the reflection coefficient of the pre-coded RIS cell is determined by the following formula:

[0167]

[0168] The RIS reflection unit is limited by hardware conditions and can only realize a partially discrete reflection phase. Q{·} represents the quantization of the ideal precoded value by the RIS reflection unit.

[0169] In the localization-aware subframe Floc, since it is already known... To improve positioning accuracy and enable real-time tracking of user (UE) position changes, the lower bound of the estimation error in the Floc codebook is optimized using the estimation error as the target. The design has been optimized.

[0170] Consider a RIS communication system model: β represents the signal amplitude and path loss. Since the actual environment is quite complex, β cannot be accurately calculated from the path loss, so it is set as an unknown to be measured. The unknown phase introduced by carrier recovery at the receiving end; H combine It is H BR and all sampling times Γ k The known concatenated channels can be accessed via codebook Γ. k Dynamic adjustment can be considered as H RU The observation matrix is ​​simplified below by A; H RU It is an unknown RIS-UE channel, which can be accessed via This means, that is:

[0171]

[0172] H RU The simplified representation below is denoted by h. All unknown parameter vectors are... The Fisher information matrix for estimating Θ is:

[0173]

[0174] Specifically, it is determined using the following formula:

[0175]

[0176] Where W = A H A is the autocorrelation matrix of the observation matrix A. The lower bound of the positioning error can be expressed as:

[0177]

[0178] Then we have:

[0179]

[0180] In the initial estimate After that, it is known. Then, the location codebook Γ k Optimization is performed, and then the observation matrix A is adjusted to reduce the impact on The Cramé-Rao bound is estimated in subsequent iterations. From the above derivation, the optimization variable is... Due to hardware limitations, the RIS unit symbol in the positioning subframe is a QPSK symbol, therefore |W ij |≤N loc If 0 ≤ i, j ≤ MN-1, then the optimization problem can be expressed as:

[0181]

[0182] st|W ij |≤N loc

[0183] This problem is similar to a semi-definite programming (SDP) problem and can be solved by optimization using the CVX toolbox.

[0184] The optimized autocorrelation matrix W is obtained. opt =A H After A, W needs to be... opt The observation matrix A is decomposed and solved. Due to the constant modulus and discrete phase characteristics of the QPSK symbols in A, a frequency optimization algorithm based on the complete set of observation matrices is used to solve A.

[0185] W opt It is N loc A at any given moment t =The sum of the autocorrelation matrices of A(t,:), that is, Consider all possible phases of observation matrix A Each observation vector A i =A all (i,:) all correspond to an autocorrelation matrix Then W opt The complete set R can be used all Each element in the array and its corresponding frequency p i Let's represent this. Then there's an optimization problem:

[0186]

[0187] st0≤p(i)≤N loc

[0188] The frequency vector p is obtained by solving using the CVX toolbox. p is then sorted, and the largest frequency vector is selected whose sum does not exceed N. loc The optimized observation matrix A can be obtained by indexing the frequency of observations. opt In the known BS-RIS static channel H BR In this case, the RIS optimized phase of the positioning subframe can be further calculated.

[0189]

[0190] Based on the optimization of the phase coefficient of the RIS reflector, high-precision positioning is achieved through subsequent feedback iterations, thereby realizing the synergistic enhancement of communication and sensing positioning.

[0191] Depend on Figure 6 and Figure 7 As can be seen, the communication and positioning integrated system based on the intelligent reflector in this embodiment of the invention utilizes the phase modulation capability of the intelligent reflector for spatial electromagnetic waves to achieve high-precision channel estimation and user-perceived positioning, optimizes the reflection coefficient of the intelligent reflector to improve channel communication quality, and reduces the lower bound of the positioning error, thereby achieving synergistic enhancement of integrated sensing.

[0192] This invention discloses a communication and positioning integrated system based on an intelligent reflector. In the communication subframe, the intelligent reflector utilizes its phase modulation capability for spatial electromagnetic waves to modulate the phase of a single-frequency carrier, avoiding the high cost, complexity, and energy consumption of traditional mixer modulation. In the sensing and positioning subframe, the reflector reflects electromagnetic waves of different beam patterns according to a preset codebook. The receiver performs high-precision estimation of the cascaded channel state information of the base station-reflector-user based on the positioning codebook of the positioning subframe, thereby calculating the user's positioning information. The reflector performs narrow beamforming and positioning codebook optimization design for the user based on the channel state information, thereby improving the signal-to-noise ratio of communication and reducing the Cramer-Rao lower bound of positioning errors, achieving synergistic enhancement of communication and sensing. This method, based on the same intelligent reflector hardware architecture and system algorithm, enhances the signal-to-noise ratio of the communication link using accurate channel estimation and positioning results, and iteratively enhances the performance of positioning and sensing, effectively realizing the integration of communication and sensing.

[0193] Next, referring to the accompanying drawings, a collaborative optimization method for an integrated communication and positioning system based on an intelligent reflective surface, according to an embodiment of the present invention, is described.

[0194] Figure 8 A flowchart illustrating a collaborative optimization method for a communication and positioning integrated system based on an intelligent reflective surface, according to an embodiment of the present invention.

[0195] like Figure 8 As shown, the collaborative optimization method for the integrated communication and positioning system based on an intelligent reflector utilizes the integrated communication and positioning system based on an intelligent reflector as described in the above embodiment. The method includes the following steps:

[0196] In step S101, a single-frequency carrier is transmitted via a signal generator.

[0197] In step S102, the intelligent reflector is subjected to reflection phase modulation according to the frame structure of the protocol, and the reflected signal is sent to the air interface channel. When the frame structure is a communication subframe, the reflection phase coefficient of the reflection unit is adjusted synchronously. When the frame structure is a positioning sensing subframe, the reflection phase coefficient of different reflection units is adjusted according to the preset codebook.

[0198] In step S103, frame synchronization and frequency offset correction are performed based on the communication subframes of the reflected signal and the protocol. The cascaded channel state information of the integrated communication and positioning system is calculated based on the preset codebook of the positioning sensing subframe to obtain the positioning information of the receiver. This information is then fed back to the intelligent reflector via the uplink, enabling the intelligent reflector to perform narrow beamforming and precoding in the communication subframe based on the feedback information. The reflection phase coefficient of the intelligent reflector is optimized in the positioning sensing subframe.

[0199] It should be noted that the foregoing explanation of the embodiment of the integrated communication and positioning system based on intelligent reflective surfaces also applies to the integrated communication and positioning method based on intelligent reflective surfaces in this embodiment, and will not be repeated here.

[0200] The communication-positioning integration method based on intelligent reflectors proposed in this invention utilizes the phase modulation capability of intelligent reflectors to modulate the phase of a single-frequency carrier wave in the communication subframe, avoiding the high cost, complexity, and energy consumption of traditional mixer modulation. In the sensing and positioning subframe, the reflector reflects electromagnetic waves of different beam patterns according to a preset codebook. The receiver performs high-precision estimation of the cascaded channel state information of the base station-reflector-user based on the positioning codebook of the positioning subframe, thereby calculating the user's positioning information. The reflector performs narrow beamforming and positioning codebook optimization design for the user based on the channel state information, thereby improving the signal-to-noise ratio of communication and reducing the Cramer-Rao lower bound of positioning error, achieving synergistic enhancement of communication and sensing integration. This method is based on the same intelligent reflector hardware architecture and system algorithm, using accurate channel estimation and positioning results to enhance the signal-to-noise ratio of the communication link, and can iteratively enhance the performance of positioning and sensing, effectively realizing communication and sensing integration.

[0201] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0202] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0203] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

Claims

1. A communication and positioning integrated system based on an intelligent reflective surface, characterized in that, The communication protocol of the integrated communication and positioning system is divided into communication subframes and positioning sensing subframes according to time. The integrated communication and positioning system includes: A signal generator used to transmit a single-frequency carrier wave; include One reflective unit The intelligent reflective surface is used to perform time-division reflection phase modulation according to the frame structure of the protocol and reflect the signal to the air interface channel. When the frame structure is a communication subframe, the reflection phase coefficient of the reflection unit is adjusted synchronously. When the frame structure is a positioning sensing subframe, the reflection phase coefficient of different reflection units is adjusted according to a preset codebook. The receiving end is used to perform frame synchronization and frequency offset correction based on the reflected signal and the communication subframe of the protocol. It calculates the cascaded channel state information of the integrated communication and positioning system based on the preset codebook of the positioning sensing subframe, obtains the positioning information of the receiving end, and feeds it back to the intelligent reflector through the uplink. This enables the intelligent reflector to perform narrow beamforming and precoding in the communication subframe based on the feedback information, and optimizes the reflection phase coefficient of the intelligent reflector in the positioning sensing subframe. The reflection phase coefficient of the intelligent reflective surface is The transmitting antenna of the signal generator transmits a single-frequency carrier wave. Distance to Reflecting unit The light is reflected by the intelligent reflective surface to the air interface channel and is then reflected by the distance reflection unit. Distance is The receiving antenna at the receiving end receives the cascaded channel status information of the integrated communication and positioning system as follows: Where E represents the energy of the received signal. It is a transmitting antenna and a reflecting unit. The combined normalized power radiation mode of the receiving antenna at the receiving end. For carrier wavelength, For carrier frequency; The phase symbol of the intelligent reflective surface is in , These represent the number of symbols in the sensing and positioning subframe and the communication subframe, respectively. , These represent the reflection phase coefficient vectors at the k-th time. ; In the communication subframe, the phase coefficients of all reflective elements of the smart reflector remain consistent. The communication subframe contains communication pilot symbols. The receiving end is further used to perform local correlation on the received signal according to the preset pilot, realize the synchronization of the frame start point, and confirm the position of the sensing and positioning subframe by the synchronization point, and perform frequency offset estimation and phase correction according to the preset pilot. In the communication subframe, the reflection phase coefficient of the reflecting unit is adjusted synchronously. for: in, For the k-th reflection phase coefficient, For the duration of the symbol, It is a rectangular pulse shaping signal. ; The combination of all the phase coefficients of the reflective elements at each moment in the positioning sensing subframe constitutes the positioning sensing symbol codebook for that moment. In the positioning sensing subframe, the phase coefficients of each reflective element of the reflective surface are set according to a preset codebook. for: 。 2. The system according to claim 1, characterized in that, The sampling symbols of the positioning sensing subframe received by the receiving end are: in, The noise at the k-th sampling time is Gaussian noise. This is the diagonal matrix of the current location-aware symbol codebook. and These are the channel state information vectors of the base station-smart reflector and the smart reflector-receiver, characterized by the incident angle and the exit angle, respectively. The static channel vector is known. in, , , , These are the azimuth and elevation angles from the smart reflector to the signal generator, and the azimuth and elevation angles from the smart reflector to the receiver, respectively.

3. The system according to claim 2, characterized in that, The relationship between the received signal vector of the receiving end and the unknown channel state information vector of the smart reflector-receiver, and the calculation method of the channel state information vector of the smart reflector-receiver, are as follows: in, yes and all sampling times Cascaded channel representation, , The receiver's white Gaussian noise, It is a least-squares estimation of the smart reflector-receiver channel, and the receiver bases it on... Given the coordinates of the base station, the system uses the MUSIC algorithm based on feature space to calculate its own location.

4. The system according to claim 3, characterized in that, The intelligent reflector performs narrow beamforming and precoding in the communication subframe based on feedback information, and optimizes the reflection phase coefficient of the intelligent reflector in the positioning and sensing subframe, including: The receiving end will use its own location coordinates and the channel state information vector of the smart reflector-receiver. The information is reported to the base station via the uplink carrier channel, enabling the base station to use the channel state information vector of the smart reflector-receiver. The reflection phase coefficients of the smart reflector are pre-coded and narrow-beamformed. The pre-coded phase coefficients of the smart reflector's reflective elements are then represented as follows: in, This represents the quantization of the ideal precoded value by the reflective unit of the smart reflective surface; Applying semidefinite programming to the autocorrelation matrix of the observation matrix To optimize the solution, a frequency optimization algorithm based on a complete set of observation matrices is used to decompose the results. The optimized phase of the positioning sensing subframe for the intelligent reflective surface is calculated as follows: 。 5. A collaborative optimization method for a communication and positioning integrated system based on an intelligent reflective surface, utilizing the communication and positioning integrated system based on an intelligent reflective surface as described in any one of claims 1-4, characterized in that, The collaborative optimization method includes the following steps: A single-frequency carrier is transmitted via a signal generator; According to the frame structure of the protocol, the intelligent reflector is subjected to reflection phase modulation and the reflected signal is sent to the air interface channel. When the frame structure is a communication subframe, the reflection phase coefficient of the reflection unit is adjusted synchronously. When the frame structure is a positioning and sensing subframe, the reflection phase coefficient of different reflection units is adjusted according to a preset codebook. Frame synchronization and frequency offset correction are performed based on the communication subframes of the reflected signal and protocol. The cascaded channel state information of the integrated communication and positioning system is calculated based on the preset codebook of the positioning sensing subframe to obtain the positioning information of the receiving end. This information is then fed back to the intelligent reflector through the uplink, enabling the intelligent reflector to perform narrow beamforming and precoding in the communication subframe based on the feedback information. The reflection phase coefficient of the intelligent reflector is optimized in the positioning sensing subframe.

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