Movable intelligent reflecting surface assisted communication and sensing integrated device

Abstract

The invention provides a movable intelligent reflecting surface assisted communication and induction integrated device. The device mainly comprises two types of radio frequency receiving and transmitting devices (RFT1 and RFT2), a movable intelligent reflecting surface (MIRS) device and a central control device (CCE). The method mainly comprises the following steps of: configuring M'perception, configuration and confirmation three-time-slot groups' in an RFT1 receiving frame structure, configuring M ACK (acknowledgement character) time slots in an RFT1 sending frame structure, and configuring M'perception and double-blank three-time-slot groups' in an RFT2 sending frame structure; the RFT1 frame structure configuration and the RFT2 frame structure configuration are executed by CEE equipment and comprise the number of the two three-time-slot groups and the positions of the two three-time-slot groups in the frame structures; the method comprises the following steps: designing an MIRS auxiliary sensing and communication process, estimating the position of RFT2 by CEE equipment in a sensing time slot before a data sending time slot, calculating the optimal MIRS position and phase configuration according to the position and the phase configuration, and performing corresponding operation.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication and perception technology, and in particular to dynamic deployment and perception application of movable intelligent reflecting surfaces (MIRS) in wireless communication networks, including IRS-assisted perception protocols, devices and methods. Background Art

[0002] As urbanization grows, next-generation wireless communication systems face unprecedented transmission obstacles, especially within the maze-like corridors of modern buildings. Signals traversing these building interiors are distorted by the waveguide properties of narrow passages and compounded by multipath effects, resulting in reduced data rates. The emerging field of smart building design incorporates wireless communication and sensing functional considerations into the early stages of building planning, proposing the use of materials and structures that are more conducive to signal propagation. However, the dynamic and unpredictable nature of the propagation environment continues to require more agile and intelligent wireless communication solutions.

[0003] In the emerging field of electromagnetic manipulation, intelligent reflecting surfaces (IRS) are a revolutionary innovation that will redefine the framework of indoor communications. IRS works by dynamically redirecting and reshaping incident electromagnetic waves through phase control of a large number of tiny, strategically arranged sub-wavelength units. Despite the revolutionary potential of IRS, there are still many challenges in integrating it into real-world environments. To date, most IRS systems rely mainly on manual phase control. Although existing technologies also provide a certain degree of adaptive adjustment, such as beam tracking based on computer vision, these functions are mainly based on a large amount of prior experience training without optimizing the IRS position. This approach poses significant challenges because any changes in the deployment environment or fluctuations in conditions will make the previous training results obsolete, requiring the IRS beam and position to be retrained.

[0004] In addition, some studies have proposed dynamic optimization of IRS position, which can achieve optimal throughput by dynamically optimizing IRS position during user mobility, providing a new direction for indoor communication. However, this work is still in its infancy, and most of it is still in the theoretical research stage. There is no report on a prototype experimental system that achieves dynamic optimal communication through joint optimization of IRS position and codebook under user mobility. Summary of the invention

[0005] This paper uses movable intelligent reflecting surfaces (MIRS) to provide additional target perception capabilities for the communication system, and further improves the communication performance based on the perception results. First, we built a MIRS-assisted integrated sensing and communication system and device; secondly, we designed a MIRS-assisted integrated sensing and communication frame structure configuration based on frequency division duplex (FDD); then, we designed a MIRS-assisted sensing and communication method based on OFDM.

[0006] The synaesthesia integrated device assisted by a movable intelligent reflective surface proposed by the present invention is as shown in the attached Figure 1 As shown, it mainly includes steps 200 to 240.

[0007] Step 200, the constructed MIRS-assisted sensory integrated device includes two types of radio frequency transceiver (RFT), a MIRS device and a central control equipment (CCE), as shown in the attached Figure 2 shown.

[0008] The first type of RFT device (RFT1) realizes the transmission of communication signals and the reception of perception signals, and the second type of RFT device (RFT2) realizes the reception of communication signals and the transmission of perception signals; the MIRS device is composed of an IRS and a movable platform, which realizes the reflection phase adjustment of perception signals and communication signals, and provides the IRS with the ability to move positions; the CCE device is connected to the RFT1 and MIRS devices, and obtains the optimal phase configuration and position of the IRS by processing the received signal of RFT1, thereby realizing the adjustment of the phase and position of the MIRS device.

[0009] Step 210, the designed FDD-based MIRS-assisted sensory integration frame structure configuration is as shown in the attached Figure 3 shown.

[0010] RFT1 and RFT2 use FDD for uplink and downlink transmission. In the receiving frame structure of RFT1, M "perception, configuration and confirmation three-slot group" are configured, represented as SR, C, and B time slots. The configuration position and quantity are controlled by the CCE device. The remaining time slots are receiving data time slots, represented as DR time slots. C time slot is the time slot where the CCE device configures the MIRS position and phase. B time slot is the empty receiving time slot of RFT1. The received signal in this slot is discarded. In the sending frame structure of RFT1, M ACK time slots are configured. The position corresponds to the position of B time slot in the receiving frame structure. The rest are configured as data transmission time slots, represented as DT time slots. In the sending frame structure of RFT2, M "perception and double blank three-slot group", namely ST and B time slots, are configured. The configuration position and quantity are controlled by the CCE device and should be the same as the configuration position and quantity of "perception, configuration and confirmation three-slot group" in the receiving frame structure of the RFT1 device. The remaining time slots are data transmission time slots, represented as DT time slots. In the B time slot, RFT2 does not send any data, which is a blank time slot. In the receiving frame structure of RFT2, all are configured as data receiving time slots, which are expressed as DR time slots.

[0011] Step 220, the designed MIRS auxiliary perception and communication process is as shown in the attached Figure 4 shown.

[0012] In the RFT1 data sending (RFT2 data receiving) process, first, RFT2 sends a perception signal and RFT1 receives the perception signal; secondly, CCE processes to obtain the position of RF2 and calculates the optimal position and phase configuration of MIRS; then, CCE adjusts the MIRS position and phase; then, MIRS feeds back an ACK signal of adjustment completion to CCE, and CCE feeds back an ACK signal of data permission to be sent to RFT1; finally, RFT1 sends a data signal and RFT2 receives a data sending signal.

[0013] In the RFT2 data sending (RFT1 data receiving) process, first, RFT2 sends a perception signal and RFT1 receives a perception signal; secondly, CCE processes to obtain the position of RF2 and calculates the optimal position and phase configuration of MIRS; then, CCE adjusts the MIRS position and phase; then, MIRS feeds back an ACK signal of adjustment completion to CCE, CCE feeds back an ACK signal of data permission to be sent to RFT1, and RFT1 sends an ACK signal of data permission to be sent to RFT2; finally, RFT2 sends a data signal and RFT1 receives a data sending signal.

[0014] Step 230, the designed OFDM signal-based sensing method, the main process is as follows. RFT2 sends the sensing signal on N subcarriers, each subcarrier sends K OFDM symbols, and RFT1 receives and obtains a data matrix of N×K dimensions. The signal propagation delay from RFT2 to RFT1 is estimated by inverse Fourier transform Signal propagation delay from RFT2 to MIRS and then to RFT1 Azimuth of RFT2 relative to MIRS and pitch angle Using the above estimated information and the known position p of RFT1 at time t b,t and MIRS position p r,t , the position of RFT2 can be calculated as follows: in

[0015]

[0016]

[0017] R is the rotation matrix in the IRS coordinate system, c is the speed of light in free space, and λ is the signal wavelength.

[0018] Step 240, based on the perception result MIRS position p at time t r,t and Phase The adjustment method of s∈{1,2,L,S} is shown in the following formula:

[0019]

[0020] in, is the distance from BS to the sth unit of MIRS at time t, is the distance from the user to the sth unit of MIRS at time t, is the distance from BS to the user at time t, and S is the number of AIRS units.

[0021]

[0022] Among them, D t is the distance from MIRS to BS and user connection at time t.

[0023] Beneficial Effects

[0024] The present invention discloses a synaesthesia integrated device assisted by a movable intelligent reflective surface, introduces the basic device composition, and introduces a new network element, namely, a movable intelligent reflective surface (MIRS), which is composed of an intelligent reflective surface (IRS) and a movable platform. The movable platform is connected to a central control equipment (CCE), and the position of the IRS can be adjusted as needed to improve the overall network performance.

[0025] Furthermore, the present invention designs a MIRS-assisted integrated communication frame structure based on frequency division duplex (FDD), and introduces "perception, configuration and confirmation three-slot group" and "perception and double blank three-slot group" into the frame structures of RFT1 and RFT2, respectively, to ensure the perception capability of the network and provide input conditions for communication enhancement.

[0026] In addition, the present invention designs a MIRS-assisted perception and communication method based on OFDM. The perception signal adopts an OFDM waveform, and CCE obtains the position information of RFT2 through inverse Fourier transform processing and further calculation; then, based on the estimated RFT2 position information, the optimal phase and position of MIRS are calculated according to the designed formula; then, MIRS is driven to the corresponding position and its phase is adjusted accordingly.

[0027] Finally, we constructed a simulation scenario based on the actual scenario parameters, and conducted a large number of simulations and comparisons, proving the advantages over fixed-position IRS. The mobile intelligent reflective surface-assisted integrated sensing device and method of the present invention can be applied to various indoor and outdoor communication systems, including but not limited to ground-to-ground communication systems, air-to-ground communication systems, air-to-air communication systems, and underground and underwater communication systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to clearly explain the technical steps of the present invention, all the drawings used in the description of the present invention are briefly described below. It should be noted that the drawings described below are only some examples of the implementation of the present invention, and other ordinary technicians in this field can still obtain other drawings in other different scenarios based on these drawings.

[0029] Attached Figure 1 It is the implementation process of the present invention;

[0030] Attached Figure 2 The device of the present invention is composed of;

[0031] Attached Figure 3 It is the FDD-based MIRS auxiliary communication integrated frame structure configuration designed by the present invention;

[0032] Attached Figure 4 This is the MIRS-assisted perception and communication process designed by the present invention;

[0033] Attached Figure 5 This is an example application scenario provided by the present invention;

[0034] Attached Figure 6 The simulation and measured results of positioning in the application example scenario provided by the present invention;

[0035] Attached Figure 7 It is a diagram of user received power variation in an application example scenario provided by the present invention;

[0036] Attached Figure 8 This is a diagram of user receiving throughput changes in an application example scenario provided by the present invention. DETAILED DESCRIPTION

[0037] The steps and processes of the present invention are described completely and clearly below in conjunction with the drawings in the present application. It is obvious that the example described in the present application is only an example application scenario of the present invention, and other results based on the content of the present invention without making substantial changes all fall within the protection scope of the present invention.

[0038] Attached Figure 5 This is an example scenario provided by the present invention, which shows all the devices included in the present invention and some parameters that will be used later. In this example scenario, the movable intelligent reflective surface (MIRS) consists of an intelligent reflective surface and a two-dimensional electric track, which are deployed within a wall. Figure 5 The base station (BS) is the RFT1 device in the present invention, the user is the RFT2 device in the present invention, and the field programmable gate array (FPGA) is the CCE device in the present invention, which is connected to the base station and MIRS to receive the base station signal for processing and control the phase and position of the MIRS.

[0039] Attached Figure 5 An example scenario provided is a single-base station, single-user, single IRS scenario. The communication between the user and the base station adopts the FDD-based MIRS-assisted sensing integrated frame structure configuration, MIRS-assisted sensing and communication process, and MIRS phase and position calculation method proposed in the present invention.

[0040] According to the attached Figure 5 For example scenario, the relevant parameters are:

[0041] The number of units in MIRS is S = M r ×M c =64×64, wavelength λ=1cm, the horizontal / vertical unit spacing of MIRS is d=0.5cm, and the speed of light in free space c=3×10 8m / s, number of OFDM subcarriers N = 3000, subcarrier bandwidth Δf = 120kHz, base station transmission power P t =N×E s =20dBm, E s is the energy of a single OFDM symbol, the noise power spectral density N0 = -174dBm / Hz, and the noise coefficient of the user receiver n f =8dB, user receiver noise power σ 2 =n f N0Δf=-115.2dBm, base station location p b = [5 5 0], one-dimensional inverse Fourier transform dimension N F =4096, 2D inverse Fourier transform dimension

[0042] Step 300: Establish a communication system model in an example scenario.

[0043] The location of MIRS is taken as the origin of coordinates, and the location of MIRS is p r , the user position p, and their rotation matrix relative to the MIRS coordinate system is R. We assume that IRS is an M with an element distance equal to d. r ×M c Uniform plane array. In IRS, the element in the lth row and the mth column has position q in the IRS coordinate system. l,m =[dl-d(M r -1) / 2,0,dm-d(M c -1) / 2],l=1,2,L,M r ,m=1,2,L,M c FPGA calculates the matrix Modulate the phase of the incident wave at time t, where Γ t The modulus of all elements in is 1.

[0044] We consider the transmission of T OFDM symbols of N subcarriers in the example scenario provided. For simplicity, we assume that all transmitted pilot symbols are equal to Then the received signal can be expressed as an N×T matrix

[0045]

[0046] where Y = [y1,y2,…,y T ], Corresponding to the tth OFDM symbol. Noise matrix It consists of zero-mean circularly symmetric independent and identically distributed Gaussian elements with variance σ 2 The complex channel gains of the direct path and the reflected path between the base station and the user are respectively expressed as gb and g r Delay τ b =||pp b || / c+Δ t and τ r =||pp r || / c+||p b -p r || / c+Δ t Denote the direct path and reflected path delays, including clock deviation Δ t The effect of these delays on the signal is represented by the vector d(τ b ) and d(τ r ) to capture, here we have defined

[0047] d(τ)=[1,e -j2πτΔf ,…,e -j2πτ(N-1)ΔfT ] (6)

[0048] Further, we have

[0049]

[0050] Where θ=[θ az ,θ el ] T represents the known azimuth and elevation angles from the BS to the IRS, φ = [φ az ,φ el ] T represents the Angle of Departure (AOD) from the IRS to the user, The IRS response vector to the angle ψ∈{φ,θ} is defined as as well as

[0051]

[0052]

[0053] Among them, β r =[k(ψ)]1(M r -1)d / 2, β c =[k(ψ)]3(M c -1)d / 2, and

[0054]

[0055] is the wave number vector. Here, we assume that the wavelength remains relatively constant within the transmission bandwidth. In the whole process, the user moves from time t1 to time t2, as shown in the following figure. Figure 5 shown.

[0056] Step 310, estimate τ from the observed Y given the IRS phase distribution, the transmitted signal, and the location and direction of the BS and IRS b , expressed as

[0057] We estimate τ based on the sum of the columns of Y b ,y c =∑ t y t , the detailed expression is as follows

[0058]

[0059] Among them, x t Denotes the tth column of the matrix N. This operation coherently adds T OFDM symbols for the direct path, but does not happen for the signal reflected by the MIRS. We assume that the T times received power from the BS is much larger than that from the MIRS, which is a relevant assumption especially when both the BS and the user are in the far field of the MIRS.

[0060] Next, we calculate the vector y c The inverse fast Fourier transform (IFFT) of in is the IFFT matrix, and each element in F can be expressed as N F is the length of the IFFT vector. If for some integer l, τ b =l / (N F Δf), then The absolute value of the element is likely to have a maximum value near l. Therefore, in order to obtain a more accurate τ b We estimate that we introduced some artificial delay δ, We order

[0061]

[0062] Among them, e k is a vector containing all zeros except for the kth element which is 1. Next, we refine our estimate by calculating

[0063]

[0064] So far, τ b can be estimated as

[0065]

[0066] Based on our numerical observations, the optimization of δ can be performed using a quasi-Newton method starting from 0. We note that the purpose of the auxiliary parameter δ is to add an artificial delay to the signal so that τ b +δ satisfies the condition that τ b +δ=l / (N F Δf), therefore, it is sufficient to constrain the range of δ in (13) to [0,1 / (N F Δf)].

[0067] Step 320, estimate τ from the observed Y given the IRS phase distribution, the transmitted signal, and the location and direction of the BS and IRS r , expressed as

[0068] To estimate τ r , we first remove the direct path component from the received signal Y by calculating

[0069]

[0070] in, Then, similar to formula (12), we first optimize as follows

[0071]

[0072] Then, we calculate

[0073]

[0074] Finally, we can estimate

[0075] Step 330, given the IRS phase distribution, the transmitted signal, and the location and direction of the BS and IRS, estimate φ from the observed Y, expressed as

[0076] To estimate φ, we first calculate r Remove the delay effect of the reflection path Secondly, we have φ Sum all rows of

[0077]

[0078] Further, based on (7), we use the Kronecker product and the vec operator to obtain

[0079]

[0080] Where A(θ) = a c(θ)a r (θ) T , inspired by (19), we use the known matrix Γ t ⊙A(θ) performs 2DIFFT to find φ

[0081]

[0082] in, and Similar to the definition of F, where and N Fc Determines the dimension of the two-dimensional IFFT transform. We note that the matrix It does not depend on the received signal and can be calculated offline.

[0083] Now, let us assume that for some integer as well as We have

[0084]

[0085] Then, by comparing (19) and (20), we can see that for some complex scalar ξ we have

[0086]

[0087] Inspired by (22) and (18), we can find and Make where w l,m =||y φ -h(η l,m )η l,m || 2 , Next, we use quadratic interpolation to obtain and The continuous (and more precise) value of

[0088]

[0089] At the same time, we also calculated m similar to (23) q Secondly, based on l q and m q , use (21) to estimate [k(φ)]1 and [k(φ)]3, and use the following relationship to calculate an estimate of φ

[0090]

[0091] Finally, we refine our estimate by performing a minimization

[0092]

[0093] We can use (24) as the initial point and apply the quasi-Newton algorithm to solve (25).

[0094] Step 340, based on the estimated Estimate the user location p at time t, expressed as

[0095] User location can be calculated in

[0096]

[0097]

[0098] R is the rotation matrix in the IRS coordinate system, c is the speed of light in free space, and λ is the signal wavelength.

[0099] Step 350, based on the perception result MIRS position p at time t r,t and Phase The adjustment method of s∈{1,2,L,S} is shown in the following formula:

[0100]

[0101] in, is the distance from BS to the sth unit of MIRS at time t, is the distance from the user to the sth unit of MIRS at time t, is the distance from BS to the user at time t, and S is the number of AIRS units.

[0102]

[0103] Among them, D t is the distance from MIRS to BS and user connection at time t.

[0104] The following is an explanation of some of the result graphs obtained in this example scenario.

[0105] Attached Figure 6 The comparison between the positioning results and the actual results is shown, including the verification of simulation and actual measurement. It can be seen from the figure that the RFT2 position estimation method proposed in the present invention has high accuracy. In the simulation, the average positioning error is less than 0.1m; in the actual test, the average positioning error is less than 0.2m.

[0106] Attached Figure 7The change of received power during the user's movement is shown. The whole process lasted for 7 seconds. We compared the solution proposed in the present invention with the IRS solution without perception capability. The comparison results show that the MIRS-assisted synaesthesia integrated system proposed in the present invention can ensure the stability of the received power during the user's movement, and is at a high level throughout the movement process, which is significantly better than the baseline level. This proves the effectiveness and robustness of the synaesthesia integrated frame structure and synaesthesia process proposed in the present invention.

[0107] Further, attached Figure 8 The throughput during the entire movement process was counted. It can be seen that during the entire movement process, the solutions proposed by the present invention are superior to the IRS solution without sensing capability, and the average throughput is increased by 7.2Mbps, which proves the advantages of the mobile intelligent reflective surface-assisted integrated sensing and communication device and method proposed by the present invention.

Claims

1. A synaesthesia integrated device assisted by a movable intelligent reflective surface, characterized in that: include: The main devices are two types of radio frequency transceiver equipment (RFT1 and RFT2), a movable intelligent reflective surface (MIRS) device and a central control equipment (CCE); the main methods are as follows: inserting perception time slots into the traditional frame structure, designing a MIRS-assisted integrated sensing frame structure based on frequency division duplex (FDD), and the RFT1 and RFT2 frame structure configurations are executed by the CEE device; designing the MIRS-assisted perception and communication process, in the perception time slot, the CEE device estimates the position of RFT2, and based on this calculates the optimal MIRS position and phase configuration and performs corresponding adjustment operations.

2. The method according to claim 1, characterized in that: The first type of RFT device (RFT1) realizes the transmission of communication signals and the reception of perception signals, and the second type of RFT device (RFT2) realizes the reception of communication signals and the transmission of perception signals; the MIRS device is composed of an IRS and a movable platform, which realizes the reflection phase adjustment of perception signals and communication signals, and provides the IRS with the ability to move positions; the CCE device is connected to the RFT1 and MIRS devices, and obtains the optimal phase configuration and position of the IRS by processing the received signal of RFT1, thereby realizing the adjustment of the phase and position of the MIRS device.

3. The method according to claim 1, characterized in that In the receiving frame structure of RFT1, M "three-time slot group of perception, configuration and confirmation" are configured, which are represented by SR, C, and B time slots. The configuration position and number are controlled by the CCE device. The remaining time slots are receiving data time slots, which are represented by DR time slots. The C time slot is the time slot for the CCE device to configure the MIRS position and phase. The B time slot is the empty receiving time slot of RFT1. The received signal in this time slot is discarded. In the sending frame structure of RFT1, M ACK time slots are configured. The position corresponds to the B time slot position in the receiving frame structure. The rest are all configured as data transmission time slots. Send time slot, expressed as DT time slot; configure M "perception and double blank three-time slot group" in the sending frame structure of RFT2, namely ST and B time slots, the configuration position and quantity are controlled by the CCE device, and should be the same as the configuration position and quantity of the "perception, configuration and confirmation three-time slot group" in the receiving frame structure of the RFT1 device. The remaining time slots are data sending time slots, expressed as DT time slots; in the B time slot, RFT2 will not send any data, which is a blank time slot; in the receiving frame structure of RFT2, all are configured as data receiving time slots, expressed as DR time slots.

4. The method according to claim 1, characterized in that: The designed MIRS auxiliary perception and communication process includes the RFT1 data sending (RFT2 data receiving) process and the RFT2 data sending (RFT1 data receiving) process; in the RFT1 data sending (RFT2 data receiving) process, first, RFT2 sends the perception signal and RFT1 receives the perception signal; secondly, CCE processes to obtain the position of RF2 and calculates the optimal position and phase configuration of MIRS; then, CCE adjusts the MIRS position and phase; then, MIRS feeds back the ACK signal of adjustment completion to CCE, and CCE feeds back the ACK signal of data permission to RFT1; finally, RFT1 Send data signal, RFT2 receives data sending signal; in the RFT2 data sending (RFT1 data receiving) process, first, RFT2 sends perception signal, and RFT1 receives perception signal; secondly, CCE processes to obtain the position of RF2 and calculates the optimal position and phase configuration of MIRS; then, CCE adjusts the MIRS position and phase; then, MIRS feeds back the ACK signal of adjustment completion to CCE, CCE feeds back the ACK signal of data permission to be sent to RFT1, and RFT1 sends the ACK signal of data permission to be sent to RFT2; finally, RFT2 sends data signal, and RFT1 receives the data sending signal.

5. The method according to claim 1, characterized in that RFT2 sends the sensing signal on N subcarriers, each subcarrier sends K OFDM symbols, and RFT1 receives and obtains a data matrix of N×K dimensions; the signal propagation delay from RFT2 to RFT1 is estimated by inverse Fourier transform. Signal propagation delay from RFT2 to MIRS and then to RFT1 Azimuth of RFT2 relative to MIRS and pitch angle Using the above estimated information and the known position p of RFT1 at time t b,t and MIRS position p r,t , the position of RFT2 can be calculated as follows: in R is the rotation matrix in the IRS coordinate system, c is the speed of light in free space, and λ is the signal wavelength.

6. The method according to claim 1, characterized in that Based on perception results MIRS position p at time t r,t and Phase The adjustment method is shown in the following formula: in, is the distance from BS to the sth unit of MIRS at time t, is the distance from the user to the sth unit of MIRS at time t, is the distance from BS to the user at time t, S is the number of AIRS units, Among them, D t is the distance from MIRS to BS and user connection at time t.

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