Star-ris assisted isac system and their beamforming method

Abstract

An integrated sensing communication system (ISAC) with STAR-RIS technology is disclosed. The disclosed integrated sensing communication system receives a sensing signal reflected from a sensing target by reflecting or refracting it on a reconfigurable intelligent reflective surface (RIS) using a linear array antenna, and receives a communication signal from a communication user by reflecting or refracting it on a reconfigurable intelligent reflective surface (RIS) using a linear array antenna. The integrated sensing system can improve sensing performance while maintaining communication performance by optimizing the reflection coefficient of the reconfigurable intelligent reflective surface and the power allocation of the sensing signal and the communication signal.

Description

Technology Field

[0001] The following embodiments relate to a STAR-RIS-supported sensing communication integration system and a beamforming optimization technique, specifically to a technique for determining a beamforming vector to maintain a balance between communication performance and sensing performance. Background Technology

[0002] Integrated Sensing and Communication (ISAC) is a technology that provides communication and sensing functions within a single framework, enabling the sharing of time, frequency, and hardware resources. It is attracting attention as a core technology for 6th generation mobile communication systems because it can significantly improve spectrum efficiency.

[0003] In addition, Reconfigurable Intelligent Surface (RIS) technology is a technology that actively controls the radio wave environment using meta-surface devices capable of reflecting or refracting electromagnetic waves, and can be used to improve wireless communication performance by manipulating the direction, phase, and amplitude of radio waves.

[0004] STAR-RIS (Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface) technology is a technology that goes beyond simply reflecting radio waves to simultaneously perform reflection and transmission. By optimizing both reflected and transmitted signals, it can cover a wider area and improve communication quality.

[0005] ISAC technology and STAR-RIS technology can be combined to develop into a STAR-RIS-enabled sensing-communication integrated system. Most research has focused on optimizing beamforming in the downlink of the STAR-RIS-enabled sensing-communication integrated system or maximizing the sensing signal-to-noise ratio (SNR), but there has not been active research on optimizing the reflection coefficient of reconfigurable intelligent reflective surfaces or optimizing power allocation in the uplink. The problem to be solved

[0006] The technical problem of the present invention is to maintain a balance between communication performance and sensing performance in a STAR-RIS-supported sensing communication integrated system.

[0007] The technical problem of the present invention is to determine STAR-RIS coefficients that can satisfy communication performance and sensing performance in a STAR-RIS-supported sensing communication integrated system. means of solving the problem

[0008] According to an exemplary embodiment, a method of operation of a STAR-RIS-supported sensing-communication integrated system is provided, comprising the steps of: transmitting a sensing signal to a sensing target using a linear array antenna; receiving the transmitted sensing signal by reflecting or transmitting the sensing signal reflected from the sensing target onto a reconfigurable intelligent reflective surface (RIS) using the linear array antenna, and receiving a communication signal from a communication user by reflecting or refracting it onto the reconfigurable intelligent reflective surface (RIS) using the linear array antenna; decoding the received communication signal by applying receiving beamforming to the received signal, and detecting the sensing target using the received sensing signal.

[0009] Here, the reflection coefficient of the above-mentioned resetting intelligent reflective surface (RIS) can be determined according to the following mathematical formula 1.

[0011] [Mathematical Formula 1]

[0012]

[0014] Here, , And, as, and All have positive values. , Is , is, , It can be determined as shown in the following mathematical formula 2.

[0016] [Mathematical Formula 2]

[0018]

[0020] Here, is a matrix It is the eigenvector corresponding to the largest eigenvalue of, and is a matrix It is the eigenvector corresponding to the largest eigenvalue of. And, is, is, is a wireless channel between the linear array antenna and the resettable intelligent reflective surface. is a wireless channel between the above-mentioned resettable intelligent reflective surface and the above-mentioned communication user, and is a wireless channel between the above-mentioned resettable intelligent reflective surface and the above-mentioned sensing target.

[0022] In addition, the reflection coefficient of the above-mentioned resetting intelligent reflective surface (RIS) can be determined according to the following mathematical formula 3.

[0024] [Mathematical Formula 3]

[0025]

[0027] Here, , And, as, and All have positive values. , Is , It is and can be determined as shown in the following mathematical formula 4.

[0029] [Mathematical Formula 4]

[0030]

[0032] Here, is a matrix It is a singular vector corresponding to the largest singular value of, and is a singular vector corresponding to the second-largest singular value.

[0033] And, am. is a wireless channel between the linear array antenna and the resettable intelligent reflective surface. is a wireless channel between the above-mentioned resettable intelligent reflective surface and the above-mentioned communication user, and is a wireless channel between the above-mentioned resettable intelligent reflective surface and the above-mentioned sensing target.

[0035] In addition, the above The value of can be determined as a value satisfying the following mathematical formula 5.

[0037] [Mathematical Formula 5]

[0038]

[0040] Here, the constraint of Equation 5 is equal to Equation 6.

[0042] [Mathematical Formula 6]

[0043]

[0045] Here, And, am.

[0046] is the average power of the reflection coefficient of the above-mentioned sensing target.

[0047] also, And,

[0048] am. is the maximum transmission power of the above linear array antenna, and is the power of the sensing signal. is the maximum transmission power of the above communication user, and as, is the lowest communication speed of the above communication user. is the power of thermal noise.

[0049] Here, the above The value of can be determined as a value satisfying the following mathematical formula 7.

[0051] [Mathematical Formula 7]

[0052]

[0054] Here, as, is the lowest communication speed of the above communication user. And, is the maximum transmission power of the above communication user. is the power of thermal noise.

[0055] And, the reflection coefficient of the above-mentioned reconfigurable intelligent reflective surface (RIS) can be determined to satisfy the following mathematical formula 10.

[0057] [Mathematical Formula 8]

[0059]

[0061] Here, And,

[0062] Is or It could be.

[0063] Here, as, is the lowest communication speed of the above communication user.

[0064] In addition, the reflection coefficient of the resettable intelligent reflective surface (RIS) is And, And, And, is a wireless channel between the linear array antenna and the resettable intelligent reflective surface. is a wireless channel between the above-mentioned resettable intelligent reflective surface and the above-mentioned communication user, and is a wireless channel between the above-mentioned resettable intelligent reflective surface and the above-mentioned sensing target.

[0065] Here, is the power of the sensing signal, and is the power of the communication signal. σ is the power of the thermal noise, and is the average power of the reflection coefficient of the above-mentioned sensing target, and is the number of symbols included in the sensing signal.

[0067] In addition, the step of applying the above-mentioned receiving beamforming may use a Minimum Mean Square Error (MMSE) beamforming vector. Effects of the invention

[0069] According to the present invention, communication performance and sensing performance can be maintained in balance in a STAR-RIS-supported sensing communication integrated system.

[0070] According to the present invention, STAR-RIS coefficients capable of satisfying communication performance and sensing performance can be determined in a STAR-RIS supported sensing communication integrated system. Brief explanation of the drawing

[0071] FIG. 1 is a diagram illustrating the concept of a STAR-RIS-supported sensing communication integration system according to an exemplary embodiment. FIG. 2 is a flowchart illustrating the operation method of a STAR-RIS-supported sensing communication integration system according to an exemplary embodiment. FIG. 3 is a diagram illustrating the relationship between communication speed and sensing SNR in a STAR-RIS-supported sensing communication integrated system according to an exemplary embodiment. FIG. 4 is a diagram illustrating the relationship between transmission power and sensing SNR in a STAR-RIS-supported sensing communication integrated system according to an exemplary embodiment. Specific details for implementing the invention

[0072] Structural or functional descriptions are provided merely for the purpose of illustrating embodiments according to the concept of the present invention, and embodiments according to the concept of the present invention may be implemented in various forms and are not limited to the embodiments described herein.

[0073] Embodiments according to the concept of the present invention may be subject to various modifications and may take various forms; therefore, embodiments are illustrated in the drawings and described in detail in this specification. However, this is not intended to limit the embodiments according to the concept of the present invention to specific disclosed forms, and includes modifications, equivalents, or substitutions that fall within the spirit and scope of the present invention.

[0074] Terms such as "first" or "second" may be used to describe various components, but said components should not be limited by said terms. For the sole purpose of distinguishing one component from another, for example, without departing from the scope of rights according to the concept of the present invention, the first component may be named the second component, and similarly, the second component may be named the first component.

[0075] When it is stated that one component is "connected" or "connected" to another component, it should be understood that while it may be directly connected or connected to that other component, there may also be other components in between. Conversely, when it is stated that one component is "directly connected" or "directly connected" to another component, it should be understood that there are no other components in between. Expressions describing the relationships between components, such as "between," "exactly between," or "directly adjacent to," should be interpreted in the same way.

[0076] The terms used herein are used merely to describe specific embodiments and are not intended to limit the invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this specification, terms such as “comprising” or “having” are intended to specify the existence of the described features, numbers, steps, actions, components, parts, or combinations thereof, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0077] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art to which the present invention pertains. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in this specification.

[0079] Hereinafter, embodiments will be described in detail with reference to the attached drawings. However, the scope of the patent application is not limited or restricted by these embodiments. Identical reference numerals provided in each drawing indicate identical components.

[0081] FIG. 1 is a diagram illustrating the concept of a STAR-RIS-supported sensing communication integration system according to an exemplary embodiment.

[0082] In FIG. 1, the base station (110) uses an array antenna (111) composed of multiple antenna elements, but the communication user (140) uses only one antenna. Additionally, since there is no direct link between the communication user (140) and the base station (110) and between the sensing target (130) and the base station (110), communication and sensing must be performed using a path passing through a reconfigurable intelligent reflective surface (120).

[0083] The linear array antenna is a Uniform Linear Array (ULA) in which M antenna elements are spaced apart by a distance of half a wavelength along the x-axis direction, and the reconfigurable intelligent reflective surface (120) It is a form (UPA, Uniform Planar Array) in which elements are arranged in the yz plane at a distance of half a wavelength. Here, N= am.

[0084] The base station (110) can transmit a sensing signal to a sensing target (130) using a linear array antenna (111). The transmitted sensing signal is transmitted via a wireless channel from the linear array antenna (111) to a reconfigurable intelligent reflective surface (120). It passes through (121) and is reflected or refracted by the resettable intelligent reflective surface (120). The sensing signal reflected or refracted by the resettable intelligent reflective surface (120) is a wireless channel from the resettable intelligent reflective surface (120) to the sensing target (130). It can be transmitted via (131).

[0086] According to one side, the wireless channel G can be modeled as a Rician fading channel as shown in Equation 1 below.

[0088] [Mathematical Formula 1]

[0090]

[0092] Here, is a wireless channel Indicates the number of multipaths, and is a wireless channel It is an index representing multiple paths. is a wireless channel Represents path loss, and is a wireless channel In this example, the complex gain of each path, the angle of arrival at the linear array antenna, and the azimuth and elevation angles at the resettable intelligent reflective surface are indicated.

[0093] The base station's steering vector is The steering vector of a resettable intelligent reflective surface, defined as It can be defined as. Here, is, and symbol represents the Kronecker product.

[0095] The transmitted sensing signal is reflected from the sensing target (130), and again the wireless channel The signal is reflected or refracted from the reconfigurable intelligent reflective surface (120) via (131). The reflected or refracted sensing signal is transmitted to the wireless channel from the reconfigurable intelligent reflective surface (120) to the linear array antenna (111). It is transmitted via (121), and the base station (110) is a wireless channel Receives the sensing signal transmitted via (121).

[0097] The base station (110) can receive a communication signal from a communication user (140). The communication signal is a wireless channel from the communication user (140) to a reconfigurable intelligent reflective surface (120). The communication signal is reflected or refracted from the reconfigurable intelligent reflective surface (120) via (141). The reflected or refracted communication signal is a wireless channel from the reconfigurable intelligent reflective surface (120) to the linear array antenna (111). It is transmitted via (121), and the base station (110) is a wireless channel Receives the sensing signal transmitted via (121).

[0099] Here, a wireless channel between a resettable intelligent reflective surface (120) and a sensing target (130). (131) can be modeled as shown in Equation 2 below.

[0101] [Mathematical Formula 2]

[0102]

[0104] Additionally, a wireless channel between a reconfigurable intelligent reflective surface (120) and a communication user (140). (141) can be modeled as shown in mathematical formula 3 below.

[0106] [Mathematical Formula 3]

[0107]

[0109] Here, is a wireless channel It can be defined similarly to in.

[0110] FIG. 2 is a flowchart illustrating the operation method of a STAR-RIS-supported sensing communication integration system according to an exemplary embodiment.

[0111] A STAR-RIS-supported sensing communication integrated system according to an exemplary embodiment can operate as a base station of FIG. 1.

[0112] In step (210), the STAR-RIS-supported sensing communication integrated system (110) can transmit a sensing signal to a sensing target using a linear array antenna.

[0113] The sensing signal transmitted by the STAR-RIS supported sensing communication integrated system (110) can be modeled as shown in Equation 4 below.

[0115] [Mathematical Formula 4]

[0117]

[0118] Here, is the number of symbols included in the sensing signal, and The sensing signal is It is transmitted with the power of.

[0120] In step (220), the STAR-RIS-supported sensing communication integration system (110) receives a transmitted sensing signal by reflecting or refracting the sensing signal reflected from a sensing target onto a reconfigurable intelligent reflective surface (RIS) using a linear array antenna, and receives a communication signal from a communication user by reflecting or refracting it onto a reconfigurable intelligent reflective surface (RIS) using a linear array antenna.

[0122] The communication signal transmitted by the communication user (140) can be modeled as shown in Equation 5 below.

[0124] [Mathematical Formula 5]

[0126]

[0128] Here, The average is and the covariance matrix is It represents a complex Gaussian distribution.

[0129] Accordingly, the signal received by the STAR-RIS supported sensing communication integrated system (110) can be represented as shown in Equation 6 below.

[0131] [Mathematical Formula 6]

[0133]

[0135] Here, And, am. Is It represents the backscatter channel. is the transmission beamforming vector of the sensing signal, and And, is the transmission power of the communication signal. This represents the reflection coefficient of a reconfigurable intelligent reflective surface. When the received signal is expressed for L symbols, it is as shown in Equation 7 below.

[0137] [Mathematical Formula 7]

[0138]

[0140] According to one aspect, in step (210), the STAR-RIS-supported sensing communication integrated system (110) can beamform the sensing signal using a transmission beamforming vector. If the transmission beamforming vector of the sensing signal is determined as in Equation 8 below, the received signal can be represented as in Equation 9 below.

[0142] [Mathematical Formula 8]

[0144]

[0146] [Mathematical Formula 9]

[0147]

[0149] Here, And, And, is. Also, am.

[0150] Since the signals received by the STAR-RIS-supported sensing communication integrated system (110) include sensing signals and communication signals, the STAR-RIS-supported sensing communication integrated system (110) can be designed as a sensing-centric design or a communication-centric design.

[0151] According to the sensing-centric design, the STAR-RIS-supported sensing communication integration system can first decode the communication signal from the received signal, remove the decoded communication signal from the received signal, and then perform a sensing operation. To decode the communication signal from the received signal, Minimum Mean Square Error (MMSE) beamforming can be applied to the received signal. Equation 10 represents the signal to which MMSE beamforming has been applied to the received signal.

[0153] [Mathematical Formula 10]

[0154]

[0156] Here, And, the mean is 0 and the covariance matrix represents the interference and noise components as shown in Equation 11 below.

[0158] [Mathematical Formula 11]

[0159]

[0161] Referring to mathematical formula 9, the communication SNR is as shown in mathematical formula 12 below.

[0163] [Mathematical Formula 12]

[0164]

[0166] In addition, the signal obtained after removing the communication signal from the received signal is as shown in Equation 13 below.

[0168] [Mathematical Formula 13]

[0169]

[0171] Here, the sensing SNR is given by the following mathematical formula 14.

[0173] [Mathematical Formula 14]

[0174]

[0176] According to the communication-centric design, the STAR-RIS-supported sensing communication integration system can first perform sensing using the received signal, remove the sensing signal from the received signal, and then decode the communication signal. Equation 9 can be re-expressed for the sensing operation as Equation 15 below.

[0178] [Mathematical Formula 15]

[0179]

[0181] Here, And, the mean is 0 and the covariance matrix represents the interference and noise components as shown in Equation 16 below.

[0183] [Mathematical Formula 16]

[0185]

[0187] The sensing SNR can be expressed as shown in Equation 17 below.

[0189] [Mathematical Formula 17]

[0190]

[0192] The communication SNR after removing the sensing signal can be expressed as shown in Equation 18 below.

[0194] [Mathematical Formula 18]

[0195]

[0197] According to one side, the STAR-RIS-supported sensing communication integration system can be optimized so that the communication speed of the communication user is above a lower limit and the sensing SNR is maximized. To this end, the reflection coefficient of a reconfigurable intelligent reflective surface and power allocation This can be optimized to satisfy mathematical equation 19 below.

[0199] [Mathematical Formula 19]

[0200]

[0202] Here, And, sc represents a sensing-centric design, and cc represents a communication-centric design. In Equation 19, the constraints are as shown in Equation 20 below.

[0204] [Mathematical Formula 20]

[0205]

[0207] Here, And, is the maximum transmission power of the STAR-RIS-supported sensing communication integrated system, and is the maximum transmission power of the communication user. Also, represents the minimum communication speed of the communication user.

[0209] In a sensing-centered design, the sensing SNR can be expressed as shown in Equation 21 below, and the constraint can be expressed as shown in Equation 22.

[0211] [Mathematical Formula 21]

[0212]

[0214] [Mathematical Formula 22]

[0215]

[0216]

[0218] Here, am.

[0220] In the last equation of mathematical equation 22, the optimal communication signal transmission power is It can be seen that it is determined as.

[0222] If STAR-RIS elements use a common ES (Energy splitter) coefficient, the reflection coefficient of a reconfigurable intelligent reflective surface It can be expressed as shown in the following mathematical formula 23.

[0224] [Mathematical Formula 23]

[0225]

[0227] Here, , And, , And, am.

[0228] To maximize the sensing SNR, the channel power must be increased so that Equation 24 below is satisfied, while the cross-correlation between channels in Equation 23 is reduced.

[0230] [Mathematical Formula 24]

[0231]

[0232]

[0234] [Mathematical Formula 25]

[0235]

[0237] Phase vector To determine this, techniques such as Channel Power Matching (CPM), Maximum Eigenvalue Matching (MEM), and Low Cross-correlation Matching (LCM) can be considered.

[0238] The purpose of CPM and MEM techniques is channel power class It is to maximize, and can be expressed by mathematical formula 26.

[0240] [Mathematical Formula 26]

[0241]

[0243] Here, And, am.

[0244] The solution of the MEM method is given by the following mathematical formula 27.

[0246] [Mathematical Formula 27]

[0247]

[0249] Here, is a matrix It is the eigenvector corresponding to the largest eigenvalue of, and is a matrix It is the eigenvector corresponding to the largest eigenvalue of.

[0251] The LCM technique is a matrix Performs singular value decomposition on, and the phase vector is determined as shown in the following mathematical formula 28.

[0253] [Mathematical Formula 28]

[0254]

[0256] Here, is a matrix It is a singular vector corresponding to the largest singular value of, and is a singular vector corresponding to the second-largest singular value.

[0257] When the phase vector is determined, common ES coefficients It can be optimized as follows.

[0259] 1) In the case of a sensing-centric design

[0261] In the case of a sensing-centric design, And, , Equations 19 and 20 can be rewritten in the form of equations 29 and 30 as follows.

[0263] [Mathematical Formula 29]

[0264]

[0266] [Mathematical Formula 30]

[0267]

[0269] Here, And, And, am. is the average power of the reflection coefficient of the above-mentioned sensing target.

[0270] also, am.

[0271] The second constraint in Equation 30 can be expressed as Equation 31 below.

[0273] [Mathematical Formula 31]

[0274]

[0276] In mathematical equation 31, for a valid solution It is restricted to. In mathematical equation 31, the left side's By maximizing, a solution to Equation 31 can be obtained, and that solution is am.

[0277] The optimal one satisfying mathematical equation 31 It can be found in the following mathematical formula 32.

[0279] [Mathematical Formula 32]

[0280]

[0282] Here, am.

[0283] class If you use it, mathematical formula 30 is It can be expressed as. silver Since it is a monotonically increasing function, it satisfies the following mathematical equation 33.

[0285] [Mathematical Formula 33]

[0286]

[0287]

[0289] And, since, In the range has one root, and its value is the optimal solution of Equation 26.

[0291] 1) In the case of communication-centric design

[0293] In the case of communication-centric design, And, And, Therefore, mathematical formula 19 can be expressed as mathematical formula 34 below, and mathematical formula 20 can be expressed as mathematical formula 35 below.

[0295] [Mathematical Formula 34]

[0296]

[0298] [Mathematical Formula 35]

[0299]

[0301] Here, And, am.

[0302] In mathematical formula 35, considering the constraints of the second line, the following mathematical formula 36 can be obtained.

[0304] [Mathematical Formula 36]

[0306]

[0307] To maximize the value of, The value of must take the largest possible value allowed by the constraints of Equation 34. Therefore, communication signal transmission power The optimal value of is It can be determined as follows. In addition, in Equation 34, the optimal ES coefficient can be determined by Equation 37 below.

[0309] [Mathematical Formula 37]

[0311]

[0313] When using common ES coefficients in both sensing-centric and communication-centric designs, assuming there is no interference effect on the sensing and communication SNRs, the theoretical performance limit (Upper Bound) can be obtained. In this case, the optimal phase vector can be calculated according to the CPM technique.

[0314] The common ES coefficient can be determined as shown in Equation 38.

[0315] [Mathematical Formula 38]

[0317]

[0319] In this case, the upper limit of the sensing SNR can be expressed as in Equation 39, and the upper limit of the communication SNR can be expressed as in Equation 40.

[0321] [Mathematical Formula 39]

[0322]

[0324] [Mathematical Formula 40]

[0325]

[0327] If the STAR-RIS elements do not use a common ES (Energy splitter) coefficient, optimization can be performed by transforming Equation 17 into a penalty function. In this case, the reflection coefficient of the reconfigurable intelligent reflective surface Is , It can be expressed as shown in the following mathematical formula 41 using .

[0329] [Mathematical Formula 41]

[0330]

[0332] Here, And, is, It is. Also, power allocation In a sensing-centric design In communication-centric design, It can be replaced with. Here, am.

[0333] Therefore, optimization parameters Is It can be replaced with, elements of Is And, am.

[0334] The objective function for solving the optimization problem can be determined as shown in Equation 42 below.

[0336] [Mathematical Formula 42]

[0337]

[0339] Here, is a penalty function and is defined as shown in Equation 43 below.

[0341] [Mathematical Formula 43]

[0342]

[0344] penalty parameter of In order to satisfy the last constraint of mathematical equation 20 It must be.

[0345] Finally, the penalty function-based optimization problem can be expressed as shown in Equation 44 below.

[0347] [Mathematical Formula 44]

[0348]

[0350] Since this function is differentiable, the optimal solution can be found using differentiation. However, since a local optimum can be found depending on the initial value, a good solution can be found by using the solution obtained using common ES coefficients as the initial value.

[0352] In step (230), the STAR-RIS-supported sensing communication integration system (110) can apply receiving beamforming to the received signal to decode the received communication signal and detect the sensing target using the received sensing signal.

[0354] FIG. 3 is a diagram illustrating the relationship between communication speed and sensing SNR in a STAR-RIS-supported sensing communication integrated system according to an exemplary embodiment.

[0355] In Fig. 3(a), the horizontal axis represents the communication speed, and the vertical axis represents the sensing SNR. The black dashed line represents the theoretical performance limit (Upper Bound). Referring to Fig. 3(a), the sensing-centric design (SC) generally exhibits a higher sensing SNR at the same communication speed. Although CPM and MEM show similar performance, MEM only demonstrates better loss at low communication speeds, and MEM may be preferred over CPM due to its lower complexity. On the other hand, LCM exhibits similar performance in both sensing-centric and communication-centric designs (CC) and generally shows better performance than MEM. However, MEM may be superior at high communication speeds.

[0356] Therefore, considering the given communication speed, an Adaptive Common Energy Splittering (CES) technique can be considered that selectively applies a technique with better performance at that communication speed.

[0357] Figure 3(b) illustrates the performance of a penalty-based NLO solution. In Figure 3(b), the horizontal axis represents the communication speed, and the vertical axis represents the sensing SNR. The black dashed line represents the theoretical performance limit (Upper Bound).

[0358] The results are compared between the case where initial values ​​are selected randomly (NLO-R) and the case where the solution of a linear optimization technique is used as the initial value (NLO-A). In addition, the performance of the STAR-RIS system using the TS (Time Splitting) protocol is also presented. When using the TS protocol, time allocation Is is, It changes as follows. Here, And, am.

[0359] Consequently, most In terms of values, the ES protocol showed superior performance compared to the TS protocol, and it can be confirmed that the performance of NLO-A is better than that of NLO-R or ACES.

[0361] FIG. 4 is a diagram illustrating the relationship between transmission power and sensing SNR in a STAR-RIS-supported sensing communication integrated system according to an exemplary embodiment. The horizontal axis represents transmission power, and the vertical axis represents sensing SNR.

[0362] Referring to Fig. 4, the maximum transmission power of the communication user (CU) It can be seen that the sensing SNR increases as increases. Maximum transmission power of the communication user When this is low, a performance trade-off is observed between MEM-based SC and CC as the influence of interference signals on communication signals decreases. LCM showed superior performance to MEM in both SC and CC, and is subsequently further improved through penalty-based NLO. Overall, the ES protocol shows higher performance than the TS protocol, and performance improvement is pronounced when the maximum transmission power of the communication user is high.

[0364] The device described above may be implemented as a hardware component, a software component, and / or a combination of a hardware component and a software component. For example, the device and components described in the embodiments may be implemented using one or more general-purpose or special-purpose computers, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing unit may execute an operating system (OS) and one or more software applications executed on said operating system. Additionally, the processing unit may access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing unit may be described as being used as a single unit, but those skilled in the art will understand that the processing unit may include multiple processing elements and / or multiple types of processing elements. For example, the processing unit may include multiple processors or one processor and one controller. In addition, other processing configurations, such as parallel processors, are also possible.

[0365] Software may include computer programs, code, instructions, or a combination of one or more of these, and may configure a processing unit to operate as desired or command the processing unit independently or collectively. Software and / or data may be permanently or temporarily embodied in any type of machine, component, physical device, virtual equipment, computer storage medium or device, or transmitted signal wave so as to be interpreted by the processing unit or to provide instructions or data to the processing unit. Software may be distributed over networked computer systems and may be stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

[0366] The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., either alone or in combination. The program instructions recorded on the medium may be those specifically designed and configured for the embodiment, or they may be those known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. The hardware devices described above may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

[0367] Although the embodiments have been described above with reference to the limited drawings, those skilled in the art can make various modifications and variations from the description above. For example, suitable results can be achieved even if the described techniques are performed in a different order than described, and / or the components of the described system, structure, device, circuit, etc. are combined or assembled in a form different from described, or replaced or substituted by other components or equivalents.

[0368] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims set forth below. Explanation of the symbols

[0370] 110: Base Station 111: Array antenna 121: Wireless Channel 130: Sensing target 131: Wireless Channel 140: Communication user 141: Wireless Channel

Claims

Claim 1 A method of operation of a STAR-RIS-supported sensing-communication integrated system comprising: a step of transmitting a sensing signal to a sensing target using a linear array antenna; a step of receiving the transmitted sensing signal by reflecting or refracting the sensing signal reflected from the sensing target onto a reconfigurable intelligent reflective surface (RIS) using the linear array antenna, and receiving a communication signal from a communication user by reflecting or refracting it onto the reconfigurable intelligent reflective surface (RIS) using the linear array antenna; and a step of decoding the received communication signal by applying receiving beamforming to the received signal and detecting the sensing target using the received sensing signal. Claim 2 A method of operation of a STAR-RIS-supported sensing-communication integrated system, wherein, in claim 1, the reflection coefficient of the reconfigurable intelligent reflective surface (RIS) is determined according to the following Equation 1. [Equation 1] Here, , And, as, and All have positive values. , Is , is, , can be determined as shown in the following mathematical formula 2.[Mathematical Formula 2] Here, is a matrix It is the eigenvector corresponding to the largest eigenvalue of, and is a matrix It is the eigenvector corresponding to the largest eigenvalue of. And, am. is a wireless channel between the linear array antenna and the resettable intelligent reflective surface. is a wireless channel between the above-mentioned resettable intelligent reflective surface and the above-mentioned communication user, and is a wireless channel between the above-mentioned resettable intelligent reflective surface and the above-mentioned sensing target. Claim 3 A method of operation of a STAR-RIS-supported sensing-communication integrated system, wherein, in claim 1, the reflection coefficient of the reconfigurable intelligent reflective surface (RIS) is determined according to the following Equation 3. [Equation 3] Here, , And, as, and All have positive values. , Is , ...and can be determined as shown in the following mathematical formula 4.[Mathematical Formula 4] Here, is a matrix It is a singular vector corresponding to the largest singular value of, and is a singular vector corresponding to the second-largest singular value. And, am. is a wireless channel between the linear array antenna and the resettable intelligent reflective surface. is a wireless channel between the above-mentioned resettable intelligent reflective surface and the above-mentioned communication user, and is a wireless channel between the above-mentioned resettable intelligent reflective surface and the above-mentioned sensing target. Claim 4 In paragraphs 2 and 3, the above A method of operation for a STAR-RIS-supported sensing-communication integrated system in which the value of is determined as a value satisfying the following mathematical formula 5. [Mathematical Formula 5] Here, the constraint of Equation 5 is equal to Equation 6.[Equation 6] Here, And, am. is the average power of the reflection coefficient of the above-mentioned sensing target. Also, And, am. is the maximum transmission power of the above linear array antenna, and is the power of the sensing signal. is the maximum transmission power of the above communication user, and as, is the lowest communication speed of the above communication user. is the power of thermal noise. Claim 5 In paragraphs 2 and 3, the above A method of operation for a STAR-RIS-supported sensing-communication integrated system in which the value of is determined as a value satisfying the following mathematical formula 7. [Mathematical Formula 7] Here, as, is the lowest communication speed of the above communication user. And, is the maximum transmission power of the above communication user. is the power of thermal noise. Claim 6 A method of operation of a STAR-RIS-supported sensing-communication integrated system according to claim 1, wherein the reflection coefficient of the reconfigurable intelligent reflective surface (RIS) is determined to satisfy the following Equation 8. [Equation 8] Here, And, Is or It could be. Here, as, is the minimum communication speed of the above communication user. In addition, the reflection coefficient of the resettable intelligent reflective surface (RIS) is And, And, And, is a wireless channel between the linear array antenna and the resettable intelligent reflective surface. is a wireless channel between the above-mentioned resettable intelligent reflective surface and the above-mentioned communication user, and is a wireless channel between the above-mentioned resettable intelligent reflective surface and the above-mentioned sensing target. Here, is the power of the sensing signal, and is the power of the communication signal. is the power of thermal noise, and is the average power of the reflection coefficient of the sensing target, and is the number of symbols included in the sensing signal. Claim 7 In claim 1, the step of applying the receiving beamforming is a method of operation of a STAR-RIS-supported sensing-communication integrated system using a Minimum Mean Square Error (MMSE) beamforming vector.

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