Channel estimation method for smart medical treatment star-ris communication system

Abstract

The application discloses a channel estimation method for a smart medical STAR-RIS communication system, and belongs to the fields of wireless communication, STAR-RIS and channel estimation. In the STAR-RIS assisted single base station communication scenario of the smart medical STAR-RIS communication system, two different STAR-RIS transmission protocols (Energy Splitting, ES and Time Switching, TS) are considered, a least square algorithm is used to construct a minimum system channel estimation mean square error optimization problem of the two transmission protocols, and joint optimization design of a sending end training signal sequence and amplitude coefficients and phase coefficients of the STAR-RIS is given, so that downlink channel estimation is realized.

Description

Technical Field

[0001] The present invention belongs to the fields of wireless communications, STAR-RIS, and channel estimation, and in particular relates to a downlink channel estimation method for a STAR-RIS communication system for smart medical treatment. Background Art

[0002] In recent years, with the rapid development of communications and artificial intelligence technologies, 5G-enabled smart healthcare has injected new impetus into society, improving people's quality of life and well-being. However, smart healthcare often requires high-speed, low-latency communication equipment, and even more importantly, a stable and reliable communication environment. In the coming decades, the penetration rate of smart medical devices will continue to increase, placing higher demands on the performance of communication systems.

[0003] The simultaneously reflective and transmissive smart metasurface (STAR-RIS) is an emerging auxiliary device for wireless communication systems. Because it can simultaneously reflect and transmit incident signals, it offers a larger coverage area and more degrees of freedom than traditional, reflective smart metasurfaces. This allows it to better adapt to the needs of communication systems, intelligently control the wireless transmission environment, and thus improve communication system performance. In the future, STAR-RIS is expected to become a key component in ensuring the quality of smart medical communications. Existing research on STAR-RIS-assisted wireless communications primarily focuses on performance analysis and optimization for different communication scenarios. The literature C.Wu, X.Mu, Y.Liu, X.Gu and X.Wang,"Resource Allocation in STAR-RIS-Aided Networks:OMA and NOMA,"in IEEE Transactions on Wireless Communications,vol.21,no.9,pp.7653-7667,Sept.2022,doi:10.1109 / TWC.2022.3160151. analyzed the resource allocation problem of STAR-RIS working under NOMA and OMA respectively. Reference H.Niu, Z.Chu, F.Zhou, P.Xiao and N.Al-Dhahir,"Weighted Sum Rate Optimization for STAR-RIS-Assisted MIMO System,"in IEEE Transactions on Vehicular Technology,vol.71,no.2,pp.2122-2127,Feb.2022,doi:10.1109 / TVT.2021.3131568. The weighted sum rate optimization problem in STAR-RIS-assisted MIMO system is studied. Reference B. Zhao, C. Zhang, W. Yi and Y. Liu,"Ergodic Rate Analysis of STAR-RIS Aided NOMA Systems," in IEEE Communications Letters, vol. 26, no. 10, pp. 2297-2301, Oct. 2022, doi: 10.1109 / LCOMM.2022.3194363. The ergodic rate of the STAR-RIS Aided NOMA system was analyzed.Reference Y.Lin, Y.Shen and A.Li,"SimultaneousTransmission and Reflection Beamforming Design for RIS-Aided MU-MISO,"in IEEE Transactions on Vehicular Technology, vol.72, no.3, pp.4040-4045, March 2023, doi:10.1109 / TVT.2022.3214829. The active and passive joint beamforming problem of STAR-RIS-assisted multi-user system is studied.

[0004] However, all of the aforementioned research works are based on the assumption that downlink channel state information (CSI) can be effectively acquired. However, accurate CSI acquisition in STAR-RIS-assisted wireless communication systems is also a challenging problem. On the one hand, STAR-RIS has a large number of reflection / transmission units, resulting in a very large number of parameters that need to be estimated. On the other hand, although there has been a lot of work on channel estimation for wireless communication systems assisted by smart reflecting surfaces (RIS), these estimation methods cannot be directly applied to STAR-RIS-assisted scenarios. In addition, STAR-RIS has more controllable coefficients and a variety of transmission protocols, which makes channel estimation for STAR-RIS-assisted communication systems more complex.

[0005] In the paper C.Wu, C.You, Y.Liu, X.Gu and Y.Cai, "Channel Estimation for STAR-RIS-Aided Wireless Communication," in IEEE Communications Letters, vol. 26, no. 3, pp. 652-656, March 2022, doi: 10.1109 / LCOMM.2021.3139198, an uplink channel estimation method for STAR-RIS-assisted communication systems is proposed. The channel estimation mean square error performance of STAR-RIS operating under ES (energy splitting) and TS (time switching) transmission protocols is compared. However, the channel information obtained by this estimation method is actually the uplink channel information. The base station then indirectly obtains the downlink channel information based on the reciprocity of the channel. This method is not very applicable for frequency division duplex or some scenarios with imperfect channel reciprocity. Summary of the Invention

[0006] The purpose of the present invention is to solve the problems existing in the prior art and provide a downlink channel estimation method for a STAR-RIS communication system for smart medical care.

[0007] The specific technical solutions adopted in the present invention are as follows:

[0008] A channel estimation method for a smart medical STAR-RIS communication system includes the following steps:

[0009] S1. In the TS mode channel estimation preparation phase, the STAR-RIS operating mode is adjusted to the TS mode. The channel estimation time t within each coherence time is divided into a TS-reflection period t1 and a TS-transmission period t2, satisfying t1+t2=t. In the TS-reflection period t1, the incident signal is only reflected to the single-antenna user userR in the reflection coverage area of ​​the STAR-RIS. In the TS-transmission period t2, the incident signal is only transmitted to the single-antenna user userT in the transmission coverage area of ​​the STAR-RIS.

[0010] S2. In the channel estimation phase of the TS mode, a base station with K antennas is pre-deployed, and the TS-reflection period t1 is evenly divided into N symbol times. During each symbol time of the TS-reflection period, the base station sends a pre-designed training signal to the single-antenna user userR in the reflection coverage area. At the same time, the reflection phase of each working unit of STAR-RIS is adjusted and the reflection energy distribution coefficient is fixed. The single-antenna user userR in the reflection coverage area uses the least squares estimation method to estimate the downlink cascade channel, and the downlink cascade channel estimation value of the single-antenna user userR in the reflection coverage area under the TS mode is obtained. ; The TS-transmission period t2 is evenly divided into N symbol times. During each symbol time of the TS-transmission period, the base station sends a pre-designed training signal to the single-antenna user userT in the transmission coverage area. At the same time, the transmission phase of each working unit of STAR-RIS is adjusted and the transmission energy allocation coefficient is fixed. The single-antenna user userT in the transmission coverage area uses the least squares estimation method to perform channel estimation on the downlink cascade channel to obtain the downlink cascade channel estimation value of the single-antenna user userT in the transmission coverage area under TS mode. The STAR-RIS has L working units and satisfies N≥K(L+1);

[0011] S3: In the new channel estimation preparation phase, STAR-RIS is first adjusted to ES mode. During the channel estimation time t3 of each coherence time, the signal is simultaneously transmitted to the single-antenna user userT in the transmission coverage area of ​​STAR-RIS and the single-antenna user userR in the reflection coverage area of ​​STAR-RIS.

[0012] S4. In the new channel estimation stage, the channel estimation time t3 of the ES mode is divided into N symbol times. In each symbol time of the ES mode, the base station simultaneously sends a pre-designed training signal to the single-antenna user userR in the reflection coverage area and the single-antenna user userT in the transmission coverage area, and adjusts the reflection phase, transmission phase, and reflection and transmission energy distribution coefficients of each working unit of STAR-RIS. The single-antenna user userR in the reflection coverage area and the single-antenna user userT in the transmission coverage area use the least squares estimation method to simultaneously perform channel estimation on the downlink cascade channel, and correspondingly obtain the downlink cascade channel estimation value of the single-antenna user userR in the reflection coverage area and the downlink cascade channel estimation value of the single-antenna user userT in the transmission coverage area under the ES mode.

[0013] Based on the above solution, each step can be implemented in the following preferred specific manner.

[0014] Preferably, the total training signal function sent by the base station to the single-antenna user is in the form of:

[0015] X=[x(1),.....,x(N)] T =FS 1 / 2

[0016] Where x(1),.....,x(N) represent the training signals sent by the base station to the single-antenna user in the 1st symbol time,.....,Nth symbol time; X represents the total training signal sent by the base station to the single-antenna user; F is an N×K unitary matrix; S=X H X is a K×K positive semidefinite matrix; T represents the transpose.

[0017] Furthermore, the functional form of the unitary matrix F is:

[0018]

[0019] Among them, F(n,k) represents the element in the nth row and kth column of the unitary matrix F; 1≤k≤K represents the kth column of the unitary matrix F; 1≤n≤N represents the nth row of the unitary matrix F; m≥L+1 represents the intermediate variable.

[0020] Furthermore, the semi-positive definite matrix S can be obtained by solving the following convex optimization problem, the function form of which is:

[0021]

[0022]

[0023] Wherein, st represents the constraint condition for solving the convex optimization problem; P krepresents the kth diagonal element of the semi-positive definite matrix S; σ 2 represents the noise power of a single antenna user; P represents the maximum power that the base station can provide.

[0024] As a preference, the reflection phase of the i-th working unit of STAR-RIS in TS mode is The function form is:

[0025]

[0026] Transmission phase of the i-th working unit of STAR-RIS in TS mode The function form is:

[0027]

[0028] Wherein, 1≤n≤N represents the nth symbol time in the TS-reflection period; 1≤i≤L represents the i-th STAR-RIS working unit; and j represents an imaginary unit.

[0029] Furthermore, the reflection phase of the i-th working unit of STAR-RIS in ES mode is The function form is:

[0030]

[0031] Transmission phase of the i-th working unit of STAR-RIS in ES mode The function form is:

[0032]

[0033] As a preference, the downlink cascade channel estimation value of the single-antenna user userR in the reflection coverage area in TS mode The function form is:

[0034]

[0035] Downlink cascade channel estimation value of single-antenna user userT in the transmission coverage area in TS mode The function form is:

[0036]

[0037] Among them, X Φr TS Represents the training signal, reflection energy distribution coefficient, and reflection phase in TS mode Related parameters; X Φt TS Represents the training signal, transmission energy distribution coefficient, and transmission phase in TS mode Related parameters; y r TS Represents the received signal of single-antenna user userR in the reflection coverage area in TS mode; t TS represents the received signal of user T with a single antenna in the transmission coverage area in TS mode; -1 represents inversion; H represents conjugate transpose.

[0038] Furthermore, the downlink cascade channel estimation value of the single-antenna user userR in the reflection coverage area in ES mode is The function form is:

[0039]

[0040] Downlink cascade channel estimation value of single-antenna user userT in the transmission coverage area in ES mode The function form is:

[0041]

[0042] Among them, X Φr ES Indicates the training signal, reflection energy distribution coefficient, and reflection phase in ES mode Related parameters; X Φt ES Represents the training signal, transmission energy distribution coefficient, and transmission phase in ES mode Related parameters; y r ES Represents the received signal of the single-antenna user userR in the reflection coverage area in ES mode; t ES Indicates the received signal of user T with a single antenna in the transmission coverage area in ES mode.

[0043] Furthermore, the received signal y of the single-antenna user userR in the reflection coverage area in TS mode is r TS The function form is:

[0044] y r TS =X Φr TS g r TS +n r TS

[0045] Received signal y for user T with a single antenna in the transmission coverage area in TS mode t TS The function form is:

[0046] yt TS =X Φt TS g t TS +n t TS

[0047] Received signal y of single-antenna user userR in the reflection coverage area in ES mode r ES The function form is:

[0048] y r ES =X Φr ES g r ES +n r ES

[0049] Received signal y for a single-antenna user userT in the transmission coverage area in ES mode t ES The function form is:

[0050] y t ES =X Φt ES g t ES +n t ES

[0051] Among them, n r TS 、n t TS 、n r ES 、n t ES All have zero mean and variance σ 2 Complex additive Gaussian white noise; g r TS 、g t TS 、g r ES 、g t ES are both vectors containing L cascade channel information.

[0052] Preferably, in the TS mode, the reflection and transmission energy distribution coefficients are both fixed at 1; in the ES mode, the reflection and transmission energy distribution coefficients are both 0.707.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] Wider Applicability: Existing research on channel estimation for STAR-RIS-assisted wireless communication systems is limited, and most studies focus on uplink channel estimation methods, which then use channel reciprocity to derive downlink channel information. However, this method is not suitable for frequency division multiplexing (FDM) scenarios. The proposed downlink channel estimation method for STAR-RIS-assisted wireless communication systems directly estimates the downlink channel, offering wider applicability.

[0055] Low system training sequence requirements: Traditionally, for uplink channel estimation, each user in the system needs to send a training sequence to the base station for channel estimation. This leads to significant training sequence overhead in scenarios with a large number of users. However, the downlink channel estimation method proposed in this invention only requires the base station to send a training sequence once, which is then shared by all users in the system to complete channel estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 is a flow chart of the steps of the present invention;

[0057] Figure 2 Schematic diagram of system channel estimation under the TS transmission protocol in this embodiment;

[0058] Figure 3 Schematic diagram of system channel estimation under the ES transmission protocol of this embodiment;

[0059] Figure 4 The following is a comparison chart of the theoretical value and simulation results of the system channel estimation results when STAR-RIS works under the TS protocol and the ES protocol respectively in this embodiment;

[0060] Figure 5 1 is a comparison chart of the channel estimation performance between the method of the present invention and the random phase design method when STAR-RIS of this embodiment works under the TS protocol and the ES protocol respectively;

[0061] Figure 6 This figure shows the simulation analysis results of the effect of the setting of the transmission / reflection amplitude coefficient of each working unit on the channel estimation performance of the transmission user / reflection user and the system when STAR-RIS operates in the ES transmission protocol in this embodiment. DETAILED DESCRIPTION

[0062] In order to make the above-mentioned objects, features and advantages of the present invention more clearly understood, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways than those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below. The technical features in the various embodiments of the present invention can be combined accordingly without conflicting with each other.

[0063] like Figure 1 As shown, for a STAR-RIS-assisted reflection / transmission user wireless communication system, in a preferred implementation of the present invention, a channel estimation method for a smart medical STAR-RIS communication system is provided, which takes into account the two working protocols (TS and ES) of STAR-RIS, constructs the optimization problem of minimizing the mean square error of the system channel estimation under the two working protocols, and provides a joint optimization design scheme for the STAR-RIS amplitude, phase coefficient and transmitter training signal sequence under the two working protocols.

[0064] The above method includes the following steps S1 to S4, and the specific implementation processes thereof are described in detail below.

[0065] S1. In the channel estimation preparation stage of the TS mode, the working mode of STAR-RIS (smart metasurface capable of simultaneous reflection and transmission) is adjusted to the TS (time switching) mode, and the channel estimation time t within each coherence time is divided into the TS-reflection period t1 and the TS-transmission period t2, satisfying t1+t2=t, wherein in the TS-reflection period t1, only the incident signal is reflected to the single-antenna user userR in the reflection coverage area of ​​STAR-RIS, and in the TS-transmission period t2, only the incident signal is transmitted to the single-antenna user userT in the transmission coverage area of ​​STAR-RIS.

[0066] It should be noted that if Figure 2 As shown in the figure, consider a two-user STAR-RIS-assisted wireless communication system. The base station has K antennas, the STAR-RIS has L reflection / transmission units, and two single-antenna medical communication devices, userT and userR, are located in the transmission and reflection zones of the STAR-RIS, respectively. When the STAR-RIS operates using the TS transmission protocol, the operating period is divided into a reflection period t1 and a transmission period t2, where t = t1 + t2. During the transmission period, the incident signal can only be transmitted by the STAR-RIS to userT. Similarly, during the reflection period, the incident signal can only be reflected by the STAR-RIS to userR.

[0067] S2. In the channel estimation phase of the TS mode, a base station with K antennas is pre-deployed. The TS-reflection period t1 is divided into N symbol times. During each symbol time of the TS-reflection period, the base station sends a pre-designed training signal to the single-antenna user userR in the reflection coverage area. At the same time, the reflection phase of each working unit of the STAR-RIS is adjusted and the reflection energy allocation coefficient is fixed. The single-antenna user userR in the reflection coverage area uses the least squares estimation method to estimate the downlink cascade channel, and obtain the downlink cascade channel estimation value of the single-antenna user userR in the reflection coverage area under the TS mode. The TS-transmission period t2 is divided into N symbol times. During each symbol time of the TS-transmission period, the base station sends a pre-designed training signal to the single-antenna user userT in the transmission coverage area. At the same time, the transmission phase of each working unit of the STAR-RIS is adjusted and the transmission energy allocation coefficient is fixed. The single-antenna user userT in the transmission coverage area uses the least squares estimation method to estimate the downlink cascade channel, and obtain the downlink cascade channel estimation value of the single-antenna user userT in the transmission coverage area under the TS mode. The STAR-RIS has L working units, and N≥K(L+1) is satisfied.

[0068] It should be noted that, in step S2 of the present invention, the function form of the total training signal sent by the base station to the single-antenna user is:

[0069] X=[x(1),.....,x(N)] T =FS 1 / 2

[0070] Where [x(1),.....,x(N)] represents the training signal sent by the base station to the single-antenna user in the 1st symbol time,.....,Nth symbol time; X represents the total training signal sent by the base station to the single-antenna user; T represents the transpose; F is an N×K unitary matrix, and the corresponding function form is:

[0071]

[0072] Where F(n,k) represents the nth row and kth column element of the unitary matrix F; 1≤k≤K represents the kth column of the unitary matrix F; 1≤n≤N represents the nth row of the unitary matrix F; m≥L+1 represents the intermediate variable; S=X H X is a K×K positive semidefinite matrix, which can be obtained by solving the following convex optimization problem, the function form of which is:

[0073]

[0074]

[0075] Wherein, st represents the constraint condition for solving the convex optimization problem; P k represents the kth diagonal element of the semi-positive definite matrix S; σ 2 represents the noise power of a single antenna user; P represents the maximum power that the base station can provide.

[0076] Furthermore, the reflection phase of the i-th working unit of STAR-RIS in TS mode The function form is:

[0077]

[0078] Furthermore, the transmission phase of the i-th working unit of STAR-RIS in TS mode The function form is:

[0079]

[0080] Wherein, 1≤n≤N represents the nth symbol time in the TS-reflection period; 1≤i≤L represents the i-th STAR-RIS working unit; and j represents an imaginary unit.

[0081] Furthermore, the downlink cascade channel estimation value of the single-antenna user userR in the reflection coverage area in TS mode is The function form is:

[0082]

[0083] Furthermore, the downlink cascade channel estimation value of the single-antenna user userT in the transmission coverage area in TS mode is The function form is:

[0084]

[0085] Among them, X Φr TS Represents the training signal, reflection energy distribution coefficient, and reflection phase in TS mode Related parameters; X Φt TS Represents the training signal, transmission energy distribution coefficient, and transmission phase in TS mode Related parameters; y r TS Represents the received signal of single-antenna user userR in the reflection coverage area in TS mode; t TS represents the received signal of user T with a single antenna in the transmission coverage area in TS mode; -1 represents inversion; H represents conjugate transpose.

[0086] Furthermore, the received signal y of the single-antenna user userR in the reflection coverage area in TS mode is r TS The function form is:

[0087] y r TS =X Φr TS g r TS +n r TS

[0088] Furthermore, the single-antenna user userT in the transmission coverage area in TS mode receives the signal y t TS The function form is:

[0089] y t TS =X Φt TS g t TS +n t TS

[0090] Among them, n r TS 、n t TS All have zero mean and variance σ 2 Additive white Gaussian noise (AWGN); g r TS 、g t TS are both vectors containing L cascade channel information.

[0091] Furthermore, in TS mode, the reflection and transmission energy distribution coefficients are both fixed at 1.

[0092] The following briefly introduces the channel estimation under the TS protocol in step S2 to facilitate understanding of the principle of the estimation process.

[0093] 1.1. Establishing a system model

[0094] In this embodiment, the channel estimation during the reflection period is considered first. The base station sends a training signal to the user end within N (N≥K×L) symbol times, such as Figure 2 Due to factors such as obstruction, the direct channel between the base station and the user is blocked, so the training signal can only reach STAR-RIS first, and then be reflected by STAR-RIS to the receiving user userR. Therefore, the received signal of userR in the nth symbol time can be expressed as:

[0095]

[0096] Among them, H i is the channel parameter from the base station to the i-th working unit of STAR-RIS, which is a K×1 complex matrix; β R,i,n is the reflection amplitude coefficient (reflection energy distribution coefficient) of the i-th working unit of STAR-RIS; h r,i is the channel parameter from userR to the i-th reflection unit of STAR-RIS, a 1×1 complex matrix; x(n) is the training sequence sent by the base station in the n-th symbol time, an M×1 complex vector. To facilitate subsequent channel estimation, Equation (1.1) can be rewritten as Equation (1.2):

[0097] y r TS (n)=(X Φr TS (n)) T g r TS +n r TS (n)(1.2)

[0098]

[0099]

[0100] g r,i =h r,i H i

[0101] Among them, β R,1,n ,......,β R,L,n It represents the reflection amplitude coefficient of the 1st, ....., Lth working unit of STAR-RIS; g represents the reflection phase of the 1st, ..., Lth working unit of STAR-RIS within the nth symbol time; r,i represents the cascade channel between the base station, STAR-RIS i-th working unit and userR; g r TS represents a vector containing L cascade channel information, which is the parameter to be estimated; X Φr TS (n) represents the parameters related to the training signal, the reflection energy distribution coefficient, and the reflection phase within the nth symbol time. It is a vector of adjustable parameters and can be regarded as prior information and is a parameter to be optimized.

[0102] Therefore, during all N symbol times, the total received signal of userR can be expressed as:

[0103] y rTS =X Φr TS g r TS +n r TS (1.3)

[0104] in:

[0105]

[0106]

[0107]

[0108]

[0109]

[0110] Among them, Θ i Represents an intermediate variable.

[0111] 1.2. Constructing the Optimization Problem

[0112] According to the least squares estimation method, the channel estimation value for the single-antenna user userR is for:

[0113]

[0114] Therefore, the MSE of the channel estimation is:

[0115]

[0116] In order to ensure the convenience and effectiveness of amplitude control in practice, this embodiment considers that the amplitude coefficient of the i-th working unit of STAR-RIS remains unchanged within N symbol times and takes the maximum value as 1, that is:

[0117] β R,i,1 =...=β R,i,N =1,i=1...L(1.6)

[0118] Therefore, the original optimization problem of channel estimation for R user under the TS protocol is:

[0119]

[0120] sttr(XX H )≤P(1.7a)

[0121]

[0122] Among them, Equation (1.7a) represents the power constraint of the transmitted training signal sequence; Equation (1.7b) represents the value constraint of the STAR-RIS phase coefficient.

[0123] 1.3. Solving Optimization Problems

[0124] Since the objective function and constraints of the optimization problem P1 are non-convex, that is, it is a non-convex problem, this embodiment first converts it into a convex problem to facilitate solution. According to the matrix inequality:

[0125]

[0126] Where Δ(1)...Δ(M) represents the M diagonal blocks of Δ. The equality of the above inequality holds if and only if Δ is a block diagonal matrix. Therefore, for the optimization problem P1, its optimal solution must satisfy the following conditions:

[0127] X H Θ i H Θ j X=0,1≤i≠j≤L (1.9)

[0128] X H Θ i H Θ i X≠0,1≤i≤L (1.10)

[0129] Therefore, for the optimization problem P1, the optimal solution is designed as follows:

[0130] X=FS 1 / 2 (1.11)

[0131]

[0132] Where S = X H X is a K×K positive semidefinite matrix; F is an N×K unitary matrix, and the elements in the nth row and kth column of F are:

[0133]

[0134] The following proves the effectiveness of the designs (1.12) and (1.13):

[0135] To prove:

[0136]

[0137] X H Θ i H Θ i X≠0,1≤i≤L

[0138] Proof:

[0139]

[0140] X H X≠0,1≤i≤L

[0141] Where: f k is the kth column of F; f k′ is the k′th column of F.

[0142] And X H X≠0 is obviously true, so we only need to prove

[0143]

[0144]

[0145]

[0146] Among them, (m(k′-k))-(ij)≠0), the proof is complete.

[0147] Substituting (1.12) and (1.13) into the optimization problem P1, we can obtain the optimization problem P2:

[0148]

[0149] sttr(S)≤P(1.14a)

[0150] According to formula (1.8), S can be designed as a diagonal matrix, that is, S = diag(p1,...,P k ). Set S=diag(p1,...,P k ) into the optimization problem P2, we can get the optimization problem P3:

[0151]

[0152]

[0153] The optimization problem P3 is obviously a convex optimization problem and can be solved using convex optimization solving tools.

[0154] The above is the channel estimation during the reflection period. The process and method of channel estimation for T user during the transmission period are exactly the same as the above. Therefore, the overall channel estimation optimization problem P4 of the system under the TS protocol can be finally expressed as:

[0155]

[0156]

[0157] S3. In the new channel estimation preparation phase, STAR-RIS's own operating mode is adjusted to ES (Energy Splitting) mode. During the channel estimation time t3 of each coherence time, the signal is simultaneously transmitted to the single-antenna user userT in the projection coverage area of ​​STAR-RIS and the single-antenna user userR in the reflection coverage area of ​​STAR-RIS.

[0158] S4. In the new channel estimation stage, the channel estimation time t3 of the ES mode is divided into N symbol times. In each symbol time of the ES mode, the base station simultaneously sends a pre-designed training signal to the single-antenna user userR in the reflection coverage area and the single-antenna user userT in the transmission coverage area, and adjusts the reflection phase, transmission phase, and reflection and transmission energy distribution coefficients of each working unit of STAR-RIS. The single-antenna user userR in the reflection coverage area and the single-antenna user userT in the transmission coverage area use the least squares estimation method to simultaneously perform channel estimation on the downlink cascade channel, and correspondingly obtain the downlink cascade channel estimation value of the single-antenna user userR in the reflection coverage area and the downlink cascade channel estimation value of the single-antenna user userT in the transmission coverage area under the ES mode.

[0159] It should be noted that in step S4 of the present invention, the reflection phase of the i-th working unit of STAR-RIS in ES mode is The function form is:

[0160]

[0161] Furthermore, the transmission phase of the i-th working unit of STAR-RIS in ES mode The function form is:

[0162]

[0163] Furthermore, the downlink cascade channel estimation value of the single-antenna user userR in the reflection coverage area in ES mode is The function form is:

[0164]

[0165] Furthermore, the downlink cascade channel estimation value of the single-antenna user userT in the transmission coverage area in ES mode is The function form is:

[0166]

[0167] Among them, X Φr ESIndicates the training signal, reflection energy distribution coefficient, and reflection phase in ES mode Related parameters; X Φt ES Represents the training signal, transmission energy distribution coefficient, and transmission phase in ES mode Related parameters; y r ES Represents the received signal of the single-antenna user userR in the reflection coverage area in ES mode; t ES Indicates the received signal of user T with a single antenna in the transmission coverage area in ES mode.

[0168] Furthermore, the received signal y of the single-antenna user userR in the reflection coverage area in ES mode is r ES The function form is:

[0169] y r ES =X Φr ES g r ES +n r ES

[0170] Furthermore, the single-antenna user userT in the transmission coverage area in ES mode receives the signal y t ES The function form is:

[0171] y t ES =X Φt ES g t ES +n t ES

[0172] Among them, n r ES 、n t ES All have zero mean and variance σ 2 Complex additive Gaussian white noise; g r ES 、g t ES are both vectors containing L cascade channel information.

[0173] Furthermore, in the ES mode, the reflection and transmission energy distribution coefficients are both 0.707.

[0174] The following briefly introduces the channel estimation under the ES protocol in step S4 to facilitate understanding of the principle of the estimation process.

[0175] 2.1. Establishing a system model

[0176] In this embodiment, Figure 3 As shown in the figure, when STAR-RIS operates in the ES transmission protocol, the incident signal will be reflected and transmitted simultaneously after reaching STAR-RIS, and STAR-RIS will independently control the amplitude and phase of the reflected signal and the transmitted signal.

[0177] Similar to the channel estimation process under the TS protocol, the base station sends a training signal to the user end within N (N≥M×L) symbol times, such as Figure 3 Due to factors such as obstruction, the direct channels dt / dr between the base station and the two users are blocked, so the training signal can only reach STAR-RIS first, and then be simultaneously reflected / transmitted by STAR-RIS to the receiving users userR / userT. Similarly, to facilitate the convenience and effectiveness of amplitude control in practice, this embodiment considers that the amplitude coefficients of reflection and transmission remain unchanged within N symbol times. Therefore, in the nth symbol time, the received signals of userR and userT can be expressed as:

[0178]

[0179]

[0180] Among them, H i β is the channel parameter from the base station to the i-th working unit of STAR-RIS, which is an M×1 complex matrix. R,i is the reflection amplitude coefficient (reflection energy distribution coefficient) of the i-th working unit of STAR-RIS; β T,i h is the transmission amplitude coefficient (transmission energy distribution coefficient) of the i-th working unit of STAR-RIS. r,i is the channel parameter from userR to the i-th reflection unit of STAR-RIS, which is a 1×1 complex matrix; h t,i is the channel parameter from userT to the i-th reflection unit of STAR-RIS, a 1×1 complex matrix; x(n) is the training sequence sent by the base station in the n-th symbol time, an M×1 complex vector. To facilitate subsequent channel estimation, (2.1) and (2.2) can be further rewritten as:

[0181] y r ES (n)=(X Φr ES (n)) T g r ES +n r ES(n)(2.3)

[0182] y t ES (n)=(X Φt ES (n)) T g t ES +n t ES (n)(2.4)

[0183] in:

[0184]

[0185]

[0186] g r,i =h r,i H i

[0187]

[0188]

[0189] g t,i =h t,i H i

[0190] Among them, β R,1 ,......,β R,L It represents the reflection amplitude coefficient of the 1st, ....., Lth working unit of STAR-RIS, β T,1 ,......,β T,L represents the transmission amplitude coefficient of the 1st, ....., Lth working unit of STAR-RIS; Indicates the reflection phase of the 1st, ..., Lth working unit of STAR-RIS within the nth symbol time, g represents the transmission phase of the 1st, ..., Lth working unit of STAR-RIS within the nth symbol time; r,i represents the cascade channel between the base station, STAR-RIS i-th working unit and userR, g t,i represents the cascade channel between the base station, the i-th working unit of STAR-RIS and userT; g r ES 、g t ES Both represent vectors containing L cascade channel information, and are parameters to be estimated; X Φr ES(n) represents the parameters related to the training signal, the reflection energy distribution coefficient, and the reflection phase within the nth symbol time. It is a vector of adjustable parameters and can be regarded as prior information and is the parameter to be optimized. Φt ES (n) represents the parameters related to the training signal, the transmission energy distribution coefficient, and the transmission phase within the nth symbol time. It is a vector of adjustable parameters and can be regarded as prior information and is a parameter to be optimized.

[0191] Therefore, in all N symbol times, the total received signals of userR and userT can be expressed as:

[0192] y r ES =X Φr ES g r ES +n r ES (2.5)

[0193] y t ES =X Φt ES g t ES +n t ES (2.6)

[0194] in:

[0195]

[0196]

[0197]

[0198]

[0199]

[0200]

[0201]

[0202]

[0203]

[0204] Where: Θ R,i 、Θ T,i Both represent intermediate variables.

[0205] 2.2. Constructing the Optimization Problem

[0206] The channel estimation process is similar to that under the TS protocol and will not be described in detail here. Therefore, this embodiment uses the LS estimation method to obtain the original optimization problem P5 of the system channel estimation under the ES protocol:

[0207]

[0208] sttr(XX H )≤P(2.7a)

[0209] β R,i 2 +β T,i 2 ≤1(2.7b)

[0210]

[0211]

[0212] Where, Equation (2.7a) represents the power constraint for sending the training sequence, and P is the maximum power that the base station can provide. Equation (2.7b) represents the energy allocation constraint for STAR-RIS under the ES protocol. Equation (2.7c) represents the value constraint for the STAR-RIS phase coefficient. Equation (2.7d) represents the coupling constraint between the reflected and transmitted phases of the STAR-RIS working unit.

[0213] It can be found that the optimization problem under ES is more complex than that under TS, and there are more constraints, which increases the difficulty of solving.

[0214] 2.3. Solving the optimization problem

[0215] According to the above derivation process, for the optimization problem P5, its optimal solution must meet the following conditions:

[0216] X H Θ χ,i H Θ χ,j X=0,χ∈{T,R};1≤i≠j≤L(2.8)

[0217] X H Θ χ,i H Θ χ,i X≠0,χ∈{T,R}; 1≤i≤L(2.9)

[0218] For the optimization problem P5, the training signal X and the reflected phase of the i-th working unit of STAR-RIS are The design of the reflected phase and training signal under the TS protocol can still be adopted, that is, But due to the constraint (2.7d), the transmission phase The design is:

[0219]

[0220] By proving the effectiveness of the design of the reflection phase and training signal under the TS protocol, the validity of the above formula (2.10) can be proved by the same logic, which will not be repeated here.

[0221] Substituting the reflection phase, transmission phase and training signal under the ES protocol into the optimization problem P5, we can obtain the optimization problem P6:

[0222]

[0223] sttr(S)≤P(2.11a)

[0224] β R,i 2 +β T,i 2 ≤1(2.11b)

[0225] Similarly, let S=diag(p1,...,P k ) into the optimization problem P6, we can get the optimization problem P7:

[0226]

[0227]

[0228] β R,i 2 +β T,i 2 ≤1(2.12b)

[0229] Easy to get, when β R,i 2 =β T,i 2 =0.5, The minimum value is obtained, so the optimization problem P7 can be simplified to:

[0230]

[0231]

[0232] Problem P8 is obviously a convex optimization problem and can be solved using convex optimization solving tools.

[0233] Example

[0234] The following simulations illustrate the performance of the proposed method. The simulation parameters are set as: K = 4, L = 3, N = 13, m = 6, P = 30 dBm, the distance between the BS and STAR-RIS is 50 meters, and the distance between userT and userR and STAR-RIS is 15 meters. All channels are modeled as Rice fading channels, and the Rice factor is set to 10 dB. The path loss determined by distance is defined as: l = β(d / d0) -α , where β = -30 dB represents the path loss at the reference distance d0 = 1 m, α is the path loss index, and the signal path loss index between the base station and STAR-RIS and the signal path loss index between STAR-RIS and the two users are set to 2.8 and 2.2, respectively.

[0235] Figure 4 The comparison between the theoretical value and simulation results of the system channel estimation results when STAR-RIS works in TS protocol and ES protocol respectively under the parameter design method proposed in this invention. The horizontal axis is set to the system signal-to-noise ratio, and the vertical axis is set to the normalized mean square error of the channel estimation. Figure 4 As shown in Figure 3, the derived theoretical channel estimation values ​​are consistent with the simulation results.

[0236] Figure 5 The figure compares the channel estimation performance of the phase design method proposed in this invention with that of a random phase design method when STAR-RIS operates under the TS and ES protocols, respectively. The horizontal axis represents the system signal-to-noise ratio, and the vertical axis represents the normalized mean square error (NMSE) of the channel estimation. From the perspective of the transmission protocol used by STAR-RIS, TS performs better than ES, but TS consumes more training sequences and training time. In terms of phase design effectiveness, the channel estimation performance using the phase design proposed in this invention is superior for both TS and ES.

[0237] Figure 6 This is a simulation analysis of the effect of the transmission / reflection amplitude coefficient setting of each working unit on the channel estimation performance of the transmission user / reflection user and the system when STAR-RIS works in the ES transmission protocol. t , represents the transmission amplitude coefficient of each working unit, and the vertical axis is set to the normalized mean square error of the channel estimation. First, as the horizontal axis increases, the power allocated by STAR-RIS to the transmission side user is also greater, and the channel estimation performance of the transmission side user is also better. Correspondingly, the channel estimation performance of the reflection side user is getting worse and worse. At the same time, it can be seen that the channel estimation performance of the system is in beta t The optimum value is achieved when the amplitude coefficient is 0.5, which proves the rationality of the amplitude coefficient setting proposed in the present invention.

[0238] The embodiment described above is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Persons skilled in the art may make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, any technical solution obtained by equivalent substitution or equivalent transformation falls within the scope of protection of the present invention.

Claims

1. A channel estimation method for a smart medical STAR-RIS communication system, characterized in that: The following steps are involved: S1. In the TS mode channel estimation preparation phase, the STAR-RIS operating mode is adjusted to the TS mode. The channel estimation time within each coherence time is divided into a TS-reflection period and a TS-transmission period. During the TS-reflection period, the incident signal is only reflected to the single-antenna user in the STAR-RIS reflection coverage area. During the TS-transmission period, the incident signal is only transmitted to the single-antenna user in the STAR-RIS transmission coverage area. S2. In the channel estimation phase of the TS mode, a base station with K antennas is pre-deployed. The TS-reflection period is divided into N symbol times. During each symbol time of the TS-reflection period, the base station sends a pre-designed training signal to the single-antenna user in the reflection coverage area. At the same time, the reflection phase of each working unit of the STAR-RIS is adjusted and the reflection energy distribution coefficient is fixed. The single-antenna user in the reflection coverage area uses the least squares estimation method to estimate the downlink cascade channel, and the downlink cascade channel estimation value of the single-antenna user in the reflection coverage area under the TS mode is obtained. The TS-transmission period is divided into N symbol times. During each symbol time of the TS-transmission period, the base station sends a pre-designed training signal to a single-antenna user in the transmission coverage area. At the same time, the transmission phase of each working unit of the STAR-RIS is adjusted and the transmission energy allocation coefficient is fixed. The single-antenna user in the transmission coverage area uses the least squares estimation method to estimate the downlink cascade channel, and obtains the downlink cascade channel estimation value of the single-antenna user in the transmission coverage area in the TS mode. The STAR-RIS has L working units, and N ≥ K (L + 1) is satisfied. S3. In the new channel estimation preparation phase, STAR-RIS is first adjusted to ES mode. During the channel estimation time of each coherence time, the signal is simultaneously transmitted to single-antenna users in the transmission coverage area of ​​STAR-RIS and single-antenna users in the reflection coverage area of ​​STAR-RIS. S4. In the new channel estimation stage, the channel estimation time of the ES mode is evenly divided into N symbol times. In each symbol time of the ES mode, the base station simultaneously sends a pre-designed training signal to the single-antenna user in the reflection coverage area and the single-antenna user in the transmission coverage area, and adjusts the reflection phase, transmission phase, and reflection and transmission energy distribution coefficients of each working unit of STAR-RIS. The single-antenna user in the reflection coverage area and the single-antenna user in the transmission coverage area simultaneously use the least squares estimation method to perform channel estimation on the downlink cascade channel, and correspondingly obtain the downlink cascade channel estimation value of the single-antenna user in the reflection coverage area and the downlink cascade channel estimation value of the single-antenna user in the transmission coverage area under the ES mode.

2. A channel estimation method for a smart medical STAR-RIS communication system according to claim 1, characterized in that: The total training signal function sent by the base station to the single-antenna user is: X=[x(1),.....,x(N)] T =FS 1 / 2 Where x(1),.....,x(N) represent the training signals sent by the base station to the single-antenna user in the 1st symbol time,.....,Nth symbol time; X represents the total training signal sent by the base station to the single-antenna user; F is an N×K unitary matrix; S=X H X is a K×K positive semidefinite matrix; T represents the transpose.

3. A channel estimation method for a smart medical STAR-RIS communication system according to claim 2, characterized in that: The functional form of the unitary matrix F is: Among them, F(n,k) represents the element in the nth row and kth column of the unitary matrix F; 1≤k≤K represents the kth column of the unitary matrix F; 1≤n≤N represents the nth row of the unitary matrix F; m≥L+1 represents the intermediate variable.

4. A channel estimation method for a smart medical STAR-RIS communication system according to claim 2, characterized in that: The semi-positive definite matrix S can be obtained by solving the following convex optimization problem, the function form of which is: Wherein, st represents the constraint condition for solving the convex optimization problem; P k represents the kth diagonal element of the semi-positive definite matrix S; σ 2 represents the noise power of a single antenna user; P represents the maximum power that the base station can provide.

5. A channel estimation method for a smart medical STAR-RIS communication system according to claim 1, characterized in that: Reflection phase of the i-th working unit of STAR-RIS in TS mode The function form is: Transmission phase of the i-th working unit of STAR-RIS in TS mode The function form is: Wherein, 1≤n≤N represents the nth symbol time in the TS-reflection period; 1≤i≤L represents the i-th STAR-RIS working unit; and j represents an imaginary unit.

6. A channel estimation method for a smart medical STAR-RIS communication system according to claim 5, characterized in that: Reflection phase of the i-th working unit of STAR-RIS in ES mode The function form is: Transmission phase of the i-th working unit of STAR-RIS in ES mode The function form is:

7. A channel estimation method for a smart medical STAR-RIS communication system according to claim 1, characterized in that: Downlink cascade channel estimation value of single-antenna user userR in the reflection coverage area in TS mode The function form is: Downlink cascade channel estimation value of single-antenna user userT in the transmission coverage area in TS mode The function form is: Among them, X Φr TS Represents the training signal, reflection energy distribution coefficient, and reflection phase in TS mode Related parameters; X Φt TS Represents the training signal, transmission energy distribution coefficient, and transmission phase in TS mode Related parameters; y r TS Represents the received signal of single-antenna user userR in the reflection coverage area in TS mode; t TS represents the received signal of user T with a single antenna in the transmission coverage area in TS mode; -1 represents inversion; H represents conjugate transpose.

8. A channel estimation method for a smart medical STAR-RIS communication system according to claim 7, characterized in that: Downlink cascade channel estimation value of single-antenna user userR in the reflection coverage area in ES mode The function form is: Downlink cascade channel estimation value of single-antenna user userT in the transmission coverage area in ES mode The function form is: Among them, X Φr ES Indicates the training signal, reflection energy distribution coefficient, and reflection phase in ES mode Related parameters; X Φt ES Represents the training signal, transmission energy distribution coefficient, and transmission phase in ES mode Related parameters; y r ES Represents the received signal of the single-antenna user userR in the reflection coverage area in ES mode; t ES Indicates the received signal of user T with a single antenna in the transmission coverage area in ES mode.

9. A channel estimation method for a smart medical STAR-RIS communication system according to claim 8, characterized in that: Received signal y of single-antenna user userR in the reflection coverage area in TS mode r TS The function form is: y r TS =X Φr TS g r TS +n r TS Received signal y for user T with a single antenna in the transmission coverage area in TS mode t TS The function form is: y t TS =X Φt TS g t TS +n t TS Received signal y of single-antenna user userR in the reflection coverage area in ES mode r ES The function form is: y r ES =X Φr ES g r ES +n r ES Received signal y for a single-antenna user userT in the transmission coverage area in ES mode t ES The function form is: y t ES =X Φt ES g t ES +n t ES Among them, n r TS 、n t TS 、n r ES 、n t ES All have zero mean and variance σ 2 Complex additive Gaussian white noise; g r TS 、g t TS 、g r ES 、g t ES are both vectors containing L cascade channel information.

10. A channel estimation method for a smart medical STAR-RIS communication system according to claim 1, characterized in that: In TS mode, the reflection and transmission energy distribution coefficients are both fixed at 1; in ES mode, the reflection and transmission energy distribution coefficients are both 0.707.

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