Terahertz Intelligent Metasurface Multi-User Communication System and Broadband Precoding Method

Abstract

The present invention provides a terahertz intelligent metasurface multi-user communication system and a broadband precoding method. The system includes: a base station and a delay-based RIS system; the base station includes a terahertz multi-antenna system for actively beamforming the multi-antenna array and controlling the amplitude and phase of each antenna; the delay-based RIS system includes assisting the terahertz multi-antenna system and performing passive beamforming. The present invention utilizes the terahertz intelligent metasurface multi-user communication system and the broadband precoding method to jointly achieve active and passive beamforming with the original multi-antenna system, alleviates the beam dispersion phenomenon, and improves the transmission efficiency of the terahertz system.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communication, and specifically, to a terahertz intelligent reconfigurable intelligent surface (RIS) multi-user communication system and a broadband precoding method. Background Art

[0002] Terahertz (THz) communication has become a promising candidate technology for future sixth-generation (6G) wireless communication due to its ultra-wide bandwidth, and theoretically can achieve data rates up to several terabits per second (Tb / s). However, THz signals face severe transmission attenuation and poor scattering, which limit their transmission range. Reconfigurable intelligent surface (RIS) provides a promising solution to address these challenges. By using a large number of passive reflecting elements, RIS can direct signals to any direction, thereby enhancing signal strength and making it a practical solution for THz communication.

[0003] Despite many studies, most RIS beamforming schemes perform poorly in broadband systems, especially in practical THz communication systems. This is because practical RIS is usually equipped with frequency-independent phase shift circuits, resulting in frequency-independent beamforming, which causes beam splitting problems and significant beam gain loss. To solve this problem, existing research work has proposed a tunable delay metasurface, with a time delay module connected to each RIS element. By applying time delay, frequency-dependent RIS beamforming is achieved, thus solving the beam splitting effect.

[0004] Existing research mainly focuses on single-user scenarios, which solves the beam splitting effect but fails to address the joint beamforming optimization problem in multi-user scenarios. In addition, in THz scenarios, due to the large number of RIS elements, equipping each element with a time delay module is neither practical nor cost-effective in terms of hardware and power consumption. Therefore, designing a system that can achieve active and passive joint beamforming in multi-user scenarios while controlling system costs is an important topic. Finding a low-cost method that can significantly improve the performance of THz communication systems is particularly crucial for next-generation networks. Summary of the Invention

[0005] Aiming at the deficiencies in the prior art, the purpose of the present invention is to provide a terahertz intelligent reconfigurable intelligent surface (RIS) multi-user communication system and a broadband precoding method.

[0006] According to a terahertz intelligent reconfigurable intelligent surface (RIS) multi-user communication system provided by the present invention, it includes:

[0007] A base station and a time-delay-based RIS system;

[0008] The base station includes a terahertz multi-antenna system for actively beamforming a multi-antenna array and controlling the amplitude and phase of each antenna;

[0009] The delay-based RIS system includes an auxiliary terahertz multi-antenna system and performs passive beamforming.

[0010] Preferably, the delay-based RIS system includes an RIS panel, an FPGA intelligent controller, and a delay module;

[0011] The RIS panel includes a plurality of reflection units, and performs passive beamforming through the FPGA intelligent controller to control the phase of each reflection unit, and realizes the frequency-dependent reflection phase through the delay module.

[0012] Preferably, the base station further includes a terahertz base station; the terahertz base station generates an active beamforming control signal, and obtains the multi-antenna signal after digital beamforming of the radar base station through the baseband signal of the base station.

[0013] Preferably, the delay-based RIS system generates a passive beamforming control signal, and performs passive beamforming on the incident signal of the RIS panel by establishing the amplitude and phase of all elements in the RIS coefficient matrix Θ.

[0014] Preferably, when the delay-based RIS system assists the terahertz multi-antenna system in beamforming, an optimization problem is constructed with the constraints of maximizing the weighted sum rate, the maximum transmit power, the delay capacity of the delay module, and the reflection capacity of the reflection unit; this optimization problem is a non-convex optimization problem, and based on the semidefinite relaxation and successive convex approximation algorithms, all optimization variables are alternately optimized and solved.

[0015] Preferably, the terahertz multi-antenna system has N t transmitting antennas; the RIS panel has a total of N = N x × N y reflection units, which are divided into S sub-panels, each sub-panel has N s reflection units, and is connected to a delay module; the system adopts a multi-carrier information transmission scheme, the bandwidth is denoted as B, and is evenly divided into M sub-carriers, and the center frequency is denoted as f c ; then the received signal y k,m of the k-th user on the m-th sub-carrier is expressed as:

[0016]

[0017] Among them, is the signal that the user expects to receive; is the interference between multi-users; n represents the noise interference; represents the channel between the k-th user and the RIS; (·) H represents the conjugate transpose operator of a matrix or vector, and Θ represents the matrix when the RIS assists in signal beamforming; T mdenotes the time delay matrix; G m denotes the near - field channel between the base station antenna array and the RIS; w denotes the base station beamforming vector; s denotes the transmitted discrete baseband signal;

[0018] is expressed as:

[0019]

[0020] where e denotes the natural constant; denotes the channel path gain between the k - th user and the RIS, τ ru,k denotes the channel path delay between the k - th user and the RIS; denotes the azimuth angle of the RIS emission angle, denotes the elevation angle of the RIS emission angle; C N×1 denotes a vector of dimension N×1; a(·) denotes the uniform planar array steering vector, which is expressed as:

[0021]

[0022] where c denotes the speed of light; (·) T denotes the transpose operator of a matrix or vector; j denotes the imaginary unit; f m denotes the m - th sub - carrier frequency; d denotes the element spacing;

[0023] is expressed as:

[0024]

[0025] where τ br denotes the channel path delay between the RIS and the base station, denotes the azimuth angle of the RIS arrival angle, denotes the elevation angle of the RIS arrival angle, denotes the transmission angle of the base station; b(·) denotes the uniform linear array steering vector, which is expressed as:

[0026]

[0027] The matrix Θ during RIS - assisted signal beamforming is expressed as:

[0028]

[0029] where θ N denotes the phase of the N - th element during RIS - assisted signal beamforming; v H is the vector representation of the RIS coefficient matrix Θ, and diag(·) denotes the operator that converts a vector into a diagonal matrix;

[0030] Divide the entire RIS panel into S sub - panels, each sub - panel contains N s reflective units, and connect each sub - panel to a delay module. Then the delay matrix T m is expressed as:

[0031]

[0032] where, t m represents the phase - shift vector caused by delay on the m - th sub - carrier, and is expressed as:

[0033]

[0034] where, τ s represents the parameter of the s - th delay module;

[0035] The signal - to - noise ratio of the received signal of the k - th user on the m - th sub - carrier is expressed as:

[0036]

[0037] where, represents the power of the noise. To maximize the weighted sum - rate, the original optimization problem P0 is expressed as:

[0038]

[0039] where, ω k represents the weighting coefficient; Tr(·) represents the operator of matrix trace, P max represents the maximum transmit power of the base station. The first constraint is the constraint of the maximum transmit power; the second constraint is the phase constraint of the RIS; the third constraint is the constraint of the delay ability of the delay module;

[0040] When the optimization problem is a non - convex optimization problem with respect to variables w, Θ, and t, the alternating optimization method is used to solve it.

[0041] Preferably, the base station includes active beamforming during signal transmission, establishing base - station multi - antenna beams for different users to maximize the weighted sum - rate;

[0042] Solve the optimal beamforming vector w of the base station:

[0043] Through semi - definite relaxation SDR transformation, let Then is re - expressed as:

[0044]

[0045] where, If \(W\) is the variable to be optimized for the first optimization problem, then when solving \(W\) alternately, the first optimization problem \(P1\) is transformed into:

[0046]

[0047] It is observed that the objective function is the difference between two concave functions. Perform the first-order Taylor expansion on the second term of the objective function:

[0048]

[0049] where, \((\cdot)\) ub is defined as the upper bound value of the numerical value;

[0050] At this time:

[0051]

[0052] Through semi-definite relaxation SDR transformation, removing the rank-1 constraint, the first optimization problem \(P1\) is transformed into the first optimization problem \(P1.1\), expressed as:

[0053]

[0054] The optimal solution \(W\) is obtained by solving with the convex optimization problem solving software, and the optimal \(w\) is obtained through matrix decomposition.

[0055] Preferably, the delay-based RIS system includes the establishment of passive beamforming for assisting terahertz communication. For each reflection unit of the RIS for different users, the phase is established to maximize the weighted sum rate;

[0056] Solve the RIS-assisted transmit beamforming matrix \(\Theta\):

[0057] Let

[0058]

[0059] where, \(v\) is the variable to be optimized for the second optimization problem. Then when solving \(v\) alternately, relaxing the modulus-1 constraint, the second optimization problem \(P2\) is transformed into:

[0060]

[0061] Introduce a set of relaxation variables Satisfy the following constraints:

[0062]

[0063] where,

[0064] Perform the first-order Taylor expansion:

[0065]

[0066] Among them, (·) lb is defined as the lower bound value of the numerical value; the second optimization problem P2 is transformed into the second primary optimization problem P2.1, expressed as:

[0067]

[0068] The optimal v is obtained by solving with the software for solving convex optimization problems.

[0069] Preferably, the RIS system based on time delay includes the time delay matrix optimization for assisting terahertz communication, sets the parameters of each time delay module for different frequencies, and maximizes the weighted sum rate;

[0070] Solve the time delay matrix T m :

[0071] Let

[0072] Among them, h k,m,n represents the nth element of the vector ; represents the nth row of the matrix G m ; Let is the variable to be optimized in the third optimization problem, then alternately solve When, relax the constraint with a relaxation modulus of 1, and transform the third optimization problem P3 into:

[0073]

[0074] Among them,

[0075] Introduce a set of relaxation variables satisfying the following constraints:

[0076]

[0077] Perform the first-order Taylor expansion:

[0078]

[0079] The third optimization problem P3 is transformed into the third primary optimization problem P3.1, expressed as:

[0080]

[0081] The optimal

[0082] According to a broadband precoding method provided by the present invention, it includes:

[0083] Active beamforming step: The base station performs active beamforming on the terahertz multi-antenna array to generate an active beamforming control signal, controlling the amplitude and phase of each antenna;

[0084] Passive beamforming step: The RIS panel performs passive beamforming through the FPGA intelligent controller to generate a passive beamforming control signal, controlling the phase of each reflection unit;

[0085] Delay parameter derivation step: According to the active beamforming control signal and the passive beamforming control signal, derive the parameters of each delay module to achieve the frequency-dependent RIS reflection phase.

[0086] Preferably, the RIS panel includes a plurality of reflection units, and performs passive beamforming through the FPGA intelligent controller to control the phase of each reflection unit, and realizes the frequency-dependent reflection phase through the delay module.

[0087] Preferably, the base station further includes a terahertz base station; the terahertz base station generates an active beamforming control signal, and obtains the multi-antenna signal after digital beamforming by the radar base station through the baseband signal of the base station.

[0088] Preferably, the passive beamforming step includes generating a passive beamforming control signal, and performing passive beamforming on the incident signal of the RIS panel by establishing the amplitude and phase of all elements in the RIS coefficient matrix Θ.

[0089] Preferably, when the passive beamforming step includes assisting the terahertz multi-antenna system to perform beamforming, an optimization problem is constructed with the maximization of the weighted sum rate, the maximum transmit power, the delay capacity of the delay module, and the reflection capacity of the reflection unit as constraints; this optimization problem is a non-convex optimization problem, and based on the semidefinite relaxation and successive convex approximation algorithms, all optimization variables are alternately optimized and solved.

[0090] Preferably, the terahertz multi-antenna system has a total of N t transmitting antennas; the RIS panel has a total of N = N x ×N y reflection units, which are divided into S sub-panels, each sub-panel has N s reflection units, and is connected to a delay module; the system adopts a multi-carrier information transmission scheme, the bandwidth is denoted as B, and is evenly divided into M sub-carriers, and the center frequency is denoted as f c ; then the received signal y k,m of the k-th user on the m-th sub-carrier is expressed as:

[0091]

[0092] Among them, is the signal that the user expects to receive; is the interference among multiple users; n represents the noise interference; represents the channel between the k-th user and the RIS; (·) H represents the conjugate transpose operator of a matrix or vector, and Θ represents the matrix during RIS-aided signal beamforming; T m represents the delay matrix; G m represents the near-field channel between the base station antenna array and the RIS; w represents the base station beamforming vector; s represents the transmitted discrete baseband signal;

[0093] is expressed as:

[0094]

[0095] where e represents the natural constant; represents the channel path gain between the k-th user and the RIS, τ ru,k represents the channel path delay between the k-th user and the RIS; represents the azimuth angle of the emission angle of the RIS, represents the elevation angle of the emission angle of the RIS; C N×1 represents a vector with dimension N×1; a(·) represents the uniform planar array steering vector, which is expressed as:

[0096]

[0097] where c represents the speed of light; (·) T represents the transpose operator of a matrix or vector; j represents the imaginary unit; f m represents the m-th subcarrier frequency; d represents the element spacing;

[0098] is expressed as:

[0099]

[0100] where τ br represents the channel path delay between the RIS and the base station, represents the azimuth angle of the arrival angle of the RIS, represents the elevation angle of the arrival angle of the RIS, represents the emission angle of the base station; b(·) represents the uniform linear array steering vector, which is expressed as:

[0101]

[0102] The matrix Θ during RIS-aided signal beamforming is expressed as:

[0103]

[0104] where θ N represents the phase of the Nth element during RIS-assisted signal beamforming; v H is the vector representation of the RIS coefficient matrix Θ, and diag(·) represents the operator for converting a vector into a diagonal matrix;

[0105] The entire RIS panel is divided into S sub-panels, each sub-panel contains N s reflecting elements, and each sub-panel is connected to a delay module. Then the delay matrix T m , is expressed as:

[0106]

[0107] where t m represents the phase shift vector caused by delay on the mth subcarrier, and is expressed as:

[0108]

[0109] where τ s represents the parameter of the sth delay module;

[0110] The signal-to-noise ratio of the received signal of the kth user on the mth subcarrier is expressed as:

[0111]

[0112] where represents the power of the noise. To maximize the weighted sum rate, the original optimization problem P0 is expressed as:

[0113]

[0114] where ω k represents the weighting coefficient; Tr(·) represents the operator for matrix trace, and P max represents the maximum transmit power of the base station. The first constraint is the constraint of the maximum transmit power; the second constraint is the phase constraint of the RIS; the third constraint n s is the constraint of the delay capacity of the delay module;

[0115] When the optimization problem is a non-convex optimization problem with respect to variables w, Θ, and t, alternating optimization is used to solve it.

[0116] Preferably, the base station includes active beam establishment during signal transmission, establishing base station multi-antenna beams for different users to maximize the weighted sum rate;

[0117] Solve for the optimal beamforming vector w of the base station:

[0118] Through semi - definite relaxation (SDR) transformation, let Then It is re - expressed as:

[0119]

[0120] Wherein, W is the variable to be optimized in the first optimization problem. When alternately solving for W, the first optimization problem P1 is transformed into:

[0121]

[0122] Observing that the objective function is the difference between two concave functions, perform a first - order Taylor expansion on the second term of the objective function:

[0123]

[0124] Wherein, (·) ub Is defined as the upper bound value of the numerical value;

[0125] At this time:

[0126]

[0127] Through semi - definite relaxation (SDR) transformation, remove the rank - 1 constraint, then the first optimization problem P1 is transformed into the first - order optimization problem P1.1, expressed as:

[0128]

[0129] Obtain the optimal solution W by solving with the convex optimization problem solving software, and obtain the optimal w through matrix factorization.

[0130] Preferably, the delay - based RIS system includes the establishment of passive beamforming for assisting terahertz communication, and for each reflection unit of the RIS for different users, the phase is established to maximize the weighted sum rate;

[0131] Solve the RIS - assisted transmit beamforming matrix Θ:

[0132] Let

[0133]

[0134] Wherein, v is the variable to be optimized in the second optimization problem. When alternately solving for v, relax the modulus - 1 constraint, and transform the second optimization problem P2 into:

[0135]

[0136] Introduce a set of slack variables Satisfy the following constraints:

[0137]

[0138] Among them,

[0139] Perform first-order Taylor expansion:

[0140]

[0141] Among them, (·) lb Is defined as the lower bound value of the numerical value; the second optimization problem P2 is transformed into the second-first optimization problem P2.1, expressed as:

[0142]

[0143] The optimal v is obtained by solving through the software for solving convex optimization problems.

[0144] Preferably, the RIS system based on delay includes the delay matrix optimization for assisting terahertz communication, sets the parameters of each delay module for different frequencies, and maximizes the weighted sum rate;

[0145] Solve the delay matrix T m :

[0146] Let

[0147] Among them, h k,m,n Represents the nth element of the vector , Represents the nth row of the matrix G m ; Let Is the variable to be optimized in the third optimization problem, then alternately solve When, relax the constraint with a modulus of 1, and transform the third optimization problem P3 into:

[0148]

[0149] Among them,

[0150] Introduce a set of relaxation variables Satisfy the following constraints:

[0151]

[0152] Perform first-order Taylor expansion:

[0153]

[0154] The third optimization problem P3 is transformed into the third-first optimization problem P3.1, expressed as:

[0155]

[0156] Obtained optimally through the solution software of convex optimization problems

[0157] Compared with the prior art, the present invention has the following beneficial effects:

[0158] 1. The present invention uses a terahertz intelligent metasurface multi-user communication system and a broadband precoding method to jointly achieve active and passive beamforming with the original multi-antenna system, alleviates the beam dispersion phenomenon, and improves the transmission efficiency of the terahertz system.

[0159] 2. The present invention uses a time-delay module to realize a frequency-dependent RIS reflection beam, solves the problem that the frequency-independent RIS phase-shift circuit performs poorly in a broadband system, and has high practicability.

[0160] 3. The architecture proposed in the present invention adds a RIS and an intelligent controller, has a simple structure, requires a small number of time-delay modules, has low hardware deployment costs and additional power overheads, and is a new type of green terahertz communication system.

[0161] Other beneficial effects of the present invention will be elaborated in the specific implementation manners through the introduction of specific technical features and technical solutions. Those skilled in the art should be able to understand the beneficial technical effects brought by the described technical features and technical solutions through these introductions. BRIEF DESCRIPTION OF THE DRAWINGS

[0162] By reading the following detailed description of non-limiting embodiments with reference to the accompanying drawings, other features, objects, and advantages of the present invention will become more apparent:

[0163] Figure 1 It is a system schematic diagram of the present invention.

[0164] Figure 2 It is a comparison diagram of RIS-assisted terahertz communication with and without time delay varying with the base station transmission power in the present invention.

[0165] Figure 3 It is a comparison diagram of RIS-assisted terahertz communication with and without time delay varying with the number of RIS units in the present invention.

[0166] Figure 4 It is a method flow chart of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0167] The present invention will be described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several changes and improvements can still be made. These all belong to the protection scope of the present invention.

[0168] Referring to Figure 1 as shown, a terahertz intelligent metasurface multi-user communication system includes:

[0169] a terahertz multi-antenna system, an RIS panel, an FPGA intelligent controller, a time-delay module, and a user group.

[0170] The RIS system based on time delay assists the terahertz multi-antenna system to jointly perform beamforming, and realizes frequency-dependent passive beamforming by designing the parameters of the time-delay module, alleviates the beam dispersion phenomenon in the terahertz ultra-wideband system, and improves the system transmission efficiency.

[0171] The base station needs to perform digital beamforming on the transmitting array multi-antenna array, control the amplitude and phase of each antenna, the RIS panel performs passive beamforming through the FPGA intelligent controller, controls the phase of each reflection unit, and realizes the frequency-dependent reflection phase through the time-delay module. The joint beamforming design of the base station and the RIS and the optimization of the time-delay matrix are considered together. The base station generates corresponding control signals in the multi-antenna array, the RIS unit generates corresponding control signals in the intelligent controller, and realizes the frequency-dependent reflection phase through the time-delay module.

[0172] The terahertz base station generates an active beamforming control signal: Considering that the baseband signal of the base station is s, the multi-antenna signal after the base station performs active beamforming design is ws, including the design of amplitude and phase in beamforming.

[0173] The RIS generates a passive beamforming control signal: The RIS performs reflection beamforming on the incident signal, controls the RIS coefficient matrix as Θ to perform the phase design of all elements, so that the reflected signal can be aligned with the user.

[0174] The time-delay module generates a frequency-dependent phase shift signal: Optimize the time-delay matrix T m , deduce the parameters of each time-delay module, realize the frequency-dependent RIS reflection phase, and eliminate the beam dispersion phenomenon in the broadband system.

[0175] Beamforming Scheme in a Time-Delay-Based RIS Transceiver System: With maximizing the weighted sum rate as the performance metric and restricting the main beam width. By constructing an optimization problem with constraints of maximizing the weighted sum rate, maximum transmit power, time-delay module delay capacity, and reflection unit reflection capacity, the present invention realizes the scheme design of this novel terahertz intelligent metasurface multi-user communication system and broadband precoding.

[0176] Scheme Design of Terahertz Intelligent Metasurface Multi-User Communication System and Broadband Precoding: The constructed weighted sum rate maximization optimization problem is a non-convex optimization problem and the global optimal solution cannot be directly obtained. The present invention obtains a suboptimal solution of relatively high quality based on the semi-definite relaxation and successive convex approximation algorithms in the following text and alternately optimizes all optimization variables.

[0177] The base station antenna array needs to consider the beamforming design when transmitting signals and realizes active transmit beamforming by controlling the amplitude and phase of each antenna. The RIS needs to control the phase of each reflection unit when assisting in transmitting signals to realize passive transmit beamforming. The time delay needs to consider the system bandwidth to realize frequency-dependent phase shift.

[0178] Consider a terahertz multi-antenna system with a total of N t transmitting antennas. The RIS panel has a total of N = N x × N y reflection units, which are divided into S sub-panels, and each sub-panel is connected to a time-delay module; the system adopts a multi-carrier information transmission scheme, the bandwidth is denoted as B and is evenly divided into M sub-carriers, and the center frequency is denoted as f c ; then the received signal y k,m of the k-th user on the m-th sub-carrier is expressed as:

[0179]

[0180] where, is the signal that the user expects to receive; is the interference between multi-users; n represents the noise interference; represents the channel between the k-th user and the RIS; (·) H represents the conjugate transpose operator of a matrix or vector, Θ represents the matrix when the RIS assists in signal beamforming; T m represents the time-delay matrix; G m represents the near-field channel between the base station antenna array and the RIS; w represents the base station beamforming vector; s represents the transmitted discrete baseband signal;

[0181] is expressed as:

[0182]

[0183] where \(e\) represents the natural constant; represents the channel path gain between the \(k\)-th user and the RIS, and \(\tau\) ru,k represents the channel path delay between the \(k\)-th user and the RIS; represents the azimuth angle of the emission angle of the RIS, represents the elevation angle of the emission angle of the RIS; \(C\) N×1 represents a vector of dimension \(N\times1\); \(a(\cdot)\) represents the uniform planar array steering vector, which is expressed as:

[0184]

[0185] where \(c\) represents the speed of light; \((\cdot)\) T represents the transpose operator of a matrix or vector; \(j\) represents the imaginary unit; \(f\) m represents the \(m\)-th subcarrier frequency; \(d\) represents the element spacing;

[0186] which is expressed as:

[0187]

[0188] where \(\tau\) br represents the channel path delay between the RIS and the base station, represents the azimuth angle of the angle of arrival of the RIS, represents the elevation angle of the angle of arrival of the RIS, represents the emission angle of the base station; \(b(\cdot)\) represents the uniform linear array steering vector, which is expressed as:

[0189]

[0190] The matrix \(\Theta\) for RIS-aided signal beamforming is expressed as:

[0191]

[0192] where \(\theta\) n represents the phase of the \(n\)-th element during RIS-aided signal beamforming; \(v\) H is the vector representation of the RIS coefficient matrix \(\Theta\), and \(diag(\cdot)\) represents the operator that converts a vector into a diagonal matrix;

[0193] The entire RIS panel is divided into \(S\) sub-panels, each sub-panel contains \(N\) s reflecting elements, and each sub-panel is connected to a time-delay module. Then the time-delay matrix \(T\) m is expressed as:

[0194]

[0195] where \(t\) mDenote the phase shift vector caused by time delay on the \(m\)-th subcarrier, which is expressed as:

[0196]

[0197] where \(\tau\) s denotes the parameter of the \(s\)-th time delay module;

[0198] The signal-to-noise ratio of the received signal of the \(k\)-th user on the \(m\)-th subcarrier is expressed as:

[0199]

[0200] where denotes the power of the noise. To maximize the weighted sum rate, the original optimization problem \(P0\) is expressed as:

[0201]

[0202] where \(\omega\) k denotes the weighting coefficient; \(Tr(\cdot)\) denotes the operator for matrix trace, and \(P\) max denotes the maximum transmit power of the base station. The first constraint is the constraint on the maximum transmit power; the second constraint is the phase constraint of the RIS; the third constraint \(n\) s is the constraint on the time delay capacity of the time delay module;

[0203] When the optimization problem is a non-convex optimization problem with respect to variables \(w\), \(\Theta\), and \(t\), alternating optimization is used to solve it.

[0204] The above is the basic embodiment of the present invention. Next, the technical solution of the present invention will be further described through four preferred embodiments.

[0205] Embodiment 1

[0206] This embodiment gives the active beam design of the base station when transmitting signals. For different users, the multi-antenna beam of the base station is established to maximize the weighted sum rate;

[0207] (1) Solve the optimal beamforming vector \(w\) of the base station:

[0208] Through semi-definite relaxation SDR transformation, let Then is re-expressed as where \(W\) is the variable to be optimized in the first optimization problem. When alternately solving \(W\), the first optimization problem \(P1\) is transformed into:

[0209]

[0210] It is observed that the objective function is the difference between two concave functions. Perform a first-order Taylor expansion on the second term of the objective function:

[0211]

[0212] where (·) ub is defined as the upper bound value of the numerical value;

[0213] To ensure that the solution of W is decomposed into ww H , the rank of W needs to be 1, that is:

[0214]

[0215] Through semi-definite relaxation SDR transformation, remove the rank-1 constraint, then the first optimization problem P1 is transformed into the first optimization problem P1.1, expressed as:

[0216]

[0217] Obtain the optimal solution W by solving the convex optimization problem with a software, and obtain the optimal w through matrix decomposition.

[0218] Example 2

[0219] This example gives the passive beamforming design for RIS-assisted terahertz communication. For different users, establish the phase of each reflection unit of RIS to maximize the weighted sum rate;

[0220] (2) Solve the RIS-assisted transmit beamforming matrix Θ:

[0221] Let v be the variable to be optimized in the second optimization problem. When alternately solving v, relax the constraint of modulus 1, and transform the second optimization problem P2 into:

[0222]

[0223] Introduce a set of slack variables satisfying the following constraints

[0224]

[0225] where Perform a first-order Taylor expansion:

[0226]

[0227] where (·) lb is defined as the lower bound value of the numerical value; The second optimization problem P2 is transformed into the second optimization problem P2.1, expressed as:

[0228]

[0229] The optimal v is obtained by solving the convex optimization problem using a software tool.

[0230] Example 3

[0231] This example presents the optimization of the delay matrix in a RIS-assisted terahertz communication system based on delay. The parameters of each delay module are designed for different frequencies to maximize the weighted sum rate.

[0232] (3) Solve the delay matrix T m :

[0233] Let where h k,m,n represents the -th element of the vector n , represents the m -th row of the matrix G n ; Let be the variable to be optimized in the third optimization problem. Then, when alternately solving , the constraint with a relaxation modulus of 1 is relaxed, and the third optimization problem P3 is transformed into:

[0234]

[0235] where

[0236] Introduce a set of relaxation variables that satisfy the following constraints:

[0237]

[0238] Perform a first-order Taylor expansion:

[0239]

[0240] The third optimization problem P3 is transformed into the third primary optimization problem P3.1, which is expressed as:

[0241]

[0242] The optimal

[0243] is obtained by solving the convex optimization problem using a software tool. After alternately optimizing the above 3 sub-problems until full convergence, the obtained v and may not satisfy the transverse mode constraint. Therefore, a feasible solution v * and

[0244]

[0245] Furthermore, based on the obtained MS delay values, the S delay values required by the system are derived through the following method:

[0246]

[0247] Among them, The phase shift generated by the sth delay value on different subcarriers is expressed as:

[0248]

[0249] Obtain the final system design.

[0250] The present invention particularly provides a terahertz intelligent metasurface multi-user communication system and a broadband precoding method. As Figure 1 shown, it describes the basic structural composition of the invention; as Figure 2 and Figure 3 shown, it compares the performance gain of the present invention.

[0251] As a revolutionary technology, RIS (Reconfigurable Intelligent Surface) is expected to solve the challenges of performance improvement and deployment cost in the development of terahertz communication systems. For communication systems, RIS can achieve channel reconstruction, providing sufficient multipath components for precise beamforming. In addition, RIS can also solve the problems of severe transmission attenuation and poor scattering in terahertz communication. First of all, RIS can achieve the ability of passive beamforming, which can increase the information transmission range, align the user position, and enhance the signal strength. In addition, the passive characteristics of RIS greatly reduce the deployment cost and can be well combined with future terahertz communication systems. Therefore, using RIS to improve the performance of terahertz multi-antenna systems is efficient and can reduce the deployment cost of a single base station and network, which has important implementation value in the next-generation wireless network.

[0252] The present invention provides a novel beam alignment method for a terahertz intelligent metasurface multi-user communication system and a beamforming design scheme under this system. The novel system includes a terahertz antenna array, RIS, an FPGA intelligent controller, and a delay module. The full English name of FPGA is Field Programmable Gate Array, and the Chinese translation is Field Programmable Logic Gate Array.

[0253] In the system, the RIS system based on delay assists the terahertz multi-antenna system to jointly perform beamforming, alleviates the beam dispersion phenomenon in the terahertz ultra-wideband system, and improves the system transmission efficiency.

[0254] The present invention designs a joint beamforming scheme for a novel time-delay-based RIS system-assisted terahertz multi-antenna system with the maximum weighted sum rate as the performance metric, while restricting the maximum transmit power, the delay capacity of the delay module, and the reflection capacity of the reflection unit.

[0255] Compared with the traditional terahertz multi-antenna system, the time-delay-based RIS system-assisted terahertz multi-antenna system of the present invention does not add a large number of additional RF links and complex signal processing units, and is a design that can achieve better performance at lower cost and power consumption. Through the design of the active and passive beamforming matrices of the multi-antenna array and RIS in combination, the weighted sum rate performance of the present invention is significantly improved.

[0256] Embodiment 4

[0257] Referring to Figure 4 As shown, a broadband precoding method is applied to a RIS-assisted terahertz information transmission system. The time-delay-based RIS system-assisted terahertz multi-antenna system jointly performs beamforming, and frequency-dependent passive beamforming is achieved by designing the parameters of the delay module, alleviating the beam dispersion phenomenon in the terahertz ultra-wideband system and improving the system transmission efficiency.

[0258] The method includes the following steps:

[0259] Active beamforming step: The base station performs active beamforming on the terahertz multi-antenna array, controlling the amplitude and phase of each antenna; the terahertz base station generates an active beamforming control signal, and through the baseband signal of the base station, obtains the multi-antenna signal after digital beamforming by the terahertz base station.

[0260] Passive beamforming step: The RIS panel performs passive beamforming through the FPGA intelligent controller, controlling the phase of each reflection unit: the RIS system generates a passive beamforming control signal, and by establishing the phases of all elements in the RIS coefficient matrix Θ, performs passive beamforming on the incident signal of the RIS panel so that the reflected signal is aligned with the user.

[0261] Time-delay parameter derivation step: Derive the parameters of each delay module to achieve frequency-dependent RIS reflection phase: By establishing the delay amounts of the delay modules in the delay matrix T m the frequency-dependent RIS reflected signal is realized, alleviating the beam dispersion phenomenon of the reflected signal.

[0262] Those skilled in the art know that, in addition to implementing the system and its various devices, modules, and units provided by the present invention in the form of pure computer-readable program code, the method steps can be logically programmed to enable the system and its various devices, modules, and units provided by the present invention to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers, etc., to achieve the same functions. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a kind of hardware component, and the devices, modules, and units included therein for implementing various functions can also be regarded as the structures within the hardware component; the devices, modules, and units for implementing various functions can also be regarded as either software modules for implementing the method or structures within the hardware component.

[0263] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. Without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A terahertz intelligent metasurface multi-user communication system, characterized in that, Including: A base station and a delay-based RIS system; The base station includes a terahertz multi-antenna system for performing active beamforming on a multi-antenna array and controlling the amplitude and phase of each antenna; The delay-based RIS system assists the terahertz multi-antenna system and performs passive beamforming; The delay-based RIS system includes an RIS panel, an FPGA intelligent controller, and a delay module; The RIS panel includes multiple reflection units and performs passive beamforming through the FPGA intelligent controller to control the phase of each reflection unit, and realizes frequency-dependent reflection phase through the delay module; The THz multi-antenna system has a total of N t transmitting antennas; the RIS panel has a total of N = N x × N y reflecting elements, which are divided into S sub-panels, each sub-panel has N s reflecting elements and is connected to a time-delay module; the system adopts a multi-carrier information transmission scheme, the bandwidth is denoted as B and is evenly divided into M sub-carriers, and the center frequency is denoted as f c ; then the received signal y k,m of the k-th user on the m-th sub-carrier is expressed as: Among them, is the signal that the user expects to receive; is the interference among multiple users; n represents the noise interference; represents the channel between the k-th user and the RIS panel; (·) H represents the conjugate transpose operator of a matrix or vector, Θ represents the matrix when the RIS panel assists in signal beamforming; T m represents the delay matrix; G m represents the near-field channel between the base station antenna array and the RIS panel; w represents the base station beamforming vector; s represents the transmitted discrete baseband signal; Expressed as: where \(e\) represents the natural constant; represents the channel path gain between the \(k\)th user and the RIS panel, \(\tau\) ru,k represents the channel path delay between the \(k\)th user and the RIS panel; represents the azimuth angle of the emission angle of the RIS panel, \(\theta\) RIS,t represents the elevation angle of the emission angle of the RIS panel; \(C\) N×1 represents a vector of dimension \(N\times1\); \(a(\cdot)\) represents the uniform planar array steering vector, expressed as: where c represents the speed of light; (·) T represents the transpose operator of a matrix or vector; j represents the imaginary unit; f m represents the m-th subcarrier frequency; d represents the element spacing; Expressed as: where, τ br represents the channel path delay between the RIS panel and the base station, represents the azimuth angle of the angle of arrival of the RIS panel, θ RIS,r represents the elevation angle of the angle of arrival of the RIS panel, represents the transmission angle of the base station; b(·) represents the uniform linear array steering vector, expressed as: The matrix Θ when the RIS panel assists in signal beamforming is expressed as: where, θ N represents the phase of the Nth element during RIS panel-assisted signal beamforming; v H is the vector representation of the matrix Θ during RIS panel-assisted signal beamforming, and diag(·) represents the operator for converting a vector into a diagonal matrix; Divide the entire RIS panel into S sub - panels, each sub - panel contains N s reflecting units, and connect a time - delay module to each sub - panel. Then the time - delay matrix T m is expressed as: where t m represents the phase shift vector caused by time delay on the m-th subcarrier, expressed as: Among them, τ s represents the parameter of the s-th time delay module; The signal-to-noise ratio of the received signal of the k-th user on the m-th subcarrier is expressed as: wherein, represents the power of noise, and the original optimization problem P0 is expressed as: Among them, W k represents the weighting coefficient; Tr(·) represents the operator for matrix trace, and P max represents the maximum transmit power of the base station. The first constraint is the constraint on the maximum transmit power; the second constraint is the phase constraint of the RIS panel; the third constraint n s is the constraint on the delay capacity of the delay module; When the optimization problem is a non-convex optimization problem with respect to variables w, variable Θ, and variable t, alternating optimization is used to solve it.

2. The terahertz intelligent metasurface multi-user communication system according to claim 1, wherein The base station also includes a terahertz base station; the terahertz base station generates an active beamforming control signal, and through the baseband signal of the base station, obtains the multi-antenna signal after digital beamforming by the radar base station.

3. The terahertz intelligent metasurface multi-user communication system according to claim 1, characterized in that, The delay-based RIS system generates a passive beamforming control signal, and through establishing the amplitude and phase of all elements in the matrix Θ when the RIS system assists in signal beamforming, performs passive beamforming on the incident signal of the RIS panel.

4. The terahertz intelligent metasurface multi-user communication system according to claim 1, characterized in that When the delay-based RIS system assists the terahertz multi-antenna system in beamforming, an optimization problem is constructed with maximizing the weighted sum rate, maximum transmit power, delay module delay capability, and reflection unit reflection capability as constraints; This optimization problem is a non-convex optimization problem, and based on the semi-definite relaxation and successive convex approximation algorithms, alternating optimization is used to solve all optimization variables.

5. The terahertz intelligent metasurface multi-user communication system according to claim 1, wherein The active beam establishment when the base station transmits a signal, establishes the base station multi-antenna beam for different users, and maximizes the weighted sum rate; Solve the optimal beamforming vector w of the base station: Through semi-definite relaxation SDR transformation, let Then Redefine it as: wherein, If W is the variable to be optimized for the first optimization problem, then when alternately solving for W, the first optimization problem P1 is transformed into: It is observed that the objective function is the difference between two concave functions, and the second term of the objective function is expanded by the first-order Taylor expansion: where (·) ub is defined as the upper bound value of a numerical value; At this time: Through the semi-definite relaxation SDR transformation, removing the rank-1 constraint, the first optimization problem P1 is transformed into the first-first optimization problem P1.1, expressed as: The optimal solution W is obtained by solving through the software for solving convex optimization problems, and the optimal w is obtained through matrix factorization.

6. The terahertz intelligent metasurface multi-user communication system according to claim 5, characterized in that, The delay-based RIS system includes the establishment of passive beamforming when assisting terahertz communication, establishes the phase of each reflection unit of the RIS system for different users, and maximizes the weighted sum rate; Solve the matrix Θ when the RIS system assists in signal beamforming: Let where v is the variable to be optimized in the second optimization problem. Then, when alternately solving v, relaxing the constraint of modulus 1, the second optimization problem P2 is converted to: Introduce a set of slack variables Satisfy the following constraints: Among them, Perform the first-order Taylor expansion: where, (·) lb is defined as the lower bound value of the numerical value; the second optimization problem P2 is transformed into a second single optimization problem P2.1, expressed as: The optimal v is obtained by solving through the software for solving convex optimization problems.

7. The terahertz intelligent metasurface multi-user communication system according to claim 6, wherein The delay-based RIS system includes the optimization of the delay matrix when assisting terahertz communication, sets the parameters of each delay module for different frequencies, and maximizes the weighted sum rate; Solve the delay matrix T m : Let where h k,m,n represents the n-th element of the vector ; represents the n-th row of the matrix G m ; Let be the variable to be optimized for the third optimization problem, then when alternately solving , the constraint with a relaxation modulus of 1 is relaxed, and the third optimization problem P3 is transformed into: Among them, Introduce a set of slack variables Satisfy the following constraints: Perform the first-order Taylor expansion: The third optimization problem P3 is transformed into the third-first optimization problem P3.1, expressed as: Obtained optimally by solving software for convex optimization problems 8. A broadband precoding method, characterized in that The terahertz intelligent metasurface multi-user communication system according to any one of claims 1 to 7, comprising: Active beamforming step: enabling the base station to perform active beamforming on the terahertz multi-antenna array to generate an active beamforming control signal, and controlling the amplitude and phase of each antenna; Passive beamforming step: enabling the RIS panel to perform passive beamforming through the FPGA intelligent controller to generate a passive beamforming control signal, and controlling the phase of each reflection unit; Time delay parameter derivation step: deriving each time delay module parameter according to the active beamforming control signal and the passive beamforming control signal to implement the reflection phase of the frequency-dependent RIS system.

Images