Terahertz intelligent metasurface multi-user communication system and broadband precoding method

Abstract

The invention provides a terahertz intelligent metasurface multi-user communication system and a broadband precoding method. The system comprises a base station and an RIS system based on time delay. The base station comprises a terahertz multi-antenna system which is used for performing active beam forming on a multi-antenna array and controlling the amplitude and the phase of each antenna; the RIS system based on time delay comprises an auxiliary terahertz multi-antenna system and performs passive beam forming. The terahertz intelligent metasurface multi-user communication system and the broadband precoding method are combined with an original multi-antenna system to achieve active and passive beam forming, the beam dispersion phenomenon is relieved, and the transmission efficiency of the terahertz system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communications, and in particular to a terahertz intelligent metasurface multi-user communication system and a broadband precoding method. Background Art

[0002] Terahertz (THz) communication has become a strong candidate technology for the future sixth-generation (6G) wireless communication due to its ultra-wide bandwidth, and can theoretically achieve data rates of up to terabits per second (Tb / s). However, THz signals face severe transmission attenuation and poor scattering, which limits their transmission range. Smart metasurfaces (RIS) provide a promising solution to these challenges. By using a large number of passive reflective elements, RIS can guide signals in any direction, thereby enhancing signal strength, 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 are usually equipped with frequency-independent phase shift circuits, which makes their beamforming frequency-independent, thus causing beam splitting problems and leading to significant beam gain loss. To solve this problem, existing research work proposes a metasurface with adjustable delay, where each RIS element is connected to a time delay module. By applying a time delay, frequency-dependent RIS beamforming is achieved, thus solving the beam splitting effect.

[0004] Existing studies mostly focus on single-user scenarios and solve the beam splitting effect, but fail to deal with the joint beamforming optimization problem in multi-user scenarios. In addition, in THz scenarios, due to the large number of RIS components, equipping each component with a delay module is not only impractical, but also leads to high hardware cost and power consumption. Therefore, it is an important topic to design a system that can realize active and passive joint beamforming in multi-user scenarios while controlling the system cost. Finding a low-cost method that can significantly improve the performance of THz communication systems is particularly critical for next-generation networks. Summary of the invention

[0005] In view of the defects in the prior art, the purpose of the present invention is to provide a terahertz intelligent metasurface multi-user communication system and a broadband precoding method.

[0006] A terahertz intelligent metasurface multi-user communication system provided by the present invention comprises:

[0007] Base stations and delay-based RIS systems;

[0008] 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;

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

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

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

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

[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 constraints such as maximizing the weighted sum rate, the maximum transmission power, the delay capability of the delay module, and the reflection capability of the reflection unit; this optimization problem is a non-convex optimization problem, and based on semi-positive definite relaxation and continuous convex approximation algorithms, all optimization variables are alternately optimized and solved.

[0015] Preferably, the terahertz multi-antenna system has a total of N t transmitting antennas; RIS panels have N = N x ×N y Reflection units are divided into S sub-panels, each with N s A reflection unit is connected to a delay module. The system adopts a multi-carrier information transmission scheme, with a bandwidth denoted as B and divided into M subcarriers, with a center frequency denoted as f. c ; Then the received signal y of the kth user on the mth subcarrier k,m It is expressed as:

[0016]

[0017] in, The signal that the user expects to receive; is the interference among multiple users; n represents the noise interference; represents the channel between the kth user and RIS; (·) H represents the conjugate transpose operator of a matrix or vector, Θ represents the matrix of RIS auxiliary signal beamforming; T mrepresents 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;

[0018] It is expressed as:

[0019]

[0020] Among them, e represents a natural constant; represents the channel path gain between the kth user and RIS, τ ru,k represents the channel path delay between the kth user and RIS; represents the azimuth of the RIS launch angle, represents the elevation angle of the RIS launch angle; C N×1 represents a vector with dimension N×1; a(·) represents a uniform planar array steering vector, which is expressed as:

[0021]

[0022] Where c is the speed of light; (·) T represents the transpose operator of a matrix or vector; j represents the imaginary unit; f m represents the mth subcarrier frequency; d represents the unit spacing;

[0023] It is expressed as:

[0024]

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

[0026]

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

[0028]

[0029] Among them, θ N represents the phase of the Nth element during RIS auxiliary signal beamforming; v H is the vector representation of the RIS coefficient matrix Θ, and diag(·) represents the operator that converts the vector into a diagonal matrix;

[0030] Divide the entire RIS panel into S sub-panels, each of which contains N s reflection units, each sub-panel is connected to a delay module, then the delay matrix T m , expressed as:

[0031]

[0032] Among them, t m represents the phase shift vector caused by the delay on the mth subcarrier, expressed as:

[0033]

[0034] Among them, τ s Represents the parameters of the sth delay module;

[0035] The signal-to-noise ratio of the received signal of the kth user on the mth subcarrier is expressed as:

[0036]

[0037] in, Represents the power of the noise, maximizing the weighted sum rate, then the original optimization problem P0 is expressed as:

[0038]

[0039] Among them, ω k represents the weighting coefficient; Tr(·) represents the matrix trace operator, P max Indicates 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 RIS; the third constraint The delay capability constraint of the delay module;

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

[0041] Preferably, the base station includes active beam establishment when transmitting signals, establishing base station multi-antenna beams for different users, and maximizing weighted sum rate;

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

[0043] Through the semi-positive definite relaxation SDR transformation, let but Re-expressed as:

[0044]

[0045] in, W is the variable to be optimized in the first optimization problem. When solving W alternately, the first optimization problem P1 is converted to:

[0046]

[0047] Observe that the objective function is the difference between two concave functions, and perform a first-order Taylor expansion on the second term of the objective function:

[0048]

[0049] in,(·) ub Defined as the upper bound of the value;

[0050] at this time:

[0051]

[0052] By using the semi-positive definite relaxation SDR transformation and removing the rank 1 constraint, the first optimization problem P1 is transformed into the first optimization problem P1.1, which can be expressed as:

[0053]

[0054] The optimal solution W is obtained by using convex optimization problem solving software, and the optimal w is obtained by matrix decomposition.

[0055] Preferably, the delay-based RIS system includes passive beamforming establishment during auxiliary terahertz communication, establishing the phase of each reflection unit of RIS for different users, and maximizing the weighted sum rate;

[0056] Solve the RIS-assisted transmit beamforming matrix Θ:

[0057] make

[0058]

[0059] Among them, v is the variable to be optimized in the second optimization problem. When solving v alternately, the constraint with a modulus of 1 is relaxed, and the second optimization problem P2 is converted to:

[0060]

[0061] Introducing a set of slack variables The following constraints are met:

[0062]

[0063] in,

[0064] Perform a first-order Taylor expansion:

[0065]

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

[0067]

[0068] The optimal v is obtained by using convex optimization problem solving software.

[0069] Preferably, the delay-based RIS system includes delay matrix optimization during auxiliary terahertz communication, setting parameters of each delay module for different frequencies, and maximizing the weighted sum rate;

[0070] Solve the delay matrix T m :

[0071] make

[0072] Among them, h k,m,n Representation vector The nth element of Denotes the matrix G m The nth row of is the variable to be optimized in the third optimization problem, then solve it alternately When , the constraint with a modulus of 1 is relaxed, and the third optimization problem P3 is transformed into:

[0073]

[0074] in,

[0075] Introducing a set of slack variables The following constraints are met:

[0076]

[0077] Perform a first-order Taylor expansion:

[0078]

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

[0080]

[0081] The optimal solution is obtained by solving the convex optimization problem using software

[0082] A broadband precoding method provided according to the present invention includes:

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

[0084] Passive beamforming steps: the RIS panel performs passive beamforming through the FPGA intelligent controller to generate a passive beamforming control signal to control the phase of each reflector unit;

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

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

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

[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, the passive beamforming step includes constructing an optimization problem with constraints such as maximizing the weighted sum rate, the maximum transmission power, the delay capability of the delay module and the reflection capability of the reflection unit when assisting the terahertz multi-antenna system in beamforming; this optimization problem is a non-convex optimization problem, and all optimization variables are alternately optimized and solved based on semi-positive relaxation and continuous convex approximation algorithms.

[0090] Preferably, the terahertz multi-antenna system has a total of N t transmitting antennas; RIS panels have N = N x ×N y Reflection units are divided into S sub-panels, each with N s A reflection unit is connected to a delay module. The system adopts a multi-carrier information transmission scheme, with a bandwidth denoted as B and divided into M subcarriers, with a center frequency denoted as f. c ; Then the received signal y of the kth user on the mth subcarrier k,m It is expressed as:

[0091]

[0092] in, The signal that the user expects to receive; is the interference among multiple users; n represents the noise interference; represents the channel between the kth user and RIS; (·) H represents the conjugate transpose operator of a matrix or vector, Θ represents the matrix of RIS auxiliary 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] It is expressed as:

[0094]

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

[0096]

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

[0098] It is expressed as:

[0099]

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

[0101]

[0102] The matrix Θ of RIS-assisted signal beamforming is expressed as:

[0103]

[0104] Among them, θ N represents the phase of the Nth element during RIS auxiliary signal beamforming; v H is the vector representation of the RIS coefficient matrix Θ, and diag(·) represents the operator that converts the vector into a diagonal matrix;

[0105] Divide the entire RIS panel into S sub-panels, each of which contains N s reflection units, each sub-panel is connected to a delay module, then the delay matrix T m , expressed as:

[0106]

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

[0108]

[0109] Among them, τ s Represents the parameters 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] in, Represents the power of the noise, maximizing the weighted sum rate, then the original optimization problem P0 is expressed as:

[0113]

[0114] Among them, ω k represents the weighting coefficient; Tr(·) represents the matrix trace operator, P max Indicates 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 RIS; the third constraint n s The delay capability constraint of the delay module;

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

[0116] Preferably, the base station includes active beam establishment when transmitting signals, establishing base station multi-antenna beams for different users, and maximizing weighted sum rate;

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

[0118] Through the semi-positive definite relaxation SDR transformation, let but Re-expressed as:

[0119]

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

[0121]

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

[0123]

[0124] in,(·) ub Defined as the upper bound of the value;

[0125] at this time:

[0126]

[0127] By using the semi-positive definite relaxation SDR transformation and removing the rank 1 constraint, the first optimization problem P1 is transformed into the first optimization problem P1.1, which can be expressed as:

[0128]

[0129] The optimal solution W is obtained by using convex optimization problem solving software, and the optimal w is obtained by matrix decomposition.

[0130] Preferably, the delay-based RIS system includes passive beamforming establishment during auxiliary terahertz communication, establishing the phase of each reflection unit of RIS for different users, and maximizing the weighted sum rate;

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

[0132] make

[0133]

[0134] Among them, v is the variable to be optimized in the second optimization problem. When solving v alternately, the constraint with a modulus of 1 is relaxed, and the second optimization problem P2 is converted to:

[0135]

[0136] Introducing a set of slack variables The following constraints are met:

[0137]

[0138] in,

[0139] Perform a first-order Taylor expansion:

[0140]

[0141] in,(·) lb is defined as the lower bound of the value; the second optimization problem P2 is transformed into the second optimization problem P2.1, expressed as:

[0142]

[0143] The optimal v is obtained by using convex optimization problem solving software.

[0144] Preferably, the delay-based RIS system includes delay matrix optimization during auxiliary terahertz communication, setting parameters of each delay module for different frequencies, and maximizing the weighted sum rate;

[0145] Solve the delay matrix T m :

[0146] make

[0147] Among them, h k,m,n Representation vector The nth element of Denotes the matrix G m The nth row of is the variable to be optimized in the third optimization problem, then solve it alternately When , the constraint with modulus 1 is relaxed, and the third optimization problem P3 is transformed into:

[0148]

[0149] in,

[0150] Introducing a set of slack variables The following constraints are met:

[0151]

[0152] Perform a first-order Taylor expansion:

[0153]

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

[0155]

[0156] The optimal solution is obtained by solving the convex optimization problem using software

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

[0158] 1. The present invention utilizes the terahertz intelligent metasurface multi-user communication system and the broadband precoding method, and combines it with the original multi-antenna system to realize active and passive beamforming, alleviate the beam dispersion phenomenon, and improve the transmission efficiency of the terahertz system.

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

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

[0161] Other beneficial effects of the present invention will be explained in the specific implementation manner through the introduction of specific technical features and technical solutions. Through the introduction of these technical features and technical solutions, those skilled in the art should be able to understand the beneficial technical effects brought about by the technical features and technical solutions. BRIEF DESCRIPTION OF THE DRAWINGS

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

[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 according to the change of base station transmission power in the present invention.

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

[0166] Figure 4 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0167] The present invention is 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 are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0168] Reference Figure 1 As shown, a terahertz intelligent metasurface multi-user communication system comprises:

[0169] Hertz multi-antenna system, RIS panel, FPGA intelligent controller, delay module and user group.

[0170] The delay-based RIS system assists the terahertz multi-antenna system in joint beamforming, and realizes frequency-dependent passive beamforming by designing the delay module parameters, thereby alleviating the beam dispersion phenomenon in the terahertz ultra-wideband system and improving the system transmission efficiency.

[0171] The base station needs to perform digital beamforming on the transmitting array multi-antenna array to control the amplitude and phase of each antenna. The RIS panel performs passive beamforming through the FPGA intelligent controller to control the phase of each reflector unit and realize the frequency-related reflection phase through the delay module. The base station and RIS jointly consider the beamforming design and delay matrix optimization. The base station generates the corresponding control signal in the multi-antenna array, and the RIS unit generates the corresponding control signal in the intelligent controller, and realizes the frequency-related reflection phase through the delay module.

[0172] Generation of active beamforming control signals for terahertz base stations: 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, which includes the design of amplitude and phase in beamforming.

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

[0174] The delay module generates frequency-dependent phase-shifted signals: optimize the delay matrix T m , derive the parameters of each delay module, realize the frequency-dependent RIS reflection phase, and eliminate the beam dispersion phenomenon in broadband systems.

[0175] The beamforming scheme in the delay-based RIS transceiver system: taking the maximization of the weighted sum rate as the performance indicator and limiting the main beam width. By constructing an optimization problem with the maximization of the weighted sum rate, the maximum transmission power, the delay capability of the delay module and the reflection capability of the reflection unit as constraints, the present invention realizes the design of the novel terahertz intelligent metasurface multi-user communication system and broadband precoding scheme.

[0176] Design of terahertz intelligent metasurface multi-user communication system and broadband precoding scheme: The weighted sum rate maximization optimization problem constructed in this paper is a non-convex optimization problem, and the global optimal solution cannot be directly obtained. The present invention is based on semi-positive relaxation and continuous convex approximation algorithms, and alternately optimizes all optimization variables to obtain a suboptimal solution of higher quality.

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

[0178] Consider a terahertz multi-antenna system with N t There are N transmitting antennas, and the RIS panels have N = N x ×N y The system adopts a multi-carrier information transmission scheme, with a bandwidth of B and divided into M subcarriers, and a center frequency of f. c ; Then the received signal y of the kth user on the mth subcarrier k,m It is expressed as:

[0179]

[0180] in, The signal that the user expects to receive; is the interference among multiple users; n represents the noise interference; represents the channel between the kth user and RIS; (·) H represents the conjugate transpose operator of a matrix or vector, Θ represents the matrix of RIS auxiliary 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;

[0181] It is expressed as:

[0182]

[0183] Among them, e represents a natural constant; represents the channel path gain between the kth user and RIS, τ ru,k represents the channel path delay between the kth user and RIS; represents the azimuth of the RIS launch angle, represents the elevation angle of the RIS launch angle; C N×1 represents a vector with dimension N×1; a(·) represents a uniform planar array steering vector, which is expressed as:

[0184]

[0185] Where c is the speed of light; (·) T represents the transpose operator of a matrix or vector; j represents the imaginary unit; f m represents the mth subcarrier frequency; d represents the unit spacing;

[0186] It is expressed as:

[0187]

[0188] Among them, τ br represents the channel path delay between RIS and the base station, represents the azimuth of the RIS arrival angle, represents the elevation angle of the RIS arrival angle, represents the transmission angle of the base station; b(·) represents the uniform linear array steering vector, which is expressed as:

[0189]

[0190] The matrix Θ of RIS-assisted signal beamforming is expressed as:

[0191]

[0192] Among them, θ n represents the phase of the nth element during RIS auxiliary signal beamforming; v H is the vector representation of the RIS coefficient matrix Θ, and diag(·) represents the operator that converts the vector into a diagonal matrix;

[0193] Divide the entire RIS panel into S sub-panels, each of which contains N s reflection units, each sub-panel is connected to a delay module, then the delay matrix T m , expressed as:

[0194]

[0195] Among them, t mrepresents the phase shift vector caused by the delay on the mth subcarrier, expressed as:

[0196]

[0197] Among them, τ s Represents the parameters of the sth delay module;

[0198] The signal-to-noise ratio of the received signal of the kth user on the mth subcarrier is expressed as:

[0199]

[0200] in, Represents the power of the noise, maximizing the weighted sum rate, then the original optimization problem P0 is expressed as:

[0201]

[0202] Among them, ω k represents the weighting coefficient; Tr(·) represents the matrix trace operator, P max Indicates 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 RIS; the third constraint n s The delay capability constraint of the delay module;

[0203] When the optimization problem is a non-convex optimization problem about variables w, variables Θ and variables t, alternating optimization is used to solve it.

[0204] The above are basic embodiments of the present invention. The technical solution of the present invention is further described below through four preferred embodiments.

[0205] Example 1

[0206] This embodiment provides an active beam design when the base station transmits a signal, establishes a base station multi-antenna beam for different users, and maximizes the weighted sum rate;

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

[0208] Through the semi-positive definite relaxation SDR transformation, let but Re-expressed as in, W is the variable to be optimized in the first optimization problem. When solving W alternately, the first optimization problem P1 is converted to:

[0209]

[0210] Observe that the objective function is the difference between two concave functions, and perform a first-order Taylor expansion on the second term of the objective function:

[0211]

[0212] in,(·) ub Defined as the upper bound of the value;

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

[0214]

[0215] By using the semi-positive definite relaxation SDR transformation and removing the rank 1 constraint, the first optimization problem P1 is transformed into the first optimization problem P1.1, which can be expressed as:

[0216]

[0217] The optimal solution W is obtained by using convex optimization problem solving software, and the optimal w is obtained by matrix decomposition.

[0218] Example 2

[0219] This embodiment provides a passive beamforming design for RIS system-assisted terahertz communication, and establishes the phase of each reflection unit of RIS for different users to maximize the weighted sum rate;

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

[0221] make v is the variable to be optimized in the second optimization problem. When solving v alternately, the constraint with a modulus of 1 is relaxed, and the second optimization problem P2 is converted to:

[0222]

[0223] Introducing a set of slack variables Satisfy the following constraints

[0224]

[0225] in, Perform a first-order Taylor expansion:

[0226]

[0227] in,(·) lb is defined as the lower bound of the 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 using convex optimization problem solving software.

[0230] Example 3

[0231] This embodiment provides a delay matrix optimization for RIS system-assisted terahertz communication based on delay, designs parameters of each delay module for different frequencies, and maximizes the weighted sum rate;

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

[0233] make Among them, h k,m,n Representation vector No. n elements, Denotes the matrix G m No. n to do; to order is the variable to be optimized in the third optimization problem, then solve it alternately When , the constraint with modulus 1 is relaxed, and the third optimization problem P3 is transformed into:

[0234]

[0235] in,

[0236] Introducing a set of slack variables The following constraints are met:

[0237]

[0238] Perform a first-order Taylor expansion:

[0239]

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

[0241]

[0242] The optimal solution is obtained by solving the convex optimization problem using software

[0243] The above three sub-problems are optimized alternately until all convergence. v and The transverse mode constraint may not be satisfied, so a feasible solution v is reconstructed by the following method * and

[0244]

[0245] Then, based on the solved MS delay values, the S delay values ​​required by the system are derived by the following method:

[0246]

[0247] in, The phase shift corresponding to the sth delay value on different subcarriers is expressed as:

[0248]

[0249] Get the final system design.

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

[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 realize channel reconstruction and provide sufficient multipath components to facilitate accurate beamforming. In addition, RIS can also solve the problems of severe transmission attenuation and poor scattering in terahertz communication. First of all, RIS can realize the ability of passive beamforming, which can improve the information transmission range, align the user's location, 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 and network, which has important implementation value in the next generation of wireless networks.

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

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

[0254] The present invention takes the maximum weighted sum rate as the performance index, and limits the maximum transmission power, the delay capacity of the delay module and the reflection capacity of the reflection unit to jointly design a beamforming scheme for a novel delay-based RIS system-assisted terahertz multi-antenna system;

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

[0256] Example 4

[0257] Reference Figure 4 As shown, a broadband precoding method is shown, which applies the RIS-assisted terahertz information transmission system. The delay-based RIS system assists the terahertz multi-antenna system to jointly perform beamforming, and realizes frequency-dependent passive beamforming by designing the delay module parameters, thereby alleviating the beam dispersion phenomenon in the terahertz ultra-wideband system and improving the system transmission efficiency.

[0258] The method comprises the following steps:

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

[0260] Passive beamforming steps: The RIS panel performs passive beamforming through the FPGA intelligent controller to control the phase of each reflector unit: The RIS system generates a passive beamforming control signal and passively beamforms the incident signal of the RIS panel by establishing the phase of all elements in the RIS coefficient matrix Θ so that the reflected signal is aimed at the user.

[0261] Delay parameter derivation steps: derive each delay module parameter to achieve frequency-dependent RIS reflection phase: by establishing the delay matrix T m The delay amount of the medium delay module realizes the frequency-dependent RIS reflection signal and alleviates the beam dispersion phenomenon of the reflection signal.

[0262] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0263] The above describes the specific embodiments of the present invention. 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. In the absence of 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: include: Base stations and delay-based RIS systems; 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 time-delay-based RIS system includes an auxiliary terahertz multi-antenna system and performs passive beamforming.

2. The terahertz intelligent metasurface multi-user communication system according to claim 1, characterized in that: The delay-based RIS system includes a RIS panel, an FPGA intelligent controller and a delay module; The RIS panel includes multiple reflection units, and performs passive beamforming through an FPGA intelligent controller to control the phase of each reflection unit, and realizes frequency-dependent reflection phase through a delay module.

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

4. The terahertz intelligent metasurface multi-user communication system according to claim 2, characterized in that: 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.

5. The terahertz intelligent metasurface multi-user communication system according to claim 2, characterized in that: When the delay-based RIS system assists the terahertz multi-antenna system in beamforming, an optimization problem is constructed with the maximum weighted sum rate, the maximum transmission power, the delay capability of the delay module and the reflection capability of the reflection unit as constraints; This optimization problem is a non-convex optimization problem, and based on semi-positive definite relaxation and continuous convex approximation algorithm, all optimization variables are solved by alternating optimization.

6. The terahertz intelligent metasurface multi-user communication system according to claim 2, characterized in that: The terahertz multi-antenna system has a total of N t transmitting antennas; RIS panels have N = N x ×N y Reflection units are divided into S sub-panels, each with N s A reflection unit is connected to a delay module. The system adopts a multi-carrier information transmission scheme, with a bandwidth denoted as B and divided into M subcarriers, with a center frequency denoted as f. c ; Then the received signal y of the kth user on the mth subcarrier k,m It is expressed as: in, The signal that the user expects to receive; is the interference among multiple users; n represents the noise interference; represents the channel between the kth user and RIS; (·) H represents the conjugate transpose operator of a matrix or vector, Θ represents the matrix of RIS auxiliary 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; It is expressed as: Among them, e represents a natural constant; represents the channel path gain between the kth user and RIS, τ ru,k represents the channel path delay between the kth user and RIS; represents the azimuth of the RIS launch angle, represents the elevation angle of the RIS launch angle; C N×1 represents a vector with dimension N×1; a(·) represents a uniform planar array steering vector, which is expressed as: Where c is the speed of light; (·) T represents the transpose operator of a matrix or vector; j represents the imaginary unit; f m represents the mth subcarrier frequency; d represents the unit spacing; It is expressed as: Among them, τ br represents the channel path delay between RIS and the base station, represents the azimuth of the RIS arrival angle, represents the elevation angle of the RIS arrival angle, represents the transmission angle of the base station; b(·) represents the uniform linear array steering vector, which is expressed as: The matrix Θ of RIS-assisted signal beamforming is expressed as: Among them, θ N represents the phase of the Nth element during RIS auxiliary signal beamforming; v H is the vector representation of the RIS coefficient matrix Θ, and diag(·) represents the operator that transforms the vector into a diagonal matrix; Divide the entire RIS panel into S sub-panels, each of which contains N s reflection units, each sub-panel is connected to a delay module, then the delay matrix T m , expressed as: Among them, t m represents the phase shift vector caused by the delay on the mth subcarrier, expressed as: Among them, τ s Represents the parameters of the sth delay module; The signal-to-noise ratio of the received signal of the kth user on the mth subcarrier is expressed as: in, Represents the power of the noise, maximizing the weighted sum rate, then the original optimization problem P0 is expressed as: Among them, ω k represents the weighting coefficient; Tr(·) represents the matrix trace operator, P max Indicates 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 RIS; the third constraint The delay capability constraint of the delay module; When the optimization problem is a non-convex optimization problem about variables w, variables Θ and variables t, alternating optimization is used to solve it.

7. The terahertz intelligent metasurface multi-user communication system according to claim 6, characterized in that: The base station includes active beam establishment when transmitting signals, establishing base station multi-antenna beams for different users, and maximizing weighted sum rate; Solve the optimal beamforming vector w of the base station: Through the semi-positive definite relaxation SDR transformation, let but Re-expressed as: in, W is the variable to be optimized in the first optimization problem. When solving W alternately, the first optimization problem P1 is converted to: Observe that the objective function is the difference between two concave functions, and perform a first-order Taylor expansion on the second term of the objective function: in,(·) ub Defined as the upper bound of the value; at this time: By using the semi-positive definite relaxation SDR transformation and removing the rank 1 constraint, the first optimization problem P1 is transformed into the first optimization problem P1.1, which can be expressed as: The optimal solution W is obtained by using convex optimization problem solving software, and the optimal w is obtained by matrix decomposition.

8. The terahertz intelligent metasurface multi-user communication system according to claim 7, characterized in that: The delay-based RIS system includes passive beamforming establishment during auxiliary terahertz communication, establishing the phase of each reflection unit of RIS for different users, and maximizing the weighted sum rate; Solve the RIS-assisted transmit beamforming matrix Θ: make Among them, v is the variable to be optimized in the second optimization problem. When solving v alternately, the constraint with a modulus of 1 is relaxed, and the second optimization problem P2 is converted to: Introducing a set of slack variables The following constraints are met: in, Perform a first-order Taylor expansion: in,(·) lb is defined as the lower bound of the value; the second optimization problem P2 is transformed into the second optimization problem P2.1, expressed as: The optimal v is obtained by using convex optimization problem solving software.

9. The terahertz intelligent metasurface multi-user communication system according to claim 8, characterized in that: The delay-based RIS system includes delay matrix optimization for assisting terahertz communication, setting parameters of each delay module for different frequencies, and maximizing weighted sum rate; Solve the delay matrix T m : make Among them, h k,m,n Representation vector The nth element of Denotes the matrix G m The nth row of is the variable to be optimized in the third optimization problem, then solve it alternately When , the constraint with modulus 1 is relaxed, and the third optimization problem P3 is transformed into: in, Introducing a set of slack variables The following constraints are met: Perform a first-order Taylor expansion: The third optimization problem P3 is transformed into the third optimization problem P3.1, which is expressed as: The optimal solution is obtained by solving the convex optimization problem using software 10. A broadband precoding method, characterized in that: include: Active beamforming step: enabling the base station to perform active beamforming on the terahertz multi-antenna array to generate an active beamforming control signal to control the amplitude and phase of each antenna; Passive beamforming steps: the RIS panel performs passive beamforming through the FPGA intelligent controller to generate a passive beamforming control signal to control the phase of each reflector unit; Delay parameter derivation step: According to the active beamforming control signal and the passive beamforming control signal, derive each delay module parameter to achieve the frequency-dependent RIS reflection phase.

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