CN116865795A - Transmission type RIS auxiliary MIMO multi-beam alignment system and method - Google Patents

Transmission type RIS auxiliary MIMO multi-beam alignment system and method Download PDF

Info

Publication number
CN116865795A
CN116865795A CN202310823241.5A CN202310823241A CN116865795A CN 116865795 A CN116865795 A CN 116865795A CN 202310823241 A CN202310823241 A CN 202310823241A CN 116865795 A CN116865795 A CN 116865795A
Authority
CN
China
Prior art keywords
ris
transmission
base station
target
beam forming
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202310823241.5A
Other languages
Chinese (zh)
Inventor
张子恒
陈文�
李振东
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shanghai Jiaotong University
Original Assignee
Shanghai Jiaotong University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shanghai Jiaotong University filed Critical Shanghai Jiaotong University
Priority to CN202310823241.5A priority Critical patent/CN116865795A/en
Publication of CN116865795A publication Critical patent/CN116865795A/en
Pending legal-status Critical Current

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842—Weighted combining
    • H04B7/086—Weighted combining using weights depending on external parameters, e.g. direction of arrival [DOA], predetermined weights or beamforming
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The application provides a transmission type RIS auxiliary MIMO multi-beam alignment system and a method thereof, wherein the system comprises a base station, a transmission type RIS system and multiple targets; the base station comprises a MIMO multi-antenna system; the transmission RIS system assists the MIMO multi-antenna system to jointly perform beam forming, and the minimum value in the beam gain of the maximized multi-target beam direction is used as a performance index, and the multi-beam width is limited, so that the expected multi-target beam direction is obtained. The application adopts the transmission RIS auxiliary MIMO multi-antenna system, realizes the active and passive beam forming, improves the accuracy of the beam forming, enhances the beam intensity in the target direction, reduces the main lobe width, and has good compatibility when being used in combination with the original multi-antenna MIMO system.

Description

Transmission type RIS auxiliary MIMO multi-beam alignment system and method
Technical Field
The application relates to the technical field of wireless communication, in particular to a transmission type RIS auxiliary MIMO multi-beam alignment system and method.
Background
The multiple-in multiple-out (MIMO) technology has a wide application prospect in the wireless network field. With the rapid development of intelligent devices and the internet of things, the demands for high resolution and high accuracy in high-speed, high-bandwidth, low-delay data transmission, sensing and positioning are increasing. In this regard, beamforming techniques of multi-antenna MIMO technology play an important role. Beamforming is a technique for generating a directional beam by adjusting the phase and amplitude of an antenna, and can more intensively transmit signal energy to a specific direction or area, thereby improving the strength and accuracy of a communication signal. The multi-antenna MIMO technology can transmit signals simultaneously using a plurality of antennas, so that signal energy is more intensively transmitted to a desired direction or region without increasing transmission power, thereby improving the beamforming effect. Meanwhile, the multi-antenna MIMO technology can also reduce multipath interference in beam forming and improve the reliability and stability of signals. In the next generation wireless network, the multi-antenna MIMO technology has become an indispensable component, and has been widely used in various fields such as internet of vehicles, smart home, smart manufacturing, and the like. The application of the large-scale array antenna can further improve the performance of the multi-antenna MIMO technology, so that the multi-antenna MIMO technology plays a more important role in wider application scenes. Therefore, the prospect of multi-antenna MIMO technology is very clear, and will play an increasingly important role in future wireless networks. In next generation wireless networks, high-band signals are typically used in order to increase communication rates and perceived positioning system resolution.
The Chinese patent document with publication number of CN105610478A discloses a method and a device for aligning millimeter wave MIMO communication multi-subarray beams, wherein the method comprises the following steps: the receiving and transmitting end analyzes the code books corresponding to the subarrays and performs space division according to the code books, each subarray extracts code words from the own code book to form corresponding subcodebooks, and the union of the extracted subcodebooks can cover the original space. Based on the extracted sub-codebook, the transmitting end uses a plurality of beams to transmit signals, and for the transmitting combination of the transmitting end, the receiving end uses a plurality of beams to receive signals simultaneously based on the extracted sub-codebook. And calculating the main direction of the channel and further realizing beam selection by using the information acquired in the training stage.
With respect to the related art described above, the inventors consider that transmission of high frequency signals suffers from higher path loss, resulting in a need for denser base station networking construction. This further increases the networking cost of the entire network. To solve this problem, it is a challenge to control the cost overhead while researching how to improve the performance of the multi-antenna base station system, because in practical applications, the networking cost of the wireless network is often very expensive, and thus a new technology needs to be found to balance the network performance and the networking cost.
Disclosure of Invention
Aiming at the defects in the prior art, the application aims to provide a transmission type RIS auxiliary MIMO multi-beam alignment system and a transmission type RIS auxiliary MIMO multi-beam alignment method.
The transmission type RIS auxiliary MIMO multi-beam alignment system provided by the application comprises a base station, a transmission type RIS system and multiple targets;
the base station comprises a MIMO multi-antenna system;
the transmission RIS system assists the MIMO multi-antenna system to jointly perform beam forming, and the minimum value in the beam gain of the maximized multi-target beam direction is used as a performance index, and the multi-beam width is limited, so that the expected multi-target beam direction is obtained.
Preferably, the transmission type RIS system comprises a transmission type RIS panel and an FPGA intelligent controller;
the transmissive RIS panel comprises a plurality of transmissive units;
the base station generates a control signal of the MIMO multi-antenna array, controls the amplitude and the phase of the MIMO multi-antenna array through digital beam forming, and performs active beam forming;
the FPGA intelligent controller generates control signals of the transmission units, and the transmission RIS panel controls the amplitude and the phase of each transmission unit through the FPGA intelligent controller to perform passive beam forming.
Preferably, the base station comprises a radar base station;
the radar base station generates an active beam forming control signal, and acquires a multi-antenna signal subjected to active beam forming by the base station through a base station baseband signal;
the transmission RIS system generates passive beam forming control signals, the transmission RIS system performs passive beam forming on the signals formed by the active beam forming of the multi-antenna array, and the transmission RIS coefficient matrix G is controlled to establish the amplitude and the phase of all elements so that the transmission signals aim at multiple targets.
Preferably, the transmissive RIS system is a passive transmissive RIS system;
when the transmission type RIS system assists the MIMO multi-antenna system to carry out beam forming, constructing an optimization problem with the minimum value in the beam gain in the maximized target direction as an objective function and the maximum transmitting power and RIS unit transmission capacity as constraints;
by taking the optimization problem of the beam gain of the maximized constructed target direction as a non-convex optimization problem, all optimization variables are solved by alternating optimization based on a semi-positive relaxation and continuous convex approximation algorithm.
Preferably, the MIMO multi-antenna system has M transmitting antennas, O target directions need to be sensed, i e {1,2, …, O }, and N transmitting units for the transmitting RIS panel; the signal y received by the ith target i Represented as
Wherein the first term gamma i a T (θ i ) GHws is the signal expected to be received by the ith target; second term n i Indicating noise interference experienced by the ith target; gamma ray i Channel fading coefficients from the base station to the ith target; θ i Indicating the position of the i-th target relative to the base station angle; a (theta) i ) Representing a received steering vector for a target of angle i; (. Cndot. T A transpose operator representing a matrix or vector, G representing a matrix when transmitting RIS auxiliary signal beamforming; h denotes a near field channel between the radar antenna array and the transmissive RIS; w represents a base station beamforming vector; s denotes the transmitted discrete baseband signal;indicating that the formula holds for any ith target;
a(θ i ) Represented as
Wherein e represents a natural constant; d represents the antenna spacing; f (f) c Representing the signal carrier frequency; c represents the speed of light; j represents an imaginary unit and,a vector representing a dimension N x 1;
wherein ,αn Representing the amplitude of the nth element in the beamforming of the transmission RIS auxiliary signal; beta n Representing the phase of the nth element when transmitting the RIS auxiliary signal for beamforming, G being the vector representation of the RIS coefficient matrix G, diag (·) representing the operator for converting the vector into a diagonal matrix;
angle of theta i Signal-to-noise ratio SNR (θ) of a target received signal i ) Represented as
wherein ,representing the power of noise received by the ith target, maximizing the beam at θ i The signal-to-noise ratio of the direction ensures the beam intensity and simultaneously ensures that the maximized beam has preset attenuation in a preset angle range, and the original optimization problem P0 is expressed as
P0:
wherein ,Pmax Representing the maximum transmit power of the radar base station, a first constraintIs a constraint of maximum transmit power; θ 3db Representing the required 3dB bandwidth angle, the second constraint +.>And a third constraint->The beam main lobe is ensured to meet the width requirement; fourth constraint->Amplitude constraints for RIS; fifth constraint->Phase constraint for RIS;
due to the maximum minimization problem, by introducing the auxiliary variable t, the original optimization problem P0 is re-expressed as:
P0:
when the optimization problem is a non-convex optimization problem with respect to w-variables and G-variables, an alternating optimization solution is employed.
Preferably, the base station establishes an active beam when transmitting a sensing signal, establishes a base station MIMO multi-antenna beam aiming at the user or target orientations of different angles, maximizes the beam gain and ensures the beam width;
solving an optimal beamforming vector w of a base station:
when alternately solving w, the first optimization problem P1 is converted into
P1:
Where w is represented in quadratic form at SNR (θ i ) In which w=ww is given by half-positive relaxation of SDR conversion H ,(·) H Representing the conjugate transpose operator of the matrix or vector, then SNR (θ i ) Re-expressed as
Where tr (·) represents the operator of the matrix-trace, W is the variable to be optimized of the first optimization problem, S 1,i For the defined intermediate quantity, expressed asAfter SDR conversion, the constraint of the objective function and the beam width becomes convex constraint; (. Cndot. * A conjugate operator representing a matrix or vector;
to ensure that the solution yields W decomposed into ww H The rank of W is required to be 1, and rank 1 constraint is equivalent to
Wherein I 2 A calculator representing a calculated maximum eigenvalue;
calculating the maximum characteristic value as non-convex operation, and performing first-order Taylor expansion
wherein ,umax (W (m) ) Representing a feature vector corresponding to the maximum feature value of the first optimization variable W in the mth iteration;to define the sign, here (·) lb A lower bound defined as a numerical value;
the first optimization problem P1 is converted into a first one-to-one problem P1.1, expressed as
P1.1:
wherein ,γ0 Represents a penalty factor, and κ represents an exponential growth factor;
and solving by a solution software of the convex optimization problem to obtain an optimal solution W, and obtaining the optimal solution W by matrix decomposition.
Preferably, according to passive beamforming establishment when transmitting RIS auxiliary MIMO multi-antenna, each unit amplitude and phase of RIS is established for different angle users or target orientation, and the maximum beam gain is carried out and the beam width is ensured;
solving an RIS auxiliary transmission beam forming matrix G:
when solving G alternately, the second optimization problem P2 is converted into
P2:
Where G is in quadratic form in SNR (θ i ) In (a) by semi-positive relaxation of SDR conversion by exploiting the characteristics of the G diagonal matrix, i.e., a T (θ i )G＝g T ·diag(a T (θ i ) By constructing a quadratic form signal-to-noise ratio re-representation
wherein ,R＝gT ·g * R is a variable to be optimized of the second optimization problem, S 2,i For defined intermediate variables, this can be expressed asAfter SDR conversion, the constraint of the signal to noise ratio is changed into a convex constraint;
to ensure that R can be decomposed into g T ·g * The rank of R is required to be 1, and rank 1 constraint is equivalent to
Performing a first order taylor expansion
wherein ,umax (R (m) ) Representing a feature vector corresponding to the maximum feature value of the optimization variable R in the mth iteration; the second optimization problem P2 is converted to a problem P2.1, denoted as
P2.1:
And solving by a solution software of the convex optimization problem to obtain an optimal R, and obtaining an optimal g by matrix decomposition.
According to the transmission type RIS auxiliary MIMO multi-beam alignment method provided by the application, a transmission type RIS auxiliary MIMO multi-beam system is applied, the transmission type RIS auxiliary MIMO multi-antenna system is combined for beam forming, and the minimum value in the maximum beam gain of the multi-target beam direction is used as a performance index, and the multi-beam width is limited, so that the expected multi-target beam direction is obtained.
Preferably, the method comprises the steps of:
an active beam forming step: the base station generates a control signal of the MIMO multi-antenna array, controls the amplitude and the phase of the MIMO multi-antenna array through digital beam forming, and performs active beam forming;
passive beamforming: the FPGA intelligent controller generates control signals of the transmission units, and the transmission RIS panel controls the amplitude and the phase of each transmission unit through the FPGA intelligent controller to perform passive beam forming.
Preferably, in the step of active beamforming, the radar base station generates an active beamforming control signal, and obtains a multi-antenna signal after the base station performs active beamforming through a base station baseband signal;
in the passive beam forming step, a transmission RIS system generates a passive beam forming control signal, the transmission RIS system performs passive beam forming on the signals formed by the active beam forming of the multi-antenna array, and a transmission RIS coefficient matrix G is controlled to establish the amplitude and the phase of all elements so as to enable the transmission signals to be aligned to multiple targets.
Compared with the prior art, the application has the following beneficial effects:
1. the application adopts a transmission RIS auxiliary MIMO multi-antenna system, realizes active and passive beam forming, improves the accuracy of beam forming, enhances the beam intensity in the target direction, reduces the main lobe width, and has good compatibility when being used in combination with the original multi-antenna MIMO system;
2. the application realizes signal transmission by using the transmission RIS, and avoids the problems of signal self-interference and signal attenuation caused by reflection RIS;
3. the application has simple structure, comprises RIS and intelligent controller, and has low hardware deployment cost and small additional power cost, thus being a novel green auxiliary sensing system.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments, given with reference to the accompanying drawings in which:
FIG. 1 is a transmissive RIS-assisted MIMO multi-antenna multi-beam aiming system;
fig. 2 is θ= [ -pi/6, pi/6]，θ 3dB Pi/16, m=18, n=36 with or without RIS auxiliary beam contrast pattern;
fig. 3 is θ= [ -pi/4, 0, pi/3]，θ 3dB Pi/16, m=18, n=36 with or without RIS auxiliary beam contrast pattern.
Detailed Description
The present application will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the present application, but are not intended to limit the application in any way. It should be noted that variations and modifications could be made by those skilled in the art without departing from the inventive concept. These are all within the scope of the present application.
The embodiment of the application discloses a transmission type RIS auxiliary MIMO multi-antenna multi-beam alignment system, which is shown in figure 1 and comprises a MIMO multi-antenna system, a transmission type RIS panel, an FPGA intelligent controller and a beam pattern of a desired multi-target. Further, the minimum and limit beam width in the beam gain to maximize the multiple target beam directions are included. A transmission RIS assisted MIMO multi-antenna system that achieves an ideal beam pattern by a joint beamforming design of the RIS surface and the MIMO multi-antennas when transmitting signals. The transmission RIS system assists the MIMO multi-antenna system to jointly perform beam forming, and the minimum value in the beam gain of the maximized multi-target beam direction is used as a performance index, and the multi-beam width is limited, so that the expected multi-target beam direction is obtained.
In the system, the base station controls the amplitude and the phase of the multi-antenna array through digital beam forming, and the RIS controls the amplitude and the phase of each transmission unit through an intelligent controller, so that the combined passive and active beam forming design is realized.
Transmissive RIS-assisted MIMO multi-antenna system: the base station and the transmission type RIS are combined to form a wave beam, control signals for the multi-antenna array are generated at the base station, and control for the transmission type RIS unit is generated at an intelligent controller.
The radar base station generates an active beam forming control signal: considering the base band signal of the base station as s, the multi-antenna signal after the base station performs active beam forming design is ws, wherein the design of amplitude and phase in the active beam forming is included.
The transmission RIS performs the generation of passive beamforming control signals: the transmission RIS carries out further passive beamforming on the signals of the multi-antenna array active beamforming, the transmission RIS coefficient matrix is expressed as G, and the transmission RIS comprises amplitude and phase designs of all element units, so that the transmission signals can be further aligned to multiple targets.
Beamforming scheme in a transmissive RIS transceiver system: the minimum value of the beam gains in the maximum multi-target directions is used as a performance index, and the multi-beam width is limited. By constructing the optimization problem that the minimum value in the beam gain in the maximum target direction is taken as an objective function and the maximum transmitting power and the RIS unit transmission capacity are taken as constraints, the application realizes the scheme design of the novel transmission type RIS auxiliary MIMO multi-antenna multi-beam alignment system.
Beamforming scheme in a transmissive RIS-assisted MIMO multi-antenna multi-beam alignment system: the increased transmission RIS system required by the design system is passive, does not require an additional radio frequency link to process the incoming signal, achieves beamforming in a passive form, and achieves better performance at a lower cost.
The wave beam shaping scheme design of the transmission type RIS auxiliary MIMO multi-antenna system comprises the following steps: the design goal is to maximize the beam gain in the target direction of the build, but the optimization problem is a non-convex optimization problem, and it is difficult to directly obtain the globally optimal solution. The application provides a method based on a semi-positive relaxation and continuous convex approximation algorithm, and a sub-optimal solution with high quality is obtained by alternately optimizing all optimization variables.
The application improves the design of novel transmission type RIS auxiliary MIMO multi-antenna multi-beam aiming in face of the requirement of the next generation wireless network on beam gain performance and cost reduction. The application provides a joint design scheme based on a transmission type RIS auxiliary MIMO multi-antenna system so as to realize a more efficient wireless communication or sensing system. The system includes a base station antenna array and a transmissive RIS, both of which require beamforming design. The beamforming design of the base station antenna array realizes active transmitting beamforming by controlling the amplitude and the phase of each antenna so as to improve the accuracy and the effectiveness of transmitting signals. The beam forming design of the transmission RIS realizes passive emission beam forming by controlling the amplitude and the phase of each transmission unit so as to improve the accuracy and the amplitude of signals.
Considering a MIMO multi-antenna system, there are M transmitting antennas in total, s represents the transmission of discrete baseband signals (which may be communication or radar signals), and there are O target directions to be sensed, numbered i ε {1,2, …, O }, θ i Representing the angle of the position of the ith target, for which the received signal can be expressed as
Wherein the first term alpha i a T (θ i ) GHws is the signal expected to be received by the ith target; second term n i Indicating the noise interference suffered by the ith target, n i Mean value 0, varianceIs a complex gaussian random variable; alpha i Channel fading coefficients from the base station to the ith target; θ i Indicating the position of the i-th target relative to the base station angle; gamma ray i Channel fading coefficients from the base station to the ith target; a (theta) i ) Representing a received steering vector for a target of angle i; (. Cndot. T A transpose operator representing a matrix or vector, G representing a matrix when transmitting RIS auxiliary signal beamforming; h denotes a near field channel between the radar antenna array and the transmissive RIS; w represents a base station beamforming vector; s denotes the transmitted discrete baseband signal; />Meaning that the formula holds for any i-th object.
a(θ i ) The steering vector representing reception for an angle i target may be expressed as
Wherein e represents a natural constant; d represents the antenna spacing; f (f) c Representing the signal carrier frequency; c represents the speed of light; j represents an imaginary unit and,representing a vector of dimension N x 1.
H is the near field channel between the radar antenna array and the transmissive RIS. G represents the matrix when transmitting the RIS auxiliary signal, wherein ,αn Representing the amplitude of the nth element in the beamforming of the transmission RIS auxiliary signal; beta n Representing the phase of the nth element when transmitting the RIS auxiliary signal for beamforming, G being the vector representation of the RIS coefficient matrix G, diag (·) representing the operator for converting the vector into a diagonal matrix; alpha n and βn The amplitude and phase of the i-th element when transmitting the RIS auxiliary signal are shown, respectively. Thus the angle is theta i Target joint of (2)The signal-to-noise ratio (Signal to Interference plus Noise Ratio, SNR) of the received signal can be expressed as
wherein ,the power representing the noise experienced by the ith target, to improve beam quality, requires maximizing the beam at θ i The signal-to-noise ratio of the direction ensures the beam intensity while ensuring that the beam has sufficient attenuation over the required angular range, so that the overall optimization problem can be expressed as, i.e., the original optimization problem P0 is
P0:
wherein ,Pmax Representing the maximum transmit power of the radar base station, a first constraintIs a constraint of maximum transmit power; θ 3db Representing the required 3dB bandwidth angle, the second constraint +.>And a third constraint->The beam main lobe is ensured to meet the width requirement; fourth constraint->Amplitude constraints for RIS; fifth constraint->Is a phase constraint of the RIS. P (P) max Representing the maximum transmission power of the radar base station, wherein the 1 st constraint is the constraint of the maximum transmission power; θ 3dB Representing the required 3dB bandwidth angle, the 2 nd, 3 rd constraint ensures that the beam main lobe meets the width requirement. The 4 th and 5 th constraints are the amplitude and phase constraints of the RIS, respectively. Since this is a max-min problem, the original problem can be re-expressed as,
P0:
the whole optimization problem is a non-convex optimization problem of two variables w and G, and the application adopts an alternate optimization method to solve.
Example 1:
the application provides an active beam design when transmitting a sensing signal, and aims at users or targets with different angles to directionally design a base station MIMO multi-antenna beam, thereby realizing the maximization of the beam gain and ensuring the beam width.
(1) Solving optimal beamforming vector w of base station
When alternately solving w, the entire optimization problem can be converted into, i.e., the first optimization problem P1 into
P1:
Because ofw is represented in quadratic form in SNR (θ i ) In, we therefore transformed by the method of semi-positive relaxation (Semidefinite Relaxation, SDR), let w=ww H ，(·) H The conjugate transpose operator representing the matrix or vector, then SNR (θ i ) Can be re-expressed as
Where tr (·) represents the operator of the matrix-trace, W is the variable to be optimized of the first optimization problem, S 1,i For the defined intermediate quantity, expressed asAfter SDR conversion, the constraint of the objective function and the beam width becomes convex constraint; (. Cndot. * Representing the conjugate operator of the matrix or vector. However, to ensure that the solution yields W that can be decomposed into ww H The rank of W is required to be 1, and the rank 1 constraint can be equivalently +.>Wherein I II 2 A calculator that calculates the maximum eigenvalue. However, the maximum eigenvalue is calculated as a non-convex operation, which can be subjected to a first-order Taylor expansion
wherein ,umax (W (m) ) And the feature vector corresponding to the maximum feature value of the optimization variable W in the mth iteration is represented.To define the sign, here (·) lb Is defined as the lower bound of the numerical value. Thus, the optimization problem P1 can be further converted into a problem P1.1, expressed as
P1.1:
wherein ,γ0 Represents a penalty factor and κ represents an exponential growth factor. The whole problem is converted into a standard Semi-defined Program (SDP) convex problem, a high-quality optimal solution W can be obtained through solving a convex optimization problem by solving software (such as CVX), and the optimal solution W can be obtained through matrix decomposition.
Example 2:
the application provides a passive beam forming design when transmitting RIS auxiliary MIMO multi-antenna, and designs each unit amplitude and phase of RIS aiming at users or targets with different angles, thereby realizing the maximization of beam gain and ensuring beam width.
(2) Solving RIS auxiliary transmitting beam forming matrix G
When solving G alternately, the whole optimization problem can be converted into
P2:
Similarly, because G appears in quadratic form in SNR (θ i ) In (2), we therefore transformed by a method of half-positively relaxing SDR, since the secondary forms of G cannot be directly combined, GG is required to be utilized t Characteristics of diagonal matrix, i.e. a T (θ i )G＝g T ·diag(a T (θ i ) By constructing a quadratic form signal-to-noise ratio that can be re-expressed as
wherein ,R＝gT ·g * ，After SDR conversion, the constraint of the signal to noise ratio becomes a convex constraint. However, to ensure that the solution yields R which can be decomposed into g T ·g * The rank of R is required to be 1, and the rank 1 constraint can be equivalently +.>Wherein I II 2 A calculator that calculates the maximum eigenvalue. However, the maximum eigenvalue is calculated as a non-convex operation, which can be subjected to a first-order Taylor expansion
wherein ,umax (R (m) ) And the feature vector corresponding to the maximum feature value of the optimization variable R in the mth iteration is represented. Thus, the optimization problem P2 can be further converted into a problem P2.1, denoted as
P2.1:
s.t.
/>
wherein ,γ0 Representing a penalty factor. After being converted into the whole problem, the whole problem becomes a standard SDP convex problem, a high-quality optimal R can be obtained through solving by a solution software CVX of the convex optimization problem, and an optimal g can be obtained through matrix decomposition.
And (3) alternately optimizing the 2 sub-problems until the whole system is converged to obtain the final system design.
Fig. 1 depicts the basic structural composition of the application, and fig. 2 and 3 compare the beam gains of the application at different target angles.
In recent years, reconfigurable super surface (RIS) technology is a technology of great interest in wireless communication and sensing systems, and has a gradually expanding application range, so that the reconfigurable super surface (RIS) technology has important significance for future wireless network development. As a brand new wireless electronic device, RIS is controlled by reflection, refraction, transmission and the like of electromagnetic waves according to the flexible and controllable characteristics, so that the performance of a communication and sensing system is obviously improved, and the deployment cost of the system is reduced. For a communication system, the application of RIS can greatly improve the quality of a communication channel, and meanwhile, the blind coverage problem of signals can be solved, so that full-coverage communication is realized. In a multi-antenna system, RIS can realize beam forming by controlling reflection, transmission and the like of signals, and improve channel capacity in multipath transmission, thereby realizing efficient data transmission. Furthermore, RIS is able to optimize communication quality and signal coverage by interference cancellation of signals. RIS can also improve system performance for a perception system. The RIS can realize passive beam forming, accurately position the target to be sensed or positioned, and improve the accuracy and strength of the sensing signal. In addition, since the RIS can receive multipath signals, it can achieve higher resolution accuracy, thereby improving the perceptual performance of the system. Therefore, the RIS has wide application prospect in future wireless sensing networks. Notably, compared with the traditional reflective RIS, the transmissive RIS can effectively reduce the problems of self-interference and feed shielding, and improve the aperture efficiency, thereby realizing the performance improvement of a more efficient MIMO multi-antenna system. In addition, the passive characteristic of RIS can also greatly reduce the deployment cost of the system, and bring great economic benefits to network construction and maintenance. In summary, RIS technology has wide application prospect and realization value, and will have profound effects on the development of future wireless communication and perception systems. Therefore, the flexible and controllable characteristics of the wireless communication system are fully utilized in the research and development process, and the important roles of the wireless communication system and the sensing system are played.
The application relates to a transmission-based intelligent super surface (RIS) auxiliary MIMO multi-antenna base station system, which aims at realizing information beams accurately aiming at a plurality of target directions by jointly designing active and passive beam forming. The system consists of a MIMO antenna array, a transmission RIS, an FPGA intelligent controller and an expected target pattern.
In the system, the MIMO antenna and the RIS intelligent controller respectively carry out beam forming on the multi-antenna transmitting array and the transmission RIS through design information of amplitude and phase, so that accurate aiming of information beams is realized and the information beams are sent to a target position. In addition, in order to optimize the system performance, the application designs a combined active and passive beam forming scheme, takes the minimum value in the beam gains of the maximum target directions as a performance index, and limits the multi-beam width.
Compared with the traditional MIMO multi-antenna system, the transmission type RIS auxiliary MIMO multi-antenna system can realize better performance, and meanwhile, the required additional cost and power consumption cost are relatively low, so that the system has the characteristics of environmental protection and greenness. Such a system is expected to be applied to next generation wireless networks.
The embodiment of the application also discloses a transmission type RIS auxiliary MIMO multi-beam alignment method, which is applied to a transmission type RIS auxiliary MIMO multi-beam system, wherein the transmission type RIS auxiliary MIMO multi-antenna system is used for carrying out beam forming in a combined way, and the expected multi-target beam direction is obtained by taking the minimum value in the maximum beam gain of the multi-target beam direction as a performance index and limiting the multi-beam width.
The method comprises the following steps:
an active beam forming step: the base station generates a control signal of the MIMO multi-antenna array, controls the amplitude and the phase of the MIMO multi-antenna array through digital beam forming, and performs active beam forming; the radar base station generates an active beam forming control signal, and obtains a multi-antenna signal after the active beam forming by the base station through a base station baseband signal.
Passive beamforming: the FPGA intelligent controller generates control signals of the transmission units, and the transmission RIS panel controls the amplitude and the phase of each transmission unit through the FPGA intelligent controller to perform passive beam forming. The transmission RIS system generates passive beam forming control signals, the transmission RIS system performs passive beam forming on the signals formed by the active beam forming of the multi-antenna array, and the transmission RIS coefficient matrix G is controlled to establish the amplitude and the phase of all elements so that the transmission signals aim at multiple targets.
Those skilled in the art will appreciate that the application provides a system and its individual devices, modules, units, etc. that can be implemented entirely by logic programming of method steps, in addition to being implemented as pure computer readable program code, in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Therefore, the system and various devices, modules and units thereof provided by the application can be regarded as a hardware component, and the devices, modules and units for realizing various functions included in the system can also be regarded as structures in the hardware component; means, modules, and units for implementing the various functions may also be considered as either software modules for implementing the methods or structures within hardware components.
The foregoing describes specific embodiments of the present application. It is to be understood that the application is not limited to the particular embodiments described above, and that various changes or modifications may be made by those skilled in the art within the scope of the appended claims without affecting the spirit of the application. The embodiments of the application and the features of the embodiments may be combined with each other arbitrarily without conflict.

Claims (10)

1. The transmission type RIS auxiliary MIMO multi-beam alignment system is characterized by comprising a base station, a transmission type RIS system and multiple targets;
the base station comprises a MIMO multi-antenna system;
the transmission RIS system assists the MIMO multi-antenna system to jointly perform beam forming, and the minimum value in the beam gain of the maximized multi-target beam direction is used as a performance index, and the multi-beam width is limited, so that the expected multi-target beam direction is obtained.
2. The transmissive RIS assisted MIMO multibeam alignment system of claim 1, wherein the transmissive RIS system comprises a transmissive RIS panel and an FPGA intelligent controller;
the transmissive RIS panel comprises a plurality of transmissive units;
the base station generates a control signal of the MIMO multi-antenna array, controls the amplitude and the phase of the MIMO multi-antenna array through digital beam forming, and performs active beam forming;
the FPGA intelligent controller generates control signals of the transmission units, and the transmission RIS panel controls the amplitude and the phase of each transmission unit through the FPGA intelligent controller to perform passive beam forming.
3. The transmissive RIS assisted MIMO multi-beam alignment system of claim 2, wherein the base station comprises a radar base station;
the radar base station generates an active beam forming control signal, and acquires a multi-antenna signal subjected to active beam forming by the base station through a base station baseband signal;
the transmission RIS system generates passive beam forming control signals, the transmission RIS system performs passive beam forming on the signals formed by the active beam forming of the multi-antenna array, and the transmission RIS coefficient matrix G is controlled to establish the amplitude and the phase of all elements so that the transmission signals aim at multiple targets.
4. The transmissive RIS-assisted MIMO multibeam alignment system of claim 2, wherein the transmissive RIS system is a passive transmissive RIS system;
when the transmission type RIS system assists the MIMO multi-antenna system to carry out beam forming, constructing an optimization problem with the minimum value in the beam gain in the maximized target direction as an objective function and the maximum transmitting power and RIS unit transmission capacity as constraints;
by taking the optimization problem of the beam gain of the maximized constructed target direction as a non-convex optimization problem, all optimization variables are solved by alternating optimization based on a semi-positive relaxation and continuous convex approximation algorithm.
5. The transmission type RIS auxiliary MIMO multibeam alignment system according to claim 2, wherein the MIMO multibeam system has M transmitting antennas in total, O target directions in total need to be perceived, i e {1,2, …, O }, and N transmitting units in total for the transmission type RIS panel; the signal y received by the ith target i Represented as
Wherein the first term gamma i a T (θ i ) GHws is the signal expected to be received by the ith target; second term n i Indicating noise interference experienced by the ith target; gamma ray i Channel fading coefficients from the base station to the ith target; θ i Indicating the position of the i-th target relative to the base station angle; a (theta) i ) Representing a received steering vector for a target of angle i; (. Cndot. T A transpose operator representing a matrix or vector, G representing a matrix when transmitting RIS auxiliary signal beamforming; h denotes a near field channel between the radar antenna array and the transmissive RIS; w represents a base station beamforming vector; s denotes the transmitted discrete baseband signal;indicating that the formula holds for any ith target;
a(θ i ) Represented as
Wherein e represents a natural constant; d represents the antenna spacing; f (f) c Representing the signal carrier frequency; c represents the speed of light; j represents an imaginary unit and,representation dimensionA vector of degree n×1;
wherein ,αn Representing the amplitude of the nth element in the beamforming of the transmission RIS auxiliary signal; beta n Representing the phase of the nth element when transmitting the RIS auxiliary signal for beamforming, G being the vector representation of the RIS coefficient matrix G, diag (·) representing the operator for converting the vector into a diagonal matrix;
angle of theta i Signal-to-noise ratio SNR (θ) of a target received signal i ) Represented as
wherein ,representing the power of noise received by the ith target, maximizing the beam at θ i The signal-to-noise ratio of the direction ensures the beam intensity and simultaneously ensures that the maximized beam has preset attenuation in a preset angle range, and the original optimization problem P0 is expressed as P0:
s.t.
wherein ,Pmax Representing the maximum transmit power of the radar base station, a first constraintIs a constraint of maximum transmit power; θ 3db Representing the required 3dB bandwidth angle, the second constraint +.>And a third constraintThe beam main lobe is ensured to meet the width requirement; fourth constraint->Amplitude constraints for RIS; fifth constraint->Phase constraint for RIS;
due to the maximum minimization problem, by introducing the auxiliary variable t, the original optimization problem P0 is re-expressed as:
P0:
s.t.
when the optimization problem is a non-convex optimization problem with respect to w-variables and G-variables, an alternating optimization solution is employed.
6. The transmission type RIS auxiliary MIMO multi-beam alignment system of claim 5, wherein the base station establishes an active beam when transmitting the perceived signal, establishes a base station MIMO multi-antenna beam for different angle user or target orientations, maximizes the beam gain and ensures the beam width;
solving an optimal beamforming vector w of a base station:
when alternately solving w, the first optimization problem P1 is converted into P1:
s.t.
where w is represented in quadratic form at SNR (θ i ) In which w=ww is given by half-positive relaxation of SDR conversion H ,(·) H Representing the conjugate transpose operator of the matrix or vector, then SNR (θ i ) Re-expressed as
Where tr (·) represents the operator of the matrix-trace, W is the variable to be optimized of the first optimization problem, S 1,i For the defined intermediate quantity, expressed asAfter SDR conversion, the constraint of the objective function and the beam width becomes convex constraint; (. Cndot. * A conjugate operator representing a matrix or vector;
to ensure that the solution yields W decomposed into ww H The rank of W is required to be 1, and rank 1 constraint is equivalent to
Wherein I 2 A calculator representing a calculated maximum eigenvalue;
calculating the maximum characteristic value as non-convex operation, and performing first-order Taylor expansion
wherein ,umax (W( m ) A) represents a feature vector corresponding to the maximum feature value of the first optimization variable W at the mth iteration;to define the sign, here (·) lb A lower bound defined as a numerical value;
the first optimization problem P1 is converted into a first one-to-one problem P1.1, expressed as
P1.1:
s.t.
wherein ,γ0 Represents a penalty factor, and κ represents an exponential growth factor;
and solving by a solution software of the convex optimization problem to obtain an optimal solution W, and obtaining the optimal solution W by matrix decomposition.
7. The transmissive RIS assisted MIMO multi-beam alignment system of claim 5, wherein maximizing beam gain and guaranteeing beam width is performed for each element amplitude and phase of the RIS established for different angle user or target orientations according to passive beamforming establishment when transmitting the RIS assisted MIMO multi-antennas;
solving an RIS auxiliary transmission beam forming matrix G:
when solving G alternately, the second optimization problem P2 is converted into
P2:
s.t.
Where G is in quadratic form in SNR (θ i ) In (a) by semi-positive relaxation of SDR conversion by exploiting the characteristics of the G diagonal matrix, i.e., a T (θ i )G＝g T ·diag(a T (θ i ) By constructing a quadratic form signal-to-noise ratio re-representation
wherein ,R＝gT ·g * R is a variable to be optimized of the second optimization problem, S 2,i For defined intermediate variables, this can be expressed asAfter SDR conversion, the constraint of the signal to noise ratio is changed into a convex constraint;
to ensure that R can be decomposed into g T ·g * The rank of R is required to be 1, and rank 1 constraint is equivalent to
Performing a first order taylor expansion
wherein ,umax (R (m) ) Representing a feature vector corresponding to the maximum feature value of the optimization variable R in the mth iteration; the second optimization problem P2 is converted to a problem P2.1, denoted as
P2.1:
s.t.
And solving by a solution software of the convex optimization problem to obtain an optimal R, and obtaining an optimal g by matrix decomposition.
8. A transmission type RIS auxiliary MIMO multi-beam alignment method, characterized in that the transmission type RIS auxiliary MIMO multi-beam system according to any one of claims 1 to 7 is applied, the transmission type RIS system auxiliary MIMO multi-antenna system is combined to perform beam forming, and a desired multi-target beam direction is obtained by taking the minimum value of the beam gains in the maximized multi-target beam direction as a performance index and limiting the multi-beam width.
9. The transmissive RIS assisted MIMO multi-beam alignment method of claim 8, comprising the steps of:
an active beam forming step: the base station generates a control signal of the MIMO multi-antenna array, controls the amplitude and the phase of the MIMO multi-antenna array through digital beam forming, and performs active beam forming;
passive beamforming: the FPGA intelligent controller generates control signals of the transmission units, and the transmission RIS panel controls the amplitude and the phase of each transmission unit through the FPGA intelligent controller to perform passive beam forming.
10. The transmission type RIS auxiliary MIMO multi-beam alignment method according to claim 9, wherein in the active beamforming step, the radar base station generates an active beamforming control signal, and obtains a multi-antenna signal after the active beamforming by the base station through a base station baseband signal;
in the passive beam forming step, a transmission RIS system generates a passive beam forming control signal, the transmission RIS system performs passive beam forming on the signals formed by the active beam forming of the multi-antenna array, and a transmission RIS coefficient matrix G is controlled to establish the amplitude and the phase of all elements so as to enable the transmission signals to be aligned to multiple targets.
CN202310823241.5A 2023-07-06 2023-07-06 Transmission type RIS auxiliary MIMO multi-beam alignment system and method Pending CN116865795A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310823241.5A CN116865795A (en) 2023-07-06 2023-07-06 Transmission type RIS auxiliary MIMO multi-beam alignment system and method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310823241.5A CN116865795A (en) 2023-07-06 2023-07-06 Transmission type RIS auxiliary MIMO multi-beam alignment system and method

Publications (1)

Publication Number Publication Date
CN116865795A true CN116865795A (en) 2023-10-10

Family

ID=88233510

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310823241.5A Pending CN116865795A (en) 2023-07-06 2023-07-06 Transmission type RIS auxiliary MIMO multi-beam alignment system and method

Country Status (1)

Country Link
CN (1) CN116865795A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117278084A (en) * 2023-11-22 2023-12-22 北京科技大学 Combined beam forming design method in unmanned aerial vehicle ventilation integrated network

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117278084A (en) * 2023-11-22 2023-12-22 北京科技大学 Combined beam forming design method in unmanned aerial vehicle ventilation integrated network
CN117278084B (en) * 2023-11-22 2024-02-13 北京科技大学 Combined beam forming design method in unmanned aerial vehicle ventilation integrated network

Similar Documents

Publication Publication Date Title
CN110166103B (en) Novel hybrid beam forming structure and setting method of millimeter wave MU-MISO system
CN113285897B (en) Positioning information assistance-based channel estimation method and system in RIS system under Internet of vehicles environment
CN111294096A (en) Channel capacity optimization method of intelligent reflector MISO wireless communication system
CN107181519B (en) Null steering expansion 3D-MIMO beam forming method based on moving target DOA
CN105098383A (en) Multi-beam antenna system and phase adjustment method thereof and polarized antenna system
CN116865795A (en) Transmission type RIS auxiliary MIMO multi-beam alignment system and method
CN110138427A (en) Extensive multiple-input and multiple-output mixed-beam forming algorithm based on part connection
CN114679208A (en) Transmitting beam forming method of millimeter wave communication perception integrated system
CN113765565A (en) Non-orthogonal multiple access communication method and system based on reconfigurable holographic super surface
CN113726411A (en) Satellite communication device based on reconfigurable holographic super surface and optimization method thereof
CN113852402B (en) IRS (intelligent communications system) -assisted NOMA-MIMO (non-multiple input multiple output) high-capacity access method
CN113747453A (en) Multi-cell wireless communication system and method based on reconfigurable holographic super-surface antenna
CN113595607B (en) Hybrid precoding method and system based on reconfigurable holographic super surface
CN116112045A (en) Precoding and reflected wave beam design method of millimeter wave MIMO system based on IRS
CN116614161A (en) Radar communication integrated beam forming method based on linear constraint power distribution
CN114513237B (en) Subarray structure design method for large-scale array communication
CN114499615B (en) Near-far field unified transmitting beam forming method in terahertz communication system
CN116054894A (en) Mixed pre-coding method for inhibiting beam squint influence
CN115833887A (en) Antenna selection and beam forming method for dynamic super-surface antenna array
CN114785387A (en) Intelligent omnidirectional surface-assisted multi-user large-scale MISO downlink weighting and rate optimization method
CN116865794A (en) Transmission type RIS auxiliary MIMO wave beam alignment system and method
CN114039638A (en) Combined design method of hybrid beam former and analog-digital converter
CN113746519A (en) Multi-point cooperative transmission system and method based on reconfigurable holographic super-surface antenna
CN112636800A (en) Mixed precoding algorithm based on millimeter wave large-scale MIMO multi-user scene
CN113761604A (en) Optimization method and system for weakening reconfigurable holographic super-surface radiation side lobe

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination