Energy efficiency optimization design method based on ris-aided mu-miso-oddm system

Abstract

The application discloses an energy efficiency optimization design method based on an RIS assisted MU-MISO-ODDM system, comprising the following steps: constructing an RIS assisted MU-MISO-ODDM system; generating and processing an ODDM modulation signal to obtain a time domain transmission signal, and transmitting the time domain transmission signal to a user equipment; constructing a double-selectivity channel model to obtain a user equipment receiving signal matrix; the user equipment performs matching filtering, sampling, CP discarding and equal-gain combining operations on the received signal matrix to obtain a combined receiving signal vector; and an energy efficiency optimization problem of the user equipment receiving signal of the MU-MISO-ODDM system is constructed and solved. The method is used to alternately optimize the pre-coding of the transmitting end and the RIS phase shift matrix, construct a joint iteration algorithm, and realize the optimal configuration of the system energy efficiency in a high mobility scene, with ODDM modulation and RIS assistance as the core.

Description

Technical Field

[0001] This invention relates to the field of high-mobility wireless communication technology, and in particular to an energy efficiency (EE) optimization design method for multi-user (MU) - multiple-input single-output (MISO) - orthogonal delay-Doppler modulation (ODDM) systems based on reconfigurable intelligent surface (RIS) assistance. Background Technology

[0002] As wireless communication systems evolve towards higher mobility, severe Doppler shift and multipath effects lead to performance degradation. Traditional orthogonal frequency-division multiplexing (OFDM) technology not only suffers from severe inter-carrier interference (ICI) in high-speed mobile scenarios, but also has other shortcomings such as out-of-band emission (OOBE) and inter-symbol interference. To address the time-varying challenges of high-mobility channels, orthogonal time-frequency space (OTFS) modulation technology has emerged. It transforms the fast time-varying channel in the time-frequency (TF) domain into a two-dimensional quasi-time-invariant channel in the delay-Doppler (DD) domain, thus exhibiting stronger robustness for high-speed mobile communication scenarios. However, OTFS is essentially a pre-coded OFDM modulation technique. Like OFDM, its transmitted signals are orthogonal pulses in the TF domain. These orthogonal pulses still cause high OOBE (Out-of-Body Response) and significant inter-symbol interference (ISI) in practical communication. To address this, ODDM (Other-Carrier Modulation) was proposed. It is a multi-carrier modulation technique that operates directly in the DD domain. By introducing a series of square-root Nyquist pulses, it achieves orthogonality of the modulated signals in the DD domain, effectively avoiding the OOBE and ISI shortcomings of OTFS. Current research on ODDM has initially covered signal detection, channel estimation, and precoding design, and has begun to integrate with non-orthogonal multiple access (NOMA) and integrated sensing technologies.

[0003] Meanwhile, RIS, as a core enabling technology in 6G communication, dynamically controls the propagation path of the wireless channel through programmable components to achieve signal enhancement, interference suppression, and wireless environment reconstruction. After several years of research and development, RIS has gradually evolved from its initial passive form to a series of forms such as active RIS and hybrid RIS, and has been widely combined with various modulation technologies to carry out resource optimization research.

[0004] After investigation, it was found that most of the current research results on resource optimization of RIS-assisted OTFS systems are based on the optimization of signal-to-noise ratio and data transmission rate. More importantly, there are few reports on the research results on resource optimization of RIS-assisted ODDM systems. Therefore, it is of great research significance to construct a RIS-assisted ODDM system EE optimization scheme to fill the technical gap in the co-optimization of ODDM systems and RIS. Summary of the Invention

[0005] The purpose of this invention is to achieve optimal energy efficiency parameter configuration at the user equipment (UE) receiving end of a RIS-assisted MU-MISO-ODDM system.

[0006] To achieve the above objectives, this invention provides an energy efficiency optimization design method based on a RIS-assisted MU-MISO-ODDM system, comprising the following steps: S1. Construct a smart reflector RIS-assisted multi-user multiple-input single-output quadrature delay Doppler diversity multiplexing (MU-MISO-ODDM) system; S2. Generate and process the quadrature delayed Doppler diversity multiplexing (ODDM) modulated signal to obtain the time-domain transmission signal, and transmit the time-domain transmission signal to... One user equipment (UEs); S3. Construct a dual-selectivity channel model for the first... User Equipment (hereinafter referred to as) The received signal in the time domain is processed to obtain... The received signal matrix; S4 The received signal matrix is ​​sequentially subjected to matched filtering, sampling, discarding the cyclic prefix (CP), equal gain combining operation, and the combined received signal vector is obtained. S5. Construct and solve the energy efficiency optimization problem of the MU-MISO-ODDM system.

[0007] Preferably, S1 is as follows: S11, Configuration A base station (BS) with one antenna. Single-antenna UEs, and deployed with RIS of one reflective unit; S12, BS and Each single-antenna UE uses ODDM modulation technology, as detailed below: definition Delay-Doppler DD mesh ;in, and They represent delay units and One Doppler unit; and These represent the number of delay symbols and Doppler symbols within a frame, respectively. and These represent the resolutions of the delay axis and the Doppler axis, respectively. and Let represent the time slot duration and subcarrier spacing, respectively, and satisfy . .

[0008] Preferably, S2 is as follows: S21, Constructing transmission to U units in the DD domain. of Quadrature amplitude modulation (QAM) symbol matrix; S22, Regarding the DD domain The QAM symbol matrix is ​​executed along the Doppler dimension. The inverse fast Fourier transform (IFFT) operation yields... Time-delay field symbol; S23. Perform a parallel / string conversion on the time-delay domain symbol to obtain... The time-domain digital sequence, and integrated indivual The time-domain digital sequence is obtained. indivual Time-delay domain symbol matrix; S24. Pre-encode the MU delay domain symbol matrix using the pre-coding matrix to generate the base station. The transmit symbol matrix of the root transmitting antenna; S25. Add CP to the... The antenna's transmitted symbols are obtained by filtering them using rectangular pulses. Time-domain transmission signals; S26. Transmit the time-domain signal from the base station. The antenna transmits to simultaneously indivual .

[0009] Preferably, S3 is as follows: S31. Define the normalized form of the DD domain biselective channel response and establish the biselective channel matrix H: ;in, Indicates the first One multipath propagation component; This represents the total number of multipath propagation components; , , They represent the first Channel gain coefficient, delay factor, and Doppler factor in each multipath propagation component; Represents the delay matrix; Represents the Doppler frequency shift matrix; S32. Decompose the actual communication link into a direct link and a reflection link, and establish the channel response for each link as follows: Direct link channel response: ;in, and These represent the delayed variable and the Doppler variable, respectively. Indicates the first in the direct link One multipath propagation component; This represents the total number of multipath propagation components in a directly connected link; Represents the unit impulse response function; , , These represent the first direct link. Channel gain coefficient, delay offset coefficient, and Doppler shift coefficient for each multipath component; The reflection link channel consists of the base station-intelligent reflector (BS-RIS) channel and the intelligent reflector-user equipment (UE) channel. The channels are cascaded, and their channel responses are as follows: (1) BS-RIS channel response: ;in, Indicates the first Channel gain coefficients for each multipath propagation component; Indicates the first Delay coefficients for each multipath propagation component; (2) Channel response: ;in, Indicates the first One multipath propagation component; This represents the total number of multipath propagation components in the reflection link; , , They represent Link number Channel gain, delay offset coefficient, and Doppler shift coefficient of each multipath component; S33. The total received signal is obtained by superimposing the direct link signal and the reflected link signal, and then processing it through discretization and matrixing. The received signal matrix, where: Direct link: ;in, , , They represent The Middle Channel gain coefficient, delay offset coefficient, and Doppler shift coefficient for each multipath propagation component; Indicates BS-UE u The Middle The multipath propagation components are in The additive white Gaussian noise (AWGN) signal at time 1; Reflection Link: ; in, In BS-RIS The first reflector unit Channel gain coefficients for each multipath propagation component; express The Middle The first reflector unit Channel gain coefficients for each multipath propagation component; , They represent BS-RIS and exist The AWGN signal at that moment.

[0010] Preferably, S4 is as follows: S41. Decompose the received signal matrix into The received signal corresponding to the antenna is subjected to matched filtering to obtain The filtered signal; S42, at the sampling time Place, to The filtered signal is sampled to obtain A discrete signal with CP; S43, to Perform a CP discarding operation on a discrete signal with CP, and obtain... A discrete-time domain signal; S44, to The discrete time-domain signals are combined with equal gain to obtain the combined received signal vector.

[0011] Preferably, S5 is as follows: S51. Establish the energy efficiency (EE) optimization problem; S52. Decompose the subproblem using the alternating optimization (AO) framework and perform sequential optimization. S521. By fixing the RIS phase shift matrix Θ, introducing auxiliary variables, and utilizing binomial inequalities to convexize non-convex constraints, the precoding vector is optimized through an iterative loop (LI) algorithm. With precoded matrix elements ; S522, By fixing the optimized precoding vector With precoded matrix elements The channel matrix is ​​decomposed, and Θ is optimized based on the triangular substitution TS algorithm; S53. Based on the LI and TS algorithms, a joint optimization algorithm based on EE is formed, and the optimal parameter configuration of EE for the MU-MISO-ODDM system is obtained iteratively.

[0012] Preferably, S51 is as follows: First, the EE of a MU-MISO-ODDM system is defined as the ratio of total speed to total power consumption: ;in, yes Signal-to-interference-plus-noise ratio; and Representing system architecture power consumption and The power consumption of the precoding matrix; Secondly, joint optimization of Θ, , The EE optimization problem is established as follows: ; ; ; ; in, , , They represent , , Constraints on power consumption; Represents the first in Θ One reflective unit Constraints; express The channel response; where, Indicates a direct link Channel matrix: Indicates that it includes all BS-RIS channel matrix for each reflection unit; Indicates that it includes all Each reflective unit Channel matrix; Then, the Dinkelbach algorithm is used, by introducing a new auxiliary variable. η The original form of dividing two terms can be equivalently transformed into the form of subtracting two terms, as shown below: ; Preferably, S521 is as follows: First, with Θ fixed, an auxiliary variable is introduced to adapt to the convexity processing for the optimization problem of the equivalent subtraction form; Secondly, the binomial inequality is used to transform the non-convex terms containing optimization variables in the equivalent subtraction form of the optimization problem into a convex form, thereby eliminating the logarithmic non-convex form in the objective function and obtaining the objective function and constraints for convex optimization. Then, through iterative iteration of the LI-based precoding matrix optimization algorithm, the output is... and The specific process is as follows: Step 1, Initialization , and iteration parameters; The second step is to iteratively update the auxiliary variables. and In each iteration, the current variable is substituted into the convexized objective function to solve for the local optimum. The third step is to terminate the iteration until the convergence condition is met, and then output the result. and .

[0013] Preferably, S522 is as follows: First, the result obtained in step S521 is fixed. and The channel matrix is ​​decomposed into BS-RIS link sub-matrices. The product form of the link submatrix and precoding related parameters; Secondly, based on the decomposed channel matrix, the Θ optimization problem is transformed into an objective function that maximizes the real part. The solution logic is simplified using the TS algorithm, and the specific process is as follows; The first step is to initialize the iteration parameters and the initial value of Θ; The second step is to iteratively update the phase of the reflection unit of Θ so that the phase of the reflection unit is consistent with the conjugate phase of the corresponding element after the channel matrix decomposition, in order to maximize the objective function value. The third step is to terminate the iteration and output Θ when the convergence condition is met. * .

[0014] Preferably, S53 is as follows: The first step is to input the initial parameters: channel matrix, system power consumption parameters, constraint thresholds, and iterative convergence conditions; The second step is to initialize auxiliary variables. , and Θ; The third step is to obtain the LI algorithm based on the current Θ. and ; Step 4: Fix the current and Execute the TS algorithm to obtain Θ * ; Step 5, Output , and Θ * .

[0015] Therefore, this invention adopts the above-mentioned RIS-assisted MU-MISO-ODDM system EE optimization design method. ODDM technology can directly perform multi-carrier modulation in the DD domain. By introducing a series of square root Nyquist pulses, the orthogonality of the modulation signal in the DD domain is achieved, thereby effectively avoiding the shortcomings of OOBE and inter-symbol interference in OTFS. At the same time, this invention is the first to combine RIS with ODDM modulation technology in the DD domain, through joint optimization of the transmitter. , And Θ, thus obtaining the receiving end UE u The optimal parameter configuration for EE fills the gap in EE optimization technology for RIS-assisted DD domain ODDM systems.

[0016] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0017] Figure 1 This is a flowchart of the EE optimization design method based on the RIS-assisted MU-MISO-ODDM system of the present invention; Figure 2 This is a block diagram of the RIS-assisted MU-MISO-ODDM system according to an embodiment of the present invention; Figure 3 This is a block diagram of the MISO-ODDM system configuration according to an embodiment of the present invention; Figure 4This is a graph showing the variation of EE when the number of RIS reflection units is different in an embodiment of the present invention. Figure 5 This is a graph showing the variation of EE when the number of BS transmitting antennas is different according to an embodiment of the present invention; Figure 6 This is an embodiment of the present invention. The graph showing the change in EE when the numbers are different; Figure 7 This is an embodiment of the present invention. The curve showing the change in EE when SINR is different; Detailed Implementation

[0018] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0019] This invention relates to an energy efficiency optimization design method for a RIS-assisted MU-MISO-ODDM system, comprising the following steps: S1. Construct a RIS-assisted MU-MISO-ODDM system; S2. Generate and process the ODDM modulated signal to obtain the time-domain transmission signal, and transmit the time-domain transmission signal to... One user equipment (UEs); S3. Construct a dual-selectivity channel model, for The received signal in the time domain is processed to obtain The received signal matrix; S4, UE u The received signal matrix is ​​sequentially subjected to matched filtering, sampling, CP discarding, and equal gain combining operations to obtain the combined received signal vector. S5. Construct and solve the EE optimization problem of the MU-MISO-ODDM system.

[0020] Example like Figure 1 As shown, the present invention provides an energy efficiency optimization design method for a RIS-assisted MU-MISO-ODDM system, comprising the following steps: S1. Construct a RIS-assisted MU-MISO-ODDM system.

[0021] S11, Configuration Base station BS with one antenna Single-antenna UEs, and deployed with The RIS of a single reflection unit, such as Figure 2 As shown.

[0022] S12, BS, and UEs adopt ODDM modulation technology, as detailed below: definition DD mesh ;in, and They represent delay units and One Doppler unit; and These represent the number of delay symbols and Doppler symbols within a frame, respectively. and These represent the resolutions of the delay axis and the Doppler axis, respectively. and Let represent the time slot duration and subcarrier spacing, respectively, and satisfy . .

[0023] S2. Generate and process the ODDM modulated signal to obtain the time-domain transmission signal, and transmit the time-domain transmission signal to... U indivual ,like Figure 3 As shown.

[0024] S21, Construct the transmission to U in the DD domain. of QAM symbol matrix ;in, express The symbol matrix; Represents the DD field In the The delay and the first The symbol for a Doppler.

[0025] S22, to implement Point IFFT yields the time-delay domain sign. ;in, Represents UEu in the time-delay domain at the th The delay and the first The symbol at each point in time; It is the imaginary unit.

[0026] S23, to Time-delay domain symbol Perform parallel / serial conversion to obtain the UE. u Time-domain digital sequence and integrate U The time-domain digital sequence of each UE is obtained. U Time-delay domain symbol matrix of each UE .

[0027] S24. Encode the MU time-delay domain symbol matrix using a precoding matrix to generate the base station. Transmit symbol matrix of root transmitting antenna As shown below: ; in, express The precoding matrix of UEs; express The precoded vector; Indicates the first The sign vector of the antenna.

[0028] S25, with a length of L CP Add CP to the first Transmission symbol of the root antenna In the middle, we obtained , The time-domain signal is then obtained through pulse shaping filtering. ;in, , It is the maximum delay spread of the communication link. It emits rectangular pulses. It is an integer.

[0029] S26. Transfer the time-domain transmission signal from the BS. The antenna transmits to simultaneously indivual .

[0030] S3. Construct a dual-selectivity channel model, for The received signal in the time domain is processed to obtain The received signal matrix.

[0031] S31. Define the biselective channel response in the DD domain as follows: ;in, p Indicates the total number of multipath components; and These represent the delay and Doppler variables, respectively. , , They represent the first The channel gain coefficient, delay offset coefficient, and Doppler shift coefficient in the sub-multipath propagation component. Meanwhile, the matrix form of this dual-selective channel response is... ;in, and They represent the first The delay factor and Doppler factor in each multipath propagation component; the delay matrix and Doppler frequency shift matrix are respectively expressed as: and .

[0032] according to Figure 1 It can be seen that the actual communication link consists of a reflection link and a direct link, where the direct link is the channel. The reflection link is provided by BS-RIS and The cascaded channels formed by these channels.

[0033] S32, The actual communication link is composed of Direct link channel and BS-RIS and It consists of cascaded reflection link channels.

[0034] BS-UE u The direct link channel response is ;in, Indicates the first in the direct link One multipath propagation component; This represents the total number of multipath propagation components in a directly connected link; Represents the unit impulse response function; , , Indicates the first direct link Channel gain coefficient, delay offset coefficient, and Doppler shift coefficient for each multipath propagation component.

[0035] The channel response of BS-RIS in the reflection link is ;in, Indicates the first Channel gain coefficients for each multipath propagation component; Indicates the first Delay offset coefficients for multipath propagation components.

[0036] The channel response is ;in, Indicates the first One multipath propagation component; This represents the total number of multipath propagation components in the reflection link; , , These represent the RIS-UE link number. Channel gain coefficient, delay offset coefficient, and Doppler shift coefficient for each multipath component.

[0037] S33. The total received signal is obtained by superimposing the direct link signal and the reflected link signal, and then obtaining the UE signal through discretization and matrixing. u The received signal matrix.

[0038] Direct link signal is ; in, express No. Channel gain coefficients for each multipath propagation component; and They represent No. Delay offset coefficient and Doppler frequency shift coefficient of each multipath propagation component; express No. The multipath component is in The AWGN signal at that moment.

[0039] The reflected link signal is ; in, Representing the first RIS The first reflection unit received the first from BS Channel gain coefficients for each multipath propagation component; express Received from RIS The first reflector unit Channel gain coefficients for each multipath propagation component; , They represent BS-RIS and exist The AWGN signal at time; therefore, The total received signal is ; in, Indicates in The sum of the AWGN terms in the direct link signal and the reflected link signal at any given moment; , Indicates the first in RIS Phase coefficient of each reflective unit.

[0040] S4 The received signal matrix is ​​sequentially subjected to matched filtering, sampling, CP discarding, and equal gain combining operations to obtain the combined received signal vector.

[0041] S41. Decompose the received signal matrix into The received signal corresponding to the antenna is subjected to matched filtering to obtain The filtered signal is shown below: ; in, For integration variables; Describes a matched filter; and satisfies .

[0042] S42, at the sampling time Place, to The filtered signal is sampled to obtain A discrete signal with CP .

[0043] S43, to A discrete signal with CP is subjected to a CP-dropping operation to obtain a discrete-time signal, whose matrix-vector form is as follows: ; in, Indicates from A matrix consisting of the received signal vectors from each transmitting antenna; Indicates by A matrix composed of AWGN vectors; Indicates a direct link Channel matrix; where, and They represent No. Delay factor and Doppler factor in each multipath propagation component; Indicates reflection link Channel matrix; where, It is the Kronecker product; express No. The channel matrix at each reflection unit; where... express No. Delay factor in a multipath propagation component; express No. Doppler factor in each multipath propagation component; Indicates that it includes all Each reflective unit Channel matrix; Represents the RIS phase shift matrix; Indicates all The RIS phase shift matrix after each reflection unit is coupled with the transmitted signal; Indicates that it includes all The BS-RIS channel matrix of each reflection unit is specifically represented as follows: ; This indicates that BS-RIS is in the... Channel matrix at each reflection unit Indicates BS-RIS number Delay factor in a multipath propagation component.

[0044] Therefore, S44, to The discrete-time signals are combined with equal gain to obtain the final received signal vector. ; in, Indicates the first One UE.

[0045] At this point SINR is ;in, Indicates UE i The elements of the precoded matrix; express The noise standard deviation.

[0046] The total rate of the MU-MISO-ODDM system is ;in, express The rate.

[0047] Total power of the MU-MISO-ODDM system: ;in, express The power consumption of the precoding matrix; This indicates the power consumption of the system architecture. , , and They represent BS, RIS, and The power consumption of each UE and the delay line.

[0048] S5. Construct and solve the EE optimization problem of the MU-MISO-ODDM system.

[0049] S51. Establish the energy efficiency (EE) optimization problem.

[0050] First, the EE of a MU-MISO-ODDM system is defined as the ratio of total speed to total power consumption, expressed as: .

[0051] Secondly, joint optimization , And with the three parameter variables Θ, we establish the EE optimization problem as follows: ; ; ; ; in, express Constraints; express Constraints; express Constraints on power consumption; Represents the first in Θ One reflective unit Constraints; express The overall channel response matrix; where, Indicates a direct link BS-UE u Channel matrix: Indicates that it includes all BS-RIS channel matrix for each reflection unit; Indicates that it includes all Each reflective unit Channel matrix.

[0052] However, P1 contains many non-convex components: Firstly, The two variables, Θ and Θ, appear in a coupled form in the numerator of the objective function and In, non-affine variables The denominator of the objective function and In addition, The relevant part of the middle The unit mode constraint of the RIS of a single reflective unit is also non-convex.

[0053] Subsequently, new variables were introduced. η And assume It is the optimal solution for P1; where, Indicates inclusion The overall rate of the variable; Indicates inclusion Total power consumption of the variable, and express η Obtain the optimal solution η * hour and The corresponding values; using the Dinkelbach algorithm, the original P1 form of dividing two terms is equivalently transformed into the P1 form of subtracting two terms. ’ The format is as follows: .

[0054] S52, Further Elimination The non-convex properties in the image are addressed using the AO algorithm. The problem is broken down into two sub-problems, and each is optimized in turn.

[0055] S521, while fixing Θ, optimize and .

[0056] First, introduce new auxiliary variables. γu ,Will Equivalent to As shown below: ; in, C 5 is The expression.

[0057] Secondly, for non-affine terms Express it using the binomial inequality as ,in express One of the values, express transpose, This indicates extracting the real part; substituting it into... Objective function and From this, we can obtain the following respectively: as well as ,in, express The upper limit; in addition, and They can be converted to equivalent values ​​respectively. ,in, ; .

[0058] At this point, the original Equivalent to As shown below: .

[0059] Obviously This is a convex problem, which can be solved directly using convex optimization (CVX). The L1-based precoding matrix optimization algorithm is as follows: 1. Input: Channel matrix Fixed matrix Auxiliary variables Maximum number of iterations and tolerance .

[0060] 2. Output: Optimal precoding vector and precoded matrix elements .

[0061] 3. Phase 1: Initialization calculation.

[0062] 4. Initialize variables , and .

[0063] 5. , , and Substitution To obtain .

[0064] 6. Phase 2: Iterative Loop.

[0065] 7. Regarding arrive implement.

[0066] 8 given and ,based on get .

[0067] 9. Update auxiliary variables.

[0068] 10 .

[0069] 11. End the loop.

[0070] 12. Phase 3: Termination of inspection.

[0071] 13. If or ,but, 14. Exit the loop and output. and .

[0072] 15. Termination condition.

[0073] S522, Fixed and At the same time, optimize Θ.

[0074] First, This is transformed into subproblem P2-2, as shown below: .

[0075] Due to the objective function and constraints in P2-2 , Both have non-convex properties, given that Θ exists only in the objective function and In Therefore, the fractions in the objective function can be further transformed into: By utilizing the monotonicity of the logarithmic function and discarding the constant term, P2-2 is further simplified to P2-2. ’ : .

[0076] Secondly, |Hu | 2 Further transformation into ;in , , θ b This represents the parameters in Θ that need to be optimized. Indicates that G corresponds to θ b That item. At this point, C 1 can be converted to ; and will Further equivalent transformation As shown below: .

[0077] Then, |H u | 2 Perform the following equivalent transformation: ;in, and These represent two coefficient values ​​respectively; and Represent matrices respectively Neutralization matrix The first in m row and number n The elements of the column; * indicates conjugate operation; and These represent the operations of extracting the real part and the imaginary part, respectively. This expresses the search for the angle corresponding to the tangent function. According to the properties of the angle-forming formula in trigonometric functions: if and only if... hour, Reaching the maximum value, at this point θ b Obtain the optimal solution .

[0078] Next, regarding Perform the following inequality transformation: It can be seen that, The objective function not only has an upper bound but also exhibits non-decreasing properties, therefore it is convergent. The optimization steps based on the TS algorithm are as follows: 1. Input: Channel matrix Fixed variables and the number of calculations .

[0079] 2. Output: Optimal RIS phase shift matrix .

[0080] 3. Phase 1: Initialization.

[0081] 4. Obtained from the channel matrix decomposition formula ,in, .

[0082] 5. Given , , , By performing the construction operations of the equivalent channel and reflection path matrix, we obtain and .

[0083] 6. Stage 2: Calculation.

[0084] 7. Regarding arrive implement.

[0085] 8 given , and The optimal value is obtained by performing an optimized calculation process for the reflection phase shift. .

[0086] 9. Update and optimize variables.

[0087] 10. .

[0088] 11. End the loop.

[0089] 12. Phase 3: Termination of inspection.

[0090] 13. If ,but, 14. Exit the loop, based on The optimal output is obtained .

[0091] 15. Termination condition.

[0092] S53. Based on the LI and TS algorithms, a joint optimization algorithm based on EE is formed to iteratively obtain the optimal parameter configuration for the EE of the RIS-assisted MU-MISO-ODDM system, as follows: 1. Input: Channel matrix Auxiliary variables .

[0093] 2. Initialize variables , , .

[0094] 3. Given , and Based on the LI algorithm, .

[0095] 4. Given , Based on the TS algorithm, .

[0096] 5. Output: Optimal precoding matrix elements Precoding matrix and RIS phase shift matrix .

[0097] Furthermore, based on the preceding analysis, this embodiment is supplemented with the following simulation results: like Figure 4 As shown, the number of RIS reflection units The changes in EE at different times.

[0098] like Figure 5 As shown, the number of BS transmitting antennas The changes in EE at different times.

[0099] like Figure 6 As shown, the number of UEs The changes in EE at different times.

[0100] like Figure 7 As shown, of The changes in EE at different times.

[0101] Therefore, this invention employs the above-described method, and by introducing ODDM modulation technology, it can further improve system performance while ensuring communication quality under high mobility time-varying channels; simultaneously, it uses RIS-assisted methods to improve the wireless channel characteristics of the transmitted signal during transmission; and by alternately optimizing the transmitter w... u , Together with Θ, they form a joint iterative algorithm based on EE to obtain the optimal parameter configuration for EE.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. An energy efficiency optimization design method based on a RIS-assisted MU-MISO-ODDM system, characterized in that, Includes the following steps: S1. Construct a smart reflector RIS-assisted multi-user multiple-input single-output quadrature delay Doppler diversity multiplexing (MU-MISO-ODDM) system; S2. Generate and process the quadrature delayed Doppler diversity multiplexing modulated signal to obtain the time-domain transmission signal, and transmit the time-domain transmission signal to U single-antenna user equipment; S3. Construct a dual-selectivity channel model for the first... The time-domain received signal of a single-antenna user equipment is processed to obtain the first... The received signal matrix of a single-antenna user equipment; S31. Define the normalized form of the DD domain biselective channel response and establish the biselective channel matrix H: ;in, Indicates the first One multipath propagation component; This represents the total number of multipath propagation components; Indicates the first Channel gain coefficient in each multipath propagation component; Indicates the first Delay factor in a multipath propagation component; Indicates the first Doppler factor in each multipath propagation component; Represents the delay matrix in the MN×MN dimensional complex matrix space; Represents the Doppler frequency shift matrix in the MN×MN dimensional complex matrix space; S32. Decompose the actual communication link into a direct link and a reflection link, and establish the channel response for each link as follows: Direct link channel response: ;in, and These represent the delay and Doppler variables, respectively. Indicates the first in the direct link One multipath propagation component; This represents the total number of multipath propagation components in a directly connected link; Represents the unit impulse response function; , and These represent the first direct link. Channel gain coefficient, delay offset coefficient, and Doppler shift coefficient for each multipath propagation component; The reflection link channel consists of the base station-intelligent reflector (BS-RIS) channel and the intelligent reflector-user equipment (UE) channel. The channels are cascaded, and their channel responses are as follows: (1) BS-RIS channel response: ;in, This represents the channel gain coefficient of the p-th multipath propagation component; Indicates the first Delay coefficients for each multipath propagation component; Indicates the subcarrier spacing; (2) Channel response: ;in, Indicates the first One multipath propagation component; This represents the total number of multipath propagation components in the reflection link; , , They represent Link number Channel gain coefficient, delay offset coefficient, and Doppler shift coefficient for each multipath component; S33. The total received signal is obtained by superimposing the direct link signal and the reflected link signal, and then discretizing and matrixing it to obtain the... The received signal matrix of a single-antenna user equipment, wherein: Direct link: ;in, express The d-th multipath propagation component of the u-th single-antenna user equipment in The additive white Gaussian noise (AWGN) signal at time t; This represents the signal state of the signal x(t) transmitted by the base station, which reaches the u-th single-antenna user at time t after propagation via direct multipath propagation. Reflection Link: ;in, This represents the channel gain coefficient of the p-th multipath propagation component on the l-th reflection unit in BS-RIS; express The Middle The first reflector unit Channel gain coefficients for each multipath propagation component; , They represent BS-RIS and exist AWGN signal at any given time; This represents the total propagation delay of the signal from the base station, through the l-th RIS reflection unit, the p-th BS-RIS multipath, and the r-th RIS-UE multipath, to the u-th single-antenna user; This indicates that the signal transmitted by the base station passes through BS-RIS and The signal status that arrives at the user end at time t after the two-stage cascaded link transmission; This represents the time-domain delay of the noise signal in the BS-RIS link as it propagates to the user end after being reflected by the RIS. , represents a complex number whose modulus is always 1; S4, the Each single-antenna user equipment performs matched filtering, sampling, discarding the cyclic prefix (CP), and equal-gain combining operations on the received signal matrix in sequence to obtain the combined received signal vector. S5. Construct the energy efficiency optimization problem of the MU-MISO-ODDM system and solve it to obtain the optimal parameter configuration for the energy efficiency of the MU-MISO-ODDM system.

2. The energy efficiency optimization design method based on RIS-assisted MU-MISO-ODDM system according to claim 1, characterized in that, S1 specifically refers to: S11, Configuration Base station with one antenna A single-antenna user equipment, and deployed with RIS of one reflective unit; S12, base station and Each single-antenna user equipment employs orthogonal delay Doppler diversity multiplexing modulation technology, as detailed below: definition Delay-Doppler DD mesh ;in, express One delay unit; express One Doppler unit; and These represent the number of delay symbols and Doppler symbols within a frame, respectively. and These represent the resolutions of the delay axis and the Doppler axis, respectively. and Let represent the time slot duration and subcarrier spacing, respectively, and satisfy . .

3. The energy efficiency optimization design method based on the RIS-assisted MU-MISO-ODDM system according to claim 2, characterized in that, S2 specifically refers to: S21, Constructing transmission in the DD domain to Single-antenna user equipment orthogonal amplitude modulation symbol matrix; S22, Regarding the DD domain The quadrature amplitude modulation symbol matrix is ​​executed along the Doppler dimension. The inverse fast Fourier transform (IFFT) operation is performed to obtain the first... Time-delay domain symbol for a single-antenna user equipment; S23. Perform a parallel / string conversion on the time-delay domain symbol to obtain the first... The time-domain digital sequence of a single-antenna user equipment, and integrated The time-domain digital sequence of a single-antenna user equipment is obtained. Time-delay domain symbol matrix for a single-antenna user equipment; S24. The multi-user delay domain symbol matrix is ​​precoded using a precoding matrix to generate the base station's... The transmit symbol matrix corresponding to each transmit antenna; S25. Add CP to the... The antenna's transmitted symbols are obtained by filtering them using rectangular pulses. Time-domain transmission signals; S26. Transmit the time-domain signal from the base station. The antenna transmits to simultaneously Single-antenna user equipment.

4. The energy efficiency optimization design method for a RIS-assisted MU-MISO-ODDM system according to claim 3, characterized in that, S4 specifically refers to: S41. Decompose the received signal matrix into The received signal corresponding to the antenna is subjected to matched filtering to obtain The filtered signal; S42, at the sampling time Place, to The filtered signal is sampled to obtain A discrete signal with CP; S43, to Perform a CP discarding operation on a discrete signal with CP, and obtain... A discrete-time domain signal; S44, to The discrete time-domain signals are combined with equal gain to obtain the combined received signal vector.

5. The energy efficiency optimization design method for a RIS-assisted MU-MISO-ODDM system according to claim 4, characterized in that, S5 specifically refers to: S51. Establish the energy efficiency (EE) optimization problem; S52. Decompose the subproblem using the alternating optimization AO framework and perform sequential optimization. S521. First, fix the RIS phase shift matrix, and for the optimization problem of equivalent subtraction form, introduce auxiliary variables to adapt to the convexity processing. Secondly, the binomial inequality is used to transform the non-convex terms containing optimization variables in the equivalent subtraction form of the optimization problem into a convex form, thereby eliminating the logarithmic non-convex form in the objective function and obtaining the objective function and constraints for convex optimization. Then, the optimal values ​​of the precoding vector and precoding matrix elements are output through iterative iteration of the LI-based precoding matrix optimization algorithm. The specific process is as follows: The first step is to initialize the precoding vector, precoding matrix elements, and iteration parameters; The second step is to iteratively update the auxiliary variables, precoding vector, and precoding matrix elements. In each iteration, the current variable is substituted into the convexized objective function to solve for the local optimum. The third step is to terminate the iteration until the convergence condition is met, and output the optimal values ​​of the precoding vector and the elements of the precoding matrix. S522. First, fix the precoding vector and precoding matrix elements obtained in step S51, and decompose the channel matrix into BS-RIS link sub-matrices. The product form of the link submatrix and precoding related parameters; Secondly, based on the decomposed channel matrix, the RIS phase shift optimization problem is transformed into an objective function that maximizes the real part. The solution logic is simplified using the TS algorithm. The specific process is as follows: The first step is to initialize the iteration parameters and the initial values ​​of the RIS phase shift matrix; The second step is to iteratively update the phase of the reflection unit in the RIS phase shift matrix so that the phase of the reflection unit is consistent with the conjugate phase of the corresponding element after the channel matrix decomposition, in order to maximize the objective function value. The third step is to continue the iteration until the convergence condition is met, then output the optimal value of the RIS phase shift matrix. S53. Based on the LI and TS algorithms, a joint optimization algorithm based on EE is formed to iteratively obtain the optimal parameter configuration for the EE of the RIS-assisted MU-MISO-ODDM system, as follows: The first step is to input the initial parameters: channel matrix, system power consumption parameters, constraint thresholds, and iterative convergence conditions; The second step is to initialize auxiliary variables, precoding vectors, precoding matrix elements, and RIS phase shift matrix. The third step is to use the LI algorithm, based on the current RIS phase shift matrix, to obtain the optimal values ​​of the precoding vector and the elements of the precoding matrix. The fourth step is to execute the TS algorithm based on the current precoding vector and precoding matrix elements to obtain the optimal value of the RIS phase shift matrix. The fifth step is to output the optimal precoding vector, precoding matrix elements, and RIS phase shift matrix.

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