Communication optimization method based on millimeter wave PD-NOMA and related equipment

Abstract

The invention relates to the technical field of wireless communication security, in particular to a millimeter wave PD-NOMA-based communication optimization method and related equipment, and an active RIS-assisted millimeter wave PD-NOMA system model, which comprise a base station, an active RIS and three types of users: an untrusted user (internal eavesdropper), a secure user and an external eavesdropper. The system establishes a direct channel from a base station to a user and an indirect channel reflected by the RIS, obtains a user signal transmission rate by decoding a transmission signal, and calculates an internal eavesdropping rate and an external eavesdropping rate. And with maximization of the security user secrecy rate as a target, an active RIS reflection coefficient matrix and PD-NOMA power distribution are jointly optimized, a target function is constructed, and optimal parameters are solved. The parameters are applied to a system model, a secure transmission mechanism is constructed by dynamically regulating and controlling RIS beam forming and power distribution strategies, internal and external eavesdropping is effectively inhibited, and millimeter wave frequency band communication security and spectrum efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communication security, and particularly to a communication optimization method and related devices based on millimeter-wave PD-NOMA. Background Art

[0002] NOMA (Non-Orthgonal Multiple Access) as a key technology of 5G breaks through the orthogonal resource constraint, allowing multiple terminals to transmit in parallel at the same time. By non-orthogonal superposition coding in the power domain or code domain, multi-user signals are multiplexed and transmitted at the transmitting end. At the receiving end, the successive interference cancellation technology is used to eliminate the interference between users through an iterative decoding mechanism, constructing a new multiple access system that supports large-scale connections, ultra-low latency, and high spectral efficiency. The PD-NOMA (Power domain Non-Orthgonal Multiple Access) technology has received more attention compared to NOMA. Due to the deep coupling between the power multiplexing characteristic of PD-NOMA and the sparsity of the millimeter-wave channel, in a millimeter-wave (mmWave) large-scale MIMO (Multiple-Input Multiple-Output) system, power allocation has a more significant impact on system performance. Especially in scenarios with a large number of users, the complexity of the dynamic power allocation algorithm directly affects the feasibility of successive interference cancellation decoding. In addition, the millimeter-wave channel has poor anti-interference ability, and numerous interference signals pose a major threat to the anti-interference performance of the system. Therefore, it is necessary to rely on reasonable power allocation to enhance the coverage range, user fairness, and anti-interference ability of the millimeter-wave PD-NOMA system. Although PD-NOMA can more efficiently utilize limited bandwidth, it brings huge challenges to secure transmission.

[0003] Specifically, the superposition coding at the transmitting end increases the risk of eavesdropping between users, and the openness of the wireless channel makes legitimate signals vulnerable to eavesdropping. Therefore, physical layer security has received great attention as a potential method to prevent eavesdropping. Physical layer security is an important research direction in information security. How to fundamentally improve the security of communication systems and provide lightweight solutions for low-power and resource-constrained devices has become a challenge that traditional encryption may face in the future. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a communication optimization method and related devices based on millimeter-wave PD-NOMA for solving the technical problem of relatively low communication security performance of the current millimeter-wave PD-NOMA system in view of the above-mentioned deficiencies in the prior art.

[0005] The object of the present invention is achieved by the following technical solutions: In a first aspect, the present invention provides a communication optimization method based on millimeter-wave PD-NOMA, including: Construct an active RIS-assisted millimeter-wave PD-NOMA system model, and obtain base station transmission parameters, active RIS parameters, and receiving user parameters according to the millimeter-wave PD-NOMA system model; the millimeter-wave PD-NOMA system model includes a base station, an active RIS, and receiving users, and the receiving users include untrusted users, secure users, and external eavesdroppers; the untrusted users act as internal eavesdroppers. Establish a first millimeter-wave channel between the base station and an untrusted user or a secure user, and establish a second millimeter-wave channel between the base station and an external eavesdropper; both the first millimeter-wave channel and the second millimeter-wave channel include a direct channel and an indirect channel; the direct channel represents direct communication between the base station and the receiving user, and the indirect channel represents communication between the base station and the receiving user through the active RIS. When the base station sends signals through the first millimeter-wave channel and the second millimeter-wave channel respectively, construct an optimization objective function according to the base station transmission parameters, active RIS parameters, and receiving user parameters, calculate the optimal variable solution according to the optimization objective function, and update the millimeter-wave PD-NOMA system model according to the optimal variable solution.

[0006] As a further improvement of the present invention, the active RIS includes M reflection elements, which are used to adjust the phase and amplitude of the signal according to the active RIS parameters, amplify the signal power and then transmit it to the receiving user, where M is the total number of reflection elements.

[0007] As a further improvement of the present invention, the active RIS parameter is a reflection coefficient matrix, and the reflection coefficient matrix is:

[0008] Among them,

[0009] In the formula, is the reflection coefficient matrix of the active RIS, is the reflection coefficient of the first reflection element, is the reflection coefficient of the mth reflection element, is the reflection coefficient of the Mth reflection element, is the amplitude corresponding to the signal in the mth reflection element, is the phase corresponding to the signal in the mth reflection element, is a diagonal matrix, is the dimension, is a complex exponential function, and j is the imaginary unit.

[0010] As a further improvement of the present invention, the first millimeter-wave channel is expressed as:

[0011] The second millimeter - wave channel is expressed as:

[0012] Wherein, is the first millimeter - wave channel; is the direct channel from the base station to the untrusted user and the legitimate user; is the channel from the active RIS to the untrusted user and the legitimate user; is the reflection coefficient matrix of the active RIS; is the channel from the base station to the active RIS; is the second millimeter - wave channel; is the direct channel from the base station to the external eavesdropper; is the channel from the active RIS to the external eavesdropper, is the untrusted user or the legitimate user, i = 1, 2; when i = 1, it is the untrusted user, and when i = 2, it is the legitimate user; is the base station, is the active RIS, is the external eavesdropper, H is the conjugate transpose operation, is the indirect channel from the base station to the untrusted user and the legitimate user; is the indirect channel from the base station to the external eavesdropper.

[0013] As a further improvement of the present invention, when the base station sends signals through the first millimeter - wave channel and the second millimeter - wave channel respectively, it further includes determining the eavesdropping rate and the secrecy rate of the corresponding receiving user according to the sent signals, and taking the eavesdropping rate and the secrecy rate as the constraints of the optimization objective function; The steps for determining the eavesdropping rate and the secrecy rate of the receiving user include: Decoding the signals of the untrusted user to obtain the signal - to - interference - plus - noise ratio (SINR) of the untrusted user's signals, and obtaining the signal transmission rate of the untrusted user according to the SINR of the untrusted user's signals; After the signals of the untrusted user are successfully decoded, decoding the legitimate user to obtain the SINR of the legitimate user's signals, and obtaining the signal transmission rate of the legitimate user based on the SINR of the legitimate user's signals; Calculating the internal eavesdropping rate according to the signal transmission rates of the untrusted user and the legitimate user; Determining the SINR of the legitimate signals of the external eavesdropper; calculating the external eavesdropping rate based on the SINR of the legitimate signals of the external eavesdropper; Calculating the secrecy rate of the legitimate user based on the internal eavesdropping rate and the external eavesdropping rate.

[0014] As a further improvement of the present invention, the signal transmission rate of the untrusted user is:

[0015] The signal transmission rate of the secure user is:

[0016] The internal eavesdropping rate is:

[0017] The external eavesdropping rate is:

[0018] Wherein, is the signal transmission rate of the untrusted user; is the signal-to-interference-plus-noise ratio (SINR) of the untrusted user when decoding the confidential signal of the untrusted user; is the signal-to-interference-plus-noise ratio (SINR) of the secure user when decoding the confidential signal of the untrusted user; is the confidential signal of the untrusted user; is the untrusted user; is the signal transmission rate of the secure user; is the signal-to-interference-plus-noise ratio (SINR) of the secure user when decoding the confidential signal of the secure user; is the signal-to-interference-plus-noise ratio (SINR) of the untrusted user when decoding the confidential signal of the secure user; is the confidential signal of the secure user; is the secure user; is the internal eavesdropping rate; is the external eavesdropping rate; is the signal-to-interference-plus-noise ratio (SINR) of the legitimate signal corresponding to the external eavesdropper; is the external eavesdropper; is the logarithmic function with base 2.

[0019] As a further improvement of the present invention, the secrecy rate of the secure user is expressed as:

[0020] Wherein, is the secrecy rate of the secure user; , which is used to represent rate scaling, is the signal transmission rate of the secure user; is the internal eavesdropping rate; is the external eavesdropping rate.

[0021] As a further improvement of the present invention, the optimization objective function is:

[0022] wherein, is the secrecy rate of the legitimate user; is the maximum secrecy rate; is the data transmission rate of the untrusted user; is the quality of service requirement of the untrusted user; is the power allocated by the base station to the untrusted user; is the power allocated by the base station to the legitimate user; is the precoding vector of the base station for the untrusted user; is the precoding vector of the base station for the legitimate user; is the transmit power of the base station; is the reflection coefficient of the m-th reflecting element; is the maximum amplitude corresponding to the signal in the reflecting element; is the transmission channel of the untrusted user; is the transmission channel of the legitimate user; is the noise power at the active RIS; is the maximum reflection power; is the identity matrix; is the transmit power allocated by the base station to the untrusted user; is the data transmission rate of the untrusted user; is the transmit power allocated by the base station to the legitimate user; is the reflected power of the downlink after reflection by the active RIS; is the reflection coefficient matrix of the active RIS; is the power consumed by the noise of the active RIS; is the square of the 2-norm of the vector, is the channel from the base station to the active RIS.

[0023] As a further improvement of the present invention, when solving the optimization objective function, it is decomposed into three optimization sub-problems, and the convex optimization algorithm is used to solve the three optimization sub-problems respectively to obtain the optimal variable solutions; The first optimization sub-problem is to optimize the precoding vector of the base station; the second optimization sub-problem is to optimize the reflection coefficient matrix of the active RIS; the third optimization sub-problem is to optimize the power allocation of the receiving user.

[0024] In a second aspect, the present invention provides a communication optimization system based on millimeter-wave PD-NOMA for implementing the above-mentioned communication optimization method based on millimeter-wave PD-NOMA, including: A wireless communication model construction module constructs an active RIS-assisted millimeter-wave PD-NOMA system model. The millimeter-wave PD-NOMA system model includes a base station, an active RIS, and receiving users. The receiving users include untrusted users, secure users, and external eavesdroppers. The untrusted users act as internal eavesdroppers. A wireless communication transmission construction module establishes a first millimeter-wave channel between the base station and an untrusted user or a secure user, and a second millimeter-wave channel between the base station and an external eavesdropper. Both the first millimeter-wave channel and the second millimeter-wave channel include a direct channel and an indirect channel. The direct channel means direct communication between the base station and the receiving user, and the indirect channel means the base station communicates with the receiving user through the active RIS. A data acquisition module is used to obtain base station transmission parameters, active RIS parameters, and receiving user parameters according to the millimeter-wave PD-NOMA system model. A communication optimization module constructs an optimization objective function based on the base station transmission parameters, active RIS parameters, and receiving user parameters, calculates the optimal variable solution according to the optimization objective function, and updates the millimeter-wave PD-NOMA system model according to the optimal variable solution.

[0025] The beneficial effects of the present invention are as follows: The present invention provides a communication optimization method for millimeter-wave PD-NOMA, mainly for millimeter-wave communication wireless networks, specifically for millimeter-wave PD-NOMA networks. The present invention constructs an active RIS-assisted millimeter-wave PD-NOMA network, enhances the signal strength of the desired channel through the active RIS, compensates for the high path loss of millimeter waves, and improves the signal-to-interference-plus-noise ratio at the receiving end. The active RIS can amplify the reflected signal, compensate for the path loss while reducing the base station transmission power, improve energy efficiency. At the same time, the beam of the active RIS can replace part of the base station array, reducing the number of base station antennas.

[0026] Furthermore, the present invention establishes a first millimeter-wave channel (i.e., from the base station to an untrusted user or a secure user) and a second millimeter-wave channel (i.e., from the base station to an external eavesdropper). Each channel includes a direct and an indirect communication path millimeter-wave PD-NOMA network, and uses the alternating direction method of multipliers (ADMM) to iteratively solve the optimal phase matrix to maximize the legitimate channel gain and suppress the eavesdropping channel.

[0027] For the new interference sources introduced by the active RIS signals, the present invention can suppress the new interference sources and the original interference through the established optimization objective function. In addition, the active RIS of the present invention can compensate for the path loss by actively amplifying the signal, and improve the gain during millimeter-wave communication.

[0028] Furthermore, by jointly optimizing the base station beamforming and RIS reflection coefficients, the signal is enhanced in the direction of legitimate users, and artificial noise is injected in the direction of eavesdroppers. Numerical results show that even if the eavesdropper is closer to the RIS, the secure rate can still remain positive. By dynamically adjusting the amplitude and phase, the system exhibits significant advantages in terms of signal quality, coverage flexibility, anti-interference ability, and energy efficiency ratio, providing theoretical support and engineering practice reference for the integration of non-orthogonal multiple access and intelligent metamaterials.

[0029] Furthermore, by taking the eavesdropping rate and secrecy rate as constraints of the optimization objective function, the active RIS-assisted millimeter-wave PD-NOMA system achieves a comprehensive improvement in security performance, spectral efficiency, and dynamic adaptability. By finely adjusting the reflection coefficient matrix and base station beamforming, the system can still maintain stable communication performance and security performance in a complex electromagnetic environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0031] Figure 1 It is a schematic diagram of the active RIS-assisted mmWave-PD-NOMA secure communication system model in the present invention; Figure 2 It is a flowchart of the implementation of the method of the present invention; Figure 3 It is a simulation result diagram of the convergence performance of the alternating optimization algorithm in the present invention; Figure 4 It is a simulation result diagram of the maximum transmit power of the base station versus the secrecy rate of secure users in the present invention; Figure 5 It is a simulation result diagram of the number of RIS reflection units versus the secrecy rate of secure users in the present invention; Figure 6 It is a simulation result diagram of the number of external eavesdroppers versus the secrecy rate of secure users in the present invention; Figure 7 It is a simulation result diagram of the quality of service of internal eavesdropping users versus the secrecy rate of secure users in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] In order to make the objectives and technical solutions of the present invention clearer and easier to understand. The following will further elaborate on the present invention in detail with reference to the drawings and embodiments. The specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0033] Glossary of Terms: Active RIS (reconfigurable intelligent surface): A reconfigurable intelligent surface composed of multiple passive reflecting elements. By adjusting the phase shift of the incident signal, the RIS can enhance the reception of desired signals and suppress interference from unintended users, thereby artificially creating favorable propagation conditions and enhancing existing wireless communications.

[0034] BS (Base Station): The base station, which is a key infrastructure in a mobile communication network and is used to enable wireless communication between mobile terminals and the core network.

[0035] PD-NOMA (Power Domain Non-Orthogonal Multiple Access): Power Domain Non-Orthogonal Multiple Access.

[0036] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings and specific embodiments. Among them, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.

[0037] Embodiment 1 As Figures 1 to 7 shown, this embodiment provides a communication optimization method for millimeter-wave PD-NOMA. By using an active RIS to assist millimeter-wave PD-NOMA communication, it is possible to protect security information and further improve the security performance of the system. The following are the specific implementation methods.

[0038] Construct an active RIS-assisted millimeter-wave PD-NOMA system model. Among them, the millimeter-wave PD-NOMA system model includes a base station, an active RIS, and receiving users. The receiving users include untrusted users, secure users, and external eavesdroppers.

[0039] In this embodiment, the frequency range of the millimeter wave is between 30 and 300 GHz, and its wavelength range is between 1 and 10 mm.

[0040] The base station includes transmitting antennas, one untrusted user and one secure user . Among them, the secure user is set at the far end and has a higher security permission. The untrusted user is set at the near end and attempts to intercept the confidential message of the secure user using successive interference cancellation after successfully decoding its own information. Therefore, the near-end user is also regarded as an internal eavesdropper. In addition, there is also An external eavesdropper surrounds the secure user and attempts to eavesdrop on the secure user's confidential information. Different from the external eavesdropper, the internal eavesdropper not only attempts to steal the confidential message but also needs to meet the quality of service of the internal eavesdropper in the power-domain non-orthogonal multiple access network for the user.

[0041] The active RIS includes M reflecting elements, which are used to adjust the phase and amplitude of the signal according to the active RIS parameters, and amplify the signal power and then transmit it to the receiving user. Each reflecting element of the active RIS is equipped with a power amplifier so that the phase and amplification factor of the signal can be adjusted simultaneously, but an additional power supply is required.

[0042] Furthermore, the active RIS parameter is the reflection coefficient matrix. The reflection coefficient matrix is:[[]]

[0043] where

[0044] In the formula is the reflection coefficient matrix of the active RIS is the reflection coefficient of the first reflecting element is the reflection coefficient of the m-th reflecting element is the reflection coefficient of the M-th reflecting element is the amplitude corresponding to the signal in the m-th reflecting element is the phase corresponding to the signal in the m-th reflecting element is a diagonal matrix is the dimension is the complex exponential function, and j is the imaginary unit.

[0045] Establish the first millimeter-wave channel between the base station and the untrusted user or the secure user, and establish the second millimeter-wave channel between the base station and the external eavesdropper. Both the first millimeter-wave channel and the second millimeter-wave channel include a direct channel and an indirect channel; the direct channel means that the base station communicates directly with the receiving user, and the indirect channel means that the base station communicates with the receiving user through the active RIS.

[0046] In this embodiment, the direct channel from the base station to the untrusted user (or secure user) is expressed as ; (i = 1, 2) is the untrusted user or the secure user; where when i is 1, it is the untrusted user, and when i is 2, it is the secure user; the channel from the base station to the active RIS is ; the channel from the active RIS to the untrusted user (or secure user) is expressed as ; The direct channel from the base station to the external eavesdropper is denoted as ; The channel from the active RIS to the j-th external eavesdropper is denoted as .

[0047] Then, the first millimeter-wave channel is denoted as:

[0048] The second millimeter-wave channel is denoted as:

[0049] Wherein, is the first millimeter-wave channel; is the direct channel from the base station to the untrusted user and the secure user; is the channel from the active RIS to the untrusted user and the secure user; is the reflection coefficient matrix of the active RIS; is the channel from the base station to the active RIS; is the second millimeter-wave channel; is the direct channel from the base station to the external eavesdropper; is the channel from the active RIS to the external eavesdropper, is the untrusted user or the secure user, i = 1, 2; when i is 1, it is the untrusted user, and when i is 2, it is the secure user; is the base station, is the active RIS, is the external eavesdropper, H is the conjugate transpose operation, is the indirect channel from the base station to the untrusted user and the secure user; is the indirect channel from the base station to the external eavesdropper.

[0050] When the base station sends signals to the receiving user through the first millimeter-wave channel and the second millimeter-wave channel respectively, an optimization objective function is constructed according to the base station transmission parameters, active RIS parameters, and receiving user parameters, and the optimal variable solution is calculated according to the optimization objective function. The optimal variable solution is used to update the millimeter-wave PD-NOMA system model to achieve communication optimization.

[0051] The base station in this embodiment sends signals to the receiving user through the first millimeter-wave channel and the second millimeter-wave channel respectively. Then the signals received by the receiving user are respectively denoted as:

[0052]

[0053] Wherein, is the signal received by the untrusted user (or secure user); The signal received by an external eavesdropper; The power allocated by the base station to a non-trusted user; The power allocated by the base station to a secure user; The precoding vector of the base station for non-trusted users; The precoding vector of the base station for secure users; and represent the noise at the RIS and the receiving user; represent the confidential information for non-trusted users; represent for secure users of the confidential information.

[0054] In addition, when the base station transmits signals to non-trusted users (or secure users) through the first millimeter-wave channel and to external eavesdroppers through the second millimeter-wave channel, it also includes determining the eavesdropping rate and the secrecy rate of the receiving user, and using the eavesdropping rate and the secrecy rate as constraints of the optimization objective function.

[0055] The steps for determining the eavesdropping rate and the secrecy rate of the receiving user include: Decode the confidential signal of the non-trusted user to obtain the signal-to-interference-plus-noise ratio (SINR) of the non-trusted user's signal, and obtain the signal transmission rate of the non-trusted user based on the SINR of the non-trusted user's signal; After successfully decoding the signal of the non-trusted user, decode the confidential signal of the secure user to obtain the SINR of the secure user's signal, and obtain the signal transmission rate of the secure user based on the SINR of the secure user's signal; Calculate the internal eavesdropping rate based on the signal transmission rates of the non-trusted user and the secure user; Determine the SINR of the legitimate signal of the external eavesdropper; calculate the external eavesdropping rate based on the SINR of the legitimate signal of the external eavesdropper; Calculate the secrecy rate of the secure user based on the internal eavesdropping rate and the external eavesdropping rate.

[0056] Specifically, the serial interference cancellation order among receiving users is mainly determined by the channel quality. Stronger users must decode and remove the information of weaker users to obtain their own information. However, to ensure the confidentiality of the secure user's information, the information of the non-trusted user needs to be decoded first. Specifically expressed as:

[0057] Therefore, when decoding the confidential signal of the non-trusted user the SINR (Signal-to-Interference-plus-Noise Ratio) corresponding to the non-trusted user and the secure user are respectively expressed as:

[0058]

[0059] wherein, is the confidential signal for decoding the non-trusted user and the signal-to-interference-plus-noise ratio (SINR) of the non-trusted user at that time; is the confidential signal for decoding the non-trusted user and the SINR of the secure user at that time. is the noise power at the active RIS, and is the thermal noise or additive white Gaussian noise of the non-trusted user (or secure user).

[0060] Then, the signal transmission rate of the non-trusted user is:

[0061] wherein, is the signal transmission rate of the non-trusted user.

[0062] When the confidential signal of the non-trusted user is successfully decoded, the secure user uses SIC (Successive Interference Cancellation) to cancel the confidential signal of the non-trusted user , and then decodes its own confidential signal . And after the non-trusted user decodes the confidential signal , it also tries to use SIC to decode the information of the confidential signal of the secure user.

[0063] Therefore, when decoding the confidential signal of the secure user, the SINRs of the corresponding non-trusted user and secure user are respectively expressed as:

[0064]

[0065] wherein, is the SINR of the non-trusted user when decoding the confidential signal of the secure user; is the SINR of the secure user when decoding the confidential signal of the secure user.

[0066] Then, the signal transmission rate of the secure user is:

[0067] wherein, is the signal transmission rate of the secure user.

[0068] Therefore, the eavesdropping rate of the non-trusted user on the secure user (i.e., the internal eavesdropping rate) is:

[0069] where is the internal eavesdropping rate.

[0070] The SINR of the external eavesdropper corresponding to the legitimate signal is expressed as:

[0071] In the formula, is the signal-to-interference-plus-noise ratio of the external eavesdropper corresponding to the legitimate signal.

[0072] Correspondingly, the eavesdropping rate of the external eavesdropper (i.e., the external eavesdropping rate) is:

[0073] Therefore, the secrecy rate of the secure user is expressed as:

[0074] where , used to represent rate scaling, is the secrecy rate of the secure user.

[0075] When solving problems such as the security and anti-interference of millimeter-wave PD-NOMA communication, it is necessary to consider the parameters corresponding to the base station, active RIS, and receiving users. Therefore, in this embodiment, an optimization problem is designed, that is, an optimization objective function is constructed, and the optimal solution of the objective function is solved to optimize the communication. Specifically, by jointly optimizing the precoding vector and at the base station, the reflection coefficient matrix of the active RIS, and the power allocation power and at the base station, to maximize the secrecy rate of the secure user . Therefore, the final optimization objective function is:

[0076] In the formula, is the secrecy rate of the secure user; is to maximize the secrecy rate; is the data transmission rate of the non-trusted user; is the user quality-of-service requirement of the non-trusted user; is the power allocated by the base station to the non-trusted user; is the power allocated by the base station to the secure user; is the precoding vector of the base station for non-trusted users; is the precoding vector of the base station for secure users; is the transmit power of the base station; is the reflection coefficient of the m-th reflecting element; is the maximum amplitude corresponding to the signal in the reflecting element; is the transmission channel of non-trusted users; is the transmission channel of secure users; is the noise power at the active RIS; is the maximum reflection power; is the identity matrix; is the transmit power allocated by the base station to non-trusted users; is the data transmission rate of non-trusted users; is the transmit power allocated by the base station to secure users; is the reflection power of the downlink after reflection by the active RIS; is the reflection coefficient matrix of the active RIS; is the power consumed by the noise of the active RIS; is the square of the 2-norm of the vector.

[0077] The optimization objective function in this embodiment constrains the following variables respectively. Specifically: Constraint Ensures that user 's data transmission requirements, where is 's user quality of service requirement; Constraint Represents the transmit power limit of the base station; Constraint Represents the reflection coefficient limit of the active RIS; Constraint Ensures the decoding order of successive interference cancellation; Constraint Represents the reflection power limit of the active RIS; Constraint Ensures the power allocation of the two users.

[0078] When solving the optimization objective function, the optimization objective function is first decomposed into three optimization sub-problems, and the convex optimization algorithm is used to solve the three optimization sub-problems respectively to obtain the optimal variable solutions. Among them, the first optimization sub-problem is to optimize the precoding vector of the base station; the second optimization sub-problem is to optimize the reflection coefficient matrix of the active RIS; the third optimization sub-problem is to optimize the power allocation of the receiving users. The optimal variable solutions are the optimal base station precoding vectors 、 , Reflection coefficient matrix of active RIS , Receive the power allocated by the user and .

[0079] In order to verify the communication optimization quality of the method of the present invention, in this embodiment, millimeter-wave PD-NOMA system models assisted by active RIS, passive RIS, and without RIS are respectively established. And when calculating the convergence of the optimization problem, the maximum number of iterations is set to 30 times, the base station, the active RIS, the untrusted user and the legitimate user The coordinates of are respectively set to , , and . In addition, the transmitting antenna is set , the base station power , the active RIS = -75 = -95 = 2 / bit / s / Hz .

[0080] As Figure 3 shown, when this embodiment adopts the active RIS, the algorithm reaches convergence fastest. In addition, two baseline plans are also considered for comparison. In the "passive RIS" scheme, the RIS only optimizes the phase shift and does not consider the reflection amplitude. In the "without RIS" scheme, only the case where there is a direct link between the base station and the user is considered. By comparing the secrecy rate of this scheme with the baseline scheme, it can be seen that the introduction of RIS can improve the system performance, and the active RIS plays a more significant role in improving the system performance.

[0081] In order to further determine the performance corresponding to the method of this embodiment, referring to Figure 4 , the comparison between the transmitting power of the base station and the secrecy rate in the present invention is given. By comparing various schemes, the superiority of the performance of the active RIS-assisted scheme proposed in this embodiment can be seen.

[0082] Referring to Figure 5 , the changes in the number of reflecting elements and the secrecy rate under various schemes are compared. Due to the increase in degrees of freedom, the secrecy rates in the cases of active and passive RIS increase with the increase of M. The algorithm with the active RIS design proposed in this embodiment has significantly better secrecy performance than the existing solutions with passive RIS. In addition, due to the "double fading" effect, when M changes from 10 to 60, the secrecy rate of the passive RIS only increases by about 22%, which is less than when = 20 dBThis is 34% achieved by the active RIS. These results strongly suggest that using an active RIS can save more reflecting units, thus obtaining better performance gains and significantly reducing the complexity of the RIS.

[0083] Referring to Figure 6 , the present invention also compares the impact of the number of external eavesdroppers on the secrecy rate. It can be seen that as the number of external eavesdroppers increases, the secrecy rate gradually decreases, but the decreasing trend significantly slows down. This is because the external eavesdroppers are randomly generated around the legitimate user . As the number of external eavesdroppers increases, the impact on the secrecy rate gradually decreases without considering collusive eavesdropping. At the same time, this embodiment also compares the relationship between the quality of service of non-trusted users and the secrecy rate. As shown in Figure 7 , as the quality of service of non-trusted users increases, the secrecy rate significantly decreases and the trend becomes more and more obvious. This is because as the quality of service of non-trusted users increases, more power is required, and the power allocated to the legitimate user will decrease, resulting in a decrease in the secrecy rate.

[0084] Embodiment 2 This embodiment provides a communication optimization system based on millimeter-wave PD-NOMA for implementing the communication optimization method based on millimeter-wave PD-NOMA in Embodiment 1. The system specifically includes: A wireless communication model construction module that constructs a millimeter-wave PD-NOMA system model assisted by an active RIS. The millimeter-wave PD-NOMA system model includes a base station, an active RIS, and receiving users. The receiving users include non-trusted users, legitimate users, and external eavesdroppers; the non-trusted users act as internal eavesdroppers.

[0085] In this embodiment, the frequency range of the millimeter wave is between 30 and 300 GHz, and its wavelength range is between 1 and 10 mm.

[0086] The base station includes transmitting antennas, one non-trusted user and one legitimate user . Among them, the legitimate user is set at the far end and has a higher security permission. The non-trusted user is set at the near end. After successfully decoding its own information, it attempts to intercept the confidential message of the legitimate user using successive interference cancellation. Therefore, the near-end user is also regarded as an internal eavesdropper. In addition, there are external eavesdroppers around the legitimate user attempting to eavesdrop on the legitimate user Confidential information. Different from external eavesdroppers, internal eavesdroppers not only try to steal confidential messages, but also need to meet the quality of service of users for internal eavesdroppers in the power-domain non-orthogonal multiple access network of the power-domain non-orthogonal multiple access network.

[0087] The active RIS includes M reflecting elements, which are used to adjust the phase and amplitude of the signal according to the active RIS parameters, and transmit the amplified signal power to the receiving user. Each reflecting element of the active RIS is equipped with a power amplifier so that the phase and amplification factor of the signal can be adjusted simultaneously, but an additional power supply is required.

[0088] Furthermore, the active RIS parameter is a reflection coefficient matrix. The reflection coefficient matrix is:

[0089] where

[0090] In the formula, is the reflection coefficient matrix of the active RIS, is the reflection coefficient of the first reflecting element, is the reflection coefficient of the m-th reflecting element, is the reflection coefficient of the M-th reflecting element, is the amplitude corresponding to the signal in the m-th reflecting element, is the phase corresponding to the signal in the m-th reflecting element, is a diagonal matrix, is the dimension, is a complex exponential function.

[0091] The wireless communication transmission building block establishes the first millimeter-wave channel between the base station and the untrusted user or the secure user, and establishes the second millimeter-wave channel between the base station and the external eavesdropper; both the first millimeter-wave channel and the second millimeter-wave channel include a direct channel and an indirect channel; the direct channel means that the base station communicates directly with the receiving user, and the indirect channel means that the base station communicates with the receiving user through the active RIS.

[0092] Specifically, in this embodiment, the direct channel from the base station to the untrusted user (or secure user) is expressed as ; (i = 1, 2) is the untrusted user or the secure user; where, when i is 1, it is the untrusted user, and when i is 2, it is the secure user; the channel from the base station to the active RIS is ; the channel from the active RIS to the untrusted user (or secure user) is expressed as ; the direct channel from the base station to the external eavesdropper is expressed as ; The channel from the active RIS to the j-th external eavesdropper is denoted as .

[0093] Therefore, the first millimeter-wave channel is denoted as:

[0094] The second millimeter-wave channel is denoted as:

[0095] Wherein, is the first millimeter-wave channel; is the direct channel from the base station to the untrusted user and the secure user; is the channel from the active RIS to the untrusted user and the secure user; is the reflection coefficient matrix of the active RIS; is the channel from the base station to the active RIS; is the second millimeter-wave channel; is the direct channel from the base station to the external eavesdropper; is the channel from the active RIS to the external eavesdropper, is the untrusted user or the secure user, i = 1, 2; when i = 1, it is the untrusted user, and when i = 2, it is the secure user; is the base station, is the active RIS, is the external eavesdropper, H is the conjugate transpose operation, is the indirect channel from the base station to the untrusted user and the secure user; is the indirect channel from the base station to the external eavesdropper When the base station sends signals to the receiving users through the first millimeter-wave channel and the second millimeter-wave channel respectively, an optimization objective function is constructed according to the base station transmission parameters, active RIS parameters, and receiving user parameters, and the optimal variable solution is calculated according to the optimization objective function. The optimal variable solution is used to update the millimeter-wave PD-NOMA system model to achieve communication optimization.

[0096] In this embodiment, the base station sends signals to the receiving users through the first millimeter-wave channel and the second millimeter-wave channel respectively. Then the signals received by the receiving users are respectively denoted as:

[0097]

[0098] Wherein, is the signal received by the untrusted user (or the secure user); is the signal received by the external eavesdropper; The power allocated by the base station to the untrusted user; The power allocated by the base station to the secure user; The precoding vector of the base station for the untrusted user; The precoding vector of the base station for the secure user; and represent the noise at the active RIS and the receiving user; represent the confidential information for the untrusted user; represent for the secure user of the confidential information.

[0099] In addition, when the base station transmits signals to the untrusted user (or secure user) through the first millimeter-wave channel and sends signals to the external eavesdropper through the second millimeter-wave channel, it also includes determining the eavesdropping rate and the secrecy rate of the receiving user, and taking the eavesdropping rate and the secrecy rate as the constraints of the optimization objective function.

[0100] The steps for determining the eavesdropping rate and the secrecy rate of the receiving user include: Decode the confidential signal of the untrusted user to obtain the signal-to-interference-plus-noise ratio (SINR) of the untrusted user's signal, and obtain the signal transmission rate of the untrusted user according to the SINR of the untrusted user's signal; After the signal decoding of the untrusted user is successful, decode the confidential signal of the secure user to obtain the SINR of the secure user's signal, and obtain the signal transmission rate of the secure user based on the SINR of the secure user's signal; Calculate the internal eavesdropping rate according to the signal transmission rates of the untrusted user and the secure user; Determine the SINR of the legitimate signal of the external eavesdropper; calculate the external eavesdropping rate based on the SINR of the legitimate signal of the external eavesdropper; Calculate the secrecy rate of the secure user based on the internal eavesdropping rate and the external eavesdropping rate.

[0101] Specifically, the serial interference cancellation order among receiving users is mainly determined by the channel quality. The stronger user must decode and remove the information of the weaker user to obtain their own information. However, to ensure the confidential information of the secure user, it is necessary to decode the information of the untrusted user first. Specifically expressed as:

[0102] Therefore, when decoding the confidential signal of the untrusted user the SINR (Signal-to-Interference-plus-Noise Ratio) corresponding to the untrusted user and the secure user are respectively expressed as:

[0103]

[0104] Wherein, is the secrecy signal of the untrusted user for decoding and the signal-to-interference-plus-noise ratio of the untrusted user at that time; is the secrecy signal of the untrusted user for decoding and the signal-to-interference-plus-noise ratio of the legitimate user at that time.

[0105] Then, the signal transmission rate of the untrusted user is:

[0106] Wherein, is the signal transmission rate of the untrusted user.

[0107] When the secrecy signal of the untrusted user is successfully decoded, the legitimate user uses SIC (Successive Interference Cancellation) to cancel the secrecy signal of the untrusted user , and then decodes its own secrecy signal , and after the untrusted user decodes the secrecy signal , it also tries to use SIC to decode the information of the secrecy signal of the legitimate user.

[0108] Therefore, when decoding the secrecy signal of the legitimate user, the SINRs of the corresponding untrusted user and legitimate user are respectively expressed as:

[0109]

[0110] Wherein, is the signal-to-interference-plus-noise ratio of the untrusted user when decoding the secrecy signal of the legitimate user; is the signal-to-interference-plus-noise ratio of the legitimate user when decoding the secrecy signal of the legitimate user.

[0111] Then, the signal transmission rate of the legitimate user is:

[0112] Wherein, is the signal transmission rate of the legitimate user.

[0113] Therefore, the eavesdropping rate of the untrusted user on the legitimate user (i.e., the internal eavesdropping rate) is:

[0114] Among them, is the internal eavesdropping rate.

[0115] The SINR of the external eavesdropper corresponding to the legitimate signal is expressed as:

[0116] In the formula, is the signal-to-interference-plus-noise ratio of the external eavesdropper corresponding to the legitimate signal.

[0117] Correspondingly, the eavesdropping rate of the external eavesdropper (i.e., the external eavesdropping rate) is:

[0118] Therefore, the secrecy rate of the secure user is expressed as:

[0119] Among them, , which is used to represent rate scaling, is the secrecy rate of the secure user.

[0120] The data acquisition module is used to obtain the base station transmission parameters, active RIS parameters, and receiving user parameters according to the millimeter-wave PD-NOMA system model.

[0121] The communication optimization module constructs an optimization objective function according to the base station transmission parameters, active RIS parameters, and receiving user parameters, and calculates the optimal variable solution according to the optimization objective function. The optimal variable solution is used to update the millimeter-wave PD-NOMA system model to achieve communication optimization.

[0122] When solving problems such as the communication security and anti-interference of millimeter-wave PD-NOMA, the parameters corresponding to the base station, active RIS, and receiving user need to be considered. Therefore, in this embodiment, an optimization problem is designed, that is, an optimization objective function is constructed, and the optimal solution of the objective function is solved, and then the communication is optimized. Specifically, by jointly optimizing the precoding vector and , the active RIS reflection coefficient matrix and the power allocation power and at the base station, to maximize the secrecy rate of the secure user . Therefore, the final optimization objective function is:

[0123] In the formula, is the secrecy rate of the secure user; is to maximize the secrecy rate; is the data transmission rate of the untrusted user; User quality of service requirements for untrusted users; Power allocated by the base station to untrusted users; Power allocated by the base station to secure users; Precoding vector for untrusted users by the base station; Precoding vector for secure users by the base station; Transmit power of the base station; Reflection coefficient of the m-th reflecting element; Maximum amplitude corresponding to the signal in the reflecting element; Transmission channel of untrusted users; Transmission channel of secure users; Noise power at the active RIS; Maximum reflection power; Identity matrix; Transmit power allocated by the base station to untrusted users; Data transmission rate of untrusted users; Transmit power allocated by the base station to secure users; Reflection power of the downlink after reflection by the active RIS; Reflection coefficient matrix of the active RIS; Power consumed by the noise of the active RIS; Square of the 2-norm of the vector.

[0124] The optimization objective function in this embodiment constrains the following variables respectively. Specifically: Constraint Ensure that user 's data transmission requirements, where is 's user quality of service requirements; Constraint Represents the transmit power limit of the base station; Constraint Represents the reflection coefficient limit of the active RIS; Constraint Ensures the decoding order of successive interference cancellation; Constraint Represents the reflection power limit of the active RIS; Constraint Ensures the power allocation for the two users.

[0125] When solving the optimization objective function, the optimization objective function is first decomposed into three optimization sub-problems. The convex optimization algorithm is used to solve the three optimization sub-problems respectively to obtain the optimal variable solutions. Among them, the first optimization sub-problem is to optimize the precoding vector of the base station; the second optimization sub-problem is to optimize the reflection coefficient matrix of the active RIS; the third optimization sub-problem is to optimize the power allocation of the receiving user. The optimal variable solutions are the optimal base station precoding vector , , the reflection coefficient matrix of the active RIS , the power allocated to the receiving user and .

Claims

1. A communication optimization method based on millimeter wave PD-NOMA, characterized in that: include: An active RIS-assisted millimeter-wave PD-NOMA system model is constructed, and base station transmission parameters, active RIS parameters, and receiving user parameters are obtained according to the millimeter-wave PD-NOMA system model; the millimeter-wave PD-NOMA system model includes a base station, an active RIS, and a receiving user, and the receiving user includes an untrusted user, a secure user, and an external eavesdropper; the untrusted user serves as an internal eavesdropper; Establishing a first millimeter wave channel between a base station and an untrusted user or a secure user, and establishing a second millimeter wave channel between the base station and an external eavesdropper; both the first millimeter wave channel and the second millimeter wave channel include a direct channel and an indirect channel; the direct channel means that the base station communicates directly with the receiving user, and the indirect channel means that the base station communicates with the receiving user through an active RIS; When the base station sends signals through the first millimeter wave channel and the second millimeter wave channel respectively, an optimization objective function is constructed according to the base station transmission parameters, active RIS parameters, and receiving user parameters, the optimal variable solution is calculated according to the optimization objective function, and the millimeter wave PD-NOMA system model is updated according to the optimal variable solution.

2. The communication optimization method based on millimeter wave PD-NOMA according to claim 1 is characterized in that: The active RIS includes M reflective elements, which are used to adjust the phase and amplitude of the signal according to the active RIS parameters, amplify the signal power and transmit it to the receiving user, where M is the total number of reflective elements.

3. The communication optimization method based on millimeter wave PD-NOMA according to claim 2 is characterized in that: The active RIS parameter is a reflection coefficient matrix, which is: in, In the formula, is the reflection coefficient matrix of active RIS, is the reflection coefficient of the first reflection element, is the reflection coefficient of the mth reflective element, is the reflection coefficient of the Mth reflection element, is the amplitude corresponding to the signal in the mth reflection element, is the phase corresponding to the signal in the mth reflection element, is a diagonal matrix, For the dimension, is a complex exponential function, and j is the imaginary unit.

4. The communication optimization method based on millimeter wave PD-NOMA according to claim 1 is characterized in that: The first millimeter wave channel is represented by: The second mmWave channel is represented by: In the formula, is the first millisecond wave channel; It is a direct channel from the base station to untrusted users and secure users; It is the channel from active RIS to untrusted users and secure user equipment; is the reflection coefficient matrix of active RIS; It is the channel from the base station to the active RIS; is the second millimeter wave channel; It is a direct channel from the base station to the external eavesdropper; For the channel from active RIS to external eavesdroppers, Is an untrusted user or a secure user, i=1,2; when i is 1, it is an untrusted user, and when i is 2, it is a secure user; For the base station, For active RIS, For external eavesdroppers, H is the conjugate transpose operation, It is an indirect channel from the base station to untrusted users and secure users; It is an indirect channel from the base station to the external eavesdropper.

5. The communication optimization method based on millimeter wave PD-NOMA according to claim 1 is characterized in that: When the base station sends signals through the first millimeter wave channel and the second millimeter wave channel respectively, it also includes determining the wiretapping rate and the confidentiality rate of the corresponding receiving user according to the sent signal, and taking the wiretapping rate and the confidentiality rate as constraints of the optimization objective function; The step of determining the eavesdropping rate and confidentiality rate of the receiving user comprises: Decoding the signal of the untrusted user to obtain a signal-to-interference-and-noise ratio of the signal of the untrusted user, and obtaining a signal transmission rate of the untrusted user according to the signal-to-interference-and-noise ratio of the signal of the untrusted user; After the signal of the untrusted user is successfully decoded, the secure user is decoded to obtain the signal-to-interference-to-noise ratio of the secure user signal, and the signal transmission rate of the secure user is obtained based on the signal-to-interference-to-noise ratio of the secure user signal; The internal eavesdropping rate is calculated based on the signal transmission rates of the untrusted users and the secure users; Determine the signal-to-interference-to-noise ratio of the legitimate signal of the external eavesdropper; calculate the external eavesdropping rate based on the signal-to-interference-to-noise ratio of the legitimate signal of the external eavesdropper; The confidentiality rate of the secure user is calculated based on the internal eavesdropping rate and the external eavesdropping rate.

6. The communication optimization method based on millimeter wave PD-NOMA according to claim 5 is characterized in that: The signal transmission rate of the untrusted user is: The signal transmission rate of the secure user is: The internal tapping rate is: The external eavesdropping rate is: In the formula, The signal transmission rate for untrusted users; To decode confidential signals from untrusted users The signal-to-interference-noise ratio of the untrusted user; To decode confidential signals from untrusted users Time, signal to interference and noise ratio of secure users; A confidential signal for untrusted users; is an untrusted user; Signaling rate for security users; To decode the confidential signal of the security user Time, signal to interference and noise ratio of secure users; To decode the confidential signal of the security user The signal-to-interference-noise ratio of the untrusted user; A confidential signal for secure users; For security users; is the internal eavesdropping rate; is the external eavesdropping rate; is the signal-to-interference-noise ratio of the legitimate signal corresponding to the external eavesdropper; For external eavesdroppers; is the logarithmic function with base 2.

7. The communication optimization method based on millimeter wave PD-NOMA according to claim 6 is characterized in that: The confidentiality rate of a secure user is expressed as: in, Confidentiality rate for secure users; Used to indicate rate scaling, Signaling rate for security users; is the internal eavesdropping rate; is the external tapping rate.

8. The communication optimization method based on millimeter wave PD-NOMA according to claim 5 is characterized in that: The optimization objective function is: In the formula, Confidentiality rate for secure users; To maximize the confidentiality rate; Data transfer rates for untrusted users; User service quality requirements for non-trusted users; The power allocated to the base station for non-trusted users; Power allocated to safety users by the base station; is a precoding vector for the base station for untrusted users; A precoding vector for a base station for a security user; is the transmission power of the base station; is the reflection coefficient of the mth reflection element; is the maximum amplitude corresponding to the signal in the reflective element; A transmission channel for untrusted users; Transmission channel for security users; is the noise power at the active RIS; is the maximum reflected power; is the identity matrix; The transmission power allocated to the untrusted user by the base station; Data transfer rates for untrusted users; The transmission power allocated to the safe user by the base station; is the reflected power of the downlink after reflection via the active RIS; is the reflection coefficient matrix of active RIS; The power consumed by the noise of the active RIS; is the 2-norm square of the vector, It is the channel from the base station to the active RIS.

9. The communication optimization method based on millimeter wave PD-NOMA according to claim 8, characterized in that: The optimization objective function is decomposed into three optimization sub-problems when solving, and the three optimization sub-problems are solved respectively using a convex optimization algorithm to obtain an optimal variable solution; The first optimization sub-problem is to optimize the precoding vector of the base station; the second optimization sub-problem is to optimize the reflection coefficient matrix of the active RIS; and the third optimization sub-problem is to optimize the power allocation of the receiving user.

10. A communication optimization system based on millimeter wave PD-NOMA, used to implement the communication optimization method based on millimeter wave PD-NOMA according to any one of claims 1 to 9, characterized in that: include: A wireless communication model building module is used to build an active RIS-assisted millimeter wave PD-NOMA system model, wherein the millimeter wave PD-NOMA system model includes a base station, an active RIS, and a receiving user, wherein the receiving user includes an untrusted user, a secure user, and an external eavesdropper; the untrusted user serves as an internal eavesdropper; A wireless communication transmission construction module is used to establish a first millimeter wave channel between a base station and an untrusted user or a secure user, and to establish a second millimeter wave channel between the base station and an external eavesdropper; the first millimeter wave channel and the second millimeter wave channel both include direct channels and indirect channels; the direct channel indicates that the base station communicates directly with the receiving user, and the indirect channel indicates that the base station communicates with the receiving user through an active RIS; A data acquisition module is used to obtain base station transmission parameters, active RIS parameters, and receiving user parameters according to the millimeter wave PD-NOMA system model; The communication optimization module constructs an optimization objective function based on the base station transmission parameters, active RIS parameters, and receiving user parameters, calculates the optimal variable solution based on the optimization objective function, and updates the millimeter wave PD-NOMA system model based on the optimal variable solution.

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