ARIS-assisted NOMA system performance analysis and linear compensation method, system and device, and medium

Abstract

The invention discloses a performance analysis and linear compensation method, system and device for an ARIS-assisted NOMA system and a medium, and belongs to the technical field of wireless communication, and the method comprises the steps: building an ARISs-NOMA-HIS model with two receiving users, and carrying out the modeling of a transmission signal; the SINR condition of a receiving end user is analyzed, the allocated signal power is determined, and performance analysis of the ARISs-NOMA-HIS model is carried out; on the basis of performance analysis, linear compensation is provided, and the performance loss of the ARISs-NOMA-HIS model is compensated by adjusting an ARIS reflection element. According to the method, the system reliability is improved, the hardware damage resistance is enhanced, the communication rate and the spectrum efficiency are improved, and better multi-scene adaptability is realized.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, specifically to a method, system, device, and medium for performance analysis and linear compensation of ARIS-assisted NOMA systems. Background Technology

[0002] Non-orthogonal multiple access (NOMA) in wireless communication scenarios has received widespread attention from academia and industry due to its suitability for rapid data growth and large-scale connection requirements [1]. However, two limitations are particularly important in existing NOMA systems. First, users at the cell edge experience severe signal attenuation due to path loss. In addition, the inherent inter-user interference caused by signal superposition on the same resource is difficult to manage. To overcome these fundamental limitations, the industry has introduced reconfigurable intelligent surface (RIS), forming the NOMA-RIS communication system. The RIS consists of many passive reflective elements, each of which can independently adjust the amplitude and phase of the incident signal to guide it to a selected direction. However, a key challenge ignored in existing work [2] is the inherent "double fading" effect in the RIS reflection link, that is, the signal undergoes two large-scale fadings before reaching the receiver. To address the challenge of "double fading," the concept of Active Reconfigurable Intelligent Surfaces (ARISs) has emerged. By integrating low-power amplifiers, ARISs can amplify the incident signal and adjust its phase, thereby directly offsetting severe path loss. This capability has driven significant research into integrating ARISs with NOMA networks. Furthermore, some existing research has considered practical factors, such as the impact of hardware impairments (HIS).

[0003] However, most studies evaluate NOMA-ARIS systems under idealized assumptions, neglecting the significant impacts of real-world scenarios such as HIS (Hyperinterference Ingress) and imperfect successive interference cancellation (ipSIC). Compensating for the resulting performance losses remains a critical unresolved issue. Therefore, performance analysis of ARIS-assisted NOMA systems is still a relatively underdeveloped area. Given these limitations, this patent provides a comprehensive performance analysis of ARIS-assisted NOMA systems considering HIS and ipSIC, including interrupt probability, ergodicity, and throughput, and proposes a linear compensation method to achieve the performance of an ideal ARIS-assisted NOMA system.

[0004] Existing ARIS-assisted NOMA systems have the following main technical shortcomings in practical applications: Communication models are too idealistic: In real-world scenarios, hardware defects exist, affecting the quality and performance of communication. This significantly impacts parameters such as the interruption probability and traversal rate of the communication system. Idealistic models often produce overly optimistic performance predictions while masking critical issues such as error propagation.

[0005] The iPSIC issue was not considered: users with good channel conditions at the receiving end need to decode the signals of users with poor channel conditions first. If errors occur during the decoding process, it will affect the decoding of useful signals and may even lead to communication interruption.

[0006] Lack of evidence to improve communication quality: In ARIS-assisted NOMA systems with HIS and ipSIC issues, HIS and ipSIC will lead to performance degradation, but there is still no research explaining how to compensate for the performance loss caused by these two factors, which restricts further improvement of the performance of ARIS-assisted NOMA systems. Summary of the Invention

[0007] In view of the above-mentioned problems, the present invention is proposed.

[0008] Therefore, this invention aims to address performance analysis when systems exhibit HIS and ipSIC issues: In the ARIS-assisted NOMA communication model, HIS and ipSIC are introduced to analyze their impact on the model, and closed-form expressions for system outage probability, throughput, and ergodicity are constructed. Power allocation analysis when HIS and ipSIC issues occur: After establishing a system model containing HIS and ipSIC, expressions for the asymptotic ergodic rate of each user in the system are derived, and the impact of power allocation on system performance is analyzed. This provides a power allocation reference for improving service quality in practical scenarios. Improving system performance with HIS and ipSIC: Through mathematical derivation, a linear compensation expression is obtained, optimizing the number of active reflective elements equipped in each ARIS, enabling systems with HIS and ipSIC issues to achieve the performance of an ideal ARISs-NOMA system.

[0009] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a performance analysis and linear compensation method for an ARIS-assisted NOMA system, comprising, An ARISs-NOMA-HIS model with two receiving users is established to model the transmitted signal. The SINR status of the receiving users is analyzed to determine the allocated signal power, and the performance of the ARISs-NOMA-HIS model is analyzed. Based on the performance analysis, linear compensation is proposed to compensate for the performance loss of the ARISs-NOMA-HIS model by adjusting the ARIS reflective element.

[0010] As a preferred embodiment of the performance analysis and linear compensation method for the ARIS-assisted NOMA system described in this invention, the method of modeling the transmitted signal includes: determining the receiving user, determining the distance between the user and the base station (BS) as near user and far user, equipping all nodes with antennas, and deploying ARIS. Based on the ARIS reflective element, the transmission signal is calculated and combined with the superposition coding principle. The BS uses ARIS to calculate and broadcast the superimposed signal to the receiving user. Two receiving users simultaneously receive the superimposed signal from the BS and the signal reflected by the ARIS.

[0011] As a preferred embodiment of the performance analysis and linear compensation method of the ARIS-assisted NOMA system described in this invention, the performance analysis of the ARIS-NOMA-HIS model includes, based on the NOMA principle, using SIC at the receiving first user, and the first user starting to decode the signal of the second user; The first user will detect the information of the second user and calculate the signal-to-interference-to-noise ratio of the second user's signal received by the first user's terminal. If the signal plus interference noise ratio is greater than the rated threshold, the first user starts decoding the second user. When the first user has a decoding defect, the system communication is interrupted.

[0012] As a preferred embodiment of the performance analysis and linear compensation method for the ARIS-assisted NOMA system described in this invention, the decoding defect includes an interruption occurring when the first user fails to detect the signal from the second user. An interrupt occurs when the first user has the ability to decode the second user's signal, but the first user's signal cannot be successfully decoded.

[0013] As a preferred embodiment of the performance analysis and linear compensation method for the ARIS-assisted NOMA system described in this invention, the performance analysis includes the interruption probability of the first user in the ARIS-NOMA-HIS system. for: in, The signal is assigned an interference-to-noise ratio, with the first user labeled as user n and the second user labeled as user f. and Indicates user and users SINR threshold, Add an interference-to-noise ratio to the signal of the first user; The channel coefficient distribution of the ARIS-assisted NOMA communication system follows a Gamma distribution, where the user... The expression for the interruption probability is: user The expression for the interruption probability is: Among them, the definition , , This represents the additive white Gaussian noise at each user location. , , , . Indicates to Calculate the average value. Indicates to Variance calculation It is incomplete function. This indicates the transmission signal-to-noise ratio.

[0014] As a preferred embodiment of the performance analysis and linear compensation method for the ARIS-assisted NOMA system described in this invention, the linear compensation includes the following: The ARIS-NOMA-HIS system, considering the effects of IPCIC and HIS, achieves the same equivalent interruption probability as the ideal ARIS-NOMA system through linear compensation, thus satisfying: in, , This represents the total number of reflective elements in an ideal ARIS-assisted NOMA system. It is the total number of reflective elements in an ARIS-assisted NOA system with ipSIC and HIS. ; To ensure equivalent interrupt performance between two ARIS-assisted NOMA systems, one system uses ipSIC and the other uses pSIC. The required linear compensation relationship is formulated as follows: in, , This is the total number of reflective elements in ARIS-assisted NOMA, HIS, and pSIC systems. This is the total number of reflective elements that ARIS assists NOMA and HIS-ipSIC in.

[0015] As a preferred embodiment of the performance analysis and linear compensation method for the ARIS-assisted NOMA system described in this invention, the linear compensation further includes, while considering latency constraints, constructing an ARISs-NOMA-HIS system and calculating the throughput of the corresponding ARISs-NOMA-HIS system: in, When the parameter When set to zero, pSIC users of ARISs-NOMA-HIS The probability of interruption in the closed form; For users The probability of interruption, For users The probability of interruption; At the same time, calculate the data traversal rate. ,in, Indicates the user's received SINR. This indicates taking the average value; in the ipSIC scenario, users in the ARISs-NOMA-HIS system... The traversal rate is: Users in the ARISs-NOMA-HIS system The data traversal rate of pSIC is: in, , , , , This represents the additive white Gaussian noise at each user location. Indicates allocation to user The ratio of power. Indicates the number of calculations. Represents the inverse gamma function. Represents the gamma function. and These are the shape and rate parameters of the receiver's Gamma distribution, respectively.

[0016] Another objective of this invention is to provide a performance analysis and linear compensation system for ARIS-assisted NOMA systems.

[0017] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a performance analysis and linear compensation system for ARIS-assisted NOMA system, comprising: a modeling module, an analysis module, and a compensation module; The modeling module establishes an ARISs-NOMA-HIS model with two receiving users to model the transmitted signal. The analysis module analyzes the SINR status of the receiving user, determines the allocated signal power, and performs performance analysis of the ARISs-NOMA-HIS model. The compensation module, based on performance analysis, proposes linear compensation to compensate for the performance loss of the ARISs-NOMA-HIS model by adjusting the ARIS reflective element.

[0018] The present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, characterized in that the processor executes the computer program to implement the steps of the performance analysis and linear compensation method of the ARIS-assisted NOMA system.

[0019] The present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of the performance analysis and linear compensation method for the ARIS-assisted NOMA system.

[0020] The beneficial effects of this invention are as follows: This invention improves system reliability. By introducing Active Reconfigurable Smart Surface (ARIS), it effectively overcomes the "double fading" problem of traditional RIS. Even in the presence of hardware damage and imperfect interference elimination, the proposed linear compensation method can still significantly reduce the probability of system interruption, thereby improving the overall stability and reliability of communication.

[0021] To enhance resistance to hardware damage, this invention proposes a linear compensation expression based on the configuration of the number of reflection units, which can offset the performance degradation caused by hardware damage and imperfect SiC, providing an operable design method for the deployment and optimization of the system under non-ideal conditions.

[0022] This patent improves communication rate and spectrum efficiency by deriving analytical expressions for ergodicity and system throughput, and maximizing communication rate through power allocation factor optimization. Compared with traditional solutions, this patent demonstrates higher spectrum utilization efficiency in multi-user NOMA scenarios.

[0023] To achieve better adaptability to multiple scenarios, the linear compensation method proposed in this patent, combined with distributed multi-ARIS deployment and power allocation strategies, can maintain excellent interrupt performance and throughput under different network environments and user distribution conditions, and is suitable for a variety of future wireless communication application scenarios. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 The above is a flowchart of the performance analysis and linear compensation method for an ARIS-assisted NOMA system provided in one embodiment of the present invention.

[0026] Figure 2 For users of the performance analysis and linear compensation method for an ARIS-assisted NOMA system provided in one embodiment of the present invention With users interruption probability and The relationship between them.

[0027] Figure 3 A centralized method for performance analysis and linear compensation of an ARIS-assisted NOMA system provided in one embodiment of the present invention. , ) and distributed ( , Comparison of outage probabilities in ARIS deployment.

[0028] Figure 4 A method for performance analysis and linear compensation of an ARIS-assisted NOMA system provided in one embodiment of the present invention. Different times The probability of user interruption.

[0029] Figure 5 The performance analysis and linear compensation method for an ARIS-assisted NOMA system provided in one embodiment of the present invention, under the same transmit power conditions, allows the user... and Interruption probability under different power allocation schemes.

[0030] Figure 6 The performance analysis and linear compensation method for an ARIS-assisted NOMA system provided in one embodiment of the present invention is achieved by modifying... (Left figure) / ipSIC and HIS coefficients (right figure) verify the correctness of the first linear compensation strategy.

[0031] Figure 7 The performance analysis and linear compensation method for an ARIS-assisted NOMA system provided in one embodiment of the present invention is achieved by modifying... (Left figure) / ipSIC (right figure) verifies the correctness of the second linear compensation strategy.

[0032] Figure 8 Performance analysis and comparison of linear compensation methods for ARIS-assisted NOMA systems provided in one embodiment of the present invention: shutdown performance of four systems: ARIS-NOMA HIS, ARIS-NOMA-HIS, RIS-NOMA-HIS, and ARIS-OMA-HIS.

[0033] Figure 9 The throughput of the ARISs-NOMA-HIS system under various power allocation schemes is presented in an embodiment of the present invention, which provides a performance analysis and linear compensation method for the ARIS-assisted NOMA system.

[0034] Figure 10 The description of the performance analysis and linear compensation method of the ARIS-assisted NOMA system provided in one embodiment of the present invention, under the conditions of M=5 and L=25, with different transmit powers. Traversal rates for near and far users. Detailed Implementation

[0035] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0036] Example 1, referring to Figure 1 This is one embodiment of the present invention, which provides a performance analysis and linear compensation method for an ARIS-assisted NOMA system, including: S100. Establish an ARISs-NOMA-HIS model with two receiving users to model the transmitted signal; S200: Analyze the SINR status of the receiving end user, determine the allocated signal power, and perform performance analysis of the ARISs-NOMA-HIS model. S300. Based on performance analysis, a linear compensation method is proposed to compensate for the performance loss of the ARISs-NOMA-HIS model by adjusting the ARIS reflective element. It should be noted that in the existing technology, there has been a lot of research on the non-orthogonal multiple access (NOMA) communication process assisted by active reconfigurable intelligent surfaces (ARISs), but these solutions mainly focus on performance improvement under ideal conditions. They overestimate the performance indicators in real scenarios, resulting in the technology failing to achieve the expected results when actually implemented.

[0037] To address the shortcomings in the performance analysis of current ARIS-assisted NOMA systems, this paper conducts a comprehensive performance analysis of ARIS-assisted NOMA systems that consider hardware impairments (HIS) and imperfect continuity interference cancellation, including parameters such as interrupt probability, traversal rate, and throughput. A linear compensation method to improve system performance is also proposed.

[0038] Therefore, to address the aforementioned problems, through steps S100-S300, this invention conducts a comprehensive performance analysis of the ARIS-assisted NOMA system under conditions of hardware damage and imperfect continuous interference cancellation. Based on the conclusions of the performance analysis, a linear compensation method is proposed to improve system performance, enabling the ARIS-assisted NOMA system containing HIS and ipSIC to achieve the same or even better performance as the ideal ARIS-assisted NOMA system. Through the technical solution of this invention, a comprehensive understanding of the performance indicators of the ARIS-NOMA-HIS system under perfect serial interference cancellation (pSIC) and ipSIC scenarios can be obtained, bringing analog communication scenarios closer to real-world scenarios and providing efficient and reliable technical support for intelligent transportation, aerial networks, emergency communications, and other scenarios.

[0039] Example 2, refer to Figure 1 This is one embodiment of the present invention, which provides a performance analysis and linear compensation method for an ARIS-assisted NOMA system, including: This invention addresses the hardware impairments (HIS) and imperfect successive interference cancellation (ipSIC) problems present in practical ARISs-NOMA communication scenarios. It establishes an ARISs-NOMA-HIS model and analyzes its performance under pSIC and ipSIC conditions. Furthermore, through mathematical derivation, a linear compensation method is proposed to improve performance by changing the number of each ARIS unit, enabling the system to achieve performance comparable to an ideal ARISs-NOMA system even with the presence of HIS and ipSIC.

[0040] This invention establishes an ARISs-NOMA system model with two receiving users, models the transmitted signal, analyzes the SINR status of the two users at the receiving end, and introduces a power allocation factor to determine the signal power allocated to the two users. Based on this, closed-form expressions for interruption probability, system achievable throughput, and ergodicity are analyzed and derived. Furthermore, the patent derives a linear compensation expression through mathematical analysis to assist the ARIS-assisted NOMA system, which is affected by ipSIC and HIS, in achieving the ideal interruption probability.

[0041] In this embodiment of the invention, S100 establishes an ARISs-NOMA-HIS model with two receiving users to model the transmitted signal, including the following steps S101-S102: S101. Determine the receiving user and the distance between the user and the base station (BS). Divide the user into near users and far users. Equip all nodes with antennas and deploy ARIS. Considering the impact of HIS, this invention studies a two-user ARIS-assisted NOMA communication scenario, in which the base station (BS) communicates via... One ARIS provides services to two users.

[0042] Each ARIS is equipped with One active reflective element; users located relatively close to BS are called near users, denoted as users. Users located further away from the BS are called remote users, denoted as users. .

[0043] Assuming all nodes are equipped with an antenna, and ARIS is a uniform planar array deployed on a wall, there is no interference from reflected signals between each ARIS.

[0044] S102. Based on the reflection element of ARIS, the transmission signal is calculated. Combined with the superposition coding principle, BS uses ARIS to calculate and broadcast the superimposed signal to the receiving users; the two receiving users simultaneously receive the superimposed signal of BS and the signal reflected by ARIS.

[0045] set up , and They represent from BS to the number The first reflective element of the ARIS, from the reflective element to the user and from the reflected element to the user The complex channel coefficients.

[0046] set up and These represent direct communication from the base station to the user. Channel coefficients, directly from base station to user The channel coefficient.

[0047] Based on the superposition coding principle, the BS uses ARIS to broadcast the superimposed signal to a pair of users, transmitting the signal. Represented as in, and For users respectively and users Normalize the unit power signal. For transmission power, and These represent the allocation to users. and users The ratio of power.

[0048] The simultaneous reception of the superimposed signal from the BS and the signal reflected from the ARIS by two users can be represented as: in, It is the dynamic noise at ARIS, defined as follows: , It is an identity matrix. and They are users and users Additive white Gaussian noise at a given location, defined , . and It's hardware noise. This represents the phase shift matrix.

[0049] set up , and They represent from BS to the number The first reflective element of the ARIS, from the reflective element to the user and from the reflected element to the user The complex channel coefficients. Let... and These represent direct communication from the base station to the user. Channel coefficients, directly from base station to user The channel coefficient.

[0050] For ease of further calculation, it is indicated that: in, , and They represent from BS to the number The first reflective element of the ARIS, from the reflective element to the user and from the reflected element to the user The complex channel coefficient components. and These represent direct communication from the base station to the user. Channel coefficients, directly from base station to user The channel coefficient components. This represents the reflection amplification factor.

[0051] In this embodiment of the invention, step S200 analyzes the SINR status of the receiving user, determines the allocated signal power, and performs performance analysis of the ARISs-NOMA-HIS model, including the following steps S201-S203: S201, based on the NOMA principle, in the user SIC is used here. (User) Start decoding user The signal, then the user User will be detected Information.

[0052] Therefore, users User received by the terminal The signal-interference-noise ratio (SINR) of a signal is expressed as: in and The distortions are caused by the transmitter and receiver HIS, respectively. For transmission power, and These represent the allocation to users. and users The ratio of power.

[0053] if When the value exceeds the rated threshold, the user Can decode user SINR is represented as: Considering the situation of iPSIC, It is an interference term caused by iPSIC. This represents the ipSIC coefficient.

[0054] user SINR is represented as: For users System communication is interrupted when one of the following two conditions occurs: 1) If the user User not detected signal An interruption will occur. 2) User With decoding The ability, and its own signal Unable to decode successfully.

[0055] Users of S202 and ARISs-NOMA-HIS systems The interruption probability can be approximated as: in and Indicates user and users SINR threshold.

[0056] There is a precise mathematical relationship between the statistical distribution of channel amplitude and its power gain: if random variables If it follows a Nakagami-m distribution, then its square... It will follow the Gamma distribution perfectly. Therefore, modeling the channel power gain as a gamma-distributed random variable is a simple and mathematically rigorous approach.

[0057] The channel coefficient distribution of an ARIS-assisted NOMA communication system can be approximated by a Gamma distribution, with PDF and CDF respectively. in It is the gamma function. For incomplete gamma functions, , These are the shape parameter and rate parameter of the gamma distribution, respectively.

[0058] S203, User The expression for the interruption probability can be derived as follows: In the formula: in, Indicates to Calculate the average value. Indicates to Variance calculation It is incomplete function. Represents the transmission signal-to-noise ratio, defined , This represents the additive white Gaussian noise at each user location.

[0059] When parameter When set to zero, pSIC users of ARISs-NOMA-HIS The probability of interruption in the closed-form can be given by the following formula. in, Indicates the transmission signal-to-noise ratio. The variable definitions in this formula are the same as in the previous formula.

[0060] When users When the achievable rate is lower than the target rate, the user If no signal is detected, an interrupt will occur, and the corresponding interrupt probability can be written as: user The expression for the interruption probability can be derived as follows: in , In an embodiment of the present invention, based on performance analysis, linear compensation is proposed in S300 to compensate for the performance loss of the ARISs-NOMA-HIS model by adjusting the ARIS reflective element, including the following steps S301-S302: The S301, ARISs-NOMA-HIS system combines the effects of two practical impairments: ipcIC and HIS. Therefore, its performance is slightly lower compared to an ideal ARIS-supported NOMA system without this impairment. Through exploration... , The relationship with the probability of interruption increases and It can improve system performance.

[0061] For ARIS-assisted NOMA systems affected by IPSIC and HIS, in order to achieve the equivalent interrupt probability of their ideal implementation (without IPSIC and HIS), the necessary linear compensation relationship must satisfy: in , and The distortions are caused by the transmitter and receiver HIS, respectively. This represents the ipSIC coefficient. Indicates the transmission signal-to-noise ratio. , Indicates user SINR threshold. This represents the total number of reflective elements in an ideal ARIS-assisted NOMA system. It is the total number of reflective elements in an ARIS-assisted NOA system with ipSIC and HIS. . and Indicates allocation to user and The ratio of power.

[0062] To ensure equivalent interrupt performance between two ARIS-assisted NOMA systems (both constrained by HIS), one system uses ipSIC and the other uses pSIC. The required linear compensation relationship can be formulated as follows: in , This is the total number of reflective elements in ARIS-assisted NOMA, HIS, and pSIC systems. This is the total number of reflective elements that ARIS assists NOMA and HIS-ipSIC in. , and The distortions are caused by the transmitter and receiver HIS, respectively. Indicates the transmission signal-to-noise ratio. , Indicates user SINR threshold. Indicates allocation to user The ratio of power.

[0063] S302. This patent considers a latency-constrained system whose throughput is related to the user's target rate and the probability of interruption. The throughput of the ARISs-NOMA-HIS system is defined as follows: Errata data rate is also an important indicator for evaluating the performance of a communication system. When channel conditions determine the user's target rate, the errata data rate can be expressed as the maximum rate at which the system can correctly transmit data on a cascaded Nakagami-m fading channel, and can be defined as: in This indicates the user's received SINR. This indicates taking the average value.

[0064] In the ipSIC scenario, users in the ARISs-NOMA-HIS system The traversal rate is approximately: In the formula, Users in the ARISs-NOMA-HIS system The data traversal rate of pSIC can be approximated as: in, , , , , This represents the additive white Gaussian noise at each user location. Indicates allocation to user The ratio of power. Indicates the number of calculations. Represents the inverse gamma function. Represents the gamma function. and These are the shape and rate parameters of the receiver's Gamma distribution. in, The principle is as follows: Establish an ARIS-assisted NOMA-HIS dual-user communication model, derive the signal model, and calculate the user... With users SINR is used to calculate the closed-form expression for the interrupt probability. Since the interrupt probability of an ARISs-NOMA system limited by HIS and ipSIC is the same as that of an ideal ARISs-NOMA system, a linear compensation expression is derived. This linear compensation expression is then used to change... and The value is compensated to improve system performance.

[0065] Example 3, referring to Figures 2-10 As one embodiment of the present invention, a performance analysis and linear compensation method for an ARIS-assisted NOMA system is provided. To verify the beneficial effects of the present invention, scientific demonstration is carried out through experiments.

[0066] Example 1, refer to Figure 2 ,user With users Interruption probability and number of ARIS arrays The relationship between them. In a wireless communication channel, an ARISs-NOMA system model is established, serving two users through an active reconfigurable smart surface. The number of reflective elements is then considered. Fixed at 25, with the base station as the origin, user The direction is the x-axis, and the user A rectangular coordinate system is established with the y-axis as the direction and the z-axis perpendicular to the user plane. and They are located at [70,0] and [96,0] respectively. When When =3, ARIS is deployed in [7,10], [35,45], and [65,40]. When When =5, ARIS is deployed at [7,10], [13,20], [35,45], [57,30], and [65,40]. When When the value is 7, ARIS is deployed at [7,10], [13,20], [25,25], [35,45], [40,40], [57,30], and [65,40]. Channel gain is calculated using the city 3GPP UMi protocol model. The antenna gains of BS and ARIS are set to 5 dBi for GBS and GRIS, respectively. and Antenna gain and Set to 0 dBi. Transmit power range set to [5, 35]. Simulation uses... Next iteration; user and The target data rate is 0.5 bit / s / Hz; the HIS value of both the transmitter and receiver is 0.1 BPCU; the thermal noise power of ARIS and the user... and The additive white Gaussian noise power is -80dBm; the reflection coefficient of ARIS is 2. ; .

[0067] The probability of interruption increases with The interrupt performance of the ARISs-NOMA-HIS system decreases monotonically with the increase of multiple ARIS systems, indicating that the interrupt performance of the ARISs-NOMA-HIS system decreases with the assistance of multiple ARIS systems. The increase in diversity gain significantly improves link reliability. This is because the synergistic effect between the diversity of multiple ARISs and the power gain enhances link reliability. Specifically, diversity gain reduces the probability of simultaneous failure of all signal paths, while power gain improves the quality of each path. This combined effect significantly reduces the probability of system downtime. These results validate the effectiveness of deploying multiple ARISs in NOMA systems.

[0068] Example 2, see reference, centralized ( , ) and distributed ( , A comparison of outage probabilities in ARIS deployments. The results show that the distributed configuration achieves a significantly lower outage probability. This clearly demonstrates the performance improvement unique to multi-ARIS deployments. This improvement cannot be achieved by merging the same total number of reflective elements onto a single ARIS. This is because a single large ARIS provides high power gain in a specific direction, while multiple distributed ARISs provide basic diversity gain. In dynamic real-world environments, this diversity is often more important for ensuring stable and reliable communication.

[0069] Example 3, refer to Figure 4 , Different times The interruption probability for the user. The interruption probability increases with... The interrupt performance of an ARISs-NOMA-HIS system decreases monotonically with increasing ARIS count, indicating that when the number of ARISs is fixed, the interrupt performance of the ARISs-NOMA-HIS system decreases with increasing ARIS count. The growth has significantly increased. From a practical deployment perspective, if... Constrained, it can be achieved by adding to each ARIS To improve system performance.

[0070] Example 4, refer to Figure 5 Under the same transmission power conditions, users and Interruption probability under different power allocation schemes. , , The results showed a negative correlation between the power allocation factor and the interruption probability. Specifically, increasing the number of users... Power allocation factor This can reduce its interruption probability, while when When added, the user Similar trends exist. These findings suggest that, under fixed system parameters, optimizing power outage performance for specific users requires adherence to constraints. At the same time, a larger proportion of the power factor is allocated to that user. This trade-off highlights the crucial role of power allocation in balancing performance among users in a NOMA system.

[0071] Example 5, refer to Figure 6 By changing (Left figure) / The ipSIC and HIS coefficients (right figure) verify the correctness of the first linear compensation strategy. Adjustment Then, the calculation is performed using the first linear compensation equation. Based on the obtained Configure the corresponding and This is to achieve performance matching with the ideal system. As can be seen from the left figure, there are users with both ipSIC and HIS. The probability of interruption is generally lower for users without ipSIC and HI. This indicates that the configuration result obtained through the first compensated linear equation is correct. As shown in the right figure, changes in the ipSIC and HIS coefficients will affect... L2 will affect and The configuration. Results show that users with ipSIC and HIS... The probability of interruption is lower than that of users without ipSIC and HIS. These results further confirm the effectiveness of the first linear compensation equation.

[0072] Example 6, refer to Figure 7 By changing (Left figure) / ipSIC (right figure) verifies the correctness of the second linear compensation strategy. First, adjust... Then, the second linear compensation equation is used to calculate... According to the obtained Configure the corresponding and This enables ARIS-assisted NOMA systems, limited by ipSIC and HIS, to achieve performance matching with ideal systems. As shown in the left figure, the user... The interrupt probability using ipSIC and HIS is typically lower than that of users. Using the downtime probabilities of pSIC and HIS, this demonstrates that the configuration result obtained through the second compensated linear equation is correct. The right figure shows the configuration in the compensated linear equation configuration. and Afterwards, the user The interrupt probability is lower when using ipSIC and HIS than when using user Using the interruption probabilities of pSIC and HIS, this again proves the correctness of the second linear compensation equation.

[0073] Example 7, refer to Figure 8 The shutdown performance of four systems was compared: ARIS-NOMA HIS, ARIS-NOMA-HIS, ARIS-NOMA-HIS, and ARIS-OMA-HIS. , When the transmit power, achievable rate, and user-allocated power are the same, it can be seen from the figure that the theoretical analysis results of ARIS-NOMA-HIS, RIS-NOMA-HIS, and ARIS-OMA-HIS perfectly match the Monte Carlo simulation results, but there is a very small error between the theoretical and simulated values ​​of ARIS-NOMA-HIS. This is because the Gamma distribution is a statistical approximation. The larger the value, the more accurate the approximation. This also indicates that using the Gamma distribution to approximate multiple ARIS channels is reasonable. Furthermore, it can be observed that the outage probability for all users in the ARISs-NOMA-HIS system is lower than that in the RIS-NOMA-HIS system, the ARIS-NOMA-HIS system, and the ARIS-OMA-HIS system. This suggests that, under the same communication scenarios and configurations, the ARISs-NOMA-HIS system should be the preferred choice.

[0074] Example 8, refer to Figure 9 Throughput of the ARISs-NOMA-HIS system under various power allocation schemes. Fixed and , When the power allocation factor is set to and At that time, the system achieved maximum throughput. If other power allocation schemes are used, this can be achieved by increasing... and This improves system throughput. It provides a power allocation scheme for the ARISs-NOMA-HIS system at its highest throughput, offering a reference solution for practical system design.

[0075] Example 9, refer to Figure 10 It describes the different transmit powers when M=5 and L=25. Traversal rates for near and far users were determined. Theoretical analysis and simulation results show that the simulated values ​​and analysis results for each traversal rate are in good agreement. At high transmit power... Below, user The traversal speed is better than that of the user. The traversal rate. Conversely, at low... The convergence of the traversal rates of the two users indicates that the impact of power allocation is limited under low signal-to-noise ratio conditions.

[0076] In the description of this invention, "several" means one or more, "multiple" means two or more, "greater than", "less than", "exceeding" are understood to exclude the number itself, and "above", "below", "within" are understood to include the number itself.

[0077] Example 4 is an embodiment of the present invention. The above is an illustrative scheme of the performance analysis and linear compensation method for the ARIS-assisted NOMA system. It should be noted that the technical solution of the performance analysis and linear compensation system for the ARIS-assisted NOMA system belongs to the same concept as the technical solution of the performance analysis and linear compensation method for the ARIS-assisted NOMA system described above. Details not described in detail in the technical solution of the performance analysis and linear compensation system for the ARIS-assisted NOMA system in this embodiment can be found in the description of the technical solution of the performance analysis and linear compensation method for the ARIS-assisted NOMA system described above.

[0078] This embodiment provides a performance analysis and linear compensation system for an ARIS-assisted NOMA system, including: a modeling module, an analysis module, and a compensation module; The modeling module establishes an ARISs-NOMA-HIS model with two receiving users to model the transmitted signal. The analysis module analyzes the SINR status of the receiving user, determines the allocated signal power, and performs performance analysis of the ARISs-NOMA-HIS model. The compensation module, based on performance analysis, proposes linear compensation to compensate for the performance loss of the ARISs-NOMA-HIS model by adjusting the ARIS reflective element.

[0079] This embodiment also provides an electronic device applicable to the performance analysis and linear compensation method of ARIS-assisted NOMA system, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the performance analysis and linear compensation method of ARIS-assisted NOMA system as proposed in the above embodiment.

[0080] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the performance analysis and linear compensation method for the ARIS-assisted NOMA system as proposed in the above embodiments.

[0081] The storage medium proposed in this embodiment and the performance analysis and linear compensation method for the ARIS-assisted NOMA system proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0082] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0083] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. 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 be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for performance analysis and linear compensation of ARIS-assisted NOMA systems, characterized by: include, An ARISs-NOMA-HIS model with two receiving users is established to model the transmitted signal; Analyze the SINR status of the receiving end users to determine the allocated signal power and perform performance analysis of the ARISs-NOMA-HIS model; Based on performance analysis, a linear compensation method is proposed to compensate for the performance loss of the ARISs-NOMA-HIS model by adjusting the ARIS reflective element.

2. The performance analysis and linear compensation method for the ARIS-assisted NOMA system as described in claim 1, characterized in that: The modeling of the transmitted signal includes determining the receiving user, determining the distance between the user and the base station (BS) and classifying them as near users and far users, equipping all nodes with antennas, and deploying ARIS; Based on the ARIS reflective element, the transmission signal is calculated and combined with the superposition coding principle. The BS uses ARIS to calculate and broadcast the superimposed signal to the receiving user. Two receiving users simultaneously receive the superimposed signal from the BS and the signal reflected by the ARIS.

3. The performance analysis and linear compensation method for the ARIS-assisted NOMA system as described in claim 2, characterized in that: The performance analysis of the ARISs-NOMA-HIS model includes, based on the NOMA principle, using SIC at the receiving end of the first user, and the first user starting to decode the signal of the second user; The first user will detect the information of the second user and calculate the signal-to-interference-to-noise ratio of the second user's signal received by the first user's terminal. If the signal plus interference noise ratio is greater than the rated threshold, the first user starts decoding the second user. When the first user has a decoding defect, the system communication is interrupted.

4. The performance analysis and linear compensation method for the ARIS-assisted NOMA system as described in claim 3, characterized in that: The decoding defect includes an interruption that occurs when the first user fails to detect the signal from the second user; An interrupt occurs when the first user has the ability to decode the second user's signal, but the first user's signal cannot be successfully decoded.

5. The performance analysis and linear compensation method for the ARIS-assisted NOMA system as described in claim 4, characterized in that: The performance analysis includes the interruption probability of the first user in the ARISs-NOMA-HIS system. for: in, The signal is assigned an interference-to-noise ratio, with the first user labeled as user n and the second user labeled as user f. and Indicates user and users SINR threshold, Add an interference-to-noise ratio to the signal of the first user; The channel coefficient distribution of the ARIS-assisted NOMA communication system follows a Gamma distribution, where the user... The expression for the interruption probability is: user The expression for the interruption probability is: Among them, the definition , , This represents the additive white Gaussian noise at each user location. , , , ; Indicates to Calculate the average value. Indicates to Variance calculation It is incomplete function; This indicates the transmission signal-to-noise ratio.

6. The performance analysis and linear compensation method for the ARIS-assisted NOMA system as described in claim 5, characterized in that: The linear compensation includes the following: If the ARISs-NOMA-HIS system, combining the effects of IPCIC and HIS, achieves the same equivalent interrupt probability as the ideal ARISs-NOMA system through a linear compensation relationship, then the following condition must be met: in, , and The distortions are caused by the transmitter and receiver HIS, respectively. Represents the ipSIC coefficient; Indicates the transmission signal-to-noise ratio. , and Indicates user and users SINR threshold; This represents the total number of reflective elements in an ideal ARIS-assisted NOMA system. It is the total number of reflective elements in an ARIS-assisted NOA system with ipSIC and HIS. ; To ensure equivalent interrupt performance between two ARIS-assisted NOMA systems, one using ipSIC and the other using pSIC, the required linear compensation relationship is formulated as follows: in, , This is the total number of reflective elements in ARIS-assisted NOMA, HIS, and pSIC systems. This is the total number of reflective elements that ARIS assists NOMA and HIS-ipSIC in; , and The distortions are caused by the transmitter and receiver HIS, respectively. Indicates the transmission signal-to-noise ratio. , Indicates user SINR threshold; Indicates allocation to user The ratio of power.

7. The performance analysis and linear compensation method for the ARIS-assisted NOMA system as described in claim 6, characterized in that: The linear compensation also includes, while considering latency constraints, constructing an ARISs-NOMA-HIS system and calculating the throughput of the corresponding ARISs-NOMA-HIS system: in, When the parameter When set to zero, pSIC users of ARISs-NOMA-HIS The probability of interruption in the closed form; For users The probability of interruption, For users The probability of interruption; At the same time, calculate the data traversal rate. ,in, Indicates the user's received SINR. This indicates taking the average value; in the ipSIC scenario, users in the ARISs-NOMA-HIS system... The traversal rate is: Users in the ARISs-NOMA-HIS system The data traversal rate of pSIC is: in, , , , , Indicates allocation to user The ratio of power; Indicates the number of calculations. Represents the inverse gamma function. Represents the gamma function. and These are the shape and rate parameters of the receiver's Gamma distribution, respectively.

8. A performance analysis and linear compensation system for an ARIS-assisted NOMA system, using the performance analysis and linear compensation method for an ARIS-assisted NOMA system as described in any one of claims 1 to 7, characterized in that, include: Modeling module, analysis module, compensation module; The modeling module establishes an ARISs-NOMA-HIS model with two receiving users to model the transmitted signal. The analysis module analyzes the SINR status of the receiving user, determines the allocated signal power, and performs performance analysis of the ARISs-NOMA-HIS model. The compensation module, based on performance analysis, proposes linear compensation to compensate for the performance loss of the ARISs-NOMA-HIS model by adjusting the ARIS reflective element.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the performance analysis and linear compensation method for the ARIS-assisted NOMA system as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the performance analysis and linear compensation method for the ARIS-assisted NOMA system as described in any one of claims 1 to 7.

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