A design method for NOMA communication system based on simultaneous transmission and reflection metasurface

Abstract

The present invention belongs to the field of wireless communication technology. The present invention proposes a design method for a non-orthogonal multiple access communication system based on a simultaneous transmission and reflection metasurface. By introducing a smart metasurface that can transmit and reflect at the same time to assist the base station in sending information to non-orthogonal users, the near-end user can also receive the information sent from the base station through a direct link. The design method includes establishing a NOMA communication system design model based on a simultaneous transmission and reflection metasurface, giving the received signal expression of the near-end user and the far-end user and detecting the signal-to-noise ratio, and deriving the interruption probability theoretical expression and diversity order of the near-end user and the far-end user by processing the channel parameters of the cascade channel through the Laguerre series and the coherent phase shift. Compared with the traditional decoding and forwarding relay, amplification and forwarding relay and smart metasurface-assisted orthogonal multiple access communication system, the method of the present invention enhances the interruption probability performance and traversal performance, and has good application value.

Description

Technical Field

[0001] The present application relates to a method for designing a NOMA communication system based on a simultaneous transmission and reflection metasurface, which belongs to the field of wireless communication technology, and in particular to a method for processing channel parameters of a Ricean cascade channel using Laguerre series and coherent phase shift. Background Art

[0002] With the commercial deployment of the fifth generation mobile communication technology (5G), the physical key technology layer of the 5G communication system has begun to conduct pre-research for the sixth generation mobile communication technology (6G). Compared with the 5G system, the goal of the 6G network is to meet dynamic services and provide enhanced effective transmission / energy efficiency, global coverage, etc. Compared with orthogonal multiple access, non-orthogonal multiple access accommodates more users through non-orthogonal resource allocation, has the characteristics of high spectrum efficiency, support for giant connections, and better fairness among users, and is regarded as a candidate for access technology for 6G networks.

[0003] Smart metasurface is an emerging wireless technology. It designs coded metamaterials by arranging a group of small scattering or apertures in a regular array throughout the space. It is an artificial electromagnetic surface structure with programmable electromagnetic properties that can be applied to various frequency bands from microwaves to visible light. Smart metasurfaces are programmed and controlled with the help of digital sequences to achieve real-time regulation of electromagnetic parameters such as electromagnetic wave amplitude, phase, and frequency, actively enrich channel scattering conditions, enhance the multiplexing gain of wireless communication systems, and achieve signal propagation direction regulation and co-phase superposition, increase the strength of received signals, and improve the transmission performance between communication devices. Smart metasurfaces can break through the limitations of uncontrollable traditional wireless channels and have been proven to be used as electromagnetic relays to improve the system performance of networks.

[0004] Existing research mainly considers the use of only reflective smart metasurfaces, that is, to receive signals from only reflective RIS, users must be on the same side as the transmitter, which brings additional topological constraints to the wireless system. In order to alleviate this shortcoming and promote more flexible system design of RIS-assisted networks, a communication system assisted by simultaneously reflecting and transmitting smart metasurfaces is considered. Compared with the traditional RIS with only reflection transmission, in the STAR-RIS-assisted communication system, users on the same side as the base station receive the reflected signal, while users on the opposite side of the base station receive the signal through transmission. This communication system achieves full spatial coverage, and STAR-RIS has a higher diversity order, a wider coverage range, and higher spectral efficiency. The NOMA communication system based on simultaneously transmitting and reflecting metasurfaces provides new degrees of freedom for manipulating signal propagation, thereby increasing the flexibility of communication system design, making the system flexible and efficient, significantly improving spectral efficiency, and improving the system's interruption performance and traversal performance. Summary of the invention

[0005] The purpose of this application is to introduce simultaneous transmission and reflection metasurfaces in the power domain NOMA system, fully explore and utilize the limited communication resources of the system, and design an efficient communication transmission solution.

[0006] 1. A method for designing a NOMA communication system based on a simultaneous transmission and reflection metasurface, characterized in that it comprises the following steps:

[0007] Step 1: Establish a NOMA communication system model based on simultaneous transmission and reflection metasurfaces, and write the received signal expressions of near-end user n and far-end user m;

[0008] Step 2: Write out the signal-to-noise ratio (SINR) of the near-end user n using the imperfect / perfect Successive Interference Cancellation (ipSIC / pSIC) mechanism to first detect the signal of the far-end user m and delete it, then write out the SINR of the near-end user n detecting its own signal, and finally the SINR of the far-end user m directly treating the signal of the near-end user n as interference to decode its own signal;

[0009] Step 3: Use coherent phase shift to process the phase shift of the simultaneously transmitting and reflecting smart metasurface, and use the first term of the Laguerre series to approximate the distribution of the cascaded Ricean channels;

[0010] Step 4: Define the interruption event of the near-end user n in the NOMA communication system based on the simultaneous transmission and reflection metasurface using the ipSIC / pSIC mechanism and the interruption event of the far-end user m;

[0011] Step 5: Write the closed-form solution expression of the outage probability of the near-end user n under the cascaded Ricean channel using the ipSIC / pSIC mechanism and the closed-form solution expression of the outage probability of the far-end user m;

[0012] Step 6: Further write out the approximate expression of the outage probability of the near-end user n under high signal-to-noise ratio using the ipSIC / pSIC mechanism and the approximate expression of the outage probability of the far-end user m;

[0013] Step 7: Write down the diversity order of near-end user n using ipSIC / pSIC mechanism and the diversity order of far-end user m under cascaded Ricean channel;

[0014] Step 8: Define the ergodic rate of the near-end user n and the ergodic rate of the far-end user m in the NOMA communication system based on the simultaneous transmission and reflection metasurface using the ipSIC / pSIC mechanism;

[0015] Step 9: Write the ergodic rate expression of the near-end user n under the cascaded Riceic channel using the ipSIC / pSIC mechanism and the ergodic rate expression of the remote user m;

[0016] Step 10: Further write the upper bound of the ergodic rate of the near-end user n when using the pSIC mechanism, and the ergodic rate expression of the far-end user m under high signal-to-noise ratio;

[0017] Step 11: Write out the high signal-to-noise ratio ergodic rate slope of the near-end user n under the ipSIC / pSIC mechanism and the high signal-to-noise ratio ergodic rate slope of the far-end user m;

[0018] Among them, step 1 specifically includes: the communication system specifically includes a base station, a simultaneously transmitting and reflecting smart metasurface and two non-orthogonal users, the near-end user n simultaneously receives the signal sent from the base station to the smart metasurface and then reflected, and the signal sent by the base station through a direct link; the far-end user m only receives the signal sent from the base station to the smart metasurface and then transmitted;

[0019] The simultaneous transmission and reflection smart metasurface includes 2K units, where K represents an arbitrary positive integer. All channels are modeled as Rice fading channels and the influence of large-scale fading is considered at the same time. represents the complex channel coefficient matrix from the base station to the smart metasurface, represents the complex channel coefficient from the base station to the kth element of the smart metasurface, where 1≤k≤K, and It obeys a complex Gaussian distribution with a mean of 0 and a variance of 1, that is represents the large-scale fading from the base station to the smart metasurface, α and η are the path loss factor and frequency factor respectively, κ is the Rice factor, and d sris the distance from the base station to the smart metasurface; represents the complex channel coefficient matrix from the smart metasurface to user n, represents the complex channel coefficient from the kth element of the smart metasurface to user n, It obeys a complex Gaussian distribution with a mean of 0 and a variance of 1, that is represents the large-scale fading from the smart metasurface to user n, d rn is the distance from the smart metasurface to user n; represents the complex channel coefficient matrix from the smart metasurface to user m, represents the complex channel coefficient from the kth element of the smart metasurface to user m, represents the large-scale fading from the smart metasurface to user m, d rm is the distance from the smart metasurface to user m; represents the complex channel coefficient from the base station to the near-end user n, It obeys a complex Gaussian distribution with a mean of 0 and a variance of 1, that is represents the large-scale fading from the base station to user n, d sn is the distance from the base station to user n, and the reflection and transmission characteristics of the smart metasurface are respectively expressed by a diagonal matrix and To reflect, and denote the reflection and transmission amplitude characteristics of the kth smart metasurface unit, respectively, and Among the 2K smart metasurface units, K units There are K units and denote the reflection phase shift and transmission phase shift of the kth smart metasurface unit respectively. Then, the received signal expression at the near-end user n is expressed as

[0020]

[0021] At the same time, the received signal expression at the remote user m is expressed as

[0022]

[0023] Among them, a n ≤a m , and are Gaussian white noise at user m and user n respectively;

[0024] Step 2 specifically includes: According to the NOMA decoding order criterion, the corresponding signal to noise ratio when the near-end user n decodes the signal of the far-end user m is expressed as

[0025]

[0026] Where ρ = P s / N0 represents the transmit signal-to-noise ratio, N0 represents the noise power, And when and indicates that the near-end user n uses the pSIC and ipSIC mechanisms, respectively. I | 2 is the channel gain corresponding to the interference signal caused by the near-end user n using ipSIC, h I :CN(0,1);

[0027] For near-end user n, the signal-to-interference-noise ratio after using the SIC mechanism to delete the signal of far-end user m is expressed as

[0028]

[0029] For the remote user m, the signal of the near-end user n is directly regarded as interference to decode its own signal. At this time, the corresponding detection signal-to-interference-to-noise ratio is expressed as:

[0030]

[0031] Step 3 specifically includes: From the application perspective, continuously changing the amplitude and phase of the reflection unit of the smart metasurface is beneficial to enhancing network performance, but it requires precise design and expensive hardware architecture, which brings high costs to the deployment of the smart metasurface. For this reason, the cascade channel gains of user n and user m are defined as: in and They represent the reflection phase shift and transmission phase shift of the kth smart metasurface unit respectively. Through the coherent phase shift design, the phase shift of the smart metasurface matches the phase of the attenuation gain of the smart metasurface, and we get According to the two characteristics of the cascaded Ricean channel, namely: ① the probability density function of the cascaded Ricean channel has a single maximum value; ② the probability density function of the cascaded Ricean channel extends to infinity on both sides of the maximum value, the probability density function expression of the cascaded Ricean channel can be obtained by approximating the first term of the Laguerre series:

[0032]

[0033] Among them, υ∈(m,n) represents the user set, υ=m represents user m, υ=n represents user n,

[0034]

[0035] α rυ ∈(α rn ,α rm ),

[0036]

[0037] K0(·) and K1(·) are the 0th and 1st order modified Bessel functions, respectively, and Γ(·) is the gamma function;

[0038] Step 4 specifically includes: the interruption compensation event at the near-end user n is interpreted as the near-end user n successfully decoding the signal of the remote user m, and then successfully decoding its own signal after deleting the signal of the remote user m using the SIC mechanism; therefore, based on formula (3) and formula (4), the interruption event of the near-end user n is defined by a mathematical expression as follows:

[0039] in, R ν Indicates the user ν detection signal x ν The target rate at .

[0040] The interruption event at the remote user m is interpreted as the inability of user m to detect the interruption of its own information. Therefore, based on formula (5), the interruption event of the remote user m is defined by a mathematical expression as

[0041]

[0042] Step 5 specifically includes: setting υ in formula (6) to n and substituting it into formula (7) to calculate the interruption probability expressions of user n under the ipSIC / pSIC mechanism:

[0043]

[0044]

[0045] in,

[0046]

[0047] represents the weighting coefficient of Gauss-Laguerre integral, x p is the Laguerre polynomial L P (x p ), P and U represent the trade-off parameters between complexity and accuracy,

[0048] Set υ in formula (6) to m and substitute it into formula (8), and the outage probability expression of remote user m in the cascaded Ricean channel is calculated as follows:

[0049]

[0050] Among them, γ(·) is the incomplete gamma function;

[0051] Step 6 specifically includes: when ρ→∞ in formula (9), the approximate expression of the interruption probability of the near-end user n using the ipSIC mechanism is calculated as

[0052]

[0053] in, express and The larger of the two;

[0054] When ρ→∞, using the first term of the incomplete gamma function series form, the approximate expression for the outage probability of near-end user n using the pSIC mechanism is obtained as follows:

[0055]

[0056] When ρ→∞, using the first term of the incomplete gamma function series form, the approximate expression for the outage probability of remote user m is obtained as follows:

[0057]

[0058] Step 7 specifically includes: According to the mathematical definition of the diversity order

[0059]

[0060] Substituting formulas (12), (13), and (14) into (15), we can calculate that the diversity order of the near-end user n in the cascaded Ricean channel is 0 when using the ipSIC mechanism, and is 0 when using the pSIC mechanism. And the diversity order of remote user m is Step 8 specifically includes: the traversal rates of the near-end user n using the ipSIC / pSIC mechanism are defined as

[0061]

[0062]

[0063] The traversal rate of remote user m is defined as

[0064]

[0065] Step nine specifically includes: Based on formula (16), the ergodic rate expression of the near-end user n using the ipSIC mechanism is calculated as follows:

[0066]

[0067] Based on formula (17), the ergodic rate expression of the near-end user n using the pSIC mechanism is:

[0068] in, Ω I The channel power of the interference signal when it is ipSIC;

[0069] Based on formula (18), the ergodic rate expression of remote user m is calculated as follows:

[0070]

[0071] Step 10 specifically includes: By introducing Jensen's inequality, the upper bound of the traversal rate of user n is

[0072] Further calculations show that the upper bound of the traversal rate of the near-end user n is

[0073]

[0074] According to formula (18), when the sending signal-to-noise ratio ρ→∞, the ergodic rate of the remote user m under high signal-to-noise ratio is calculated as

[0075]

[0076] Step 11 specifically includes: the ergodic rate slope is a key parameter for determining the ergodic rate performance under high signal-to-noise ratio conditions, and the ergodic rate slope expression is defined as:

[0077]

[0078] Substituting formulas (23) and (24) into (25), we can calculate that the ergodic rate slope of the near-end user n under the pSIC mechanism is 1, and the ergodic rate slope of the far-end user m is 0.

[0079] Compared with the prior art, the present invention has the following advantages:

[0080] This application uses the coherent phase shift method in the design of the NOMA communication system based on the simultaneous transmission and reflection smart metasurface, processes the phase angle of the simultaneous transmission and reflection metasurface, and obtains the signal-to-noise ratio of non-orthogonal users. The first term of the Laguerre series is used to approximate the cascaded Rice channel distribution of the smart metasurface, and then solves the user's interruption probability expression and ergodic rate expression, and analyzes the diversity order and high signal-to-noise ratio slope. Compared with the OMA system and the traditional collaborative communication system, the performance is better, and the method is simple and easy to implement. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 This is a model diagram of a NOMA communication system based on a simultaneously transmitting and reflecting smart metasurface described in this application;

[0082] Figure 2 It is a comparison chart of the interruption performance of the NOMA communication system based on the simultaneous transmission and reflection metasurface and the c based on the simultaneous transmission and reflection metasurface;

[0083] Figure 3 This is a comparison chart of the interruption performance of the NOMA communication system based on simultaneous transmission and reflection metasurface under different Ricean factors;

[0084] Figure 4 This is a comparison chart of the interruption performance of the NOMA communication system based on simultaneous transmission and reflection metasurfaces under different numbers of smart metasurface units;

[0085] Figure 5 This is a comparison chart of the ergodic rates of the NOMA communication system based on simultaneous transmission and reflection metasurface and the OMA communication system based on simultaneous transmission and reflection metasurface;

[0086] Figure 6 This is a flow chart of a NOMA communication system design method based on a simultaneous transmission and reflection metasurface described in this application. DETAILED DESCRIPTION

[0087] The present application is further described below in conjunction with examples and drawings. It should be noted that the embodiments do not limit the scope of protection claimed in the present application.

[0088] The purpose of this application is to introduce simultaneous transmission and reflection metasurfaces in the power domain NOMA system, fully explore and utilize the limited communication resources of the system, and design an efficient communication transmission solution.

[0089] A method for designing a NOMA communication system based on a simultaneous transmission and reflection metasurface includes the following steps:

[0090] Step 1: Establish a NOMA communication system model based on simultaneous transmission and reflection metasurfaces, and write the received signal expressions of near-end users and far-end users;

[0091] Step 2: The near-end user uses an imperfect / perfect Successive Interference Cancellation (ipSIC / pSIC) mechanism to first detect the far-end user's signal and delete it, and then detects the signal-to-noise ratio of its own signal, as well as the signal-to-noise ratio of its own signal that the far-end user directly treats the near-end user's signal as interference and decodes;

[0092] Step 3: Use coherent phase shift to process the phase angle of the simultaneously transmitting and reflecting smart metasurface, and use the first term of the Laguerre series to approximate the distribution of the cascaded Ricean channels;

[0093] Step 4: Define the interruption events of the near-end user in the NOMA communication system based on the simultaneous transmission and reflection metasurface using the ipSIC / pSIC mechanism and the interruption events of the far-end user;

[0094] Step 5: Derive the closed-form solution expression of the outage probability of the near-end user under the cascaded Ricean channel using the ipSIC / pSIC mechanism and the closed-form solution expression of the outage probability of the far-end user;

[0095] Step 6: Further derive the approximate expression of the outage probability of the near-end user using the ipSIC / pSIC mechanism and the approximate expression of the outage probability of the far-end user under high signal-to-noise ratio;

[0096] Step 7: Give the diversity order of the near-end user using the ipSIC / pSIC mechanism and the diversity order of the far-end user under the cascaded Ricean channel;

[0097] Step 8: Define the ergodic rate of the near-end user and the ergodic rate of the far-end user in the NOMA communication system based on the simultaneous transmission and reflection metasurface using the ipSIC / pSIC mechanism;

[0098] Step 9: Derive the ergodic rate expression of the near-end user using the ipSIC / pSIC mechanism and the ergodic rate expression of the far-end user under the cascaded Riceic channel;

[0099] Step 10: Further derive the upper bound of the ergodic rate when the near-end user uses the pSIC mechanism, and the ergodic rate expression of the far-end user under high signal-to-noise ratio;

[0100] Step 11: Give the high signal-to-noise ratio ergodic rate slope of the near-end user under the cascaded Riceic channel using the ipSIC / pSIC mechanism and the high signal-to-noise ratio ergodic rate slope of the far-end user.

[0101] Specifically, step one includes: the communication system includes a base station, a simultaneously transmitting and reflecting smart metasurface, and two non-orthogonal users, the near-end user simultaneously receives the signal sent from the base station to the smart metasurface and then reflected, and the signal sent by the base station through a direct link; the far-end user only receives the signal sent from the base station to the smart metasurface and then transmitted.

[0102] The transmission and reflection smart metasurfaces include 2K units. The complex channel coefficients from the base station to the smart metasurface and from the smart metasurface to the near-end user n and the far-end user m are expressed as h sr 、hrn and h rm The complex channel coefficient from the base station to the near-end user n is represented by h sn , and model all channels as Rice fading channels while considering the impact of large-scale fading, where

[0103]

[0104] α and η are the path loss factor and frequency factor respectively, κ is the Rice factor, d sr is the distance from the base station to the smart metasurface;

[0105]

[0106] d rn is the distance from the smart metasurface to user n;

[0107]

[0108] d rm is the distance from the smart metasurface to user m; d sn is the distance from the base station to user n. The reflection and transmission characteristics of the smart metasurface are respectively expressed by a diagonal matrix and To reflect, and denote the reflection and transmission amplitude characteristics of the kth smart metasurface unit, respectively, and Among the 2K smart metasurface units, K units There are K units and denote the reflection phase shift and transmission phase shift of the kth smart metasurface unit respectively. Then, the received signal expression at the near-end user n is expressed as

[0109]

[0110] At this time, the received signal expression at the remote user m is:

[0111]

[0112] Among them, a n ≤a m , and are Gaussian white noise at user m and user n respectively.

[0113] Specifically, step 2 specifically includes: according to the NOMA decoding order criterion, the corresponding signal to interference noise ratio when the near-end user n decodes the signal of the far-end user m is expressed as

[0114]

[0115] in, Indicates the signal-to-noise ratio at the sender. Specifically, when and indicates that the near-end user n uses the pSIC and ipSIC mechanisms, respectively. I | 2 The channel gain corresponding to the interference signal caused by the near-end user using ipSIC, For near-end user n, the signal-to-interference-noise ratio after using the SIC mechanism to delete the signal of far-end user m is expressed as

[0116]

[0117] For the remote user m, the signal of the near-end user n is directly regarded as interference to decode its own signal. At this time, the corresponding detection signal-to-interference-to-noise ratio is expressed as:

[0118]

[0119] Specifically, step three specifically includes: from the application perspective, continuously changing the amplitude and phase of the reflection unit of the smart metasurface is beneficial to enhancing network performance, but it requires precise design and expensive hardware architecture, which brings high cost to the deployment of the smart metasurface. To this end, the present invention defines the cascade channel gains of user n and user m as: Through the coherent phase shift design, the phase shift of the smart metasurface is matched with the phase of the attenuation gain of the smart metasurface, and we get According to the two characteristics of the cascaded Ricean channel, namely: ① the probability density function of the cascaded Ricean channel has a single maximum value; ② the probability density function of the cascaded Ricean channel extends to infinity on both sides of the maximum value, the probability density function expression of the cascaded Ricean channel can be obtained by approximating the first term of the Laguerre series:

[0120] Among them, υ∈(m,n),

[0121]

[0122] K0(·) and K1(·) are the 0th and 1st order modified Bessel functions, respectively, and Γ(·) is the gamma function.

[0123] Specifically, step 4 specifically includes: the interruption compensation event at the near-end user n is interpreted as the near-end user n decoding the signal of the remote user m, and also decoding its own signal after deleting the signal of the remote user m using the SIC mechanism. Therefore, based on formula (3) and formula (4), the interruption event of the near-end user n is expressed as

[0124] in, R υ Indicates the user υ detection signal x υ The target rate at .

[0125] The interruption event at the end user m is interpreted as the inability of user m to detect the interruption of its own information. Therefore, based on formula (5), the interruption event of the remote user m can be expressed mathematically as

[0126]

[0127] Specifically, step five includes: obtaining the interruption probability expressions of user n in the cascaded Ricean channel using the ipSIC / pSIC mechanism through theoretical derivation:

[0128]

[0129]

[0130] Among them, among them, is the larger of τ and β,

[0131] represents the weighting coefficient of Gauss-Laguerre integral, x p are the zeros of the Laguerre polynomials. P and U represent the trade-off parameters between complexity and accuracy.

[0132] Through theoretical derivation, the outage probability expression of remote user m in the cascaded Ricean channel is obtained as follows:

[0133] Among them, γ(·) is the incomplete gamma function.

[0134] Specifically, step six includes: when ρ→∞, the approximate expression of the interruption probability of the near-end user n using the ipSIC mechanism is obtained through theoretical derivation:

[0135]

[0136] in, When ρ→∞, by using the first term of the incomplete gamma function series form, the approximate expression of the outage probability of near-end user n using the pSIC mechanism is obtained:

[0137]

[0138] Similarly, when ρ→∞, by using the first term of the incomplete gamma function series form, the approximate expression for the outage probability of near-end user n using the pSIC mechanism is obtained as

[0139]

[0140] Specifically, step seven specifically includes: according to the mathematical definition of the diversity order

[0141]

[0142] Substituting formulas (12), (13) and (14) into (15), we can deduce that the diversity order of near-end user n in the cascaded Ricean channel using the ipSIC / pSIC mechanism is: and the diversity order of remote user m is equal to

[0143] Specifically, step eight specifically includes: the traversal rates of the near-end user n using the ipSIC / pSIC mechanism are defined as

[0144]

[0145]

[0146] The traversal rate of remote user m is defined as

[0147]

[0148] Specifically, step nine includes: through theoretical derivation, the ergodic rate expressions of the near-end user n under the ipSIC / pSIC mechanism are obtained as follows:

[0149]

[0150]

[0151] in, Ω I The channel power of the interference signal when it is ipSIC.

[0152] The ergodic rate expression of remote user m is obtained through theoretical derivation:

[0153]

[0154] Specifically, step ten includes: by introducing Jensen's inequality

[0155]

[0156] We further derive the upper bound of the traversal rate of the near-end user n

[0157]

[0158] According to formula (18), when ρ→∞, the ergodic rate of remote user m under high signal-to-noise ratio is derived as

[0159] Specifically, step 11 specifically includes: the ergodic rate slope is a key parameter for determining the ergodic rate under high signal-to-noise ratio conditions, and the corresponding definition expression is expressed as:

[0160]

[0161] By substituting formulas (23) and (24) into (25), it is deduced that the high SNR ergodic rate slope of the near-end user n under the pSIC mechanism in the cascaded Ricean channel is 1, and the high SNR ergodic rate slope of the far-end user m is 0. Due to the influence of interference factors, the ergodic rate of the near-end user n under the ipSIC mechanism approaches a constant under high SNR conditions, so its high SNR ergodic rate slope is 0.

[0162] This application proposes a NOMA communication system based on a simultaneous transmission and reflection metasurface, which specifically includes a base station, a simultaneous transmission and reflection intelligent metasurface, and two non-orthogonal users. The following simulation verifies the interruption probability and traversal rate performance of a NOMA communication system based on a simultaneous transmission and reflection intelligent metasurface involved in this application. The power factors of its remote user m and near-end user n are set to a m =0.8 and a n =0.2, the target rates are set to R m =0.01BPCU and R n = 0.01BPCU; set the normalized distances from the base station to the smart super surface, from the smart super surface to user n and user m, and from the base station to user n to d sr =d rn =d rm =d sn =0.5, and the loss factor α is set to α=2.

[0163] In the NOMA communication system based on simultaneous transmission and reflection metasurfaces, the outage probability of user n using the ipSIC / pSIC mechanism is calculated according to equations (9) and (10), and the outage probability of remote user m is calculated according to equation (11). The total outage event of the system is defined as the complementary event that no outage occurs to either user. The total outage probability of the system is expressed as: P t =1-(1-P n,pSIC )(1-P m ), so as to make Figure 2 .from Figure 2 It can be seen that the total system interruption performance of the NOMA communication system with simultaneous transmission and reflection metasurface is better than that of the traditional decoding and forwarding relay, amplification and forwarding relay, and OMA communication system with simultaneous transmission and reflection metasurface. Figure 2 It can also be seen that the interruption performance of the near-end user n using the pSIC mechanism is better than that of the ipSIC. The main reasons for these phenomena are: (1) For multiple users, the NOMA communication system based on the simultaneous transmission and reflection metasurface achieves better user fairness than the OMA system; (2) The full-duplex decoding and forwarding relay is affected by the loop interference signal, so it needs to use advanced loop interference elimination technology and the cost is high; (3) Compared with the decoding and forwarding relay working in half-duplex mode, the NOMA communication system of the simultaneous transmission and reflection metasurface works in full-duplex mode and is not affected by loop interference, and has higher spectrum efficiency; (4) Under the ipSIC mechanism, the performance is worse than that under the pSIC mechanism due to the influence of interference and other factors.

[0164] Figure 3 The influence of different Ricean factors on the user interruption performance of the NOMA communication system based on simultaneous transmission and reflection metasurfaces is presented. From the results, it can be seen that as the Ricean factor increases, the interruption performance of the system becomes better and better. This phenomenon is explained by the fact that under the conditions of cascaded Ricean channels, as the direct component of the Ricean channel becomes larger and the channel conditions become better, the user's received signal-to-noise ratio becomes larger, which brings better interruption performance to the near-end user n and the far-end user m.

[0165] Figure 4 The influence of the NOMA communication system based on simultaneous transmission and reflection metasurface on the interruption performance of near-end user n and far-end user m under different numbers of smart metasurface units is presented. From the results, it is observed that as the number of smart metasurface units increases, the system can achieve better interruption performance. This phenomenon is caused by the fact that as the number of transmission and reflection smart metasurface units increases, the transmission channel gain becomes stronger, and the user's received signal-to-noise ratio becomes larger, which brings better interruption performance to near-end user n and far-end user m.

[0166] Figure 5The comparison of the traversal rate of the NOMA communication system based on the simultaneous transmission and reflection metasurface and the traversal rate of the OMA system is presented. From the comparison results in the figure, it can be seen that the traversal performance of the near-end user n in the NOMA system is stronger than that in the OMA system, while for the far-end user m, its traversal performance in the NOMA system is better at low signal-to-noise ratio. This phenomenon of the near-end user n is caused by the fact that the spectrum efficiency of the near-end user n in the NOMA system is higher than that of the near-end user n in the OMA system. For the far-end user m, this phenomenon is because in the NOMA system, the far-end user m directly regards the signal of the near-end user n as interference and directly decodes its own signal, so when the signal-to-noise ratio becomes larger and larger, the transmission rate of the far-end user m will reach an upper limit.

[0167] Finally, it should be noted that the above is only a preferred example of the present application and is not intended to limit the present application. Although the present application is described in detail with reference to the aforementioned embodiments, it is still possible for a person skilled in the art to modify the technical solutions described in the aforementioned embodiments or to replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A design method for a NOMA communication system based on a simultaneous transmission and reflection metasurface, characterized in that: The following steps are involved: Step 1: Establish a NOMA communication system model based on simultaneous transmission and reflection metasurfaces, and write the received signal expressions of near-end user n and far-end user m; Step 2: Write the non-ideal / ideal serial interference removal mechanism for near-end user n (imperfect / perfect Successive Interference Cancellation, ipSIC / pSIC) First detect the signal of the remote user m and delete it, then write out the signal interference and noise ratio of the near-end user n detecting its own signal, and finally the remote user m directly regards the signal of the near-end user n as interference to decode its own signal; Step 3: Use coherent phase shift to process the phase shift of the simultaneously transmitting and reflecting smart metasurface, and use the first term of the Laguerre series to approximate the distribution of the cascaded Ricean channels; Step 4: Define the interruption event of the near-end user n in the NOMA communication system based on the simultaneous transmission and reflection metasurface using the ipSIC / pSIC mechanism and the interruption event of the far-end user m; Step 5: Write the closed-form solution expression of the outage probability of the near-end user n under the cascaded Ricean channel using the ipSIC / pSIC mechanism and the closed-form solution expression of the outage probability of the far-end user m; Step 6: Further write out the approximate expression of the outage probability of the near-end user n under high signal-to-noise ratio using the ipSIC / pSIC mechanism and the approximate expression of the outage probability of the far-end user m; Step 7: Write down the diversity order of near-end user n using ipSIC / pSIC mechanism and the diversity order of far-end user m under cascaded Ricean channel; Step 8: Define the ergodic rate of the near-end user n and the ergodic rate of the far-end user m in the NOMA communication system based on the simultaneous transmission and reflection metasurface using the ipSIC / pSIC mechanism; Step 9: Write the ergodic rate expression of the near-end user n under the cascaded Riceic channel using the ipSIC / pSIC mechanism and the ergodic rate expression of the remote user m; Step 10: Further write the upper bound of the ergodic rate of the near-end user n when using the pSIC mechanism, and the ergodic rate expression of the far-end user m under high signal-to-noise ratio; Step 11: Write out the high signal-to-noise ratio ergodic rate slope of the near-end user n under the ipSIC / pSIC mechanism and the high signal-to-noise ratio ergodic rate slope of the far-end user m; Among them, step 1 specifically includes: the communication system specifically includes a base station, a simultaneously transmitting and reflecting smart metasurface and two non-orthogonal users, the near-end user n simultaneously receives the signal sent from the base station to the smart metasurface and then reflected, and the signal sent by the base station through a direct link; the far-end user m only receives the signal sent from the base station to the smart metasurface and then transmitted; The simultaneous transmission and reflection smart metasurface includes 2K units, where K represents an arbitrary positive integer. All channels are modeled as Rice fading channels and the influence of large-scale fading is considered at the same time. represents the complex channel coefficient matrix from the base station to the smart metasurface, represents the complex channel coefficient from the base station to the kth element of the smart metasurface, where 1≤k≤K, and It obeys a complex Gaussian distribution with a mean of 0 and a variance of 1, that is represents the large-scale fading from the base station to the smart metasurface, α and η are the path loss factor and frequency factor respectively, κ is the Rice factor, and d sr is the distance from the base station to the smart metasurface; represents the complex channel coefficient matrix from the smart metasurface to user n, represents the complex channel coefficient from the kth element of the smart metasurface to user n, It obeys a complex Gaussian distribution with a mean of 0 and a variance of 1, that is represents the large-scale fading from the smart metasurface to user n, d rn is the distance from the smart metasurface to user n; represents the complex channel coefficient matrix from the smart metasurface to user m, represents the complex channel coefficient from the kth element of the smart metasurface to user m, represents the large-scale fading from the smart metasurface to user m, d rm is the distance from the smart metasurface to user m; represents the complex channel coefficient from the base station to the near-end user n, It obeys a complex Gaussian distribution with a mean of 0 and a variance of 1, that is represents the large-scale fading from the base station to user n, d sn is the distance from the base station to user n, and the reflection and transmission characteristics of the smart metasurface are respectively expressed by a diagonal matrix and To reflect, and denote the reflection and transmission amplitude characteristics of the kth smart metasurface unit, respectively, and Among the 2K smart metasurface units, K units There are K units and denote the reflection phase shift and transmission phase shift of the kth smart metasurface unit respectively; then, the received signal expression at the near-end user n is expressed as At the same time, the received signal expression at the remote user m is expressed as Among them, a n ≤a m , and are Gaussian white noise at user m and user n respectively; Step 2 specifically includes: According to the NOMA decoding order criterion, the corresponding signal to noise ratio when the near-end user n decodes the signal of the far-end user m is expressed as Where ρ = P s / N0 represents the transmit signal-to-noise ratio, N0 represents the noise power, And when and indicates that the near-end user n uses the pSIC and ipSIC mechanisms, respectively. I | 2 is the channel gain corresponding to the interference signal caused by the near-end user n using ipSIC, h I :CN(0,1); For near-end user n, the signal-to-interference-noise ratio after using the SIC mechanism to delete the signal of far-end user m is expressed as For the remote user m, the signal of the near-end user n is directly regarded as interference to decode its own signal. At this time, the corresponding detection signal-to-interference-to-noise ratio is expressed as: Step 3 specifically includes: From the application perspective, continuously changing the amplitude and phase of the reflection unit of the smart metasurface is beneficial to enhancing network performance, but it requires precise design and expensive hardware architecture, which brings high costs to the deployment of the smart metasurface. For this reason, the cascade channel gains of user n and user m are defined as: in and They represent the reflection phase shift and transmission phase shift of the kth smart metasurface unit respectively. Through the coherent phase shift design, the phase shift of the smart metasurface matches the phase of the attenuation gain of the smart metasurface, and we get According to the two characteristics of the cascaded Ricean channel, namely: ① the probability density function of the cascaded Ricean channel has a single maximum value; ② the probability density function of the cascaded Ricean channel extends to infinity on both sides of the maximum value, the probability density function expression of the cascaded Ricean channel can be obtained by approximating the first term of the Laguerre series: Among them, υ∈(m,n) represents the user set, υ=m represents user m, υ=n represents user n, α rυ ∈(α rn ,α rm )， K0(·) and K1(·) are the 0th and 1st order modified Bessel functions, respectively, and Γ(·) is the gamma function; Step 4 specifically includes: the interruption compensation event at the near-end user n is interpreted as the near-end user n successfully decoding the signal of the remote user m, and then successfully decoding its own signal after deleting the signal of the remote user m using the SIC mechanism; therefore, based on formula (3) and formula (4), the interruption event of the near-end user n is defined by a mathematical expression as follows: in, R ν Indicates the user ν detection signal x ν Target rate at ; The interruption event at the remote user m is interpreted as the inability of user m to detect the interruption of its own information; therefore, based on formula (5), the interruption event of the remote user m is defined by a mathematical expression as Step 5 specifically includes: setting υ in formula (6) to n and substituting it into formula (7) to calculate the interruption probability expressions of user n under the ipSIC / pSIC mechanism: in, represents the weighting coefficient of Gauss-Laguerre integral, x p is the Laguerre polynomial L P (x p ), P and U represent the trade-off parameters between complexity and accuracy, Set υ in formula (6) to m and substitute it into formula (8), and the outage probability expression of remote user m in the cascaded Ricean channel is calculated as follows: Among them, γ(·) is the incomplete gamma function; Step 6 specifically includes: when ρ→∞ in formula (9), the approximate expression of the interruption probability of the near-end user n using the ipSIC mechanism is calculated as in, express and The larger of the two; When ρ→∞, using the first term of the incomplete gamma function series form, the approximate expression for the outage probability of near-end user n using the pSIC mechanism is obtained as follows: When ρ→∞, using the first term of the incomplete gamma function series form, the approximate expression for the outage probability of remote user m is obtained as follows: Step 7 specifically includes: According to the mathematical definition of the diversity order Substituting formulas (12), (13), and (14) into (15), we can calculate that the diversity order of the near-end user n in the cascaded Ricean channel is 0 when using the ipSIC mechanism, and is 0 when using the pSIC mechanism. And the diversity order of remote user m is Step 8 specifically includes: the traversal rates of the near-end user n using the ipSIC / pSIC mechanism are defined as The traversal rate of remote user m is defined as Step nine specifically includes: Based on formula (16), the ergodic rate expression of the near-end user n using the ipSIC mechanism is calculated as follows: Based on formula (17), the ergodic rate expression of the near-end user n using the pSIC mechanism is: in, Ω I The channel power of the interference signal when it is ipSIC; Based on formula (18), the ergodic rate expression of remote user m is calculated as follows: Step 10 specifically includes: By introducing Jensen's inequality, the upper bound of the traversal rate of user n is Further calculations show that the upper bound of the traversal rate of the near-end user n is According to formula (18), when the sending signal-to-noise ratio ρ→∞, the ergodic rate of the remote user m under high signal-to-noise ratio is calculated as Step 11 specifically includes: the ergodic rate slope is a key parameter for determining the ergodic rate performance under high signal-to-noise ratio conditions, and the ergodic rate slope expression is defined as: Substituting formulas (23) and (24) into (25), we can calculate that the ergodic rate slope of the near-end user n under the pSIC mechanism is 1, and the ergodic rate slope of the far-end user m is 0.

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