Transmissive-reflective intelligent reflector-assisted non-orthogonal multiple access short packet communication method

Abstract

A short packet communication method for non-orthogonal multiple access assisted by a transmissive-reflective intelligent reflective surface, in which a base station sends short data packets to two users in a downlink two-user non-orthogonal multiple access system to achieve high-reliability and low-latency communication, and both users achieve high-reliability and low-latency communication with the users through the transmissive-reflective intelligent reflective surface-assisted base station with n passive units. First, given the statistical channel state information, the statistical characteristics of the end-to-end channel from the base station to the two users when the transmissive-reflective intelligent reflective surface adopts the optimal continuous phase adjustment strategy and the discrete phase adjustment strategy are determined; secondly, according to the maximum achievable rate calculation formula for short packet communication, the average block error rate of the two users in a fading channel is determined; finally, under certain reliability constraints, the optimal power allocation factor, optimal transmissive-reflective coefficient and minimum common block length of the system are determined. The present invention maximizes the use of communication resources to achieve high-reliability and low-latency communication.

Description

Technical Field

[0001] The invention relates to a transmissive-reflective intelligent reflecting surface (STAR-IRS) assisted non-orthogonal multiple access (NOMA) short packet communication method, belonging to the technical field of wireless communication. Background Art

[0002] Ultra-Reliable and Low-Latency Communication (URLLC) has become one of the major challenges facing the future wireless communication field. Many industrial control, traffic safety, medical and Internet services rely on wireless connections with latency of 1 millisecond or less and extremely high reliability. How to implement URLLC is still a difficult and hot topic in the design of wireless communication systems. URLLC requires end-to-end latency of milliseconds and extremely high reliability (block error rate of 10 -3 ~10 -9 ) (See the document H.Chen, R.Abbas, et al., "Ultra-reliable low latency cellular networks: Use cases, challenges and approaches," IEEE Commun.Mag., vol.56, no.12, pp.119–125, Dec. 2018.).

[0003] With the rapid development of artificial electromagnetic materials, the intelligent reflecting surface (IRS) based on metamaterials is considered to be one of the most promising and revolutionary technologies in the sixth generation of mobile communication technology. It is composed of many low-cost passive reflecting units. Its principle is to reconfigure the wireless propagation environment through software-controlled reflection. However, the traditional reflective intelligent reflecting surface can only reflect the incident signal alone, that is, the base station and the user must be located on the same side of the IRS, which greatly reduces the coverage of the IRS. In order to overcome this limitation, a new type of IRS that can transmit and reflect signals at the same time has been recently proposed. It is called STAR (Simultaneously Transmitting and Reflecting)-IRS. The core of STAR-IRS is that it can simultaneously reflect and transmit the incident signal to the users on the same side and the opposite side of the transmitting signal source, thereby achieving full coverage of the range. Non-orthogonal multiple access technology, short packet communication and intelligent reflecting surface technologies are all regarded as key physical layer technologies for the implementation of URLLC in the new generation of wireless communication systems. The literature (Y.Yu, H.Chen, et al. "On the performance of non-orthogonal multiple access in short-packet communications," IEEE Commun.Lett., vol.22, no.3, pp.590-593, Mar.2018.) studied the implementation method of combining non-orthogonal multiple access and short packet communication under Rayleigh fading channels. The literature (B.Zhao, C.Zhang, et al., "Ergodic rate analysis of STAR-RIS aided NOMAsystems," IEEE Commun.Lett., vol.26, no.10, pp.2297–2301, Oct.2022.) studied the implementation method of combining STAR-IRS with non-orthogonal multiple access. Both of the above literatures are designs based on instantaneous channel state information. In the STAR-IRS-assisted wireless communication system, due to the large number of passive reflection and transmission elements of STAR-IRS, it is very difficult to accurately obtain the instantaneous channel state information of the system in real time, while it is easier to obtain statistical channel state information in engineering practice. Therefore, the present invention is designed based on the known statistical channel state information of the system.

[0004] At present, there is no report on how to use statistical channel state information to design a short packet communication system combining STAR-IRS and non-orthogonal multiple access technology to realize URLLC. Therefore, it is necessary to study the implementation method of STAR-IRS assisted non-orthogonal multiple access short packet communication system based on statistical channel state information. Summary of the invention

[0005] The present invention provides a transmissive-reflective intelligent reflector-assisted non-orthogonal multiple access short packet communication method to achieve highly reliable and low-delay communication URLLC.

[0006] The objective of the present invention is achieved through the following technical solutions:

[0007] A transmissive-reflective intelligent reflective surface-assisted non-orthogonal multiple access short packet communication method, the implementation steps of which are as follows:

[0008] Step A, establishing a STAR-IRS-assisted downlink two-user non-orthogonal multiple access system;

[0009] Step B: According to the system model established in step A, the received signals of the two users are derived and analyzed; according to the statistical channel state information, the order of continuous interference elimination is determined, and the instantaneous signal-to-noise ratio (SNR) is further written;

[0010] Step C: According to the channel parameters, the number of STAR-IRS units n, and the STAR-IRS based on the statistical channel state information, optimal continuous phase adjustment or q l (l∈{t,r}) bit quantization discrete phase adjustment conditions are analyzed to give the distribution characteristics of the end-to-end channels of the two users;

[0011] Step D, respectively calculating the average block error rate (BLER) expressions of the two users according to the formula in the short packet communication;

[0012] Step E: Based on the expression calculated in step D, under reliability constraints, the relationship between the average BLER and the optimal power allocation factor, the optimal transmittance and reflection coefficient and the minimum common block length is further obtained through the bisection method and the one-dimensional traversal search algorithm.

[0013] Furthermore, the specific implementation of step A is as follows:

[0014] A1, construct a downlink two-user non-orthogonal multiple access system consisting of a single-antenna base station (BS), two single-antenna user equipments and a STAR-IRS with n passive units. UE-r is a user deployed in the reflection space of the STAR-IRS, and UE-t is a user deployed in the transmission space of the STAR-IRS.

[0015] A2, modeling channel coefficient: The channel coefficient includes two parts: path loss related to propagation distance and small-scale fading. The channel coefficient from the base station to the i-th (i=1,...,n) unit of STAR-IRS is Channel coefficients from STAR-IRS unit i to UE-r Channel coefficients from STAR-IRS ith unit to UE-t Where d0 represents the distance from the base station to the center of STAR-IRS, d r d t They represent the distances from the center of STAR-IRS to UE-r and UE-t, respectively, and β represents the corresponding path loss index; and To normalize the small-scale fading, it can be expressed as Where K0 and K l is the corresponding Rice factor, and is the corresponding line-of-sight transmission component, and is the corresponding non-line-of-sight transmission component, which obeys a cyclically symmetric complex Gaussian distribution with a mean of 0 and a variance of 1. Let h l is the end-to-end channel coefficient between the base station and the user, make represents the reflection and transmission amplitude coefficients introduced by STAR-IRS. According to the energy conservation law ξ t +ξ r =1; represents the transmission and reflection phase shifts introduced by the i-th unit of STAR-IRS, which can be adjusted independently; is the adjustment coefficient of the i-th STAR-IRS unit for UE-1.

[0016] Furthermore, the specific implementation of step B is as follows:

[0017] Assume that the total transmission power of the base station is P s , the transmission power allocated to UE-r and UE-t is denoted as α r P s and α t P s , where α lis the power allocation factor of UE-1, and satisfies α r +α t =1;

[0018] The signal received by UE-r and UE-t can be expressed as

[0019]

[0020] in x l are the signals corresponding to the two users respectively, The mean is 0 and the variance is σ 2 Complex additive Gaussian white noise; using statistical channel state information, Represents the phase error introduced by different phase adjustment strategies; when the optimal continuous phase adjustment strategy is adopted, When q is used for UE-1 l When the discrete phase adjustment strategy of bit quantization is used, obey uniform distribution, arg(·) represents the complex angle function;

[0021] make Then the channel gain can be expressed as |h l | 2 =ξ l (d0d l ) -β |H l | 2 According to the basic principle of non-orthogonal multiple access, when the end-to-end channel between two users satisfies E(|h r | 2 )>E(|h t | 2 ) is the transmission coefficient ξ t ∈(0,P), where Otherwise the transmission coefficient ξ t ∈(P,1),α r >0.5. Where |·| represents the modulus of a complex number or the absolute value of a real number, and E(·) represents the mean;

[0022] After receiving the signal, UE-t will r Treating it as noise, UE-t recovers x t The instantaneous SNR is After receiving the signal, UE-r first r Treat it as noise and recover x t UE-r recovers x t The instantaneous SNR is When UE-r correctly eliminates x through serial interference cancellation technology tAfter the interference, UE-r recovers x r The instantaneous SNR is γ r,r =ρα r ξ r (d0d r ) -β |H r | 2 , where ρ = P s / σ 2 Indicates the transmission SNR.

[0023] Furthermore, the specific implementation of step C is as follows:

[0024] The channel gain from the base station to the two users is |h l | 2 , according to step B, |h l | 2 =ξ l (d0d l ) -β |H l | 2 In order to determine the channel gain from the base station to the two users, H must first be determined. l , H l It obeys a non-cyclically symmetric complex Gaussian distribution, that is, H l =U l +jV l , where U l 、V l is a real Gaussian random variable;

[0025] 1. When the optimal continuous phase adjustment is adopted, that is When U l The mean value of U l The variance of V l The mean value of V l The variance of

[0026] 2. When using q l Discrete phase adjustment of bit quantization (i.e., quantization error in the interval When U l The mean value of U l The variance of

[0027]

[0028] V l The mean value of V l The variance of

[0029]

[0030] |H l | 2 Finally, it can be expressed as Then |H l | 2 The first and second moments of

[0031]

[0032]

[0033] Using the moment matching method, |H l | 2 Matched into a gamma distribution, that is, its probability density function is:

[0034]

[0035] in:

[0036] Furthermore, the specific implementation of step D is as follows:

[0037] When the signal-to-noise ratio γ, the short data packet block length L and the short data packet BLER ε are given, the maximum achievable rate of short data packets (in bits per symbol) can be approximately expressed as:

[0038]

[0039] Among them, Shannon capacity formula C(γ) = log2(1+γ), channel divergence Q -1 (·)express The inverse function of

[0040] Assume N l and L l is the number of information bits and block length of UE-1, then the physical layer information rate of UE-1 can be expressed as UE-t restore x t The instantaneous BLER is UE-r restore x t The instantaneous BLER is UE-r uses serial interference cancellation technology to correctly eliminate x t After the interference, UE-r recovers x r The instantaneous BLER is Due to ε r,t is a very small value, so the overall instantaneous BLERε of UE-r r is r =ε r,t+(1-ε r,t )ε r,r ≈ε r,t +ε r,r ; UE-t overall instantaneous BLERε t is t =ε t,t ;

[0041] D2. Average BLER in fading channel based on instantaneous BLER and instantaneous SNR It is expressed as:

[0042]

[0043] in For γ l,j The probability density function of; According to the literature (L.Yuan, N.Yang, et al., "Averageblock error rate of intelligent reflecting surface aided short-packetcommunications," 2022, techrxiv.20372676.), It can be approximated as Z l,j (γ l,j )

[0044]

[0045] in R j =N j / L j ;

[0046] Average BLER in fading channels It can be further expressed as:

[0047]

[0048] in For γ l,j The cumulative distribution function of the formula is obtained by partial integration. Since the block length is small in short packet communication, we can get κ by analysis. j is small enough, so we use the first-order Riemann approximation Further, we get the expression of average BLER in the formula in

[0049] So the average BLER of UE-r and UE-t is:

[0050]

[0051]

[0052] in

[0053] Furthermore, the specific implementation of step E is as follows:

[0054] We express the target BLER of the two users as Determine the optimal power allocation factor, the minimum common block length, and the optimal transflection coefficient. The specific steps for determining the optimal power allocation factor, the minimum common block length, and the optimal transflection coefficient are as follows:

[0055] 1.1 Under given system parameters such as transmittance and reflection coefficient, power allocation factor, if ξ t ∈(0,P), then 0<α r <0.5; otherwise, 0.5<α r <1; Initialize the block length and limit the block length to [M min ,M max ], let L - ←M min , L + ←M max ;

[0056] 1.2 L - , L + Substitute into the average BLER formula to calculate the corresponding average BLER of the two users

[0057] 1.3 If the calculated average BLER satisfies or Let the minimum block length be L min =-1, which means there is no optimal solution in this case;

[0058] 1.4 If the calculated average BLER satisfies both and Then let the minimum block length L min =M min ;

[0059] 1.5 If none of the above conditions are met, then + -L - ≠1, let Calculate the corresponding average BLER and represents the ceiling function;

[0060] 1.6 When satisfied and Then Otherwise,

[0061] 1.7 Update L - or L + , continue steps 1.5 to 1.6 until L + -L - =1 to stop iteration, minimum block length L min =L + ;

[0062] 1.8 Under a given transflection coefficient, select a step size of δ to traverse α r Repeat steps 1.1 to 1.7 to obtain the block length L corresponding to each power allocation factor. min , then the minimum block length The corresponding power allocation factor is the optimal power allocation factor min(·) means calculating the minimum element in an array;

[0063] 1.9 Choose a step size of δ to traverse ξ t Repeat steps 1.1 to 1.8 to obtain the corresponding transmission coefficient of each transmission coefficient. Then the minimum common block length under the traversal transmission coefficient The corresponding transmission coefficient is the optimal transmission coefficient

[0064] Compared with reflective IRS, STAR-IRS not only expands the deployment range of intelligent reflective surfaces, making system design more flexible, but also significantly improves the communication quality of users and reduces system power consumption. The present invention studies the optimal performance that the system can achieve by reasonably allocating power under a certain total power condition, while considering the channel characteristics of STAR-IRS and the influence of different phase adjustment strategies on the minimum common block length and the optimal reflection coefficient. With the reduction of block length, the system delay is effectively reduced.

[0065] The present invention uses statistical channel state information to design a STAR-IRS-assisted non-orthogonal multiple access short packet communication system for the first time. The end-to-end channel statistical characteristic distribution of the STAR-IRS-assisted non-orthogonal multiple access short packet system is obtained through analysis, and then the average block error rate expression of the two users is derived. Under the constraint of satisfying the reliability of user transmission information, the optimal power allocation factor, minimum common block length and optimal reflection coefficient of the system are obtained. URLLC is realized by jointly optimizing various resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 is the system model of the present invention;

[0067] Figure 2 It is a logic flow chart of the present invention;

[0068] Figure 3 The present invention adopts q l =1 bit quantization of the relationship between the minimum common block length and the optimal power allocation factor when discrete phase adjustment is performed, where K0 = K r =K t =5,d0=60,d r =30,d t =55,P s =1,β=2, L r =L t =200, N r =N t =300,ρ=48dB,ξ t =0.2,q r =q t =1;

[0069] Figure 4 The present invention adopts q l =1 bit quantization discrete phase adjustment when the minimum common block length and the optimal transmission coefficient, where K0 = K r =K t =5,d0=60,d r =30,d t =55,P s =1,β=2, L r =L t =200, N r =N t =300, ρ=48dB, ρ=48dB, q r =q t =1. DETAILED DESCRIPTION

[0070] The present invention will be further described below from both theoretical and practical aspects in conjunction with the accompanying drawings.

[0071] A transmissive-reflective intelligent reflective surface-assisted non-orthogonal multiple access short packet communication method, the specific implementation steps are as follows:

[0072] Step A, establishing a STAR-IRS-assisted downlink two-user non-orthogonal multiple access system;

[0073] Step B: deriving and analyzing the received signals of the two users based on the system model established in step A;

[0074] According to the statistical channel state information, the order of continuous interference elimination is determined, and the instantaneous SNR is further written;

[0075] Step C: According to the channel parameters, the number of STAR-IRS units n, and the STAR-IRS based on the statistical channel state information, optimal continuous phase adjustment or q l The bit quantization discrete phase adjustment conditions are analyzed to give the distribution characteristics of the end-to-end channel of two users;

[0076] Step D, respectively calculating the average BLER expressions of the two users according to the formula in the short packet communication;

[0077] Step E: Based on the expression calculated in step D, under reliability constraints, the relationship between the average block error rate and the optimal power allocation factor, the optimal transmission reflection coefficient and the minimum common block length is further obtained through the bisection method and the one-dimensional traversal search algorithm.

[0078] Wherein, step A specifically includes:

[0079] A1, construct a downlink two-user non-orthogonal multiple access system consisting of a single-antenna base station (BS), two single-antenna user equipments and a STAR-IRS with n passive units. UE-r is a user deployed in the reflection space of the STAR-IRS, and UE-t is a user deployed in the transmission space of the STAR-IRS.

[0080] A2, modeling channel coefficient: The channel coefficient includes two parts: path loss related to propagation distance and small-scale fading. The channel coefficient from the base station to the i-th (i=1,...,n) unit of STAR-IRS is Channel coefficients from STAR-IRS unit i to UE-r Channel coefficients from STAR-IRS ith unit to UE-t Where d0 represents the distance from the base station to the center of STAR-IRS, d r d t They represent the distances from the center of STAR-IRS to UE-r and UE-t, respectively, and β represents the corresponding path loss index; and To normalize the small-scale fading, it can be expressed as

[0081] Where K0 and K l is the corresponding Rice factor, and is the corresponding line-of-sight transmission component, and is the corresponding non-line-of-sight transmission component, which obeys a cyclically symmetric complex Gaussian distribution with a mean of 0 and a variance of 1. Let h l is the end-to-end channel coefficient between the base station and the user, make represents the reflection and transmission amplitude coefficients introduced by STAR-IRS. According to the energy conservation law ξ t +ξ r =1; represents the transmission and reflection phase shifts introduced by the i-th unit of STAR-IRS, which can be adjusted independently; is the adjustment coefficient of the i-th STAR-IRS unit for UE-1.

[0082] Wherein, step B specifically includes:

[0083] Assume that the total transmission power of the base station is P s , the transmission power allocated to UE-r and UE-t is denoted as α r P s and α t P s , where α l is the power allocation factor of UE-1, and satisfies α r +α t =1;

[0084] The signal received by UE-r and UE-t can be expressed as

[0085]

[0086] in x l are the signals corresponding to the two users respectively, The mean is 0 and the variance is σ 2 Complex additive Gaussian white noise; using statistical channel state information, Represents the phase error introduced by different phase adjustment strategies; when the optimal continuous phase adjustment strategy is adopted, When q is used for UE-1 l When the discrete phase adjustment strategy of bit quantization is used, obey uniform distribution, arg(·) represents the complex angle function;

[0087] make Then the channel gain can be expressed as |h l | 2 =ξ l (d0d l ) -β |H l | 2According to the basic principle of non-orthogonal multiple access, when the end-to-end channel between two users satisfies E(|h r | 2 )>E(|h t | 2 ) is the transmission coefficient ξ t ∈(0,P), where Otherwise the transmission coefficient ξ t ∈(P,1),α r >0.5. Where |·| represents the modulus of a complex number or the absolute value of a real number, and E(·) represents the mean;

[0088] After receiving the signal, UE-t will r Treating it as noise, UE-t recovers x t The instantaneous SNR is After receiving the signal, UE-r first r Treat it as noise and recover x t UE-r recovers x t The instantaneous SNR is When UE-r correctly eliminates x through serial interference cancellation technology t After the interference, UE-r recovers x r The instantaneous SNR is γ r,r =ρα r ξ r (d0d r ) -β |H r | 2 , where ρ = P s / σ 2 Indicates the transmission SNR.

[0089] Wherein, step C specifically includes:

[0090] The channel gain from the base station to the two users is |h l | 2 , according to step B, |h l | 2 =ξ l (d0d l ) -β |H l | 2 In order to determine the channel gain from the base station to the two users, H must first be determined. l , H l It obeys a non-cyclically symmetric complex Gaussian distribution, that is, H l =U l +jV l , where U l 、V l is a real Gaussian random variable;

[0091] 1. When the optimal continuous phase adjustment is adopted, that is When U l The mean value of U l The variance of V l The mean value of V l The variance of

[0092] 2. When using q l Discrete phase adjustment of bit quantization (i.e., quantization error in the interval When U l The mean value of U l The variance of

[0093] V l The mean value is μ Vl =0, V l The variance of

[0094]

[0095] |H l | 2 Finally, it can be expressed as Then |H l | 2 The first and second moments of

[0096]

[0097]

[0098] Using the moment matching method, |H l | 2 Matched into a gamma distribution, that is, its probability density function is:

[0099]

[0100] in:

[0101] Wherein, step D specifically comprises:

[0102] When the signal-to-noise ratio γ, the short data packet block length L and the short data packet BLER ε are given, the maximum achievable rate of short data packets (in bits per symbol) can be approximately expressed as:

[0103]

[0104] Among them, Shannon capacity formula C(γ) = log2(1+γ), channel divergence Q -1 (·)express The inverse function of

[0105] Assume N l and L l is the number of information bits and block length of UE-1, then the physical layer information rate of UE-1 can be expressed as UE-t restore x t The instantaneous BLER is UE-r restore x t The instantaneous BLER is UE-r uses serial interference cancellation technology to correctly eliminate x t After the interference, UE-r recovers x r The instantaneous BLER is Due to ε r,t is a very small value, so the overall instantaneous BLERε of UE-r r is r =ε r,t +(1-ε r,t )ε r,r ≈ε r,t +ε r,r ; UE-t overall instantaneous BLERε t is t =ε t,t ;

[0106] D2. Average BLER in fading channel based on instantaneous BLER and instantaneous SNR It is expressed as:

[0107]

[0108] in For γ l,j The probability density function of; According to the literature (L.Yuan, N.Yang, et al., "Averageblock error rate of intelligent reflecting surface aided short-packetcommunications," 2022, techrxiv.20372676.), It can be approximated as Z l,j (γ l,j )

[0109]

[0110] in R j =Nj / L j ;

[0111] Average BLER in fading channels It can be further expressed as:

[0112]

[0113] in For γ l,j The cumulative distribution function of the formula is obtained by partial integration. Since the block length is small in short packet communication, we can get κ by analysis. j is small enough, so we use the first-order Riemann approximation Further, we get the expression of average BLER in the formula in

[0114] So the average BLER of UE-r and UE-t is:

[0115]

[0116]

[0117] in

[0118] Wherein, step E specifically includes:

[0119] We express the target BLER of the two users as Determine the optimal power allocation factor, the minimum common block length, and the optimal transflection coefficient. The specific steps for determining the optimal power allocation factor, the minimum common block length, and the optimal transflection coefficient are as follows:

[0120] 1.1 Under given system parameters such as transmittance and reflection coefficient, power allocation factor, if ξ t ∈(0,P), then 0<α r <0.5; otherwise, 0.5<α r <1; Initialize the block length and limit the block length to [M min ,M max ], let L - ←M min , L + ←M max ;

[0121] 1.2 L - , L + Substitute into the average BLER formula to calculate the corresponding average BLER of the two users

[0122] 1.3 If the calculated average BLER satisfies or Let the minimum block length be L min =-1, which means there is no optimal solution in this case;

[0123] 1.4 If the calculated average BLER satisfies both and Then let the minimum block length L min =M min ;

[0124] 1.5 If none of the above conditions are met, then + -L - ≠1, let Calculate the corresponding average BLER and represents the ceiling function;

[0125] 1.6 When satisfied and Then Otherwise,

[0126] 1.7 Update L - or L + , continue steps 1.5 to 1.6 until L + -L - =1 to stop iteration, minimum block length L min =L + ;

[0127] 1.8 Under a given transflection coefficient, select a step size of δ to traverse α r Repeat steps 1.1 to 1.7 to obtain the block length L corresponding to each power allocation factor. min , then the minimum block length The corresponding power allocation factor is the optimal power allocation factor min(·) means calculating the minimum element in an array;

[0128] 1.9 Choose a step size of δ to traverse ξ t Repeat steps 1.1 to 1.8 to obtain the corresponding transmission coefficient of each transmission coefficient. Then the minimum common block length under the traversal transmission coefficient The corresponding transmission coefficient is the optimal transmission coefficient The specific implementation process of the present invention is as follows:

[0129] A transmissive-reflective intelligent reflective surface-assisted non-orthogonal multiple access short packet communication method, the specific implementation steps are as follows:

[0130] Step A: Establish a STAR-IRS-assisted downlink two-user non-orthogonal multiple access system; the system includes a single-antenna base station, two single-antenna user equipments and a downlink two-user non-orthogonal multiple access system composed of a STAR-IRS with n=64 passive units. UE-r is a user deployed in the STAR-IRS reflection space, and UE-t is a user deployed in the STAR-IRS transmission space. The channel coefficient from the base station to the i-th unit of the STAR-IRS is Channel coefficients from STAR-IRS unit i to UE-r Channel coefficients from STAR-IRS ith unit to UE-t Where d0 represents the distance from the base station to the center of STAR-IRS, d r d t denote the distances from the STAR-IRS center to UE-r and UE-t, respectively, and d0 = 60, d r =30, d t =55; β represents the corresponding path loss index, β=2; and To normalize the small-scale fading, it can be expressed as Where K0 and K l is the corresponding Rice factor, K0=K r =K t =5, and is the corresponding line-of-sight transmission component, and is the corresponding non-line-of-sight transmission component, which obeys a cyclically symmetric complex Gaussian distribution with a mean of 0 and a variance of 1. Let h l is the end-to-end channel coefficient between the base station and the user, make represents the reflection and transmission amplitude coefficients introduced by STAR-IRS. According to the energy conservation law ξ t +ξ r =1; represents the transmission and reflection phase shifts introduced by the i-th unit of STAR-IRS, which can be adjusted independently; is the adjustment coefficient of the STAR-IRS ith unit to UE-1; where ξ t =(0,0.77), that is, P = 0.77.

[0131] Step B: Derived and analyzed the received signals of the two users based on the system model established in step A. The order of continuous interference elimination is determined based on the statistical channel state information, and the instantaneous SNR is further written out.

[0132] Step C: According to the channel parameters and the number of STAR-IRS units n, STAR-IRS performs optimal continuous phase adjustment or q based on the statistical channel state information. l The statistical characteristics of the end-to-end channel between two users are analyzed and given based on the conditions of discrete phase adjustment of bit quantization.

[0133] Step D: Calculate the average BLER expressions of the two users respectively according to the relevant formulas of the short packet communication.

[0134] Step E: Based on the expression calculated in step D, When the step size δ is 0.01, the relationship between the average BLER and the optimal power allocation factor, the optimal transmittance and reflection coefficient, and the minimum common block length is further obtained through the binary search algorithm and the one-dimensional traversal search algorithm.

[0135] Figure 3 Given n = 64 and ξ t = 0.2, STAR-IRS uses q l =1 bit quantized discrete phase adjustment when the optimal power allocation factor, the optimal power allocation factor at this time And the minimum common block length symbol, Figure 4 Given n = 64 STAR-IRS adopts q l =1 bit quantized discrete phase adjustment when the optimal reflection coefficient is the case. At this time, the optimal reflection coefficient Minimum common block length Symbol, when The optimal power allocation factor corresponding to when The optimal power allocation factor corresponding to It can be seen that the selection of power allocation factor and transmission reflection coefficient has a great influence on block length.

Claims

1. A transmissive-reflective intelligent reflective surface-assisted non-orthogonal multiple access short packet communication method, the implementation steps of which are as follows: Step A: Establish a transmissive-reflective intelligent reflecting surface (STAR-IRS) assisted downlink two-user non-orthogonal multiple access system; the specific implementation is as follows: A1, construct a downlink two-user non-orthogonal multiple access system consisting of a single-antenna base station, BS, two single-antenna user equipments and a STAR-IRS with n passive units. UE-r is a user deployed in the reflection space of the STAR-IRS, and UE-t is a user deployed in the transmission space of the STAR-IRS. A2, modeling channel coefficient: The channel coefficient includes two parts: path loss related to propagation distance and small-scale fading. The channel coefficient from the base station to the i-th (i=1,...,n) unit of STAR-IRS is Channel coefficients from STAR-IRS unit i to UE-r Channel coefficients from STAR-IRS ith unit to UE-t in, d0 represents the distance from the base station to the center of STAR-IRS, d l represents the distance between the center of STAR-IRS and UE-l, l∈{t,r}, β represents the corresponding path loss index; and To normalize the small-scale fading, it can be expressed as Where K0 and K l is the corresponding Rice factor, and is the corresponding line-of-sight transmission component, and is the corresponding non-line-of-sight transmission component, which obeys a cyclically symmetric complex Gaussian distribution with a mean of 0 and a variance of 1; let h l is the end-to-end channel coefficient between the base station and the user, make represents the reflection and transmission amplitude coefficients introduced by STAR-IRS. According to the energy conservation law ξ t +ξ r =1; represents the transmission and reflection phase shifts introduced by the i-th unit of STAR-IRS, which can be adjusted independently; is the adjustment coefficient of the i-th STAR-IRS unit for UE-1. Step B: According to the system model established in step A, the received signals of the two users are derived and analyzed; according to the statistical channel state information, the order of continuous interference elimination is determined, and the instantaneous signal-to-noise ratio Signal-to-Noise Ratio, SNR, is further written; Step C: According to the channel parameters, the number of STAR-IRS units n, and the STAR-IRS based on the statistical channel state information, optimal continuous phase adjustment or q l The bit quantization discrete phase adjustment conditions are analyzed to give the distribution characteristics of the end-to-end channel of two users; Step D, calculating the average block error rate Block Error Rate, BLER, of the two users respectively according to the formula in the short packet communication; Step E: Based on the expression calculated in step D, under reliability constraints, the relationship between the average BLER and the optimal power allocation factor, the optimal transmission reflection coefficient and the minimum common block length is further obtained through the bisection method and the one-dimensional traversal search algorithm.

2. According to the transmissive-reflective intelligent reflective surface assisted non-orthogonal multiple access short packet communication method of claim 1, the specific implementation of step B is as follows: Assume that the total transmission power of the base station is P s , the transmission power allocated to UE-r and UE-t is denoted as α r P s and α t P s , where α l is the power allocation factor of UE-1, and satisfies α r +α t =1; The signal received by UE-r and UE-t can be expressed as in x l are the signals corresponding to the two users respectively, The mean is 0 and the variance is σ 2 Complex additive Gaussian white noise; using statistical channel state information, Represents the phase error introduced by different phase adjustment strategies; when the optimal continuous phase adjustment strategy is adopted, When q is used for UE-1 l When the discrete phase adjustment strategy of bit quantization is used, obey uniform distribution, arg(·) represents the complex angle function; make Then the channel gain can be expressed as According to the basic principle of non-orthogonal multiple access, when the end-to-end channel between two users satisfies E(|h r | 2 )>E(|h t | 2 ) is the transmission coefficient ξ t ∈(0,P), where α r <0.5, otherwise the transmission coefficient ξ t ∈(P,1),α r >0.5; where |·| represents the modulus of a complex number or the absolute value of a real number, and E(·) represents the mean; After receiving the signal, UE-t will r Treating it as noise, UE-t recovers x t The instantaneous SNR is After receiving the signal, UE-r first r Treat it as noise and recover x t UE-r recovers x t The instantaneous SNR is When UE-r correctly eliminates x through serial interference cancellation technology t After the interference, UE-r recovers x r The instantaneous SNR is γ r,r =ρα r ξ r (d0d r ) -β |H r | 2 , where ρ = P s / σ 2 Indicates the transmission SNR.

3. According to the transflective-reflective intelligent reflective surface assisted non-orthogonal multiple access short packet communication method of claim 1, the specific implementation of step C is as follows: The channel gain from the base station to the two users is |h l | 2 , according to step B, |h l | 2 =ξ l (d0d l ) -β |H l | 2 ; In order to determine the channel gain from the base station to the two users, H must be determined first l , H l It obeys a non-cyclically symmetric complex Gaussian distribution, that is, H l =U l +jV l , where U l 、V l is a real Gaussian random variable; 1. When the optimal continuous phase adjustment is adopted, that is When U l The mean value of U l The variance of V l The mean value of V l The variance of 2. When using q l The discrete phase adjustment of bit quantization, that is, the quantization error in When the interval follows a uniform distribution, U l The mean value of U l The variance of V l The mean value of V l The variance of |H l | 2 Finally, it can be expressed as Then |H l | 2 The first and second moments of Using the moment matching method, |H l | 2 Matched into a gamma distribution, that is, its probability density function is: in:

4. According to the transflective-reflective intelligent reflective surface assisted non-orthogonal multiple access short packet communication method of claim 1, the specific implementation of step D is as follows: When the signal-to-noise ratio γ, the short data packet block length L and the short data packet BLER ε are given, the maximum achievable rate of short data packets, in bits per symbol, can be approximately expressed as: in, Shannon capacity formula C(γ) = log2(1+γ), channel divergence Q -1 (·)express The inverse function of Assume N l and L l is the number of information bits and block length of UE-1, then the physical layer information rate of UE-1 can be expressed as UE-t restore x t The instantaneous BLER is UE-r restore x t The instantaneous BLER is UE-r uses serial interference cancellation technology to correctly eliminate x t After the interference, UE-r recovers x r The instantaneous BLER is Due to ε r,t is a very small value, so the overall instantaneous BLERε of UE-r r is r =ε r,t +(1-ε r,t )ε r,r ≈ε r,t +ε r,r ; UE-t overall instantaneous BLERε t is t =ε t,t ; D2, according to the instantaneous BLER and instantaneous SNR, the average It is expressed as: in For γ l,j The probability density function of The average value of It can be further expressed as: in R j =N j / L j . in For γ l,j The cumulative distribution function of ; using the first-order Riemann approximation, the expression of the average BLER in the formula is further obtained in So the average BLER of UE-r and UE-t is: in 5. According to the transflective-reflective intelligent reflective surface assisted non-orthogonal multiple access short packet communication method of claim 1, the specific implementation of step E is as follows: We express the target BLER of the two users as Determine the optimal power allocation factor, the minimum common block length, and the optimal transflection coefficient. The specific steps for determining the optimal power allocation factor, the minimum common block length, and the optimal transflection coefficient are as follows: 1.1 Under given system parameters such as transmittance and reflection coefficient, power allocation factor, if ξ t ∈(0,P), then 0<α r <0.5; otherwise, 0.5<α r <1; Initialize the block length and limit the block length to [M min ,M max ], let L - ←M min , L + ←M max ; 1.2 L - , L + Substitute into the average BLER formula to calculate the corresponding average BLER of the two users 1.3 If the calculated average BLER satisfies or Let the minimum block length be L min =-1, which means there is no optimal solution in this case; 1.4 If the calculated average BLER satisfies both and Then let the minimum block length be L min =M min ; 1.5 If none of the above conditions are met, then + -L - ≠1, let Calculate the corresponding average BLER and represents the ceiling function; 1.6 When satisfied and Then Otherwise, 1.7 Update L - or L + , continue steps 1.5 to 1.6 until L + -L - =1 to stop iteration, minimum block length L min =L + ; 1.8 Under a given transflection coefficient, select a step size of δ to traverse α r Repeat steps 1.1 to 1.7 to obtain the block length L corresponding to each power allocation factor. min , then the minimum block length The corresponding power allocation factor is the optimal power allocation factor min(·) means calculating the minimum element in an array; 1.9 Choose a step size of δ to traverse ξ t Repeat steps 1.1 to 1.8 to obtain the corresponding transmission coefficient of each transmission coefficient. Then the minimum common block length under the traversal transmission coefficient The corresponding transmission coefficient is the optimal transmission coefficient

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