Method for optimizing average block length of distributed star-ris assisted noma short packet communication system

Abstract

The application belongs to the technical field of resource allocation, and discloses a kind of average block length optimization method of distributed STAR-RIS assisted NOMA short packet communication system, comprising: base station obtains statistical channel state information and transmission signal-to-noise ratio;Base station obtains the short packet information downlink transmission to two users by multiple STAR-RIS in the form of NOMA according to the information received, obtains the average block error rate expression under limited signal-to-noise ratio and high signal-to-noise ratio;According to the average block error rate expression at high signal-to-noise ratio, the block length expression of two users is extracted;By optimizing the power allocation coefficient of base station and the transmission and reflection coefficient of STAR-RIS, the common block length of two users is minimized.The application combines the advantages of STAR-RIS that can reflect and transmit incident signals by 360° and NOMA that can improve spectral efficiency, effectively improves the maximum achievable rate of short packet communication system and improves system performance.

Description

Technical Field

[0001] This invention belongs to the field of resource allocation technology, specifically relating to an average block length optimization method for a distributed STAR-RIS-assisted NOMA short packet communication system. Background Technology

[0002] Recently, Ultra-Reliable and Low-Latency Communication (URLLC) has become a key technology for next-generation networks such as 5G and higher. As a crucial technology in URLLC, Short Packet Communication (SPC) offers lower latency and higher reliability compared to infinite block length (IBL) schemes. However, traditional Shannon capacity-based evaluation methods are insufficient to assess the requirements of SPC systems because the traditional method of averaging distortion and thermal noise introduced into the wireless channel requires asymptotic conditions for the receiver to correctly recover the transmitted signal and achieve channel capacity, i.e., the packet length must reach infinity. To address this issue, finite block length information theory can be used to accurately approximate the Maximum Realizable Rate (MAR) and Block Error Rate (BLER).

[0003] To meet the demands for higher data rates, spectral efficiency, and wider coverage, reconfigurable smart surfaces (RIS) have attracted considerable attention in recent years. RIS can flexibly control the propagation of wireless incident signals by adjusting the amplitude and phase shift of each element, thereby improving communication performance. However, when the user is located on the other side of the RIS and the source node, the coverage range (half-space coverage) of a RIS design that only reflects signals is limited. This necessitates the introduction of a reconfigurable smart surface (STAR-RIS) that can simultaneously transmit and reflect signals, achieving 360° all-around signal coverage.

[0004] Non-orthogonal multiple access (NOMA) was proposed to utilize spectrum resources more efficiently while ensuring user experience. Its core idea is to perform non-orthogonal transmission at the transmitting end, thus actively introducing interference. Then, at the receiving end, proper demodulation is achieved through serial interference cancellation (SIC). Although using SIC increases receiver complexity, this approach significantly improves spectral efficiency. In short, the NOMA strategy trades increased receiver processing complexity for higher spectral efficiency.

[0005] Therefore, it is necessary to propose an average block length optimization method for a distributed STAR-RIS-assisted NOMA short packet communication system, which minimizes the overall common block length of the system and determines the optimal base station power allocation coefficient and STAR-RIS transmission and reflection coefficient to solve the above problems. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention proposes an average block length optimization method for a distributed STAR-RIS-assisted NOMA short packet communication system. This method can be used in the field of resource allocation technology in URLLC short packet communication systems to improve the system's maximum achievable rate and spectral efficiency.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solution:

[0008] This invention discloses an average block length optimization method for a distributed STAR-RIS-assisted NOMA short packet communication system. This method is applicable to short packet downlink communication systems with multiple STAR-RIS, including a single-antenna base station, two users, and K STAR-RIS. Assuming there is no direct link between the base station and the users, the base station, with the assistance of the STAR-RIS, transmits short packet information to the two users via non-orthogonal multiple access (NOMA). First, a closed-form expression for the average block error rate (BLER) under finite signal-to-noise ratio is derived based on statistical channel state information. Then, under the condition of satisfying the average BLER, the power allocation coefficient, transmission coefficient, and reflection coefficient are determined based on the principle of minimizing the system's common block length.

[0009] The method includes the following steps:

[0010] S1: The base station first obtains the statistical channel state information between each device and the base station's transmission signal-to-noise ratio ρ.

[0011] S2: Based on the information received in step S1, the base station transmits short packet information to the two users via NOMA using multiple STAR-RIS downlinks, and derives the average block error rate expressions under finite and high signal-to-noise ratios.

[0012] S3: Based on the average block error rate expression obtained in step S2 for high signal-to-noise ratio, extract the block length expressions for user 1 and user 2.

[0013] S4: Based on the expression obtained in step S3, and by minimizing the common block length of the system, the optimal power allocation coefficient of the base station and the transmission and reflection coefficients of STAR-RIS are obtained.

[0014] Preferably, in step S1, the channel state information is modeled as follows: each device in the system is a single antenna, each STAR-RIS has N elements, and f is defined as follows: kn G represents the channel gain between the base station and the nth element of the k-th STAR-RIS. ikn Let represent the channel gain between the nth element of the kth STAR-RIS and user i. The channels between these devices are modeled as Nakagami-m channels.

[0015] Preferably, in step S2, the direct link between the base station and the two users is blocked, and the signal can only be reflected to the users via STAR-RIS. The signal sent by the base station to user i is represented by x. i This indicates that the number of data bits and the block length are T, respectively. i and L i Where i = 1 represents user 1 and i = 2 represents user 2.

[0016] Preferably, in step S2, the average block error rate expressions for user 1 and user 2 under finite signal-to-noise ratio are as follows:

[0017]

[0018] The expressions for the average block error rate under high signal-to-noise ratio are as follows:

[0019]

[0020] Where Γ(a) and γ(a, b) represent the gamma function and the lower incomplete gamma function, respectively: The shape and scaling parameters of the gamma distribution are as follows: ω1 = ο1 / ρα1, ω2 = ο2 / ρ(α2-α1ο2). Where ρ represents the signal-to-noise ratio at the base station transmitter, and α... i Let β be the power allocation coefficient from the base station to user i. i The transmission or reflection coefficient of STAR-RIS, μ i , and ο i Let be the mean, variance, and signal-to-interference-plus-noise ratio of the signal received by user i, respectively.

[0021]

[0022]

[0023]

[0024] Where, m Bk and m ik Let d be the formal parameters of the Nakagami distribution from the base station to the k-th STAR-RIS and from the k-th STAR-RIS to user i, respectively. Bk and d ik T represents the distance from the base station to the center of the k-th STAR-RIS, and the distance from the center of the k-th STAR-RIS to user i, respectively. i and L i These represent the data volume and block length of the signal sent by the base station to user i, respectively. When i is 1, it represents user 1; when i is 2, it represents user 2.

[0025] Preferably, in step S3, the minimum block length expressions for user 1 and user 2 are as follows:

[0026]

[0027]

[0028] in, The BLER threshold that allows user i to meet the acceptance criteria.

[0029] Preferably, in step S4, the steps for obtaining the minimum common block length of the system and its corresponding power allocation coefficient, as well as the transmission and reflection coefficients, are as follows:

[0030] S401: Combining the minimum block length expressions of the two users yields the relationship between the minimum common block length, the power allocation coefficient, and the transmission and reflection coefficients: L min =min(max(L) 1,min ,L 2,min )).

[0031] S402: Set a decision threshold δ to set an initial value for the power allocation coefficient α_old of the base station to user 1 and the reflection coefficient β_old of STAR-RIS.

[0032] S403: Substitute α_old and β_old into the least common block length expression in step S401 to obtain L min _old.

[0033] S404: Fix β1 to β_old, and find the α1 between 0 and 0.5 that minimizes the length of the common block through a one-dimensional search. It is denoted as α_new.

[0034] S405: Fix α1 as α_new, and find the β1 between 0 and 1 that minimizes the length of the common block through a one-dimensional search, denoted as β_new.

[0035] S406: Substitute α_new and β_new into the least common block length expression in step S401 to find the least common block length at this point, denoted as L. min _new.

[0036] S407: Judgment | L min _new-L min Does _old|≤δ hold true?

[0037] S408: If |L min _new-L minIf _old|≤δ is not true, then assign the values ​​of α_new and β_new to α_old and β_old respectively, and return to step S403.

[0038] S409: If |L min _new-L min If _old≤δ holds true, the iterative algorithm ends, and α_new, β_new, and L are set... min The values ​​of _new are assigned to respectively and

[0039] S410: Based on the solution from step S409, calculate the power allocation coefficient from the base station to user 2. Transmission coefficient of STAR-RIS

[0040] The beneficial effects of this invention are as follows: This invention derives an approximate closed-form expression for the average BLER under finite and high signal-to-noise ratios using statistical CSI; This invention quantifies the relationship between the minimum common block length under reliability constraints and the base station's optimal power allocation coefficient and STAR-RIS transmission and reflection coefficients; This invention combines the advantages of STAR-RIS's ability to reflect / transmit incident signals at 360° and NOMA's ability to improve spectral efficiency, effectively increasing the maximum achievable rate of short packet communication systems and improving system performance. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of the system model for distributed STAR-RIS-assisted NOMA short packet communication according to the present invention.

[0042] Figure 2 This is a flowchart of the method for optimizing the average common block length of distributed STAR-RIS-assisted NOMA short packet communication according to the present invention.

[0043] Figure 3 This is a schematic diagram showing the relationship between the minimum common block length and the power allocation coefficient of the base station in the distributed STAR-RIS assisted NOMA short packet communication system of the present invention.

[0044] Figure 4 This is a schematic diagram showing the relationship between the minimum common block length and the reflection coefficient of the distributed STAR-RIS-assisted NOMA short packet communication system of the present invention. Detailed Implementation

[0045] The embodiments of the present invention will be disclosed below with reference to the drawings. For clarity, many practical details will be described in the following description. However, it should be understood that these practical details are not intended to limit the invention. That is, in some embodiments of the invention, these practical details are not essential.

[0046] This invention discloses a method for optimizing the average block length of a distributed STAR-RIS-assisted NOMA short packet communication system. This method is applicable to short packet downlink communication systems with multiple STAR-RIS systems, such as... Figure 1 As shown, the system includes a single-antenna base station, two users, and K STAR-RIS. This invention assumes there is no direct link between the base station and the users. With the assistance of STAR-RIS, the base station sends short messages to the two users via non-orthogonal multiple access (NOMA). First, a closed-form expression for the average block error rate (BLER) under finite signal-to-noise ratio is derived based on statistical channel state information. Then, under the condition of satisfying the average BLER, the power allocation coefficient, transmission coefficient, and reflection coefficient are determined based on the principle of minimizing block length.

[0047] like Figure 2 As shown, this invention is a method for optimizing the average block length of a distributed STAR-RIS-assisted NOMA short packet communication system. The method includes the following steps:

[0048] S1: The base station first obtains the statistical channel state information between each device and the base station's transmission signal-to-noise ratio ρ.

[0049] In step S1, the channel state information is modeled as follows: each device in the system is a single antenna, each STAR-RIS has N elements, and f is defined as follows: kn G represents the channel gain between the base station and the nth element of the k-th STAR-RIS. ikn Let represent the channel gain between the nth element of the kth STAR-RIS and user i. The channels between these devices are modeled as Nakagami-m channels.

[0050] S2: Based on the information received in step S1, the base station transmits short packet information to the two users via NOMA using multiple STAR-RIS downlinks, and derives the average block error rate expressions under finite and high signal-to-noise ratios.

[0051] In this invention, the direct link between the base station and two users is blocked, and the signal can only be reflected to the users via STAR-RIS. The signal sent by the base station to user i is represented by x. i This indicates that the number of data bits and the block length are T, respectively. i and L iWhere i = 1 represents user 1 and i = 2 represents user 2.

[0052] The average block error rate expressions for User 1 and User 2 under finite signal-to-noise ratio are as follows:

[0053]

[0054] The expressions for the average block error rate under high signal-to-noise ratio are as follows:

[0055]

[0056] Where Γ(a) and γ(a, b) represent the gamma function and the lower incomplete gamma function, respectively: The shape and scaling parameters of the gamma distribution are as follows: ω1 = ο1 / ρα1, ω2 = ο2 / ρ(α2-α1ο2). Where ρ represents the signal-to-noise ratio at the base station transmitter, and α... i Let β be the power allocation coefficient from the base station to user i. i The transmission or reflection coefficient of STAR-RIS, μ i , and ο i Let be the mean, variance, and signal-to-interference-plus-noise ratio of the signal received by user i, respectively.

[0057]

[0058]

[0059]

[0060] Where, m Bk and m ik Let d be the formal parameters of the Nakagami distribution from the base station to the k-th STAR-RIS and from the k-th STAR-RIS to user i, respectively. Bk and d ik T represents the distance from the base station to the center of the k-th STAR-RIS, and the distance from the center of the k-th STAR-RIS to user i, respectively. i and L i These represent the data volume and block length of the signal sent by the base station to user i, respectively. When i is 1, it represents user 1; when i is 2, it represents user 2.

[0061] S3: Based on the average block error rate expression obtained in step S2 for high signal-to-noise ratio, extract the block length expressions for User 1 and User 2. The minimum block length expressions for User 1 and User 2 are as follows:

[0062]

[0063]

[0064] in, The BLER threshold that allows user i to meet the acceptance criteria.

[0065] S4: Based on the expression obtained in step S3, and by minimizing the common block length of the system, the optimal power allocation coefficient of the base station and the transmission and reflection coefficients of STAR-RIS are derived, specifically including the following steps:

[0066] S401: Combining the minimum block length expressions for User 1 and User 2, we obtain the relationship between the minimum common block length, the power allocation coefficient, and the transmission and reflection coefficients: L min =min(max(L) 1,min ,L 2,min )).

[0067] S402: Set a decision threshold δ to set an initial value for the power allocation coefficient α_old of the base station to user 1 and the reflection coefficient β_old of STAR-RIS.

[0068] S403: Substitute α_old and β_old into the least common block length expression in step S401 to obtain L min _old.

[0069] S404: Fix β1 to β_old, and find the α1 between 0 and 0.5 that minimizes the length of the common block through a one-dimensional search. It is denoted as α_new.

[0070] S405: Fix α1 as α_new, and find the β1 between 0 and 1 that minimizes the length of the common block through a one-dimensional search, denoted as β_new.

[0071] S406: Substitute α_new and β_new into the least common block length expression in step S401 to find the least common block length at this point, denoted as L. min _new.

[0072] S407: Judgment | L min _new-L min Does _old|≤δ hold true?

[0073] S408: If |L min _new-L min If _old|≤δ is not true, then assign the values ​​of α_new and β_new to α_old and β_old respectively, and return to step S403.

[0074] S409: If |L min_new-L min If _old≤δ holds true, the iterative algorithm ends, and α_new, β_new, and L are set... min The values ​​of _new are assigned to respectively and

[0075] S410: Based on the solution from step S409, calculate the power allocation coefficient from the base station to user 2. Transmission coefficient of STAR-RIS

[0076] When analyzing the least common block length, it is assumed that the transmission signal-to-noise ratio of the base station transmitter is known and fixed. Thus, the expression for the least common block length is a binary function of α1 and β1.

[0077] The relationship between the minimum common block length of the system and the power allocation coefficient of the base station is as follows: Figure 3 As shown in the figure, the minimum common block length of the system first decreases and then increases with the power allocation coefficient of the base station to user 1, reaching a minimum value when α1 = 0.18. Compared with the single STAR-RIS case, the distributed STAR-RIS can significantly reduce the minimum common block length of the system, thereby improving the maximum reachable rate.

[0078] The relationship between the minimum common block length of the system and the transmission coefficient of the STAR-RIS of the base station is as follows: Figure 4 As shown in the figure, the minimum common block length of the system first decreases and then increases with the transmission coefficient of STAR-RIS. This is because when β1 is very small, the channel quality between the base station and user 1 is very poor. In order to ensure the effectiveness of the signal, the signal transmitted by the base station needs a large block length. As β1 increases, the channel quality between the base station and user 1 is enhanced, and the block length required to satisfy the signal effectiveness decreases. However, at the same time, the channel quality between the base station and user 2 gradually declines, and the block length required to satisfy the signal reception effectiveness of user 2 increases. As shown in the figure, the common block length of the entire system reaches its minimum value when β1 = 0.57.

[0079] This invention utilizes statistical CSI, combining the advantages of STAR-RIS (which can reflect and transmit incident signals 360°) and NOMA (which improves spectral efficiency), to effectively increase the maximum achievable rate of short packet communication systems and improve system performance.

[0080] The above description is merely an embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A method for optimizing the average block length of a distributed STAR-RIS-assisted NOMA short packet communication system, characterized in that: This method is applicable to short-packet downlink communication systems with multiple STAR-RIS, which include a single-antenna base station, two users, and K STAR-RIS. Assuming there is no direct link between the base station and the users, the single-antenna base station, with the assistance of the STAR-RIS, sends short packet information to the two users via non-orthogonal multiple access (NOMA). The specific average block length optimization method includes the following steps: Step 1: The single-antenna base station first acquires the statistical channel state information between each device and the transmit signal-to-noise ratio of the single-antenna base station. ; Step 2: Based on the statistical channel state information received in Step 1, the single-antenna base station transmits short packet information to User 1 and User 2 through multiple STAR-RIS downlinks using non-orthogonal multiple access (NOMA) to derive the average block error rate expressions under finite and high signal-to-noise ratios. Step 3: Based on the average block error rate expression obtained in Step 2 for high signal-to-noise ratio, extract the block length expressions for User 1 and User 2. Step 4: Based on the block length expressions for User 1 and User 2 obtained in Step 3, and focusing on minimizing the common block length of the short packet downlink communication system, derive the optimal base station power allocation coefficient and the STAR-RIS transmission and reflection coefficients; where, In step 2, the single-antenna base station can only reflect signals to the two users via STAR-RIS. The signal sent by the single-antenna base station to user i is... express; In step 2, the average block error rate expressions for user 1 and user 2 under finite signal-to-noise ratio are as follows: ， The expressions for the average block error rate under high signal-to-noise ratio are as follows: ， in, and Let Gamma and Incomplete Gamma be the gamma function and the incomplete gamma function, respectively. , The shape and scaling parameters of the gamma distribution are as follows: , , , , in, Indicates the signal-to-noise ratio at the base station transmitter. For base stations to users The power allocation factor, For STAR-RIS, the transmission or reflection coefficient. , and users respectively The mean, variance, and signal-to-interference-plus-noise ratio of the received signal, i.e.: ， ， ， in, and Let be the formal parameters of the Nakagami distribution from the base station to the k-th STAR-RIS and from the k-th STAR-RIS to user i, respectively. and Let represent the distance from the base station to the center of the k-th STAR-RIS, and the distance from the center of the k-th STAR-RIS to user i, respectively. and These represent the data volume and block length of the signal sent by the base station to user i, respectively. When i is 1, it represents user 1, and when i is 2, it represents user 2.

2. The method for optimizing the average block length of a distributed STAR-RIS-assisted NOMA short packet communication system according to claim 1, characterized in that: In step 1, the channel state information is modeled as follows: In a short-packet downlink communication system with multiple STAR-RIS, each device is a single antenna, and each STAR-RIS has N elements, defined as follows: This represents the channel gain between the base station and the nth element of the k-th STAR-RIS. Let represent the channel gain between the nth element of the kth STAR-RIS and user i. The channel between these devices is modeled as a Nakagami-m channel.

3. The method for optimizing the average block length of a distributed STAR-RIS-assisted NOMA short packet communication system according to claim 1, characterized in that: In step 3, the minimum block length expressions for user 1 and user 2 are as follows: in, , , Let BLER be the threshold at which user i can meet the reception conditions.

4. The method for optimizing the average block length of a distributed STAR-RIS-assisted NOMA short packet communication system according to claim 3, characterized in that: In step 4, the minimum common block length of the short packet downlink communication system block length, its corresponding power allocation coefficient, and transmission and reflection coefficients are obtained, specifically including the following steps: Step 4.1: Combine the minimum block length expressions for User 1 and User 2 to obtain the relationship between the minimum common block length, power allocation coefficient, and transmission and reflection coefficients: ； Step 4.2: Set a decision threshold The power allocation coefficient of the base station to user 1 and STAR-RIS reflectance Set an initial value; Step 4.3, and Substituting this into the least common block length expression in step 4.1, we get... ; Step 4.4, Fixed as Find the line between 0 and 0.5 that minimizes the length of the common block using a one-dimensional search. , recorded as ; Step 4.5, Fixed as Find the value between 0 and 1 that minimizes the length of the common block using a one-dimensional search. , recorded as ; Step 4.6, and Substituting this into the least common block length expression in step 4.1, we find the least common block length at this point, denoted as . ; Step 4.7, Judgment Is it valid? Step 4.8, if If not true, then and The values ​​are assigned to and Return to step 4.3; Step 4.9, if If the condition is met, the iterative algorithm ends. , and The values ​​are assigned to , and ; The solutions from steps 4.10 and 4.9 are used to calculate the power allocation coefficient from the base station to user 2. Transmission coefficient of STAR-RIS .

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