Large-scale MIMO network service quality guarantee method and system based on short codes

Abstract

The invention discloses a large-scale MIMO network service quality guarantee method and system based on a short code, and relates to the technical field of communication, and the method comprises the steps: carrying out the modeling of an asymptotic behavior of an outage probability based on a large-scale MIMO signal, and obtaining the outage probability; by adopting a large deviation principle, carrying out modeling on the tail behavior of the outage probability, and describing a relationship between an outage probability index and the outage probability; updating the outage probability index; the method comprises the following steps: modeling a tail behavior of a short code bit error rate by adopting a large deviation principle, and describing a service quality guarantee index of an asymptotic short code bit error rate under the condition of a high signal-to-noise ratio based on the service quality guarantee index of the short code bit error rate; updating the service quality assurance index of the asymptotic short code error rate; and according to the updated outage probability index and the updated service quality assurance index of the asymptotic short code bit error rate, obtaining a joint time delay and reliability service quality assurance index. The invention can improve the service quality of the network.

Description

Technical Field

[0001] This invention belongs to the field of communication technology, specifically relating to a method and system for ensuring quality of service in large-scale MIMO networks based on short codes. Background Technology

[0002] With the widespread application of 5G wireless communication networks and the continuous evolution of 6G wireless communication networks, mobile wireless communication systems are facing the core requirement of large-scale ultra-reliable low-latency communication. This places extremely stringent service quality assurance requirements on wireless communication networks, manifested in: extremely low end-to-end latency (typically less than 1 millisecond) and extremely low bit error rate (e.g., less than 10^6). -5 Even 10 -7 The system needs to support large-scale device access and high-speed dynamic channel environment.

[0003] In existing technologies, the traditional Shannon limit theory is no longer applicable to large-scale ultra-reliable low-latency communication scenarios because practical services mostly involve short packet transmission. This type of transmission is often based on finite code-length communication technologies, whose decoding performance has a non-zero error probability and is closely related to codeword length, signal-to-noise ratio, and modulation scheme. Meanwhile, massive MIMO (Multiple-Input Multiple-Output) technology has become a key supporting means for 6G; however, the channel characteristics of this system are highly randomized, exhibiting rapid fading and time-varying correlations, which pose additional challenges to the quality of service analysis and assurance of short packet communication.

[0004] Therefore, how to accurately characterize and control the statistical quality of service assurance index under the dual constraints of latency and bit error rate under the condition of limited code length; and how to establish a systematic joint quality of service analysis and control theoretical framework by combining the random channel characteristics of large-scale MIMO, have become the contradictions that need to be solved in future 6G networks. Summary of the Invention

[0005] To address the aforementioned problems in the existing technology, this invention provides a method and system for ensuring quality of service in large-scale MIMO networks based on short codes. The technical problem to be solved by this invention is achieved through the following technical solution: In a first aspect, the present invention provides a method for ensuring quality of service in large-scale MIMO networks based on short codes, comprising: Based on massive MIMO signals, the asymptotic behavior of the interruption probability is modeled to obtain the interruption probability under high signal-to-noise ratio conditions; The large deviation principle is used to model the tail behavior of the outage probability and describe the relationship between the outage probability exponent and the outage probability. The outage probability exponent is a function of the coding rate and the diversity of the large-scale MIMO wireless channel, and is used to measure the exponential decay rate when the outage probability tends to infinity as the number of fading sub-channels increases. In the case of high signal-to-noise ratio and when the transmitting and receiving antennas approach infinity, update the interruption probability index; The tail behavior of short code error rate is modeled using the large deviation principle. Based on the service quality assurance index of short code error rate, the service quality assurance index of asymptotic short code error rate under high signal-to-noise ratio is described. The service quality assurance index of short code error rate is a function of coding rate and long short code length, and is used to measure the exponential decay rate of short code error rate as code length increases and tends to infinity. As the code length approaches infinity, update the service quality assurance index for the asymptotically shorter code error rate; Based on the updated outage probability index and the updated asymptotic short code error rate service quality assurance index, obtain the joint latency and reliability service quality assurance index.

[0006] Secondly, the present invention also provides a quality of service assurance system for large-scale MIMO networks based on short codes, comprising: The interruption probability acquisition module is used to model the asymptotic behavior of the interruption probability based on the massive MIMO signal, and obtain the interruption probability under high signal-to-noise ratio conditions. The tail behavior modeling module for outage probability is used to model the tail behavior of outage probability using the large deviation principle, describing the relationship between the outage probability exponent and the outage probability. The outage probability exponent is a function of the coding rate and the diversity of the massive MIMO wireless channel, and is used to measure the exponential decay rate corresponding to the outage probability as the number of fading sub-channels increases. The interruption probability index update model is used to update the interruption probability index under high signal-to-noise ratio conditions and when the transmitting and receiving antennas tend to be infinite. The short code error rate tail behavior modeling module is used to model the tail behavior of the short code error rate using the large deviation principle. Based on the service quality assurance index of the short code error rate, it describes the service quality assurance index of the asymptotic short code error rate under high signal-to-noise ratio conditions. The service quality assurance index of the short code error rate is a function of the coding rate and the long short code length, and is used to measure the exponential decay rate of the short code error rate as the code length increases and tends to infinity. The Service Quality Assurance Index Update Model for Asymptotic Short Code Error Rate is used to update the Service Quality Assurance Index of Asymptotic Short Code Error Rate when the code length tends to infinity. The joint index modeling module is used to obtain the joint latency and reliability service quality assurance index based on the updated outage probability index and the updated asymptotic short code error rate service quality assurance index.

[0007] The beneficial effects of this invention are: This invention provides a method and system for quality of service assurance in large-scale MIMO networks based on short codes. Combining the large-scale MIMO channel environment, it designs an exponential function for outage probability and proposes a modeling and control method for delay and reliability quality of service assurance, defining relevant control functions. This enables more accurate joint quality of service assurance and control under highly random large-scale MIMO channel conditions, improving the robustness of the system in complex wireless environments.

[0008] Furthermore, this invention simultaneously considers the joint quality of service (QoS) modeling of latency and bit error rate. It eliminates the need to calculate and analyze the coupling between the two indicators independently. Instead, by introducing a joint QoS index based on latency and bit error rate, it can simultaneously constrain both types of performance indicators in short packet communication scenarios. This ensures truly low latency and high reliability for large-scale ultra-reliable low-latency services and improves the network's QoS.

[0009] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0010] Figure 1 This is a flowchart of a method for ensuring quality of service in large-scale MIMO networks based on short codes, provided in an embodiment of the present invention. Figure 2 This is another flowchart of the method for ensuring quality of service in large-scale MIMO networks based on short codes provided in this embodiment of the invention; Figure 3 The interruption probability exponential function provided in this embodiment of the invention under different signal-to-noise ratios varies with... A graph showing the relationship between ratio changes; Figure 4 This is a graph showing the relationship between the Quality of Service Assurance Index of the Asymptotic Short Code Error Rate and the number of receiving antennas, provided in an embodiment of the present invention. Figure 5 The Quality of Service (QoS) assurance index for the asymptotic short code error rate provided in this embodiment of the invention varies with code length. A graph showing the relationship between the average signal-to-noise ratio and its variation. Figure 6 This is a graph illustrating the relationship between the joint quality of service assurance index of latency and bit error rate and the number of receiving antennas, provided in an embodiment of the present invention. Figure 7 This is provided by the embodiments of the present invention. Effective capacity varies with code length A graph showing the relationship between latency and bit error rate in the joint quality of service assurance index. Detailed Implementation

[0011] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0012] Most existing technologies are based on a single evaluation index and lack joint modeling of service quality assurance indexes under large-scale MIMO channels. As a result, service quality assurance control cannot reflect the highly random channel characteristics of large-scale MIMO, and the reliability and low latency guarantees are insufficient. Furthermore, there is a lack of performance limit analysis and verification, resulting in insufficient engineering applications.

[0013] In view of this, this invention proposes a method and system for quality of service assurance in large-scale MIMO networks based on short codes. It proposes a joint modeling and control method for statistical delay and bit error rate for large-scale MIMO channels, which can effectively characterize and utilize the random characteristics of the channel, thereby effectively establishing an asymptotic performance limit analysis and verification method. It quantitatively characterizes the reliability, delay default probability and effective capacity boundary in large-scale ultra-reliable low-latency scenarios, and improves the accuracy and reliability of the modeling results.

[0014] Please see Figure 1 and Figure 2 , Figure 1 This is a flowchart of a method for ensuring quality of service in large-scale MIMO networks based on short codes, provided in an embodiment of the present invention. Figure 2 This is another flowchart of a method for ensuring quality of service in large-scale MIMO networks based on short codes, provided in an embodiment of the present invention. The method for ensuring quality of service in large-scale MIMO networks based on short codes provided by the present invention includes: S101. Based on large-scale MIMO signals, the asymptotic behavior of the interruption probability is modeled to obtain the interruption probability under high signal-to-noise ratio conditions.

[0015] Specifically, in this embodiment, the approximation function of the interruption probability under high signal-to-noise ratio conditions is expressed as: (1); in, This represents the interruption probability under high signal-to-noise ratio conditions. Represents a probability function. , Indicates the number of transmitting antennas. Indicates the number of receiving antennas. Indicates the first One antenna, Indicates the signal-to-noise ratio of the transmitted signal. Indicates after the first Subchannel fading function of each antenna This represents the information drying ratio function. Indicates the signal transmission rate. Represents a logarithmic function.

[0016] S102. The large deviation principle is used to model the tail behavior of the outage probability and describe the relationship between the outage probability exponent and the outage probability. The outage probability exponent is a function of the coding rate and the diversity of the large-scale MIMO wireless channel, and is used to measure the exponential decay rate when the outage probability tends to infinity as the number of fading sub-channels increases.

[0017] Specifically, in this embodiment, the relationship between the interruption probability exponent and the interruption probability under high signal-to-noise ratio conditions is expressed as follows: (2); in, Indicates the probability index of interruption; Obtain the interruption probability index The expression: (3); Among them, when the receiving antenna When the number of elements approaches infinity, the interruption probability... The rate of decrease is exponential, and the probability of interruption is... The larger the value, the lower the interruption probability under high signal-to-noise ratio conditions. The symbol for a limit, This represents an exponential function.

[0018] S103. Under high signal-to-noise ratio conditions and when the transmitting and receiving antennas tend to be infinite, update the interruption probability index.

[0019] Specifically, in this embodiment, the updated interruption probability index is expressed as: (4); ; in, Describing the degrees of freedom as Statistically independent chi-square random variables, This represents the channel capacity under high signal-to-noise ratio conditions. This represents a function for calculating variance.

[0020] S104. Using the large deviation principle, the tail behavior of the short code error rate is modeled. Based on the quality of service (QoS) guarantee index of the short code error rate, the QoS guarantee index of the asymptotic short code error rate under high signal-to-noise ratio is described. The QoS guarantee index of the short code error rate is a function of the coding rate and the long short code length, and is used to measure the exponential decay rate of the short code error rate as the code length increases and tends to infinity.

[0021] Specifically, in this embodiment, the Quality of Service Assurance Index for the asymptotic short code error rate is expressed as: (5); The service quality assurance index of asymptotically short code bit error rate under high signal-to-noise ratio conditions is expressed in closed form as follows: (6); in, Indicates the code length. The service quality assurance index represents the short code error rate. The service quality assurance index represents the bit error rate of the asymptotic short code. Indicates the number of transmitting antennas. Indicates the number of receiving antennas. Indicates the first One antenna, Indicates the signal-to-noise ratio of the transmitted signal. Indicates after the first The attenuation index of the sub-channels of each antenna, Represents the logarithmic function. Symbols representing limits.

[0022] In existing technologies, most quality of service (QoS) assurance theories are based on the assumption of unlimited code length. However, in large-scale ultra-reliable low-latency (mURLLC) services, short packet communication based on finite code length technology must be adopted. However, existing technologies lack systematic modeling methods under short packet communication conditions and cannot accurately describe core indicators such as outage probability, bit error rate, latency default probability, and effective capacity. This invention constructs a QoS assurance index that approximates the bit error rate of asymptotically short code length, and further establishes a system model and QoS assurance analysis framework based on finite code length to adapt to the future requirements of 6G ultra-reliable low-latency communication.

[0023] S105. When the code length approaches infinity, update the service quality assurance index of the asymptotic short code error rate.

[0024] Specifically, in this embodiment, the updated Quality of Service (QoS) index for the asymptotic short code error rate is expressed as: (7); in, This indicates the service quality assurance index that makes the short code error rate lower. Maximize the optimal Lagrange multipliers. ; When the number of transmitting and receiving antennas approaches infinity, and the number of transmitting antennas is greater than or equal to the number of receiving antennas, under the condition that... and The updated Quality of Service Assurance Index for the asymptotic short code error rate is expressed as: (8); in, and Represents different presupposed rational numbers.

[0025] S106. Obtain the joint latency and reliability quality of service assurance index based on the updated outage probability index and the updated asymptotic short code error rate service quality assurance index.

[0026] Specifically, in this embodiment, the joint latency and reliability quality of service assurance index is expressed as: (9); in, This represents the joint latency and reliability quality of service assurance index, which is an indicator that simultaneously calculates the probability of breaching the upper bound of latency and the bit error rate. Indicates the maximum achievable coding rate. This indicates that the delay violates the threshold. This represents the probability that the queue is not empty. This represents the combined probability of violation of latency and short code error rate. Indicates the code length. Represents the logarithmic function. Represents an exponential function. The service quality assurance index represents the bit error rate of the asymptotic short code. This represents the information drying ratio function.

[0027] Existing technologies mostly focus on statistical delay quality of service (QoS) assurance control, such as the probability distribution of delay defaults, without fully considering the impact of non-zero decoding error rates in finite code length communication scenarios. This results in the inability to provide statistical QoS that simultaneously guarantees outage probability, delay, and error rate in short packet communication and large-scale ultra-reliable low-latency scenarios. This invention proposes a statistical QoS assurance modeling and analysis method that can jointly characterize delay and short code error rate constraints by studying the tail behavior of outage probability in large-scale MIMO systems, thus overcoming the shortcomings of existing technologies that rely on single-dimensional analysis.

[0028] Furthermore, as a key technology for future wireless networks, massive MIMO's random channel characteristics significantly impact the statistical distribution of delay and bit error rate. Existing technologies lack a joint quality of service (QoS) assurance modeling method for massive MIMO channels, resulting in a lack of a reliable theoretical foundation for QoS assurance control. This invention constructs a joint delay and reliability QoS assurance index to improve the accuracy of QoS control.

[0029] Furthermore, this embodiment also includes: Based on the joint latency and reliability service quality assurance index, obtain Effective capacity is expressed as: (10); in, express Effective capacity This represents the statistical average function based on the information-to-dryness ratio.

[0030] It should be noted that, Effective capacity is defined as the maximum arrival rate that a given service process can support under a finite code length mechanism, while simultaneously satisfying the service quality assurance constraints of statistical latency and bit error rate.

[0031] Please see Figure 2 In this embodiment, at the service layer, the user's corresponding large-scale ultra-reliable low-latency (mURLLC) requirements are obtained. Within the theoretical analysis framework, based on stochastic dynamic characterization and statistical QoS analysis, a joint latency and bit error rate QoS assurance index is further constructed by analyzing the outage probability index and the bit error rate QoS assurance index to obtain... Based on the effective capacity, and within the framework of asymptotic performance analysis, under the assumptions of signal-to-noise ratio limits, code length limits, and antenna number limits, asymptotic analysis is conducted to improve the quality of service guarantee capability.

[0032] In summary, the quality of service assurance method for large-scale MIMO networks based on short codes provided by this invention has the following beneficial effects: First, this invention constructs an outage probability exponent for large-scale MIMO architecture based on the tail behavior of outage probability under large-scale MIMO channels. It uses this exponent as a function of coding rate and diversity of large-scale MIMO wireless channel to measure the exponential decay rate when the outage probability tends to infinity as the number of fading sub-channels increases, and studies its asymptotic approximation function. This enables the modeling and performance limit derivation of the outage probability exponent in multi-antenna large-scale systems, combined with the characteristics of random channels, and analyzes its mathematical relationship with the number of receiving antennas.

[0033] Second, this invention uses an analytical framework based on the short code bit error rate (BBER) to construct a BBER service quality assurance index suitable for large-scale MIMO random channel environments. This enables the modeling and performance limit derivation of the BBER service quality assurance index of the asymptotic short code bit error rate in large-scale multi-antenna systems, combining short code transmission technology with random channel characteristics.

[0034] Third, this invention proposes a joint latency and reliability quality of service assurance index and control function, and A function for obtaining effective capacity to improve the precision of service quality control.

[0035] Based on the same inventive concept, this invention also provides a short-code-based quality of service (QoS) assurance system for large-scale MIMO networks, used to implement the short-code-based QoS assurance method for large-scale MIMO networks provided in the above embodiments of this invention. Embodiments of the method can be referred to the above description and will not be repeated here. The system includes: The interruption probability acquisition module is used to model the asymptotic behavior of the interruption probability based on the massive MIMO signal, and obtain the interruption probability under high signal-to-noise ratio conditions. The tail behavior modeling module for outage probability is used to model the tail behavior of outage probability using the large deviation principle, describing the relationship between the outage probability exponent and the outage probability. The outage probability exponent is a function of the coding rate and the diversity of the massive MIMO wireless channel, and is used to measure the exponential decay rate corresponding to the outage probability as the number of fading sub-channels increases. The interruption probability index update model is used to update the interruption probability index under high signal-to-noise ratio conditions and when the transmitting and receiving antennas tend to be infinite. The short code error rate tail behavior modeling module is used to model the tail behavior of the short code error rate using the large deviation principle. Based on the service quality assurance index of the short code error rate, it describes the service quality assurance index of the asymptotic short code error rate under high signal-to-noise ratio conditions. The service quality assurance index of the short code error rate is a function of the coding rate and the long short code length, and is used to measure the exponential decay rate of the short code error rate as the code length increases and tends to infinity. The Service Quality Assurance Index Update Model for Asymptotic Short Code Error Rate is used to update the Service Quality Assurance Index of Asymptotic Short Code Error Rate when the code length tends to infinity. The joint index modeling module is used to obtain the joint latency and reliability service quality assurance index based on the updated outage probability index and the updated asymptotic short code error rate service quality assurance index.

[0036] In an optional embodiment of the present invention, the effectiveness of the short-code-based quality of service assurance method for large-scale MIMO networks provided in the above embodiment is verified through simulation experiments, specifically as follows: Please see Figure 3 , Figure 3 The interruption probability exponential function provided in this embodiment of the invention under different signal-to-noise ratios varies with... A graph showing the relationship between the ratio and the signal-to-noise ratio (SNR), where, for a given average coding rate, the outage-probability exponent function increases with increasing SNR; simultaneously, the value of the outage-probability exponent function increases with... It decreases as it increases, that is, when At that time, the interruption probability exponent approaches 0.

[0037] Please see Figure 4 , Figure 4 This is a graph showing the relationship between the Quality of Service (QoS) Exponent Function (QFS) of the asymptotic short code bit error rate and the number of receiving antennas, provided by an embodiment of the present invention. Under the condition of finite code length and signal-to-noise ratio approaching infinity, the QFS of the asymptotic short code bit error rate decreases with the increase of the number of receiving antennas.

[0038] Please see Figure 5 , Figure 5 The Quality of Service (QoS) assurance index for the asymptotic short code error rate provided in this embodiment of the invention varies with code length. A graph showing the relationship between the average signal-to-noise ratio and the asymptotic error rate (BER) and the Quality of Service (QoS) Exponent Function (QoS) as a function of the BER length. The service quality assurance index of the asymptotic short code error rate decreases as the average signal-to-noise ratio (ANR) increases.

[0039] Please see Figure 6 , Figure 6 This is a graph illustrating the relationship between the joint delay / error-rate QoS exponent and the number of receiving antennas, as provided in this embodiment of the invention. In the performance modeling scheme using a finite code length, the joint delay / error-rate QoS exponent decreases with increasing number of receiving antennas. Given a large delay violation threshold... The system is able to achieve a lower joint quality of service index with lower latency and bit error rate, indicating that the decay rate of the joint quality of service index is slower, and that the system can tolerate longer latency and higher bit error rate.

[0040] Please see Figure 7 , Figure 7 This is provided by the embodiments of the present invention. Effective capacity varies with code length A graph showing the relationship between latency and bit error rate in the joint Quality of Service Assurance Index, given a certain error probability. Effective capacity It is a decreasing function of the joint quality of service assurance index of latency and bit error rate, indicating that when , At that time, respectively, The upper and lower bounds of the effective capacity.

[0041] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations are intended to cover non-exclusive inclusion, such that an article or device comprising a list of elements includes not only those elements but also other elements not expressly listed. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device comprising said element. Terms such as "connected" or "linked" are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect. The orientations or positional relationships indicated by terms such as "upper," "lower," "left," and "right" are based on the orientations or positional relationships shown in the accompanying drawings and are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as limiting the invention.

[0042] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0043] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A method for ensuring quality of service in large-scale MIMO networks based on short codes, characterized in that, include: Based on massive MIMO signals, the asymptotic behavior of the interruption probability is modeled to obtain the interruption probability under high signal-to-noise ratio conditions; The large deviation principle is used to model the tail behavior of the outage probability and describe the relationship between the outage probability exponent and the outage probability. The outage probability exponent is a function of the coding rate and the diversity of the large-scale MIMO wireless channel, and is used to measure the exponential decay rate when the outage probability tends to infinity as the number of fading sub-channels increases. In the case of high signal-to-noise ratio and when the transmitting and receiving antennas tend to be infinite, the interruption probability index is updated; The tail behavior of short code error rate is modeled using the large deviation principle. Based on the service quality assurance index of short code error rate, the service quality assurance index of asymptotic short code error rate under high signal-to-noise ratio is described. The service quality assurance index of short code error rate is a function of coding rate and long short code length, and is used to measure the exponential decay rate of short code error rate as code length increases and tends to infinity. As the code length approaches infinity, update the Quality of Service Assurance Index of the asymptotically shorter code error rate; Based on the updated outage probability index and the updated asymptotic short code error rate service quality assurance index, obtain the joint latency and reliability service quality assurance index.

2. The method for ensuring quality of service in large-scale MIMO networks based on short codes according to claim 1, characterized in that, The approximation function for the interruption probability under the high signal-to-noise ratio condition is expressed as: ； in, This represents the interruption probability under high signal-to-noise ratio conditions. Represents a probability function. , Indicates the number of transmitting antennas. Indicates the number of receiving antennas. Indicates the first One antenna, Indicates the signal-to-noise ratio of the transmitted signal. Indicates after the first The attenuation index of the sub-channels of each antenna, This represents the information drying ratio function. Indicates the signal transmission rate. Represents a logarithmic function.

3. The method for ensuring quality of service in large-scale MIMO networks based on short codes according to claim 2, characterized in that, The large deviation principle is used to model the tail behavior of the interruption probability, describing the relationship between the interruption probability exponent and the interruption probability under the high signal-to-noise ratio condition, including: The relationship between the interruption probability index and the interruption probability under the high signal-to-noise ratio condition is expressed as follows: ； in, Indicates the probability index of interruption; Obtain the interruption probability index The expression: ； Wherein, when the receiving antenna When the number of interruptions approaches infinity, the interruption probability... The rate represented decays exponentially, and the interruption probability... The larger the value, the lower the interruption probability under the high signal-to-noise ratio condition. The symbol for a limit, This represents an exponential function.

4. The method for ensuring quality of service in large-scale MIMO networks based on short codes according to claim 3, characterized in that, In the case of high signal-to-noise ratio and when the transmitting and receiving antennas tend to infinity, the interruption probability index is updated, including: The updated interruption probability index is expressed as: ； ； in, Describing the degrees of freedom as Statistically independent chi-square random variables, This represents the channel capacity under high signal-to-noise ratio conditions. This represents a function for calculating variance.

5. The method for ensuring quality of service in large-scale MIMO networks based on short codes according to claim 1, characterized in that, The Quality of Service Assurance Index for the asymptotic short code error rate is expressed as: ； The closed-form expression of the Quality of Service Assurance Index for the asymptotic short code bit error rate under high signal-to-noise ratio conditions is as follows: ； in, Indicates the code length. The service quality assurance index represents the short code error rate. The service quality assurance index represents the bit error rate of the asymptotic short code. Indicates the number of transmitting antennas. Indicates the number of receiving antennas. Indicates the first One antenna, Indicates the signal-to-noise ratio of the transmitted signal. Indicates after the first The attenuation index of the sub-channels of each antenna, Represents the logarithmic function. Symbols representing limits.

6. The method for ensuring quality of service in large-scale MIMO networks based on short codes according to claim 5, characterized in that, As the code length approaches infinity, the service quality assurance index for the asymptotically shorter code error rate is updated, including: The updated Quality of Service (QoS) index for the asymptotic short code error rate is expressed as: ； in, This indicates the service quality assurance index that makes the short code error rate lower. Maximize the optimal Lagrange multipliers. ; When the number of transmitting and receiving antennas approaches infinity, and the number of transmitting antennas is greater than or equal to the number of receiving antennas, under the condition that... and The updated Quality of Service Assurance Index for the asymptotic short code error rate is expressed as: ； in, and Represents different presupposed rational numbers.

7. The method for ensuring quality of service in large-scale MIMO networks based on short codes according to claim 1, characterized in that, The joint latency and reliability quality of service assurance index is expressed as follows: ； in, This represents the combined latency and reliability quality of service assurance index. Indicates the maximum achievable coding rate. This indicates that the delay violates the threshold. This represents the probability that the queue is not empty. This represents the combined probability of violation of latency and short code error rate. Indicates the code length. Represents the logarithmic function. Represents an exponential function. The service quality assurance index represents the bit error rate of the asymptotic short code. This represents the information drying ratio function.

8. The method for ensuring quality of service in large-scale MIMO networks based on short codes according to claim 7, characterized in that, Also includes: Based on the joint latency and reliability quality of service assurance index, obtain Effective capacity is expressed as: ； in, express Effective capacity This represents the statistical average function based on the information-to-dryness ratio.

9. A quality of service assurance system for large-scale MIMO networks based on short codes, characterized in that, include: The interruption probability acquisition module is used to model the asymptotic behavior of the interruption probability based on the massive MIMO signal, and obtain the interruption probability under high signal-to-noise ratio conditions. The tail behavior modeling module for the outage probability is used to model the tail behavior of the outage probability using the large deviation principle, and to describe the relationship between the outage probability exponent and the outage probability; wherein the outage probability exponent is a function of the coding rate and the diversity of the massive MIMO wireless channel, and is used to measure the exponential decay rate corresponding to the outage probability tending to infinity as the number of fading sub-channels increases. An interruption probability index update model is used to update the interruption probability index under high signal-to-noise ratio conditions and when the transmitting and receiving antennas tend to be infinite. The short code error rate tail behavior modeling module is used to model the tail behavior of the short code error rate using the large deviation principle. Based on the service quality assurance index of the short code error rate, it describes the service quality assurance index of the asymptotic short code error rate under high signal-to-noise ratio conditions. The service quality assurance index of the short code error rate is a function of the coding rate and the long short code length, and is used to measure the exponential decay rate of the short code error rate as the code length increases and tends to infinity. A Quality of Service Assurance Index (QoS) update model for asymptotically short code error rate is used to update the QoS index of the asymptotically short code error rate as the code length approaches infinity. The joint index modeling module is used to obtain the joint latency and reliability service quality assurance index based on the updated outage probability index and the updated asymptotic short code error rate service quality assurance index.

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