Performance evaluation method for short packet coding communication

Abstract

The invention provides a performance evaluation method for short packet coding communication, and belongs to the technical field of short packet communication. The method comprises the following steps that a system model of short packet coding communication is constructed, the system model comprises a ground base station, an unmanned aerial vehicle, a legal user side and a non-target user side which are in communication connection, and a reconfigurable intelligent surface is configured on the unmanned aerial vehicle; and according to all channel state information of the system model, carrying out average reachable secrecy rate analysis, average decoding error probability analysis and secrecy interruption probability analysis on the system model in sequence, and evaluating the performance of the system model according to all analysis results. According to the invention, the safety and reliability of performance evaluation of short packet coding communication can be improved.

Description

Technical Field

[0001] This application relates to the technical field of short-packet communication, and in particular to a method for evaluating the performance of short-packet encoded communication. Background Art

[0002] The deployment of 5G / 6G networks is driving the wide application of various large-scale Internet of Things. One of the key technical indicators is Ultra-Reliable and Low-Latency Communication (URLLC), which is specifically applied to support communication scenarios that require extremely high reliability and an average decoding error probability not exceeding and ultra-low latency (usually less than 1 ms). Short-packet communication networks usually play a crucial role in achieving ultra-reliable low-latency communication. It generally involves the transmission of small data packets ranging from dozens of bytes to hundreds of bytes, which helps the exchange of high-frequency data. However, small data packets bring many limitations and face the following challenges: On the one hand, the traditional Shannon theorem is usually based on the assumption of infinitely long data blocks, so it is not applicable to ultra-reliable low-latency communication scenarios; on the other hand, there is often a lack of systematic verification methods for evaluating the performance of short-packet communication networks, which has become an urgent problem to be solved.

[0003] Reconfigurable Intelligent Surface (RIS) is a key technology in 5G / 6G communication systems and is widely used in various wireless communication scenarios. Different from traditional technologies, RIS does not perform analog-to-digital conversion on the radio frequency link. Instead, it redirects the incident signal by adjusting the phase and amplitude of multiple reflection units and optimizes the propagation path, thereby improving the signal quality and spectral efficiency of the receiver. Unmanned Aerial Vehicle (UAV) can be combined with RIS to form a UAV-RIS system due to its compact size and high mobility, which can be used to meet communication scenarios that require flexible network deployment. Due to the open transmission environment of UAVs, privacy information is easily intercepted by non-target user terminals. Therefore, a line-of-sight link can be quickly established in a complex environment through the UAV-RIS system, thus effectively protecting privacy information. Compared with traditional relay security devices, the UAV-RIS system can greatly reduce the cost of network construction and maintenance, providing strong technical support for the high security of data transmission in ultra-reliable low-latency communication.

[0004] However, for short-packet communication scenarios including non-target user terminals, the existing technologies lack methods for evaluating their performance, which are mainly manifested in:

[0005] First, in the performance evaluation of the long-packet communication network that includes the UAV-RIS system and non-target user-end attacks, the infinite block length theory involved has not been fully extended to the finite block length theory, and the reliability of the short-packet communication network has not been fully explored;

[0006] Second, in the performance evaluation of the short-packet communication network that includes the UAV-RIS system but does not include non-target user-end attacks, the UAV-RIS system, as a relay system, can meet the reliability requirements of the short-packet communication network, but the information security issues in actual data transmission have not been considered.

[0007] Therefore, it is necessary to propose a solution to improve one or more problems existing in the above-related technical solutions.

[0008] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present application, and therefore may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0009] The embodiment of the present application provides a performance evaluation method for short-packet coded communication, and the method includes the following steps:

[0010] Construct a system model of short-packet coded communication, where the system model includes a ground base station, a UAV, a legitimate user end, and a non-target user end that are communicatively connected, and a reconfigurable intelligent surface is configured on the UAV;

[0011] According to all the channel state information of the system model, perform an average achievable secrecy rate analysis, an average decoding error probability analysis, and a secrecy outage probability analysis on the system model in sequence;

[0012] Evaluate the performance of the system model according to the results of the average achievable secrecy rate analysis, the results of the average decoding error probability analysis, and the results of the secrecy outage probability analysis.

[0013] Further, the reconfigurable intelligent surface includes a reflection array composed of a plurality of reflection elements with the same structure, and a single antenna is respectively configured on each of the reflection elements; the ground base station, the legitimate user end, and the non-target user end are respectively configured with the single antenna;

[0014] The expression of the phase shift matrix of the reconfigurable intelligent surface is:

[0015] (1)

[0016] Where, represents the phase shift matrix of the reconfigurable intelligent surface, represents constructing a diagonal matrix, denotes the imaginary unit, denotes the phase shift of the th reflecting element of the reconfigurable intelligent surface;

[0017] The ground base station is denoted by The location of the ground base station is denoted by denoted by, , denotes the axis coordinate of the ground base station, denotes the axis coordinate of the ground base station;

[0018] The UAV is denoted by The location of the UAV is denoted by denoted by, , denotes the axis coordinate of the UAV, denotes the axis coordinate of the UAV, denotes the altitude of the UAV;

[0019] The legitimate user terminal is denoted by The location of the legitimate user terminal is denoted by denoted by, , denotes the axis coordinate of the legitimate user terminal, denotes the axis coordinate of the legitimate user terminal;

[0020] The non - target user terminal is denoted by The location of the non - target user terminal is denoted by denoted by, , denotes the axis coordinate of the non - target user terminal, denotes the axis coordinate of the non - target user terminal.

[0021] Furthermore, both the legitimate user terminal and the non - target user terminal receive two types of channel signals. The first type of channel signal is the direct - link signal transmitted from the ground base station, and the second type of channel signal is the reflected - link signal from the reconfigurable intelligent surface;

[0022] The expression of the received signal of the legitimate user terminal is:

[0023] (2)

[0024] where, Represents the received signal of a legitimate user terminal, Represents the signal transmission power of the ground base station, Represents the transmitted signal of the ground base station and satisfies , Represents The expected value of, Represents the channel distance from the ground base station to the UAV, Represents the channel distance from the UAV to the legitimate user terminal, Represents the path loss coefficient of the channel signal from the ground base station to the UAV, Represents the path loss coefficient of the channel signal from the UAV to the legitimate user terminal, Represents the th reflection element of the reconfigurable intelligent surface, Represents the number of all reflection elements of the reconfigurable intelligent surface, Represents the complex channel gain from the ground base station to the reconfigurable intelligent surface on the UAV, , Represents the th channel phase shift coefficient of the reflection element from the ground base station to the reconfigurable intelligent surface on the UAV, ξ S → R, n ∈(0,2π] , Represents the imaginary unit, Represents the complex channel gain from the reconfigurable intelligent surface on the UAV to the legitimate user terminal, , Represents the th channel phase shift coefficient of the reflection element from the reconfigurable intelligent surface on the UAV to the legitimate user terminal, ξ R, n → D ∈(0,2π] , Represents the th phase shift of the reflection element of the reconfigurable intelligent surface, Represents the channel distance from the ground base station to the legitimate user terminal, Represents the path loss coefficient of the channel signal from the ground base station to the legitimate user terminal, Represents the interference noise of the legitimate user terminal, Represents the complex channel gain from the ground base station to the legitimate user terminal, , Represents the channel phase shift coefficient from the ground base station to the legitimate user terminal, ξ S → D ∈(0,2π] ;

[0025] The expression of the received signal of the non-target user terminal is:

[0026] (3)

[0027] Among them, represents the received signal of the non-target user terminal, represents the path loss coefficient of the channel signal from the UAV to the non-target user terminal, represents the complex channel gain from the reconfigurable intelligent surface on the UAV to the non-target user terminal, , represents the th channel phase shift coefficient of the reconfigurable intelligent surface on the UAV to the non-target user terminal, ξ R, n → I ∈(0,2π] , represents the channel distance from the ground base station to the non-target user terminal, represents the channel distance from the UAV to the non-target user terminal, represents the path loss coefficient of the channel signal from the ground base station to the non-target user terminal, represents the interference noise of the non-target user terminal, represents the complex channel gain from the ground base station to the non-target user terminal, , represents the channel phase shift coefficient from the ground base station to the non-target user terminal, ξ S → I ∈(0,2π] .

[0028] Furthermore, according to all the channel state information of the system model, the steps of performing the average achievable secrecy rate analysis on the system model include:

[0029] Adjust the reconfigurable intelligent surface to the optimal phase shift according to the received signal of the legitimate user terminal, and respectively obtain the optimal signal-to-noise ratio of the legitimate user terminal and the instantaneous signal-to-noise ratio of the non-target user terminal;

[0030] Model the optimal signal-to-noise ratio of the legitimate user terminal as a random distribution variable of the gamma function, and use the moment matching method to respectively derive the probability density function and the cumulative distribution function of the legitimate user terminal;

[0031] Model the instantaneous signal-to-noise ratio of the non-target user terminal as an exponential distribution variable of the gamma function, and use the moment matching method to respectively derive the probability density function and the cumulative distribution function of the non-target user terminal;

[0032] Use the achievable secrecy rate of the system model, the probability density function of the legitimate user terminal, and the probability density function of the non-target user terminal to determine the closed form of the average achievable secrecy rate of the system model.

[0033] Furthermore, the expression of the probability density function of the legitimate user terminal is:

[0034] (4)

[0035] wherein, represents the probability density function when the signal-to-noise ratio of the received signal at the legitimate user terminal is ; represents the signal transmission power of the ground base station; represents the signal-to-noise ratio of the received signal of the legitimate user terminal; represents the optimal signal-to-noise ratio of the legitimate user terminal; , , represents the th reflection element of the reconfigurable intelligent surface; represents the number of all reflection elements of the reconfigurable intelligent surface; represents the complex channel gain from the ground base station to the reconfigurable intelligent surface on the unmanned aerial vehicle; , represents the channel phase shift coefficient of the th reflection element from the ground base station to the reconfigurable intelligent surface on the unmanned aerial vehicle; ξ S → R, n ∈(0,2π] , represents the imaginary unit; represents the complex channel gain from the reconfigurable intelligent surface on the unmanned aerial vehicle to the legitimate user terminal; , represents the channel phase shift coefficient of the th reflection element from the reconfigurable intelligent surface on the unmanned aerial vehicle to the legitimate user terminal; ξ R, n → D ∈(0,2π] , , represents the path loss coefficient of the channel signal from the ground base station to the unmanned aerial vehicle; represents the path loss coefficient of the channel signal from the unmanned aerial vehicle to the legitimate user terminal; represents the channel distance from the ground base station to the unmanned aerial vehicle; represents the channel distance from the unmanned aerial vehicle to the legitimate user terminal; , represents the channel distance from the ground base station to the legitimate user terminal; represents the path loss coefficient of the channel signal from the ground base station to the legitimate user terminal; represents the complex channel gain from the ground base station to the legitimate user terminal; , represents the channel phase shift coefficient from the ground base station to the legitimate user terminal; ξ S → D ∈(0,2π] , represents the shape parameter, represents the exponential function, represents the scale parameter, represents the gamma function;

[0036] The expression of the cumulative distribution function of the legitimate client is:

[0037] (5)

[0038] where, represents the cumulative distribution function of the legitimate client when the signal-to-noise ratio of the received signal is ;

[0039] The expression of the probability density function of the non-target client is:

[0040] (6)

[0041] where, represents the probability density function of the non-target client when the signal-to-noise ratio of the received signal is ; represents the signal-to-noise ratio of the received signal of the non-target client, represents the rate parameter of the exponential distribution, represents the instantaneous signal-to-noise ratio of the non-target client, , , represents the path loss coefficient of the channel signal from the UAV to the non-target client, represents the channel distance from the UAV to the non-target client, represents the complex channel gain from the reconfigurable intelligent surface on the UAV to the non-target client, , represents the th reflection element on the reconfigurable intelligent surface on the UAV to the channel phase shift coefficient of the non-target client, ξ R, n → I ∈(0,2π] , represents the net phase difference of the non-target client, , represents the channel distance from the ground base station to the non-target client, represents the path loss coefficient of the channel signal from the ground base station to the non-target client, represents the complex channel gain from the ground base station to the non-target client, , represents the channel phase shift coefficient from the ground base station to the non-target client, ξ S → I ∈(0,2π] ;

[0042] The expression of the cumulative distribution function of the non-target user terminal is as follows:

[0043] (7)

[0044] where represents the cumulative distribution function of the non-target user terminal when the signal-to-noise ratio of the received signal is .

[0045] Furthermore, the steps of determining the closed-form of the average achievable secrecy rate of the system model by using the achievable secrecy rate of the system model, the probability density function of the legitimate user terminal, and the probability density function of the non-target user terminal include:

[0046] When the length of the channel block of the ground base station is constant, and the decoding error probability of the legitimate user terminal is less than or equal to the decoding error probability threshold, and the information leakage rate of the legitimate user terminal is less than or equal to the information leakage rate threshold, if , then the achievable secrecy rate is 0, and the achievable secrecy rate is denoted by , represents the length of the channel block of the ground base station, represents the decoding error probability of the legitimate user terminal, represents the information leakage rate of the legitimate user terminal;

[0047] If , the closed-form expression of the achievable secrecy rate is:

[0048] (8)

[0049] where represents the closed-form of the achievable secrecy rate of the system model, represents the achievable secrecy rate of the legitimate user terminal, , represents the achievable secrecy rate of the non-target user terminal, , represents the secrecy rate in long-packet coding communication, , represents the channel dispersion of the legitimate user terminal, , represents the channel dispersion of the non-target user terminal, , represents the inverse function of the function, represents the inverse function of the function, represents the integration variable;

[0050] The closed-form expression of the average achievable secrecy rate is as follows:

[0051] (9)

[0052] where represents the closed-form of the average achievable secrecy rate, represents the Meijer’G function, represents the Fox-H function, , , represents the summation variable. When , When , .

[0053] Furthermore, according to all the channel state information of the system model, the steps for analyzing the average decoding error probability of the system model include:

[0054] When , the decoding error probability is equal to 1;

[0055] When , the expression of the decoding error probability is:

[0056] (10)

[0057] where represents the right-tail function of the standard normal distribution, , represents variable, represents the number of bits of the transmitted signal of the ground base station;

[0058] Using the linear approximation theory, let be approximated to the linear function to simplify the computational complexity of formula (10), that is, satisfying , the expression of the linear function is:

[0059] (11)

[0060] where , , represents the lower bound of the achievable secrecy rate, represents the upper bound of the achievable secrecy rate, , represents the variable of the linear function ;

[0061] Let , after re - representing as , substitute the said linear function into formula (10), and calculate the average value of all the said decoding error probabilities to obtain the said average decoding error probability;

[0062] The expression of the said average decoding error probability is:

[0063] (12)

[0064] wherein, represents the average decoding error probability, represents the auxiliary variable, represents the cumulative distribution function when the legitimate user terminal is at the lower bound of the achievable secrecy rate, represents the cumulative distribution function when the legitimate user terminal is at the upper bound of the achievable secrecy rate, represents when the variable equals the linear function;

[0065] Solve using the integration - by - parts method, and at the same time rewrite using the Riemann integral to obtain the closed - form of the said average decoding error probability;

[0066] The expression of the closed - form of the said average decoding error probability:

[0067] (13)

[0068] wherein, represents the closed - form of the average decoding error probability, , represents the cumulative distribution function of the legitimate user terminal.

[0069] Furthermore, according to all the said channel state information in the said system model, the steps of performing the secrecy outage probability analysis on the said system model include:

[0070] When the length of the channel block of the said ground base station is , and the threshold of the said achievable secrecy rate is , and , calculate the closed - form of the secrecy outage probability using the moment - matching method;

[0071] Calculate the cumulative distribution function of the said legitimate user terminal under the condition of high signal - to - noise ratio in the said system model;

[0072] Using the system model, when the signal-to-noise ratio is large, the cumulative distribution function of the legitimate user terminal is used to derive the closed form of the asymptotic secrecy outage probability and the positive secrecy asymptotic capacity respectively.

[0073] Furthermore, the expression of the closed form of the secrecy outage probability is:

[0074] F ACR a ACR th =U{ ACR th - ACR a ¯ Ψ(AC R a ) }= 1 2πΨ( ACR a ) ∫ -∞ ACR th exp{- [ t- ACR a ¯ ] 2 2Ψ( ACR a ) }dt (14)

[0075] where, represents the closed form of the secrecy outage probability, represents the variance of the closed form of the achievable secrecy rate, represents the Gaussian function;

[0076] When the signal-to-noise ratio is large for the system model, the expression of the cumulative distribution function of the legitimate user terminal is:

[0077] (15)

[0078] where, represents the cumulative distribution function of the legitimate user terminal when the signal-to-noise ratio is large for the system model, represents the signal-to-noise ratio of the received signal of the legitimate user terminal when the signal-to-noise ratio is large for the system model;

[0079] The expression of the closed form of the asymptotic secrecy outage probability is:

[0080] (16)

[0081] where, represents the closed form of the asymptotic secrecy outage probability, ;

[0082] The expression of the positive secrecy asymptotic capacity is:

[0083] (17)

[0084] where, represents the positive secrecy asymptotic capacity, represents the probability when the achievable secrecy rate is positive, .

[0085] Further, the step of evaluating the performance of the system model according to the results of the achievable secrecy rate analysis, the average decoding error probability analysis, and the secrecy outage probability analysis includes:

[0086] When the result of the achievable secrecy rate analysis is greater than or equal to , and the result of the average decoding error probability analysis is less than or equal to , and the result of the secrecy outage probability analysis is less than or equal to , the performance of the system model is determined to be excellent;

[0087] When the result of the achievable secrecy rate analysis is between , and the result of the average decoding error probability analysis is greater than and less than or equal to , and the result of the secrecy outage probability analysis is greater than and less than or equal to , the performance of the system model is determined to be medium;

[0088] When the result of the achievable secrecy rate analysis is less than or equal to , and the result of the average decoding error probability analysis is greater than and less than or equal to , and the result of the secrecy outage probability analysis is greater than and less than or equal to , the performance of the system model is determined to be poor.

[0089] The present application provides a method for evaluating the performance of short-packet coding communication, which has at least the following beneficial effects:

[0090] (1) The method for evaluating the performance of short-packet coding communication proposed in the present application improves the communication quality of the entire system model by configuring a reconfigurable intelligent surface on the unmanned aerial vehicle and using it as a passive relay station for signal transmission;

[0091] (2) The present application analyzes the average achievable secrecy rate, the average decoding error probability, and the secrecy outage probability of the system model in sequence according to all the channel state information of the system model, thereby forming a complete performance evaluation scheme and achieving the optimal utilization of resources. Description of the Drawings

[0092] The accompanying drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present application and used together with the specification to explain the principles of the present application. Obviously, the accompanying drawings in the following description are only some embodiments of the present application, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

[0093] Figure 1 Schematic diagram showing the steps of a performance evaluation method for short-packet coding communication in an exemplary embodiment of the present application;

[0094] Figure 2 Schematic diagram showing the structure of a system model for short-packet coding communication in an exemplary embodiment of the present application;

[0095] Figure 3 Comparative curve graph showing the average achievable secrecy rate when changing the signal-to-noise ratio of the transmitted signal under conditions of different numbers of reflecting elements and lengths of channel blocks in an exemplary embodiment of the present application;

[0096] Figure 4 Comparative curve graph showing the average decoding error probability when changing the length of the channel block under conditions of different numbers of reflecting elements and Rice factors in an exemplary embodiment of the present application;

[0097] Figure 5 Comparative curve graph showing the secrecy outage probability when changing the signal-to-noise ratio of the transmitted signal under conditions of different thresholds of achievable secrecy rate in an exemplary embodiment of the present application;

[0098] Figure 6 Comparative curve graph showing the positive secrecy asymptotic capacity when changing the signal-to-noise ratio of the transmitted signal under conditions of different numbers of reflecting elements, lengths of channel blocks, decoding error probabilities, information leakage rates, and UAV flight altitudes in an exemplary embodiment of the present application. Detailed implementation manners

[0099] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more complete and comprehensive, and will fully convey the concept of the example embodiments to those skilled in the art. The features, structures, or characteristics described may be combined in any suitable manner in one or more embodiments.

[0100] In addition, the accompanying drawings are only schematic illustrations of the present application and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0101] Next, a performance evaluation method for short-packet coded communication proposed in this exemplary embodiment will be described in more detail.

[0102] This exemplary embodiment provides a performance evaluation method for short-packet coded communication. As Figure 1 shown, this method may include the following steps:

[0103] Step S101 of this embodiment: Construct a system model for short-packet coded communication.

[0104] In step S101 of this embodiment, as Figure 2 shown, this system model includes a ground base station, a drone, a legitimate user terminal, and a non-target user terminal that are communicatively connected. A reconfigurable intelligent surface is configured on the drone.

[0105] Furthermore, the ground base station, the legitimate user terminal, and the non-target user terminal are respectively configured with a single antenna. The ground base station is denoted by , and the position of the ground base station is denoted by , , denotes the axis coordinate of the ground base station, and denotes the axis coordinate of the ground base station. The drone is denoted by , and the position of the drone is denoted by , , denotes the axis coordinate of the drone, denotes the axis coordinate of the drone, and denotes the height of the drone. The legitimate user terminal is denoted by , and the position of the legitimate user terminal is denoted by , , denotes the axis coordinate of the legitimate user terminal, and denotes the axis coordinate of the legitimate user terminal. The non-target user terminal is denoted by , and the position of the non-target user terminal is denoted by , , denotes the axis coordinate of the non-target user terminal, and denotes the axis coordinate of the non-target user terminal.

[0106] Furthermore, the reconfigurable intelligent surface is a rectangular reflection array composed of a plurality of reflection elements with the same structure arranged uniformly, and a single antenna is configured on each reflection element. The expression of the phase shift matrix of the reconfigurable intelligent surface is:

[0107] (1)

[0108] Among them, represents the phase shift matrix of the reconfigurable intelligent surface, represents the constructed diagonal matrix, represents the imaginary unit, that is , represents the th phase shift of the reflection element of the reconfigurable intelligent surface.

[0109] Furthermore, the distance between the air and the ground should be significantly greater than the spacing between the reflection elements of the reconfigurable intelligent surface. Therefore, it is assumed that the distances between each reflection element and each node on the ground are uniform. Then both the legitimate user terminal and the non-target user terminal can receive two types of channel signals. The first type of channel signal is the direct link signal transmitted by the ground base station; the second type of channel signal is the reflected link signal from the reconfigurable intelligent surface. The direct link signal is modeled as a Rayleigh fading channel, and the reflected link signal is modeled as a Rice fading channel.

[0110] It can be obtained that the expression of the received signal of the legitimate user terminal is:

[0111] (2)

[0112] Among them, represents the received signal of the legitimate user terminal, represents the signal transmission power of the ground base station, represents the transmitted signal of the ground base station, and satisfies , represents the expected value of, represents the channel distance from the ground base station to the UAV, represents the channel distance from the UAV to the legitimate user terminal, represents the path loss coefficient of the channel signal from the ground base station to the UAV, represents the path loss coefficient of the channel signal from the UAV to the legitimate user terminal, represents the th reflection element of the reconfigurable intelligent surface, represents the number of all reflection elements of the reconfigurable intelligent surface, represents the complex channel gain from the ground base station to the reconfigurable intelligent surface on the UAV, , represents the channel phase shift coefficient of the th reflection element from the ground base station to the reconfigurable intelligent surface on the UAV, ξ S → R, n ∈(0,2π] , denotes the imaginary unit, denotes the complex channel gain from the reconfigurable intelligent surface on the UAV to the legitimate user terminal, , denotes the th channel phase shift coefficient of the ξ R, n → D ∈(0,2π] , denotes the th phase shift of the th reflecting element of the reconfigurable intelligent surface, denotes the channel distance from the ground base station to the legitimate user terminal, denotes the path loss coefficient of the channel signal from the ground base station to the legitimate user terminal, denotes the interference noise at the legitimate user terminal, , denotes the complex channel gain from the ground base station to the legitimate user terminal, ξ S → D ∈(0,2π] .

[0113] The expression for the received signal at the non-target user terminal is:

[0114] (3)

[0115] where, denotes the received signal at the non-target user terminal, denotes the path loss coefficient of the channel signal from the UAV to the non-target user terminal, denotes the complex channel gain from the reconfigurable intelligent surface on the UAV to the non-target user terminal, , denotes the th channel phase shift coefficient of the ξ R, n → I ∈(0,2π] , denotes the channel distance from the ground base station to the non-target user terminal, denotes the channel distance from the UAV to the non-target user terminal, denotes the path loss coefficient of the channel signal from the ground base station to the non-target user terminal, denotes the interference noise at the non-target user terminal, denotes the complex channel gain from the ground base station to the non-target user terminal, , denotes the channel phase shift coefficient from the ground base station to the non-target user terminal, ξ S → I ∈(0,2π] 。

[0116] Step S102 of this embodiment: According to all the channel state information (Channel State Information, CSI) of the system model, perform the average achievable secrecy rate analysis, average decoding error probability analysis, and secrecy outage probability analysis on the system model in sequence. Step S102 of this embodiment may include the following sub-steps:

[0117] Sub-step S1021: Perform the average achievable secrecy rate analysis on the system model to determine the closed form of the average achievable secrecy rate of the system model. The specific process is as follows:

[0118] First, adjust the reconfigurable intelligent surface to the optimal phase shift according to the received signal of the legitimate user terminal, and obtain the optimal signal-to-noise ratio of the legitimate user terminal and the instantaneous signal-to-noise ratio of the non-target user terminal respectively.

[0119] Furthermore, in this embodiment, adjusting the reconfigurable intelligent surface to the optimal phase shift means adjusting the phase of the reconfigurable intelligent surface to eliminate the phase error, so that the reconfigurable intelligent surface reaches the optimal phase shift. At this time, the following can be obtained: the optimal signal-to-noise ratio of the legitimate user terminal: , where, , , . The instantaneous signal-to-noise ratio of the non-target user terminal is: , where, , .

[0120] Furthermore, the optimal phase shift of the reconfigurable intelligent surface is represented by , and the expression is . The net phase difference of the non-target user terminal is represented by , and the expression is: . Here, the value ranges of , , , and are all (0,2π] .

[0121] Secondly, model the optimal signal-to-noise ratio of the legitimate user terminal as a random distribution variable of the gamma function, and use the moment matching method to derive the probability density function and cumulative distribution function of the legitimate user terminal respectively.

[0122] Here, it means defining a random variable , letting , and introducing the moment matching method to directly derive the random variable The cumulative distribution function approximates the distribution of the random variable as a Gamma distribution with the same parameters. The Gamma distribution has two parameters, one is the shape parameter , and the other is the scale parameter . The two parameters satisfy , and the transformation relationship of the Gamma distribution is: and . By setting the scale parameter , , substituting into the Gamma distribution, the probability density function and cumulative distribution function of the legitimate user terminal can be obtained. denotes 's variance; denotes 's mean; denotes 's probability density function; denotes 's cumulative distribution function.

[0123] Furthermore, the expression of the probability density function of the legitimate user terminal is:

[0124] (4)

[0125] where denotes the probability density function of the legitimate user terminal when the signal-to-noise ratio of the received signal is , denotes the signal transmission power of the ground base station, denotes the signal-to-noise ratio of the received signal of the legitimate user terminal, denotes the optimal signal-to-noise ratio of the legitimate user terminal, , , denotes the -th reflecting element of the reconfigurable intelligent surface, denotes the number of all reflecting elements of the reconfigurable intelligent surface, denotes the complex channel gain from the ground base station to the reconfigurable intelligent surface on the UAV, , denotes the channel phase shift coefficient of the -th reflecting element from the ground base station to the reconfigurable intelligent surface on the UAV, ξ S → R, n ∈(0,2π] , denotes the imaginary unit, denotes the complex channel gain from the reconfigurable intelligent surface on the UAV to the legitimate user terminal, , denotes the The channel phase shift coefficient from the reflection element to the legitimate user terminal ξ R, n → D ∈(0,2π] , , represents the path loss coefficient of the channel signal from the ground base station to the UAV represents the path loss coefficient of the channel signal from the UAV to the legitimate user terminal represents the channel distance from the ground base station to the UAV represents the channel distance from the UAV to the legitimate user terminal , represents the channel distance from the ground base station to the legitimate user terminal represents the path loss coefficient of the channel signal from the ground base station to the legitimate user terminal represents the complex channel gain from the ground base station to the legitimate user terminal , represents the channel phase shift coefficient from the ground base station to the legitimate user terminal ξ S → D ∈(0,2π] , represents the shape parameter represents the exponential function represents the scale parameter represents the gamma function

[0126] The expression of the cumulative distribution function of the legitimate user terminal is:

[0127] (5)

[0128] where represents the cumulative distribution function of the legitimate user terminal when the signal-to-noise ratio of the received signal is

[0129] Next, the instantaneous signal-to-noise ratio of the non-target user terminal is modeled as an exponential distribution variable of the gamma function, and the probability density function and cumulative distribution function of the non-target user terminal are respectively derived using the moment matching method

[0130] Here, it is said that another random variable is defined, and let Assume When , can be approximated as a complex Gaussian distribution with a mean of 0 and a variance of , that is . From this, the probability density function and cumulative distribution function of the non-target user terminal can be obtained

[0131] Furthermore, the expression of the probability density function of the non-target user terminal is: ​

[0132] (6)

[0133] Among them, represents the probability density function when the signal-to-noise ratio of the received signal at the non-target user terminal is at that time, represents the signal-to-noise ratio of the received signal at the non-target user terminal, represents the rate parameter of the exponential distribution, , represents the instantaneous signal-to-noise ratio of the non-target user terminal, , , represents the path loss coefficient of the channel signal from the UAV to the non-target user terminal, represents the channel distance from the UAV to the non-target user terminal, represents the complex channel gain from the reconfigurable intelligent surface on the UAV to the non-target user terminal, , represents the th reflection element on the reconfigurable intelligent surface on the UAV to the channel phase shift coefficient of the non-target user terminal, ξ R, n → I ∈(0,2π] , represents the net phase difference of the non-target user terminal, , represents the channel distance from the ground base station to the non-target user terminal, represents the path loss coefficient of the channel signal from the ground base station to the non-target user terminal, represents the complex channel gain from the ground base station to the non-target user terminal, , represents the channel phase shift coefficient from the ground base station to the non-target user terminal, ξ S → I ∈(0,2π] .

[0134] The expression of the cumulative distribution function of the non-target user terminal is:

[0135] (7)

[0136] Among them, represents the cumulative distribution function when the signal-to-noise ratio of the received signal at the non-target user terminal is at that time.

[0137] Finally, using the achievable secrecy rate of the system model, the probability density function of the legitimate user terminal, and the probability density function of the non-target user terminal, the closed form of the average achievable secrecy rate of the system model is determined.

[0138] Furthermore, when the length of the channel block of the ground base station is constant, and the decoding error probability of the legitimate user terminal is less than or equal to the decoding error probability threshold, and the information leakage rate of the legitimate user terminal is less than or equal to the information leakage rate threshold, if , then the achievable secrecy rate is 0, and the achievable secrecy rate is denoted by . represents the length of the channel block of the ground base station, represents the decoding error probability of the legitimate user terminal, represents the information leakage rate of the legitimate user terminal;

[0139] If , then the closed-form expression of the achievable secrecy rate is:

[0140] (8)

[0141] where represents the closed-form of the achievable secrecy rate of the system model, represents the achievable secrecy rate of the legitimate user terminal, , represents the achievable secrecy rate of the non-target user terminal, , represents the secrecy rate in long-packet coding communication, , represents the channel dispersion of the legitimate user terminal, , represents the channel dispersion of the non-target user terminal, , represents the inverse function of the , represents the inverse function of the , represents the integration variable.

[0142] The expression of the closed-form of the average achievable secrecy rate is:

[0143] (9)

[0144] where represents the closed-form of the average achievable secrecy rate, represents the Meijer’G function, represents the Fox-H function, , , represents the summation variable. When , , when , .

[0145] The closed - form expression of the average achievable secrecy rate, as a security evaluation metric, can be used to analyze the interception resistance ability of the entire system model against non - target users.

[0146] Sub - step S1022: Analyze the average decoding error probability of the system model. Using the right - tail function of the standard normal distribution, linear approximation theory, and Riemann integral, determine the closed - form expression of the average decoding error probability of the system model. The specific process is as follows:

[0147] When the decoding error probability is equal to 1;

[0148] When the expression of the decoding error probability is:

[0149] (10)

[0150] where represents the right - tail function of the standard normal distribution, represents the variable of and represents the number of bits of the transmitted signal of the ground base station;

[0151] Using linear approximation theory, let be approximated by the linear function to simplify the computational complexity of formula (10), that is, satisfying , and the expression of the linear function is:

[0152] (11)

[0153] where represents the lower bound of the achievable secrecy rate, represents the upper bound of the achievable secrecy rate, represents the variable of the linear function .

[0154] Let , after re - representing as , substitute the linear function into formula (10), and calculate the average value of all decoding error probabilities to obtain the average decoding error probability;

[0155] The expression of the average decoding error probability is:

[0156] (12)​​​​​

[0157] Among them, represents the average decoding error probability, represents the auxiliary variable, represents the cumulative distribution function of the legitimate user terminal at the lower bound of the achievable secrecy rate, represents the cumulative distribution function of the legitimate user terminal at the upper bound of the achievable secrecy rate, represents when the variable is equal to a linear function at this time.

[0158] Solve using the integration by parts method, and at the same time rewrite using the Riemann integral to obtain a closed - form expression for the average decoding error probability;

[0159] The expression of the closed - form of the average decoding error probability:

[0160] (13)

[0161] Among them, represents the closed - form of the average decoding error probability, , represents the cumulative distribution function of the legitimate user terminal.

[0162] The closed - form of the average decoding error probability can be used to evaluate the security and reliability of the entire system model.

[0163] Sub - step S1023: Analyze the secrecy outage probability of the system model, which can solve the problem of unknown achievable secrecy rate distribution. In addition, analyze the asymptotic performance of the secrecy capacity of the secrecy outage probability of the system model, which can evaluate the performance of the system model in the high - SNR scenario. Specifically, it includes the following process:

[0164] First, in the short - packet coding communication process, since the length of the channel block of the ground base station is limited, the decoding error probability and the information leakage probability can be constrained to ensure the security and reliability of network transmission. The secrecy outage probability can be defined as: when the length of the given channel block and the threshold of the achievable secrecy rate are given, if the achievable secrecy rate is less than the threshold of the achievable secrecy rate, and if the probability of violating the predetermined constraint, then the distribution of the achievable secrecy rate cannot be determined and cannot be directly solved. For this problem of unknown distribution, the moment - matching method is selected to calculate all moments, which can replace the unknown parameters. and are independent of each other, and it is relatively simple to solve all moments separately. Therefore, the achievable secrecy rate is approximated as a Gaussian distribution to obtain its various parameters.

[0165] Therefore, when the length of the channel block of the ground base station is and the threshold of the achievable secrecy rate is and when, the closed - form of the secrecy outage probability is calculated using the moment - matching method.

[0166] Furthermore, the expression of the closed - form of the secrecy outage probability is:

[0167] F ACR a ACR th =U{ ACR th - ACR a ¯ Ψ(AC R a ) }= 1 2πΨ( ACR a ) ∫ -∞ ACR th exp{- [ t- ACR a ¯ ] 2 2Ψ( ACR a ) }dt (14)

[0168] where represents the closed - form of the secrecy outage probability, represents the variance of the achievable secrecy rate, represents the Gaussian function.

[0169] Secondly, calculate the cumulative distribution function of the legitimate user terminal under the condition of high signal - to - noise ratio for the system model.

[0170] The parameters in the closed - form of the secrecy outage probability include complex forms of multiplication and accumulation, which are complex to solve when analyzing the performance of the system model. Therefore, the asymptotic secrecy outage probability is proposed under the scenario of signal - to - noise ratio Based on this condition, there is: , , the cumulative distribution function of the legitimate user terminal is Taylor - expanded, ignoring the high - order terms and only retaining the first - order terms, where represents the channel dispersion of represents or .

[0171] Therefore, the expression of the cumulative distribution function of the legitimate user terminal under the condition of high signal - to - noise ratio for the system model can be obtained as:

[0172] (15)

[0173] where represents the cumulative distribution function of the legitimate user terminal under the condition of high signal - to - noise ratio for the system model, represents the signal - to - noise ratio of the received signal of the legitimate user terminal under the condition of high signal - to - noise ratio for the system model.

[0174] Finally, using the cumulative distribution function of the legitimate user terminal under the condition of high signal - to - noise ratio for the system model, the closed - form of the asymptotic secrecy outage probability and the positive secrecy asymptotic capacity are respectively derived.

[0175] Furthermore, the closed-form expression for the asymptotic secrecy outage probability is as follows:

[0176] (16)

[0177] where denotes the closed-form of the asymptotic secrecy outage probability, .

[0178] The expression for the positive secrecy asymptotic capacity is:

[0179] (17)

[0180] where denotes the positive secrecy asymptotic capacity, denotes the probability when the achievable secrecy rate is positive, .

[0181] Under the condition of high signal-to-noise ratio, the positive secrecy asymptotic capacity of the system model can be defined as the probability that the achievable secrecy rate is greater than zero. The positive secrecy asymptotic capacity can be used as an indicator to evaluate the secrecy performance of the entire system model. High signal-to-noise ratio means that the signal-to-noise ratio of the signal is greater than 30 dB.

[0182] Step S103 of this embodiment: Evaluate the performance of the system model according to the results of the average achievable secrecy rate analysis, the average decoding error probability analysis, and the secrecy outage probability analysis. Step 103 of this embodiment may include the following sub-steps:

[0183] Sub-step S1031: When the result of the achievable secrecy rate analysis, i.e., the closed-form of the average achievable secrecy rate, is greater than or equal to , and the result of the average decoding error probability analysis, i.e., the closed-form of the average decoding error probability, is less than or equal to , and the result of the secrecy outage probability analysis, i.e., the closed-form of the secrecy outage probability, is less than or equal to , determine that the performance of the system model is excellent.

[0184] Sub-step S1032: When the result of the achievable secrecy rate analysis is between , and the result of the average decoding error probability analysis is greater than and less than or equal to , and the result of the secrecy outage probability analysis is greater than and less than or equal to , determine that the performance of the system model is medium.

[0185] Sub-step S1033: When the result of the achievable secrecy rate analysis is less than or equal to , and the result of the average decoding error probability analysis is greater than and less than or equal to , and the result of the secrecy outage probability analysis is greater than and less than or equal to , the performance of the system model is determined to be poor.

[0186] When the secrecy performance of the system model is poor, by increasing the number of reflecting elements in the reconfigurable intelligent surface, the result of the secrecy outage probability analysis is enhanced, and by increasing the length of the channel block of the ground base station and simultaneously enhancing the proportion of the line-of-sight link, the secrecy performance of the system model is improved.

[0187] To verify the applicability and superiority of a performance evaluation method for short-packet coded communication proposed in this application, the following simulation experiments were carried out.

[0188] In the simulation experiment, the position of the communication tower of the ground base station was set to (0,0), the position of the legitimate user terminal was set to (60,60m), the position of the non-target user terminal was set to (56,85m), and the position of the unmanned aerial vehicle carrying the reconfigurable intelligent surface was set to (40,40m). The path loss factor was set to 2.3. The number of bits of the transmitted signal per unit time was set to 100.

[0189] The data under the following 6 conditions were counted:

[0190] The number of reflecting elements of the reconfigurable intelligent surface;

[0191] The length of the channel block of the ground base station;

[0192] The Rice factor;

[0193] The threshold of the achievable secrecy rate;

[0194] The flight altitude of the unmanned aerial vehicle;

[0195] Security constraints and reliability constraints.

[0196] Based on this, simulation experiments were carried out and the following was obtained:

[0197] Figure 3 shows the relationship between the signal-to-noise ratio of the transmitted signal of the system model and the average achievable secrecy rate. From Figure 3 it can be seen that as the signal-to-noise ratio of the transmitted signal increases, more reflecting elements on the reconfigurable intelligent surface regulate the channel, enhancing the signal of the legitimate user terminal while suppressing the signal of the non-target user terminal, significantly improving the average achievable secrecy rate of the system model. Figure 3 in represents the length of the channel block of the ground base station, represents the number of reflecting elements in the reconfigurable intelligent surface.

[0198] Increasing the length of the channel block of the ground base station can support efficient coding and accurate channel observation. Short channel blocks are unreliable because a lot of error correction information is compressed, which will lead to a decline in the performance of the system model, especially when the number of reflecting elements of the reconfigurable intelligent surface is insufficient, the attenuation will be exacerbated. It can be seen that this simulation experiment verifies that the collaborative optimization between the number of reflecting elements of the reconfigurable intelligent surface and the length of the channel block of the ground base station plays a key role in balancing security and transmission rate, and also verifies the effectiveness of the average achievable secrecy rate analysis framework of the system model in this application.

[0199] Figure 4 It shows that the average decoding error probability of the system model decreases as the length of the channel block of the ground base station increases. Longer channel blocks are more reliable because they contain more error correction information, and the channel gain gradually saturates. Shorter channel blocks have insufficient coding redundancy, resulting in a sharp increase in the average decoding error probability, making it difficult to meet the requirements of the ultra-low decoding error rate in the short-packet coding communication scenario.

[0200] The number of reflecting elements of the reconfigurable intelligent surface and the Rice factor jointly regulate the performance of the system model. The larger the number of reflecting elements or the Rice factor, the stronger the path control and line-of-sight component of the channel signal, which significantly reduces the average decoding error probability. When the number of reflecting elements or the Rice factor becomes smaller and smaller, the performance of the system model will gradually deteriorate. This simulation experiment shows that the length of the channel block of the ground base station needs to balance delay and reliability. If the channel block is short, it is necessary to increase the compensation performance of the reflecting elements or the Rice factor, and enhancing the line-of-sight component is crucial for improving the security of the system model. The Monte Carlo results are consistent with the theoretical trend, which also verifies the effectiveness of the average decoding error probability analysis framework of the system model in this application.

[0201] Figure 5 It shows that as the signal-to-noise ratio of the transmitted signal increases, the secrecy outage probability of the system model will decrease significantly. This is because the expansion of the channel quality difference between the legitimate user terminal and the non-target user terminal will enhance the secrecy performance of the system model. When the threshold of the achievable secrecy rate is very low, for example, , the secrecy outage probability of the system model will be even lower, indicating that the security requirements of the system model are more easily met. The Monte Carlo simulation results are highly consistent with the Gaussian approximation results, which verifies the effectiveness of the theoretical method in this application.

[0202] Figure 6It is shown that with the increase in the number of reflecting elements of the reconfigurable intelligent surface and the length of the channel block of the ground base station, the positive secrecy asymptotic capacity of the system model can be significantly improved. By increasing the number of reflecting elements of the reconfigurable intelligent surface, the performance gain of the system model can be achieved by optimizing the quality of the signal channel and interference suppression; by increasing the length of the channel block of the ground base station, the data processing ability is enhanced, thereby improving the secrecy performance of the system model. However, more stringent reliability constraints (i.e., the decoding error probability of the legitimate user terminal ), and security constraints (i.e., the information leakage rate of the legitimate user terminal ), require additional power compensation to maintain the level of the positive secrecy asymptotic capacity of the system model. Increasing the altitude of the unmanned aerial vehicle will weaken the secrecy performance of the system model due to the path loss of the channel signal and environmental changes. The results of this simulation experiment show that it is necessary to jointly optimize various parameters such as the number of reflecting elements , the length of the channel block , the signal power and layout, etc., so as to achieve the global optimization of the security performance of the system model under complex conditions.

[0203] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of the present application, "a plurality" means two or more, unless otherwise specifically defined.

[0204] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example" or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, those skilled in the art can combine and combine the different embodiments or examples described in this specification.

[0205] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or substitutions within the technical scope disclosed by the present application, and these modifications or substitutions should all be covered within the protection scope of the present application.

[0206] Those skilled in the art will readily conceive of other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include known common general knowledge or conventional technical means in the technical field not disclosed in the present application.

Claims

1. A performance evaluation method for short packet coding communication, characterized in that, The method includes the following steps: Construct a system model for short-packet coded communication, where the system model includes a ground base station, a drone, a legitimate user terminal, and a non-target user terminal connected by communication. A reconfigurable intelligent surface is configured on the drone. According to all the channel state information of the system model, perform average achievable secrecy rate analysis, average decoding error probability analysis, and secrecy outage probability analysis on the system model in sequence. Evaluate the performance of the system model according to the results of the average achievable secrecy rate analysis, the results of the average decoding error probability analysis, and the results of the secrecy outage probability analysis.

2. The performance evaluation method for short packet coding communication according to claim 1, characterized in that, The reconfigurable intelligent surface includes a reflection array composed of multiple reflection elements with the same structure, and a single antenna is respectively configured on each reflection element; the ground base station, the legitimate user terminal, and the non-target user terminal are respectively configured with the single antenna. The expression of the phase shift matrix of the reconfigurable intelligent surface is: (1) Among them, represents the phase shift matrix of the reconfigurable intelligent surface, represents the constructed diagonal matrix, represents the imaginary unit, represents the phase shift of the th reflecting element of the reconfigurable intelligent surface; The one for the ground base station indicates that the position of the ground base station is represented by . , represents the axis coordinate of the ground base station, and represents the For the drone It is indicated that the position of the drone is represented by and , represents the axial coordinate of the drone, represents the axial coordinate of the drone, and represents the height of the drone; The legal client uses to indicate that the location of the legal client is indicated by , indicating the x-axis coordinate of the legal client and indicating the y-axis coordinate of the legal client; The non-target client uses to indicate that the position of the non-target client is indicated by , indicating the axial coordinate of the non-target client, and indicating the axial coordinate of the non-target client.

3. The performance evaluation method for short packet coding communication according to claim 1, characterized in that Both the legitimate user terminal and the non-target user terminal receive two types of channel signals. The first type of channel signal is the direct link signal transmitted from the ground base station, and the second type of channel signal is the reflected link signal from the reconfigurable intelligent surface. The expression of the received signal of the legitimate user terminal is: (2) Among them, represents the received signal of a legitimate user terminal, represents the signal transmission power of a ground base station, represents the transmitted signal of the ground base station and satisfies , represents the expected value of represents the channel distance from the ground base station to the UAV, represents the channel distance from the UAV to the legitimate user terminal, represents the path loss coefficient of the channel signal from the ground base station to the UAV, represents the path loss coefficient of the channel signal from the UAV to the legitimate user terminal, represents the th reflecting element of the reconfigurable intelligent surface, represents the number of all reflecting elements of the reconfigurable intelligent surface, represents the complex channel gain from the ground base station to the reconfigurable intelligent surface on the UAV, , represents the channel phase shift coefficient of the th reflecting element from the ground base station to the reconfigurable intelligent surface on the UAV, , represents the imaginary unit, represents the complex channel gain from the reconfigurable intelligent surface on the UAV to the legitimate user terminal, , represents the channel phase shift coefficient of the th reflecting element from the reconfigurable intelligent surface on the UAV to the legitimate user terminal, , represents the phase shift of the th reflecting element of the reconfigurable intelligent surface, represents the channel distance from the ground base station to the legitimate user terminal, represents the path loss coefficient of the channel signal from the ground base station to the legitimate user terminal, represents the interference noise of the legitimate user terminal, represents the complex channel gain from the ground base station to the legitimate user terminal, , represents the channel phase shift coefficient from the ground base station to the legitimate user terminal, ; The expression of the received signal of the non-target user terminal is: (3) Among them, represents the received signal of the non-target user terminal, represents the path loss coefficient of the channel signal from the UAV to the non-target user terminal, represents the complex channel gain from the reconfigurable intelligent surface on the UAV to the non-target user terminal, , represents the th reflection element on the reconfigurable intelligent surface on the UAV to the channel phase shift coefficient of the non-target user terminal, , represents the channel distance from the ground base station to the non-target user terminal, represents the channel distance from the UAV to the non-target user terminal, represents the path loss coefficient of the channel signal from the ground base station to the non-target user terminal, represents the interference noise of the non-target user terminal, represents the complex channel gain from the ground base station to the non-target user terminal, , represents the channel phase shift coefficient from the ground base station to the non-target user terminal, .

4. The performance evaluation method for short packet coding communication according to claim 1, wherein According to all the channel state information of the system model, the steps for performing the average achievable secrecy rate analysis on the system model include: Adjust the reconfigurable intelligent surface to the optimal phase shift according to the received signal of the legitimate user terminal, and respectively obtain the optimal signal-to-noise ratio of the legitimate user terminal and the instantaneous signal-to-noise ratio of the non-target user terminal. Model the optimal signal-to-noise ratio of the legitimate user terminal as a random distribution variable of the gamma function, and use the moment matching method to respectively deduce the probability density function and the cumulative distribution function of the legitimate user terminal. Model the instantaneous signal-to-noise ratio of the non-target user terminal as an exponential distribution variable of the gamma function, and use the moment matching method to respectively deduce the probability density function and the cumulative distribution function of the non-target user terminal. Use the achievable secrecy rate of the system model, the probability density function of the legitimate user terminal, and the probability density function of the non-target user terminal to determine the closed form of the average achievable secrecy rate of the system model.

5. The performance evaluation method for short packet encoding communication according to claim 4, characterized in that The expression of the probability density function of the legitimate user terminal is: (4) Among them, represents the probability density function when the signal-to-noise ratio of the received signal by the legitimate user terminal is ; represents the signal transmission power of the ground base station, represents the signal-to-noise ratio of the received signal of the legitimate user terminal, represents the optimal signal-to-noise ratio of the legitimate user terminal, , , represents the th reflection element of the reconfigurable intelligent surface, represents the number of all reflection elements of the reconfigurable intelligent surface, represents the complex channel gain from the ground base station to the reconfigurable intelligent surface on the unmanned aerial vehicle, , represents the channel phase shift coefficient of the th reflection element from the ground base station to the reconfigurable intelligent surface on the unmanned aerial vehicle, , represents the imaginary unit, represents the complex channel gain from the reconfigurable intelligent surface on the unmanned aerial vehicle to the legitimate user terminal, , represents the channel phase shift coefficient of the th reflection element from the reconfigurable intelligent surface on the unmanned aerial vehicle to the legitimate user terminal, , , represents the path loss coefficient of the channel signal from the ground base station to the unmanned aerial vehicle, represents the path loss coefficient of the channel signal from the unmanned aerial vehicle to the legitimate user terminal, represents the channel distance from the ground base station to the unmanned aerial vehicle, represents the channel distance from the unmanned aerial vehicle to the legitimate user terminal, , represents the channel distance from the ground base station to the legitimate user terminal, represents the path loss coefficient of the channel signal from the ground base station to the legitimate user terminal, represents the complex channel gain from the ground base station to the legitimate user terminal, , represents the channel phase shift coefficient from the ground base station to the legitimate user terminal, , represents the shape parameter, represents the exponential function, represents the scale parameter, represents the gamma function; The expression of the cumulative distribution function of the legitimate user terminal is: (5) Among them, represents the cumulative distribution function when the signal-to-noise ratio of the legitimate client for receiving signals is ; The expression of the probability density function of the non-target user terminal is: (6) Among them, represents the probability density function when the signal-to-noise ratio of the received signal at the non-target user terminal is ; represents the signal-to-noise ratio of the received signal at the non-target user terminal, represents the rate parameter of the exponential distribution, represents the instantaneous signal-to-noise ratio of the non-target user terminal, , , represents the path loss coefficient of the channel signal from the UAV to the non-target user terminal, represents the channel distance from the UAV to the non-target user terminal, represents the complex channel gain from the reconfigurable intelligent surface on the UAV to the non-target user terminal, , represents the th channel phase shift coefficient of the reflection element from the reconfigurable intelligent surface on the UAV to the non-target user terminal, , represents the net phase difference of the non-target user terminal, , represents the channel distance from the ground base station to the non-target user terminal, represents the path loss coefficient of the channel signal from the ground base station to the non-target user terminal, represents the complex channel gain from the ground base station to the non-target user terminal, , represents the channel phase shift coefficient from the ground base station to the non-target user terminal, ; The expression of the cumulative distribution function of the non-target user terminal is: (7) Among them, represents the cumulative distribution function when the signal-to-noise ratio of the non-target client for receiving signals is .

6. The performance evaluation method for short packet coding communication according to claim 5, characterized in that The steps for using the achievable secrecy rate of the system model, the probability density function of the legitimate user terminal, and the probability density function of the non-target user terminal to determine the closed form of the average achievable secrecy rate of the system model include: When the length of the channel block of the ground base station is constant, and the decoding error probability of the legitimate user terminal is less than or equal to the decoding error probability threshold, and the information leakage rate of the legitimate user terminal is less than or equal to the information leakage rate threshold, if , then the achievable secrecy rate is 0, and the achievable secrecy rate is represented by . represents the length of the channel block of the ground base station, represents the decoding error probability of the legitimate user terminal, represents the information leakage rate of the legitimate user terminal; If , the closed-form expression of the achievable secrecy rate is as follows: (8) Among them, represents the closed-form expression of the achievable secrecy rate of the system model, represents the achievable secrecy rate of the legitimate user terminal, , represents the achievable secrecy rate of the non-target user terminal, , represents the secrecy rate during long-packet coded communication, , represents the channel dispersion of the legitimate user terminal, , represents the channel dispersion of the non-target user terminal, , represents the inverse function of the function, represents the inverse function of the function, represents the integration variable; The expression of the closed form of the average achievable secrecy rate is: (9) Among them, represents a closed-form expression for the average achievable secrecy rate, represents the Meijer's G function, represents the Fox-H function, , , represents the summation variable. When , , and when , .

7. The performance evaluation method for short packet coding communication according to claim 6, wherein According to all the channel state information of the system model, the steps for performing the average decoding error probability analysis on the system model include: When the decoding error probability is equal to 1; When the expression of the decoding error probability is as follows: (10) Among them, represents the right-tail function of the standard normal distribution, , denotes the variable of denotes the number of bits of the transmission signal of the ground base station; Using the linear approximation theory, let be approximated to a linear function to simplify the computational complexity of formula (10), that is, to satisfy , and the expression of the linear function is: (11) Among them, , , represents the lower bound of the achievable secrecy rate, , represents the upper bound of the achievable secrecy rate, , represents the variable of the linear function . Let , after re - expressing as , substitute the linear function into formula (10), and calculate the average value of all the decoding error probabilities to obtain the average decoding error probability; The expression of the average decoding error probability is: (12) Among them, represents the average decoding error probability, represents the auxiliary variable, represents the cumulative distribution function when the legitimate user end is at the lower bound of the achievable secrecy rate, represents the cumulative distribution function when the legitimate user end is at the upper bound of the achievable secrecy rate, represents when the variable is equal to a linear function at this time; Solve using integration by parts , and at the same time use the Riemann integral to rewrite to obtain a closed form of the average decoding error probability; The expression of the closed form of the average decoding error probability: (13) Among them, represents a closed - form expression for the average decoding error probability, the cumulative distribution function of the legitimate user terminals.

8. The performance evaluation method for short packet encoded communication according to claim 6, wherein The steps of performing the secrecy outage probability analysis on the system model according to all the channel state information in the system model include: When the length of the channel block of the ground base station is , and the threshold of the achievable secrecy rate is , and , the closed - form of the secrecy outage probability is calculated using the moment - matching method; Calculating the cumulative distribution function of the legitimate user terminal under the condition of high signal-to-noise ratio in the system model; Using the cumulative distribution function of the legitimate user terminal under the condition of high signal-to-noise ratio in the system model to respectively derive the closed form of the asymptotic secrecy outage probability and the positive secrecy asymptotic capacity.

9. The performance evaluation method of short-packet coding communication according to claim 8, characterized in that The expression of the closed form of the secrecy outage probability is: (14) wherein a closed - form expression representing the secrecy outage probability the variance of a closed - form expression representing the achievable secrecy rate denotes the Gaussian function The expression of the cumulative distribution function of the legitimate user terminal under the condition of high signal-to-noise ratio in the system model is: (15) Among them, represents the cumulative distribution function of the legitimate user terminal under the condition of large signal-to-noise ratio in the system model, represents the signal-to-noise ratio of the received signal of the legitimate user terminal under the condition of large signal-to-noise ratio in the system model; The expression of the closed form of the asymptotic secrecy outage probability is: (16) Among them, represents a closed formula for the asymptotic secrecy outage probability, ; The expression of the positive secrecy asymptotic capacity is: (17) Among them, represents the positive secrecy asymptotic capacity, represents the probability when the achievable secrecy rate is positive, .

10. The performance evaluation method for short packet coding communication according to claim 1, wherein The steps of evaluating the performance of the system model according to the results of the achievable secrecy rate analysis, the average decoding error probability analysis, and the secrecy outage probability analysis include: When the result of the achievable secrecy rate analysis is greater than or equal to , and the result of the average decoding error probability analysis is less than or equal to , and the result of the secrecy outage probability analysis is less than or equal to , the performance of the system model is determined to be excellent; When the result of the achievable secrecy rate analysis is between and the result of the average decoding error probability analysis is greater than and less than or equal to , and the result of the secrecy outage probability analysis is greater than and less than or equal to , the performance of the system model is determined to be medium; When the result of the achievable secrecy rate analysis is less than or equal to , and the result of the average decoding error probability analysis is greater than and less than or equal to , and the result of the secrecy outage probability analysis is greater than and less than or equal to , the performance of the system model is determined to be poor.

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