Discrete simulator for wireless channel attenuation in 5G non-orthogonal mobile communication network

Abstract

The invention provides a discrete simulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network, and the method comprises the following steps: 1, building a first-order finite state Markov chain according to the input of the simulator; step 2, constructing a new Markov chain based on the first-order finite state Markov chain obtained in the step 1 according to the set number of users in a single user group in the 5G non-orthogonal mobile communication network, and obtaining a state space and a transition probability matrix; and step 3, generating and outputting a simulation result according to the state space and the transition probability matrix obtained in the step 2 and the set length of the time sequence output by the simulator, and completing discrete simulation of wireless channel attenuation in the 5G non-orthogonal mobile communication network. The system has the advantages of being clear in structure, high in self-adaption and high in execution efficiency, the requirements of 5G network construction operation and maintenance and academic research are well met, and the system has high practical value and generalizability.

Description

Technical Field

[0001] The present invention relates to a simulator for wireless channel attenuation, in particular to a discrete simulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network. Background Art

[0002] The information provided in this part is only background information related to the present disclosure, and it is not necessarily prior art.

[0003] Compared with the 4G network, the 5G network serves more users, supports higher rates, supports unlimited connections, provides personalized experiences, and opens the door to the Internet of Everything. Wireless non-orthogonal multiple access is a new multiple access technology in the physical layer of 5G mobile communication. It uses joint superposition coding at the transmitter and successive interference cancellation at the receiver to provide services to different users in the same resource block. In a 5G non-orthogonal mobile communication network, the data transmission rate of each user within the same user group is affected by the sorting of the wireless channel attenuation magnitudes of the users in this group.

[0004] Currently, whether it is the actual construction and operation and maintenance of the 5G network or its theoretical academic research, a wireless channel attenuation simulator for a single user is required to support related work. In particular, a simulator based on a discrete finite-state random variable is highly favored. Specifically, according to the probability density function of the instantaneous signal-to-noise ratio SNR at the receiver input and the artificially set N state numbers, a simulator can automatically and continuously output a series of random state sequences indicating the magnitudes of the wireless channel attenuation SNR.

[0005] Considering the technical characteristics of wireless non-orthogonal multiple access, a traditional simulator cannot meet the requirements of wireless channel testing and simulation for a single user in a 5G non-orthogonal mobile communication network. Then, multiple traditional simulators with the same number as the users in the user group where the user is located can be set to output in parallel. After further comparing, sorting, and calculating the output results, the discrete state to which the wireless channel attenuation of the target user belongs in the current corresponding wireless non-orthogonal multiple access environment can be determined. Although such a method is intuitive, it occupies a lot of resources, has a slow result output, and low efficiency, and its application is limited. Therefore, there is currently a lack of a simple and practical discrete simulator that can match the wireless channel attenuation in a 5G non-orthogonal mobile communication network.

[0006] It should be noted that the information disclosed in the above background art section is only used to enhance the understanding of the background of the present disclosure. Therefore, it may include information that does not constitute prior art known to those of ordinary skill in the art. Summary of the Invention

[0007] Object of the Invention: The technical problem to be solved by the present invention is to provide a discrete simulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network in view of the deficiencies of the prior art.

[0008] To solve the above technical problems, the present invention discloses a discrete emulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network, including the following steps: Step 1, establish a first-order finite-state Markov chain according to the input of the emulator; Step 2, based on the number of users in a single user group in the set 5G non-orthogonal mobile communication network , construct a new Markov chain based on the first-order finite-state Markov chain obtained in Step 1 , and obtain the state space and the transition probability matrix; Step 3, generate and output a simulation result according to the state space and the transition probability matrix obtained in Step 2 and the length of the time series set to be output by the emulator, and complete the discrete simulation of the wireless channel attenuation in the 5G non-orthogonal mobile communication network.

[0009] Furthermore, the input of the emulator in Step 1, that is, the probability density function of the instantaneous signal-to-noise ratio SNR at the receiving end and the set number of states of a single wireless channel , time interval unit value.

[0010] Furthermore, the simulation result in Step 3 is a time series including state identifiers and the magnitudes of the corresponding instantaneous signal-to-noise ratio SNR at the receiving end.

[0011] Furthermore, the establishment of the first-order finite-state Markov chain in Step 1 includes: Step 1-1, use to represent the instantaneous signal-to-noise ratio SNR thresholds at the receiving end arranged in ascending order, and satisfy and conditions, divide the entire SNR range into a series of non-overlapping intervals with boundary values of ; among them, the boundary values are calculated and selected by the equal probability EP method; selection; Step 1-2, use to represent the state space of a stationary first-order finite-state Markov chain containing states, which is expressed as follows: ; Among them, represents the th state, and the intervals divided in Step 1-1 correspond to states; Step 1-3, calculate the state transition probability, which is expressed as follows: ; Among them, is the transition probability from the th state to the th state . In steps 1-4, the time axis is divided into intervals of equal size . Then, at discrete time , a first-order finite-state Markov chain is constructed to represent the time-varying characteristics of the wireless channel attenuation, as follows: ; Among them, is the steady-state probability, is the instantaneous SNR threshold at the receiving end, represents the level crossing rate of the SNR value at the receiving end at , and the calculation method is as follows: ; Among them, represents the maximum Doppler frequency, is the exponential function; the steady-state probability is calculated as follows: ; The average value of the instantaneous signal-to-noise ratio SNR at the receiving end is , and the specific calculation method is as follows: ; Among them, represents the instantaneous signal-to-noise ratio SNR at the receiving end, and its probability density function is .

[0012] Furthermore, the construction of the new Markov chain described in step 2 includes: Step 2-1, according to the set number of users within a single user group in the 5G non-orthogonal mobile communication network, a coding table is constructed and used to represent the state space of the new Markov chain . In the coding table, numbers represent the corresponding states, and the number of states is set to ; Step 2-2, according to the coding table, the state space of the new Markov chain is represented as follows: ; Among them, represents the state space of the new Markov chain in the th state; Step 2-3, let be the transition probability from state to state . Calculate the transition probability according to the coding table, then the transition probability matrix of the new Markov chain is expressed as .

[0013] Furthermore, the construction of the coding table described in Step 2-1 includes: Step 2-1-1, define that in the coding table represents the column number, represents the highest digit, represents the lowest digit, and the digits decrease successively from to ; Step 2-1-2, set the coding table rules and generate the coding table according to the rules; Step 2-1-3, calculate the number of states in the state space of the new Markov chain according to the coding table.

[0014] Furthermore, the setting of the coding table rules described in Step 2-1-2 includes: The content in the coding table is set according to the following rules: Rule 1, all columns in the table start from 1 and end with ; Rule 2, among the numbers in the th column in the same row of the coding table, the number in the higher digit is not greater than the number in the lower digit; Rule 3, combining the columns, it is based on a -ary counting method; where the radix is , the digits on the digits are composed of 1 to , add 1 successively on the lowest digit, and carry 1 to the higher digit every time ; Rule 4, the valid numbers in each row of the coding table satisfy Rule 2 and Rule 3; Rule 5, the numbers in column increase by 1 for each row starting from 1.

[0015] Furthermore, the calculation of the number of states in the state space of the new Markov chain described in Step 2-1-3 includes: After generating the coding table according to Rules 1 to 5, calculate that in the state space of the new Markov chain , the number of states is : .

[0016] Furthermore, the transition probability calculated according to the coding table in step 2-3 , includes: Step 2-3-1, let the state be denoted as , and the state be denoted as , and for the state , construct the set , and for the state , construct the set ; Step 2-3-2, list all possible permutations of the elements in the set , which are represented as follows: ; List all possible permutations of the elements in the set , which are represented as follows: ; Step 2-3-3, define a mapping function , which is represented as follows: ; According to the above mapping function, make a mapping on the permutation , and obtain a new set , which is represented as follows: ; Step 2-3-4, construct the target set based on the set , specifically including: For any element in the set , successively take a number from each of the numbers in , and form a group with the selected numbers. For this element of the set , list all possible obtained groups, denoted as , record the correspondence information between the element in the set and the group , denoted as ; Store all the groups and the correspondence information in the set , and obtain the target set ; Step 2-3-5, take the set as the arrow set, and check The results are as follows: If , then ; If , then calculate , and the specific method is as follows: ; Among them, the set , let be an element of the set , then according to the corresponding relationship information, the corresponding element of this element in the set is obtained , represents the transition probability from the th state to the th state of the first-order finite-state Markov chain established in step 1.

[0017] Furthermore, the generation and output of the simulation results described in step 3 include: Step 3-1, determine the initial state, that is, select a state from the state space as the initial state ; Step 3-2, generate subsequent states, that is, set the current time as , the current state as , according to the row corresponding to the state in the transition probability matrix as the transition probability distribution , and calculate a series of intervals , , ,…, , the number of intervals is ; Generate a uniform random number , compare with this interval , then the serial number of the interval where falls is the serial number of the next state, so as to determine the next state ; Step 3-3, repeat the generation, add the state generated in step 3-2 to the time series, and set it as the new current state , repeat steps 3-2 and 3-3 until the generated time series meets the length of the time series output by the set simulator; , the output includes a time series containing status identifiers and the corresponding instantaneous SNR size intervals of the receiving end.

[0018] Beneficial effects

[0019] 1. The emulator proposed by the present invention meets the needs of network construction, operation and maintenance, and academic research. This design has the advantages of clear structure, strong adaptability, high execution efficiency, etc., as follows: 2. Each part of the emulator of the present invention is relatively independent and has a simple logic.

[0020] 3. The discrete emulator of the present invention only requires 5 input quantities, including: the probability density function of the instantaneous SNR of the receiving end, the number of states of a single wireless channel, the numerical value of the time interval unit, the number of users in a single user group, and the length of the time series required for the output of the emulator. These are all general variables and functions. In particular, the specific type and expression of the probability density function are not limited, which makes the present invention have strong adaptability.

[0021] 4. The present invention realizes that only a single discrete emulator can meet the wireless channel test simulation requirements of a single user in a 5G non-orthogonal multiple access mobile communication network, and only one process of generating a time series is used in the design, so the execution efficiency is high. Description of the drawings

[0022] The following further specifically describes the present invention in conjunction with the drawings and specific embodiments, and the above and / or other advantages of the present invention will become clearer.

[0023] Figure 1 It is a schematic diagram of a first-order FSMC model.

[0024] Figure 2 It is a schematic diagram of the coding representation of the state space of the present invention.

[0025] Figure 3 It is a schematic diagram of the overall architecture of the present invention.

[0026] Figure 4 It is a schematic diagram of an example of the coding table rule in an embodiment. Specific embodiments

[0027] The present invention proposes a discrete emulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network, as Figure 3 shown, including: Step 1, according to the input probability density function of the instantaneous SNR of the receiving end and the artificially set number of states of a single wireless channel and the numerical value of the time interval unit , establish a first-order finite state Markov chain FSMC, as Figure 1 shown, and the specific process includes: Use to represent the instantaneous signal-to-noise ratio SNR at the receiving end, and its probability density function is ; given by an external input specific expression; calculate average value of as:

[0028] Use to represent the state space of a stationary first-order FSMC with states. The state transitions of this FSMC only occur between adjacent states. Therefore, it can be obtained that:

[0029] where is the transition probability from state to state . Based on the properties of the first-order FSMC, for , there is . In addition, there are and . Use to represent the steady-state probability.

[0030] The time axis is divided into intervals of equal size with a unit of , then a first-order FSMC can be constructed at discrete time to represent the time-varying characteristics of the wireless channel attenuation. Use to represent the instantaneous SNR thresholds at the receiving end arranged in ascending order, and and . The entire SNR range is divided into a series of non-overlapping interval intervals with boundary values of . If the instantaneous SNR value at the receiving end at time is within the interval , then the state of the channel at this time is called state . That is, in short, there is . In a wireless network, the movement of a mobile terminal at a certain speed will cause the Doppler frequency effect. It determines the fading characteristics of the signal envelope in the channel. Use to represent the maximum Doppler frequency, then given the boundary value of the fading channel, the transition probabilities and can be approximated as the following expressions:

[0031] where represents at The level passing rate of the received - end SNR value is deduced as . In addition, through Equation , the steady - state probability can be obtained. The boundary value is calculated by the equal - probability EP method for selection.

[0032] Step 2: According to the number of users in a single user group in the artificially set 5G non - orthogonal mobile communication network, a new Markov chain is constructed based on the FSMC obtained in Step 1. Its state space and transition probability matrix are given. The specific process includes: For the number of users in a single user group in the artificially set 5G non - orthogonal mobile communication network , the state space is represented as Figure 2 . A coding table is used to represent 's state space. For the sake of simplicity, in the coding table, and 's " " are omitted, and the corresponding states are directly represented by numbers. In this coding table, is set as the highest digit, is set as the lowest digit. The digits decrease successively from to .

[0033] The rules of the coding table are as follows: 1) All columns in the table start from 1. When the whole table ends, the column ends simultaneously with .

[0034] 2) In the same row of the coding table, for , the number on the high - digit should not be greater than the number on the low - digit .

[0035] 3) Combining the columns is based on a -ary counting method. The radix is , and the digits on the number are composed of 1 to . The counting rule is to increment by 1 successively on the digit , and carry over to the higher - level digit whenever , where .

[0036] 4) The valid digits in each row of the coding table must satisfy Rule 2) and Rule 3) above.

[0037] 5) Column Each increment is 1.

[0038] Then, in the state space of The number of states is, which is a multi - level series summation and can be obtained as:[[]]

[0039] Construct The transition probability matrix of is as follows: Use to represent the state space of, then . Here represents the number of elements in a set. is the transition probability from state to state , then the transition probability matrix of is . Corresponding to Figure 2 in the coding table of , let state be , and state be . Then, through the following steps, obtain , that is: 1) For state , construct the set . For state , construct the set .

[0040] 2) List all possible permutations of the elements in set A:

[0041] List all possible permutations of the elements in set B:

[0042] It should be noted that here the permutations obtained from the same set are distinguished from each other by specific numbers, rather than by the abstract symbols in step 2).

[0043] 3) Define a mapping function , that is:

[0044] This means that for , a new set is generated. Here for , is an element in of In the whole If a mapping is made above, a new set is obtained:

[0045] Obviously, the set is nested in the elements of .

[0046] 4) Construct a set called the target set from . .

[0047] Specifically, consider an element of the set , and take one number from each of the K in turn, and form a group with these selected numbers. For this element of the set , list all possible groups obtained, that is , and record the correspondence information between and in and . .

[0048] Finally, the set contains all possible formed from all elements of . And all correspondence information is recorded in a table in the form of . It should be noted that allows duplicate data, while the corresponding are distinct.

[0049] 5) Call the arrow set and check the result of . If , then it is impossible for a transition to occur from state to state , that is . If , then can be calculated. Further assume that , is an element of the set . According to the table , the corresponding element in is obtained, that is .

[0050] In other words, there is . For , the derived formula is obtained, where is in the steady-state first-order FSMC from state to the state transition probability. Then, when it is the case that it can be obtained from obtained.

[0051] Step 3, based on the state space and transition probability matrix obtained in Step 2, generate and output a time series containing state identifiers and the corresponding instantaneous signal-to-noise ratio SNR magnitudes at the receiving end according to the length of the desired emulator output time series set by humans. The specific process includes: 1) Determine the initial state, that is, select a state from the state space as the initial state arbitrarily. .

[0052] 2) Generate subsequent states. That is, let the current time be , and the state be . According to the row corresponding to the state in the transition probability matrix as the transition probability distribution ; Generate a uniform random number , calculate the cumulative probability, and accumulate item by item until it falls into the corresponding interval to determine the next state .

[0053] 3) Repeat generation, add the new state to the time series and use it as the new current state , and repeat Step 2) until a sequence of the length of the desired emulator output set by humans is generated.

[0054] 4) Organize and output a time series containing state identifiers and the corresponding instantaneous signal-to-noise ratio SNR magnitude intervals at the receiving end.

[0055] Example 1: A discrete emulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network provided by an embodiment of the present invention is applied to the wireless channel test of a single user in a 5G non-orthogonal multi-user access mobile communication network to support network construction operation and maintenance and academic theoretical research, and includes the following steps: Step 1: Complete the calculation according to the input variables and functions, and establish a first-order finite state Markov chain FSMC as follows: 1-1. The equal probability EP method determines the boundary value through . Considering , can be obtained by solving the equation . Then, It can be obtained by solving the equation , and so on. Finally, unknowns, that is can be obtained by solving equations.

[0056] 1 - 2. Calculate ; successively calculate to obtain the steady - state probability .

[0057] 1 - 3. Successively calculate , (where ), (where ), so as to obtain the transition probability matrix of the first - order finite - state Markov chain FSMC.

[0058] Step 2: Construct a new Markov chain , and give its state space and transition probability matrix , as follows: 2 - 1. Calculate the number of states in the state space of , and generate the state - space coding table shown in Figure 2 .

[0059] 2 - 2. Calculate the values of each in the transition probability matrix of , as follows: 2 - 2 - 1. Corresponding to of the coding table, when state is , state is , for state , construct the set . For state , construct the set .

[0060] 2 - 2 - 2. List all possible permutations of the elements in set A:

[0061] List all possible permutations of the elements in set B:

[0062] It should be noted that the permutations obtained from the same set are distinguished by specific numbers here, rather than the abstract symbols in this step. For example, when assuming , there are and . Although from the perspective of abstract symbols, is different from , from the perspective of specific numbers, the two are the same, that is, . Therefore, in , only one is retained.

[0063] 2-2-3. Give the mapping function .

[0064] This means that for , a new set is generated. Here for , is an element in . Mapping over the entire , then a new set is obtained:

[0065] Obviously, the set is nested in the elements of . For example, given , then in there is .

[0066] 2-2-4. Construct a target set from .

[0067] Specifically, consider an element of the set . Take a number from each of the K in turn, and form a group with these selected numbers. For the element of the set , list all possible groups obtained, that is, , and record the correspondence information between in and . For example, given , in , and in , then there is , which contains a total of groups. At the same time, is .

[0068] Finally, the set contains elements from All possible formed by all elements . And all the corresponding relationship information is simultaneously recorded in a table in the form of . It should be noted that allows duplicate data, while the corresponding are distinct. For example, given and in , then contains . And there is . Considering correspondingly has in there is . And there is . Therefore, although there are two in , they can be distinguished according to the corresponding in , that is:

[0069] 2-2-5. Call the arrow set and check the result of . If , then it is impossible to have a transition from state to state , that is . If , then the can be calculated. Further assume that , is an element of the set . According to the table , the corresponding element in is obtained, that is .

[0070] In other words, there is . For , the derived formula , where is the transition probability from state to state in the steady-state first-order FSMC. Then, when , can be obtained from .

[0071] Step 3: For , generate and output a time series containing the state identifier and the corresponding instantaneous SNR size interval of the receiving end, as follows: 3-1. From the state space Select any one of the states as the initial state .

[0072] 3-2. Let the current time be , the state be , according to the transition probability matrix , use the row corresponding to the state as the transition probability distribution ; Generate a uniform random number , calculate the cumulative probability, and accumulate item by item until it falls into the corresponding interval to determine the next state . For example, for , , four intervals can be divided: . When , there is , then , the next state of the current state is .

[0073] 3-3. Add the new state to the time series and use it as the new current state , and repeat step 3-2 until a sequence with the required emulator output length set by humans is generated.

[0074] 3-4. Organize and output a time series containing state identifiers and the corresponding instantaneous SNR size intervals at the receiving end.

[0075] Example 2: In one embodiment, as shown in Figure 4 , taking , as an example, the coding table rules are specifically described.

[0076] Example 3: In the case where the coding table rules are as in Example 2, assume that after steps 3-1, 3-2, and 3-3, a state sequence is obtained, that is, .

[0077] For the time t = 2, according to the coding table shown in Example 2, , then according to the first-order finite-state Markov chain established in step 1, the entire SNR range is divided into a series of non-overlapping interval intervals with boundary values of , until The one corresponding to "2" is the SNR interval 2, and the one corresponding to "4" is the SNR interval 4. Therefore, at the output time t = 2, there is "( ) status identifier 16", "The instantaneous SNR size interval of the receiving end: SNR interval 2, SNR interval 4, SNR interval 4".

[0078] Those skilled in the art can clearly understand that the technical solutions in the embodiments of the present invention can be implemented by means of a computer program and its corresponding general hardware platform. Based on such an understanding, the essence of the technical solutions in the embodiments of the present invention, or the part that contributes to the prior art, can be embodied in the form of a computer program, that is, a software product. The computer program software product can be stored in a storage medium, including several instructions for causing a device including a data processing unit (which can be a personal computer, a server, a single-chip microcomputer, an MCU or a network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of the present invention.

[0079] The present invention provides an idea and method for a discrete emulator of wireless channel attenuation in a 5G non-orthogonal mobile communication network. There are many methods and ways to specifically implement this technical solution. The above is only the preferred embodiment of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention. Each component not clearly defined in this embodiment can be implemented by the prior art.

Claims

1. A discrete emulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network, characterized in that Including the following steps: Step 1: Establish a first-order finite-state Markov chain according to the input of the emulator; Step 2, according to the number of users within a single user group in the configured 5G non-orthogonal mobile communication network , based on the first-order finite state Markov chain obtained in Step 1, construct a new Markov chain , and obtain the state space and the transition probability matrix; Step 3: Generate and output a simulation result according to the state space and transition probability matrix obtained in Step 2 and the set length of the time series output by the emulator, and complete the discrete simulation of the wireless channel attenuation in the 5G non-orthogonal mobile communication network.

2. The discrete emulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network according to claim 1, wherein The input of the emulator described in Step 1, namely, the probability density function of the instantaneous SNR at the receiving end and the number of states of a single wireless channel and the time interval unit numerical value.

3. The discrete emulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network according to claim 2, characterized in that The simulation result described in Step 3 is a time series including state identifiers and the magnitudes of the instantaneous signal-to-noise ratio (SNR) at the corresponding receiving end.

4. A discrete emulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network according to claim 3, characterized in that, The establishment of the first-order finite-state Markov chain described in Step 1 includes: Step 1-1, use to represent the instantaneous SNR threshold of the receiving end arranged in ascending order, and satisfy and Under the condition, divide the entire SNR range into a series of non-overlapping intervals with boundary values of ; among them, the boundary value is calculated by the equal probability EP method; of the selection. Step 1-2, use to represent the state space of a stationary first-order finite-state Markov chain with states, which is represented as follows: ； Among them, represents the th state, and corresponds to the intervals divided in Step 1-1 for states; Step 1-3: Calculate the state transition probability, expressed as follows: ； Among them, is from the th state to the th state transition probability; Steps 1-4, divide the time axis into intervals of equal size with a unit of , then, at discrete times , construct a first-order finite-state Markov chain to represent the time-varying characteristics of the wireless channel attenuation, as follows: ； wherein, is the steady-state probability, is the instantaneous SNR threshold at the receiving end, represents the level crossing rate of the SNR value at the receiving end at , and the calculation method is as follows: ； Among them, represents the maximum Doppler frequency, is an exponential function; the steady-state probability is calculated as follows: ； The average value of the instantaneous signal-to-noise ratio SNR at the receiving end is , and the specific calculation method is as follows: ； Among them, represents the instantaneous signal-to-noise ratio SNR at the receiving end, and its probability density function is .

5. A discrete emulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network according to claim 4, characterized in that, The construction of the new Markov chain described in Step 2 includes: Step 2-1, according to the number of users within a single user group in the set 5G non-orthogonal mobile communication network , construct a coding table and use it to represent the state space of a new Markov chain . In the coding table, numbers are used to represent corresponding states, and let the number of states be ; Step 2-2, according to the coding table, the state space of the new Markov chain is as follows: ,which is shown as follows: ； Among them, represents the state space of the new Markov chain ; The th state Step 2-3, set as the transition probability from state to state obtained by calculating according to the coding table, then the transition probability matrix of the new Markov chain is expressed as .

6. A discrete emulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network according to claim 5, characterized in that, The construction of the coding table described in Step 2-1 includes: Step 2-1-1, define that in the coding table, represents the column number, represents the highest digit, represents the lowest digit, and the digits decrease successively from to one by one. Step 2-1-2: Set the coding table rules and generate the coding table according to the rules; Step 2-1-3: Calculate the number of states in the state space of the new Markov chain according to the coding table.

7. A discrete emulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network according to claim 6, characterized in that The setting of the coding table rules described in Step 2-1-2 includes: The content in the coding table is set according to the following rules: Rule 1: All columns in the table start from 1 and end with ; Rule 2, among the numbers in the column in the same row of the coding table, the digit in the higher position is not greater than the digit in the lower position; Rule 3, combining columns results in a -ary counting method; where the base is , the digits on the digit positions are composed of 1 to , adding 1 successively on the lowest digit position, and carrying 1 to the higher digit position every time is reached; Rule 4, the valid digits in each row of the coding table Meet Rule 2 and Rule 3; Rule Five, Column The numbers in it increase by 1 for each row starting from 1.

8. A discrete emulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network according to claim 7, characterized in that, The calculation of the number of states in the state space of the new Markov chain according to the coding table described in Step 2-1-3 includes: After generating the coding table according to Rules 1 to 5, it is calculated that in the state space of the new Markov chain the number of states is : 。 9. A discrete emulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network according to claim 8, characterized in that The transition probability calculated according to the coding table as described in step 2-3 , including: Step 2-3-1, set the state is represented as , the state is represented as , and for the state , construct the set , for the state , construct the set ; Step 2-3-2, list the set All possible permutations of the elements in are represented as follows: ； List the set All possible permutations of the elements in, are represented as follows: ； Step 2-3-3, define a mapping function , which is expressed as follows: ； According to the above mapping function, on the permutation perform mapping to obtain a new set , which is represented as follows: ； Step 2-3-4, based on the set Construct the target set, specifically including: For the set in any element , successively from a in each take a number, and form a group with the selected numbers. For the element of the set , list all possible groups obtained, denoted as , record the correspondence information between the elements in the set and the group , denoted as ; ; Store all group and corresponding relationship information in a set to obtain a target set ; Step 2-3-5, take the set as the arrow set, and check the results, as follows: If , then ; If , then calculate as follows: ； Among them, the set is set to be an element of the set . Then, according to the corresponding relationship information, the corresponding element of this element in the set is obtained. represents the transition probability from the th state to the th state of the first-order finite state Markov chain established in Step 1.

10. A discrete emulator for wireless channel attenuation in a 5G non-orthogonal mobile communication network according to claim 9, characterized in that, The generation and output of the simulation result described in Step 3 includes: Step 3-1, determine the initial state, that is, select a state from the state space as the initial state ; Step 3-2, generate subsequent states, that is, set the current time as , the current state is , according to the transition probability matrix in the corresponding state of the row, as the transition probability distribution , and calculate a series of intervals , , , …, , the number of intervals is ; Generate a uniform random number , compare with this interval , then the serial number of the interval where it falls is the next state serial number, thereby determining the next state ; Step 3-3, repeated generation, add the state generated in Step 3-2 to the time series and set it as the new current state , and repeat Steps 3-2 and 3-3 until the generated time series meets the length of the time series set for the emulator output; Step 3-4, sort the state sequence , and output a time series containing state identifiers and the corresponding time intervals of the instantaneous signal-to-noise ratio (SNR) of the receiving end.

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