RIS-assisted D2D cache network task unloading modeling method

Abstract

The invention discloses an RIS-assisted D2D cache network task unloading modeling method, and belongs to the technical field of queue modeling, a reconfigurable intelligent surface (RIS) technology is combined with a D2D cache network, content unloading comprises a self-unloading method and a D2D unloading method, the situation that an auxiliary cache technology combines the dual characteristics of user terminal cache and D2D communication is considered, and the content unloading efficiency is improved. In other words, content unloading comprises a self-unloading method and a D2D unloading method, and content transmission needs to meet double constraints of a receiver signal-to-interference ratio and a D2D distance. A randomly generated service model is established based on a queuing theory, and a queuing model is established by combining the performance advantages of RIS and the advantages of a D2D cache network. And establishing an M / G / 1 queuing model for the cache queue of the user, and analyzing the conversion of the queue state. Then, constructing a Markov chain containing a queue length state and a transmission state, and deriving a closed expression of a successful unloading probability, an average queue length of a cache network and average waiting time;

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of queue modeling, and particularly relates to a RIS assisted D2D cache network task offloading modeling method. BACKGROUND

[0002] With the commercialization of 5G and the development of 6G, accompanied by the advent and development of the era of self-media, mobile Internet traffic has shown an explosive growth trend. Device-to-device (D2D) communication is well known as one of the key technologies of 5G. In D2D communication, users who are physically close to each other can communicate directly without forwarding through a base station (BS). Device-to-device (D2D) communication has significant advantages such as short distance and low energy consumption. By utilizing D2D communication for caching on mobile user devices, this method combines the advantages of caching and D2D communication technology, reduces the heavy load on the backhaul link, and improves the throughput of the cellular network.

[0003] D2D communication effectively improves the spectral efficiency of the communication network by reusing the cellular spectrum resources, but also introduces new interference to the cellular network. Due to the sharing of the same frequency band, there is serious co-channel interference between the D2D communication link and the cellular link. A software-defined metasurface called reconfigurable intelligent surface (RIS) is proposed to solve this problem, which can be used to effectively eliminate D2D interference and meet stringent data rates. This can be achieved by configuring the RIS to control the reflection, refraction, and scattering of electromagnetic waves hitting the surface. Combining RIS with D2D can further improve the performance of future mobile communication systems. Many documents have conducted in-depth research on resource allocation in RIS assisted D2D communication systems.

[0004] Reconfigurable intelligent surface (RIS) can effectively control the phase of the signal with low-cost reflective elements, and it has great practical significance to apply this technology to D2D communication networks that are highly dependent on the propagation environment. However, it is very challenging to integrate RIS into D2D caching communication, and research on this topic has not been fully developed. In addition to the direct path, RIS also brings a reflected path, which not only provides diversity gain, but also enhances the interference between users. Modeling the traffic of D2D caching networks in this complex interference scenario is important but difficult. How to model and analyze D2D networks in dynamic environments and achieve resource optimization, the existing scheme cannot be directly applied. SUMMARY

[0005] In view of the above technical problems, the purpose of the present application is to provide a RIS-assisted D2D cache network task offloading modeling method, taking into account the influence of dynamic interference on the successful transmission probability of the cache network, the complementary cumulative distribution function of the user SINR is derived, and it is used as the service probability of the queue, a two-dimensional Geo / G / 1 Markov chain is established for the user requesting the file, and the transfer state of successfully transmitting the file through the D2D link and the cellular base station is analyzed by using the quasi-birth-and-death process, and the expressions of the key performance parameters such as system delay and successful offloading probability are obtained.

[0006] In order to achieve the above purpose, the technical scheme adopted by the present application is as follows: 1. A RIS-assisted D2D cache network task offloading modeling method, comprising the following steps:

[0007] Step 1: For the cache network scene of multiple D2D and multiple cellular users, reconfigurable intelligent surface is applied to D2D cache network, by analyzing the direct link interference and reflection link interference in RIS-assisted D2D network, the expression of SINR is derived, and the base station transmission success probability is obtained;

[0008] Step 2: For the communication system with all mobile users having cache capability, combining the double constraints of content hit and satisfying the SINR condition required for successful transmission of content, a file acquisition protocol is given, that is, content offloading includes self-offloading and D2D offloading;

[0009] Step 3: M / G / 1 queuing model is established at the request user end, considering the cache hit rate of the file and the actual interference, the change of the queue state is analyzed;

[0010] Step 4: Based on the generality of service time, the queues for storing D2D transmission files and base station transmission files are established, and two-dimensional discrete-time Markov chains of the two states are constructed;

[0011] Step 5: The quasi-birth-and-death process method is used to solve the steady-state probability distribution of the Markov chain, and the expressions of the key performance parameters such as successful offloading probability, average queue length and average waiting time of the cache network are obtained.

[0012] Compared with the prior art, the present application has the following beneficial effects:

[0013] (1) The present application applies reconfigurable intelligent surface to D2D cache communication system, analyzes the direct link interference and reflection link interference in RIS-assisted D2D communication system, and derives the expression of SINR, which represents the signal-to-interference-plus-noise ratio.

[0014] (2) This invention targets D2D-assisted mobile caching networks. D2D caching technology integrates the dual characteristics of user terminal caching and D2D communication. Specifically, content offloading includes two offloading modes: self-offloading and D2D offloading. Content transmission must meet the dual constraints of the receiver's signal-to-interference-and-noise ratio and the D2D distance. A user cache Geo / G / 1 queue model is established to analyze the transmission process of requested files.

[0015] (3) The present invention constructs the queue state of files as a Markov chain, uses a pseudo-birth-death process to analyze the queue state of files under different transmission modes, and obtains expressions for key performance parameters such as the probability of successful unloading. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a schematic diagram of the file receiving model in this embodiment.

[0017] Figure 2 Schematic diagram of the state transition of the file queuing model in the cache in this embodiment.

[0018] Figure 3 In this embodiment Captain arrival rate with requests and Changing curve graph.

[0019] Figure 4 This is a curve diagram of the change of average delay with request arrival rate in this embodiment.

[0020] Figure 5 is the self-unloading probability in this embodiment Follow and 's change curve. DETAILED DESCRIPTION

[0021] In order to better understand the technical solution of the present invention, it is further explained below with reference to the accompanying drawings and specific embodiments.

[0022] This embodiment considers a distributed RIS-assisted D2D communication cache network, a cache network scenario of multiple D2D and multiple cellular users, and assumes that the channel resources of a cellular user (CU) are shared by at most one pair of D2D links. In order to maintain generality, this embodiment simplifies the model and focuses on the single-cell scenario, such as Figure 1 As shown, it includes a base station, 1 RIS, CUs and S (S≤K) for D2D users, the cellular users connected to the base station are represented as CUs, , D2D pair Including D2D transmitter DT, and the D2D receiver DR, The base station, D2D user, and CU are all assumed to be equipped with a single antenna. The RIS contains M reflective elements. The reflection coefficient of each reflective element in the RIS is adjusted by an intelligent controller.

[0023] Furthermore, this embodiment considers the downlink communication link scenario. The subchannels assigned by the base station to the CUs are mutually orthogonal, resulting in no interference between the CUs. A CU's channel resources are shared by at most one pair of D2D links. Cellular users can receive not only direct signals from the D2D transmitter and the base station, but also reflected signals from the RIS. After receiving these two superimposed signals, the base station interprets the signal from the D2D transmitter as interference. Similarly, the D2D receiver can receive direct signals from the D2D transmitter and the base station, as well as reflected signals from the RIS. The D2D receiver interprets the signal from the base station as interference.

[0024] The D2D user transmit power is expressed as , the receiving end DRs demodulates the signal received from DTs, where D in DRs represents D2D user, R represents receiver, and s represents the sth user. In DTs, D represents D2D user, T represents transmitter, and s represents the sth user. The received SINR value is Expressed as:

[0025] (1)

[0026] in, and Represents DT respectively to DR and BS to DR Direct link channel, and Represents BS and DT respectively The signal transmission power, BS means Base Station; and Respectively represent from DT Reflection channel to IRS and from BS to IRS, IRS stands for intelligent reflection surface, Indicates from IRS to DR reflection channel; assuming that the CSI of all channels is known, CSI stands for Channel State Information. The phase shift matrix of RIS is expressed as , represents a diagonal matrix, express The complex matrix of is a complex field, is the mth diagonal element of a diagonal matrix, represents the control coefficient of the mth unit on the signal amplitude, It is a complex exponential form, corresponding to the control of the signal phase by the mth unit, is the phase offset, is an imaginary unit. Based on the continuous phase shift reflection coefficient model, , ; Indicates CU With the The link reuse factor between D2D user pairs is CU, which means Cellular User. Multiplexing CU When resources =1, otherwise =0 ; Indicates the receiving end DR The power of the additive white Gaussian noise AWGN received at .

[0027] For cellular users, they can receive communication signals from base stations, but also receive interference signals. The SINR of the demodulated signal from the base station can be expressed as:

[0028] (2)

[0029] in, and Represents BS to CU respectively and DT to CU Direct link channel, and Respectively represent from BS to IRS and from DT Reflection channel to IRS, Indicates from IRS to CU reflection channel.

[0030] This embodiment considers a heterogeneous cellular network for D2D communication, where the base station location distribution follows the independent and identically distributed PPP , the density is , cellular users and D2D users obey PPP respectively and , the densities are and , are independent and identically distributed. Assuming that all users have cache capabilities, if the distance between the requesting user and the user storing the target file is less than D2D communication link can be established between users to transmit files to the requesting user.

[0031] The multimedia file set is where is the total number of files, is the file set , and the dimension of the file set is , all multimedia files are set to the same size , the probability of a user requesting any one of the files obeys the popularity distribution of the file , it is assumed that obeys the Zipf distribution, which is expressed as:

[0032] (3)

[0033] where reflects the skewness of the popularity function, and a higher indicates greater file reusability. The physical meaning of is the probability that the requested file is , and the first few files with smaller values have greater popularity, which also corresponds to most requests.

[0034] Define as the probability set of each file stored by the user, where represents the probability that the user stores the file , and , since the user's cache capacity is limited, then must satisfy:

[0035] (4)

[0036] In the D2D caching network, the end user can be both a content cache and a content requester. When the requesting user has content request requirements, it can obtain the required content through three ways: local caching, caching other users within the effective range of the cache D2D, and through the backhaul link from the core network by the cellular base station, and the successful transmission of the content needs to meet the dual constraints of content hit and SINR condition. The file acquisition protocol of the embodiment includes the following three parts:

[0037] Self-request cache hit probability: since each user randomly caches a part of all files, the probability of finding the requested file in its own cache. The embodiment defaults to the self-unloading mode, and as long as the local cache hits, the target content can be obtained without error,

[0038] (5)

[0039] D2D cache hit probability: the probability that the requested file is not cached in its own memory, but in the memory of a device within a certain D2D communication distance R. If at least one user has the requested content, the user will establish D2D transmission with the nearest user and the cached content. File Probability of being hit by D2D users is expressed as:

[0040] (6)

[0041] When the received signal-to-interference ratio of the requesting user is not less than the decoding threshold, the content transmission is considered successful, and the probability of successfully transmitting the file through D2D communication is represented. Considering the cache hit and the success of content transmission, in the D2D offloading method, when the content meets the requirements, the location proximity, and the received signal-to-interference ratio is greater than the decoding threshold, the D2D offloading is considered successful, and its probability can be expressed as:

[0042] (7)

[0043] where represents the SINR of the requesting user end is not less than the minimum threshold for successful decoding information The probability is expressed as

[0044] (8)

[0045] where represents the probability of occurrence of event .

[0046] Base station transmission success probability: when the requested file cannot be found through the above two methods, assuming that the requesting user can always obtain the content from the core network through the backhaul link from the cellular base station, the success probability of obtaining content from the base station is the link SINR greater than the decoding threshold, which is expressed as:

[0047] (9)

[0048] The queuing modeling and performance analysis are described in detail as follows:

[0049] This embodiment establishes an M / G / 1 queuing model at the requesting user end, where M represents a Poisson arrival process, and G represents a service sending process subject to a general distribution, while considering the cache hit rate and actual interference of the file, and analyzing the change of its queue state. Then, based on the general service time, a two-dimensional Markov chain including the queue length state and the transmission state is constructed. Assuming that the request arrival follows a Bernoulli distribution with parameter , and the total capacity of the user's cache is A joint request-caching strategy is analyzed.

[0050] Let the queue storing the files transmitted by D2D be called and the queue storing the files transmitted by the base station be called . According to the aforementioned caching strategy, if a user requests a file and does not have it randomly stored, the user needs to obtain it from surrounding users in a D2D manner or send it by the base station. In this embodiment, a queuing model is established at the request user end, and the changes in the queue length of the file transmitted by the D2D link and the queue length of the file transmitted by the base station are discussed respectively. The state set of the two-dimensional Markov chain is defined as .

[0051] As Figure 2 is the state transition diagram, the behavior of the queue is evaluated by a quasi-birth-and-death process (QBD). The state of the classical birth-and-death process is decomposed into sub-states . This structure complies with the requirements of depicting the evolution of the process under the conditions of multiple levels, multiple phases, and variable parameters. In this embodiment, the states of the queue length are rearranged, where and represent the queue length of the file transmitted by the D2D link and the queue length of the file transmitted by the base station respectively, and the queue length is regarded as a one-dimensional process . Define , where is named as the level, is the phase.

[0052] Therefore, the corresponding probability transition matrix is a cell matrix, which is expressed as:

[0053] (10)

[0054] Each element in the cell matrix is also a matrix. The transition between the levels is described by the non-zero matrix , the sub-matrix on the diagonal represents the event set that the number of (levels) does not change in one time slot, while the number of (phases) increases by 1, decreases by 1, or remains unchanged, i.e. . The sub-matrix below the diagonal represents the event set that the number of (levels) decreases by 1 after one service period, while the number of (phases) remains unchanged, i.e. . represents Sub-matrix contains all events of adding a file.

[0055] The expression of all elements in the sub-matrix is given below. First, for the boundary condition , , , and remains unchanged during a time slot, while changes contain the following three cases:

[0056] Case 1: remains unchanged, i.e. , indicating that the user does not initiate a request with a probability of , or generates a request, and the stored file can meet it, in addition, the event that the file fails to be successfully transmitted from the core network through the D2D link or backhaul link will also cause .

[0057] Case 2: increases a file, i.e. , indicating that the request is generated and cannot be satisfied by the self-cached file, and the request user still cannot find a matching content cache user in the effective D2D communication range, and finally the event set of successful transmission and saving by the base station.

[0058] Case 3: decreases a file, i.e. , indicating the event of deleting the request after being satisfied.

[0059] (11)

[0060] where

[0061] (12)

[0062] (13)

[0063] (14)

[0064] For , indicates the change of state when .The difference from is that because in , when a request is generated, in addition to checking whether the user's pre-stored file meets the request, it is also necessary to check whether the file stored in the D2D queue and the BS queue has the required file.

[0065] (15)

[0066] (16)

[0067] (17)

[0068] (18)

[0069] For the boundary conditions of the sub-matrix ,

[0070] (19)

[0071] Wherein:

[0072] (20)

[0073] (21)

[0074] Contains Reduce all events of a file, this request only occurs when the request, itself pre-stored can not meet, The existing file can meet.

[0075] (22)

[0076] Wherein:

[0077] (23)

[0078] In the same way, Indicates . The sub-matrix Contains Increase all events of a file, which occurs when the request cannot be met by the pre-stored file, there is no file in the two queues, and the user requests and transmits successfully to the surrounding users.

[0079] (24)

[0080] Wherein:

[0081] (25)

[0082] Substitute formulas (11)-(23) into formula (10) to obtain the transition probability matrix of the queuing model built in this embodiment.

[0083] Next, we solve the steady-state distribution of the quasi-birth-death process. Since the queue system reaches stability after a long period of operation, we assume that is the transition probability matrix The column matrix of the steady-state probability distribution, in order to use the block matrix The rule structure of this embodiment will According to the level of pseudo-birth and death process, it can be divided into:

[0084] (26)

[0085] in Given the normalization and probability, using , the steady-state distribution can be obtained by solving the following matrix equations

[27] :

[0086] (27)

[0087] This embodiment defines several important performance parameters. First, considering the uncertainty of the content of a typical user request, the probability of successful uninstallation can be expressed as:

[0088] (28)

[0089] and The average length of the lengths are expressed as:

[0090] (29)

[0091] (30)

[0092] Given a steady-state probability distribution, and The average throughput is defined as and , their respective expressions can be derived as:

[0093] (31)

[0094] (32)

[0095] Little's law can be used to estimate the average waiting time before packets from two queues are sent. and Expressed as:

[0096] (33)

[0097] (34)

[0098] Numerical and simulation results:

[0099] This embodiment uses MATLAB simulation to verify the correctness of the results obtained by the analysis under the above caching strategy. Consider a two-dimensional square cell of 150 m x 150 m, with the four corners at (0,0), (150,0), (0,150), and (150,150). The base station is deployed at (0,0). The RIS is deployed near the base station at (5,0). K CUs are evenly distributed in the square cell. S pairs of D2D users are distributed in an area 20 m away from the BS. The distance between the D2D transmitter and receiver is 10-50 m. The user's transmission power is 20 , path loss fading coefficient , the Gaussian white noise power is -104 , Content Library , and The cache space is , During the simulation, the user's position is fixed and the user's mobility is not considered.

[0100] Figure 3 Given Under three parameters The curve of the length of the queue changes with the request arrival rate. The figure shows that the theoretical value and the simulation result are consistent, proving the correctness of the theoretical deduction. As the number of RIS reflection units increases, it quickly reaches saturation, which fully demonstrates that deploying RIS in wireless networks can alleviate channel interference and obtain files faster through D2D links when the request arrival rate increases.

[0101] Figure 4 Given the path loss factor Under the change of average delay, the influence curve of request arrival rate is and compared to, The average length reaches saturation faster, the path loss factor is smaller, the average throughput is lower, the average latency is longer, and the packet loss rate is higher. The results show that a higher path loss factor reduces the impact of interfering links on the D2D receiver and increases the probability of successful file transmission. The figure shows that the theoretical values ​​​​are consistent with the simulation results.

[0102] from Figure 5 As can be seen in The increase in self-unloading probability This is because more D2D links can be established to provide files to requesting users, and the requested files are stored in the user cache, which increases the probability of self-unloading. It is shown that the larger the file is, the more reusability it has. The larger the file is, the more likely it is to be requested by users, and the higher the probability of self-unloading is. The numerical calculation and computer simulation are basically consistent.

[0103] In this embodiment, the reconfigurable intelligent surface is applied to the D2D cache communication system, the direct link interference and the reflection link interference in the RIS-assisted D2D communication system are analyzed, and the expression of the SINR is derived. For the D2D-assisted mobile cache network, the D2D cache technology combines the double characteristics of user terminal cache and D2D communication, that is, the content offloading includes two offloading modes of self-unloading and D2D offloading, and the content transmission needs to meet the dual constraints of the receiving end signal-to-interference-and-noise ratio and the D2D distance. A user cache Geo / G / 1 queue model is established to analyze the transmission process of the requested file. The queue state of the file is constructed as a Markov chain, the quasi-birth-and-death process is used to analyze the file queue state under different transmission modes, the expressions of the successful offloading probability, the average queue length and the average waiting time of the cache network and other key performance parameters are obtained, the simulation results and the numerical calculation are basically consistent, and the correctness of the model is illustrated.

[0104] Although the present application has been disclosed with the preferred embodiments as above, the embodiments and the drawings are not intended to limit the present application, and any person skilled in the art can make various changes or modifications without departing from the spirit and scope of the present application, and the changes or modifications are also within the protection scope of the present application. Therefore, the protection scope of the present application should be defined by the protection scope of the claims of the present application.

Claims

1. A RIS-assisted D2D cache network task offloading modeling method, characterized by: The following steps are involved: Step 1: For a caching network scenario with multiple D2D and multiple cellular users, a reconfigurable smart surface is applied to the D2D caching network. By analyzing the direct link interference and reflected link interference in the RIS-assisted D2D network, an expression for SINR is derived, thereby obtaining the base station transmission success probability. Step 2: For a communication system where all mobile users have caching capabilities, a file retrieval protocol is proposed, considering that successful content transmission requires both content hits and SINR requirements. This protocol includes content offloading in two ways: self-offloading and D2D offloading. Step 3: Establish an M / G / 1 queuing model on the requesting user side, taking into account the cache hit rate and actual interference of the file, and analyze the changes in its queue status; Step 4: Based on the generality of service time, a queue is established to store D2D transmission files and a queue is established to store base station transmission files, and then a two-dimensional discrete-time Markov chain is constructed for these two states. Step 5: Use the quasi-birth-death process method to solve the steady-state probability distribution of the Markov chain and obtain the expression of the key performance parameters.

2. A RIS-assisted D2D cache network task offloading modeling method according to claim 1, characterized in that: The step 1 specifically includes: The D2D user transmit power is expressed as , receiving end DR For the received data from DT The signal is demodulated, DR In the figure, D represents D2D user, R represents receiver, represents the sth user, DT D represents D2D user, T represents transmitter, Indicates that the sth user will receive the SINR value Expressed as: (1) in, and Represents DT respectively to DR and BS to DR Direct link channel, and Represents BS and DT respectively The signal transmission power, BS means Base Station; and Respectively represent from DT Reflection channel to IRS and from BS to IRS, IRS stands for intelligent reflection surface, Indicates from IRS to DR Assuming that the CSI of all channels is known, CSI represents the channel state information, and the phase shift matrix of RIS is expressed as , represents a diagonal matrix, express The complex matrix of is a complex field, is the mth diagonal element of a diagonal matrix, Represents the control coefficient of the mth unit on the signal amplitude, It is a complex exponential form, corresponding to the control of the signal phase by the mth unit. is the phase offset, is an imaginary unit; Based on the continuous phase shift reflection coefficient model, , ; Indicates CU With the The link reuse factor between D2D user pairs is CU, which means Cellular User. Multiplexing CU When resources =1, otherwise =0 ; Indicates the receiving end DR The power of the additive white Gaussian noise AWGN received at ; For cellular users, they can receive communication signals from base stations, but also receive interference signals. The SINR of the demodulated signal from the base station can be expressed as: (2) in, and Represents BS to CU respectively and DT to CU Direct link channel, and Respectively represent from BS to IRS and from DT Reflection channel to IRS, Indicates from IRS to CU reflection channel.

3. A RIS-assisted D2D cache network task offloading modeling method according to claim 1, characterized in that: The step 2 specifically includes: Heterogeneous cellular network based on D2D communication, base station location distribution follows PPP , PPP represents Poisson distribution, and the density is , cellular users and D2D users obey PPP respectively and , the densities are and , are independent and identically distributed; assuming that all users have cache capabilities, if the distance between the requesting user and the user storing the target file is less than When a D2D communication link is established between users, the file is transferred to the requesting user.

4. A RIS-assisted D2D cache network task offloading modeling method according to claim 3, characterized in that: Multimedia file collection is ,in is the total number of files, For file collection dimensions, all multimedia files have the same size of , user request The probability of any file in follows the popularity distribution function of the file , assuming the function Obey the Zipf distribution, expressed as: （3） in Reflects the skewness of the popularity function, high Indicates large file reusability; Indicates the file number, The physical meaning is The probability of The first few files with small values ​​have large popularity and correspond to most requests. Is a normalization factor used to ensure that the sum of the probabilities of all elements is 1, satisfying the basic properties of probability distribution. represents the normalization parameter; definition There is a probability set of each file stored for the user, where Indicates that the user has files The probability that , due to the limited capacity of D2D user buffer area, Must meet: （4）。 5. A RIS-assisted D2D cache network task offloading modeling method according to claim 4, characterized in that: In a D2D caching network, end users can be both content cachers and content requesters. When a requesting user requests content, the required content is obtained through three methods: local caching, caching users within the D2D effective range, and cellular base stations from the core network via backhaul links. Successful content transmission requires both content hit and SINR requirements to be met. The file acquisition protocol includes: Self-request cache hit probability: Since each user randomly caches a portion of all files, the probability that the requested file can be found in its own cache for: (5) D2D cache hit probability: the probability that the requested file is not cached in its own memory but is cached in a device within a specific D2D communication distance R; if at least one user has the requested content, the user will establish a D2D transmission with the nearest user and the cached content; file The probability of being hit by a D2D user Expressed as: (6) When the received signal interference ratio of the requesting user is not less than the decoding threshold, the content transmission is considered successful, and it represents the probability of successful file transmission through D2D communication; considering the cache hit and content transmission success, in the D2D offloading method, when the content meets the requirements, the location proximity and the received signal interference ratio are greater than the decoding threshold, it is considered that the D2D offloading is successful, and its probability is It can be expressed as: (7) in Indicates the SINR of the requested user end Not less than the minimum threshold for successful decoding information The probability is expressed as: (8) in Representing an event probability of occurrence; Base station transmission success probability: Assuming that the requesting user can always be obtained from the core network through the cellular base station via the backhaul link, the successful transmission probability of obtaining content from the base station is whether the link SINR is greater than the decoding threshold, expressed as: (9)。 6. A RIS-assisted D2D cache network task offloading modeling method according to claim 1, characterized in that: The steps 3 and 4 specifically include: Assume that the queue storing the files transmitted by D2D is called , the queue for storing files transmitted from the base station is called When a user requests a file, if the user does not have the file stored randomly, it needs to obtain it from the surrounding users in a D2D manner or be sent by the base station. The user terminal is requested to establish an M / G / 1 queuing model, where M represents the Poisson arrival process, G represents the service delivery process that follows the general distribution, and 1 represents the number of service stations. The length of the file queue transmitted by the D2D link is discussed separately. and the queue leader for files transferred by the base station The state set of the two-dimensional Markov chain is defined as ; Rearrange captains state, where and They represent the file queue lengths of the D2D link transmission. and the queue leader for files transferred by the base station , and consider it as a one-dimensional process ;definition ,in Named Level, is the phase; Therefore, the corresponding probability transfer matrix is ​​a cell matrix, expressed as: (10) Cell Matrix Each element in is also a matrix; the transition between levels is represented by a non-zero matrix Description, diagonal The sub-matrix on represents the time slot The number of levels remains unchanged, while The set of events whose phase increases by 1, decreases by 1, or remains unchanged, that is, ; Submatrix below the diagonal Indicates that after a service cycle, Reduce one file, and The set of events that does not change, i.e. ; express ; Submatrix Contains Add all events for a file.

7. A RIS-assisted D2D cache network task offloading modeling method according to claim 6, characterized in that: All sub-matrices The expression of the elements in is: First, for Boundary conditions In terms of and remains unchanged after a time slot, and The changes include the following three situations: Case 1: remain unchanged, that is , indicating that the user The probability of no request being initiated, or a request being generated, and the files stored in the system can satisfy it. In addition, the event that the file is not successfully transmitted from the core network through the D2D link or the backhaul link will also cause ; Case 2: Add a file, namely , indicating that the request generated cannot be satisfied by its own cache, and the requesting user still cannot find a matching content cache user within the effective D2D communication range, and is finally successfully transmitted and saved by the base station; Case 3: Reduce one file, i.e. , indicating that the request is Events that are deleted after being satisfied; (11) in (12) (13) (14) for , Indicates when hour, Change of state; The difference is that, because middle , when a request is generated, in addition to checking whether the user's pre-stored files are satisfied, it is also necessary to check whether the required files are already in the D2D queue and BS queue; (15) （16) (17) (18) For the boundary conditions of the submatrix , (19) in: (20) (21) Contains Reduce all events of a file. This request only occurs when a request is generated and the pre-stored file cannot satisfy the request. Existing documents can satisfy; (22) in: (23) express ; Submatrix Contains Add all events for a file. This event occurs when a request cannot be satisfied by a pre-stored file, the file is not stored in either queue, and the user requests the file from a neighboring user and the file is successfully transferred. (24) in: (25) Substituting formulas (11)-(23) into formula (10) yields the transition probability matrix of the queuing model.

8. A RIS-assisted D2D cache network task offloading modeling method according to claim 1, characterized in that: In step 5, the key performance parameters include the probability of successful offloading, the average length of the cache network, and the average waiting time. The specific derivation process is as follows: Assumptions is the transition probability matrix The column matrix of the steady-state probability distribution, in order to use the block matrix The rule structure of According to the level of pseudo-birth and death process, it can be divided into: (26) in ; Given normalization and probability, using , the steady-state distribution can be obtained by solving the following matrix equations: (27) The following defines several important performance parameters. First, considering the uncertainty of the request content, the probability of successful uninstallation is expressed as: (28) and The average length of the lengths are expressed as: (29) (30) Given a steady-state probability distribution, and The average throughput is defined as and , their respective expressions are derived as: (31) (32) Little's law is used to evaluate the average waiting time before packets from two queues are sent. and , expressed as: (33) (34)。

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