Design method and device of wired and wireless hybrid network, storage medium and equipment

Abstract

The application discloses a design method and device of a wired and wireless hybrid network, a storage medium and equipment, relates to the technical field of mobile communication network architecture optimization, and mainly solves the problem of network congestion in the wired and wireless hybrid network architecture, and comprises the following steps: acquiring the transmission rate conditions between users and base stations and between base stations in a system and constructing a transmission rate matrix; setting the connection mode between the base stations as wireless connection, and constructing a wireless optimization objective function based on the transmission rate matrix; performing optimization and solution on the wireless optimization objective function, and obtaining unbalanced base stations under the wireless connection condition; the unbalanced base stations comprise congested base stations and surplus base stations; establishing wired connection between the congested base stations and the surplus base stations, and establishing a wired optimization objective function with the minimum wired connection path as the target; performing successive optimization and solution on the wired optimization objective function according to the flow in-out difference value of the congested base stations from small to large, and obtaining a wired connection optimization result.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of mobile communication network architecture optimization, in particular to a wired and wireless hybrid network design method and device, a storage medium and equipment. BACKGROUND

[0002] With the explosive growth of user traffic, the wireless network structure will become more dense and heterogeneous. Under the premise of ensuring the connectivity and capacity of various applications, wired and wireless hybrid has become a development trend. Through the effective combination of wired optical fiber and wireless link, the high speed, low delay and anti-interference advantages of optical fiber communication technology are utilized to realize the resource integration between unbalanced base stations, thereby to a certain extent, reducing the huge overhead generated by real-time calculation in pure wireless scheduling, and avoiding the high cost of using wired links which is difficult to change after construction.

[0003] In the existing wired and wireless hybrid network architecture, the macro base station (MBS) is usually directly connected with the core network (CN) through optical fiber or high-bandwidth wired link, while the micro base station (μBS) and the macro base station are generally connected through wireless backhaul link (such as millimeter wave, Sub-6GHz or free space optical communication FSO) to realize flexible networking. This hierarchical topology structure can effectively balance the deployment cost and network coverage demand in low traffic load scenarios. However, with the exponential growth of user traffic demand, the existing wired and wireless hybrid network architecture is limited by spectrum resources (such as shared frequency band interference) and physical layer capacity (such as Shannon limit), and network congestion often occurs during peak hours. SUMMARY

[0004] Therefore, the present application provides a wired and wireless hybrid network design method and device, a storage medium and equipment, which mainly aims to solve the network congestion problem in the traditional wired and wireless hybrid network architecture.

[0005] According to one aspect of the present application, a wired and wireless hybrid network design method is provided, comprising:

[0006] Obtaining the transmission rate between users and base stations, and between base stations in the system, and constructing a transmission rate matrix based on the transmission rate;

[0007] Setting the connection mode between all base stations as wireless connection, and constructing a wireless optimization objective function based on the transmission rate matrix;

[0008] Optimizing and solving the wireless optimization objective function to obtain unbalanced base stations under wireless connection; the unbalanced base stations include congested base stations and surplus base stations;

[0009] A wired connection is established between the congested base station and the surplus base station, and a wired optimization objective function is established with the objective of minimizing the wired connection path;

[0010] The wired optimization objective function is solved by successive optimization in the order of the traffic in-out difference of the congested base station from small to large, to obtain a wired connection optimization result.

[0011] Further, the transmission rate matrix is constructed based on the transmission rate condition, including:

[0012] The spatial positions of base stations and the distribution positions of users in the system are obtained, and the straight-line distance between end-to-end is determined based on the spatial positions of the base stations and the determined distribution positions of the users;

[0013] The received signal power and the interference power are calculated based on the straight-line distance between end-to-end and the channel condition;

[0014] The transmission rate between end-to-end in the system is determined by using Shannon formula based on the received signal power and the interference power, and the transmission rate matrix is constructed based on the transmission rates between all end-to-end in the system.

[0015] Further, the wireless optimization objective function is constructed based on the transmission rate matrix, including:

[0016] The user equipment is connected to the base station with the highest transmission rate within a preset range;

[0017] The output traffic and the input traffic corresponding to each base station in the system are determined based on the transmission rate matrix;

[0018] The traffic in-out difference between the output traffic and the input traffic corresponding to each base station is calculated;

[0019] The wireless optimization objective function is constructed with the objective of minimizing the system traffic in-out difference.

[0020] Further, the wireless optimization objective function is solved to obtain the unbalanced base station under the wireless connection condition, including:

[0021] The first constraint condition is configured for the wireless optimization objective function, and the first constraint condition includes a half-duplex communication constraint, a user next-hop connection number constraint, and a base station next-hop connection number constraint;

[0022] The connection state parameters in the wireless optimization objective function and the first constraint condition are relaxed, and a penalty term is added to the wireless optimization objective function to obtain a first to-be-solved model;

[0023] iteratively solving the first to-be-solved model until a tolerance is less than a preset value or a maximum iteration number is reached, to obtain a wireless optimization solving result; and determining the unbalanced base station under a system-in-wireless connection condition based on the wireless optimization solving result.

[0024] Further, after the wire connection between the congested base station and the surplus base station is established and a wire optimization objective function is established with a wire connection path minimization as a target, the method further comprises:

[0025] configuring a second constraint condition for the wire optimization objective function, the second constraint condition including a wire connection symmetry constraint, a wire connection body selective constraint, a wire connection body internal base station number constraint, a wire connection edge number constraint, a selected base station number constraint, a wire connection body flow in-out constraint, and a wire connection body aggregation constraint.

[0026] Further, the wire connection body aggregation constraint is constructed based on a single commodity flow model, and includes:

[0027] setting an auxiliary variable Z i,j ;

[0028] setting an output flow of the congested base station to each surplus base station i as Z 1,i , and setting an input flow of each surplus base station i to the congested base station as Z i,1 ; and setting a wire connection body flow constraint based on the output flow Z 1,i and the input flow Z i,1 ;

[0029] constructing a flow conservation constraint and a connection constraint based on the auxiliary variable Z i,j ;

[0030] The wire connection body flow constraint, the flow conservation constraint, and the connection constraint jointly constitute the wire connection body aggregation constraint.

[0031] Further, the wire connection optimization result is obtained by sequentially optimizing and solving the wire optimization objective function in an order from small to large of the flow in-out difference of the congested base station, and includes:

[0032] relaxing 0-1 variables in the wire optimization objective function and the second constraint condition, and adding a penalty term in the wire optimization objective function, to obtain a second to-be-solved model;

[0033] sorting all the congested base stations in an order from small to large of the flow in-out difference, and determining the order of the sorted congested base stations as the order of the sequential optimization and solving;

[0034] obtaining a current optimized congested base station from the order of the successive optimization solution, substituting the current optimized congested base station and all the surplus base stations into the second to-be-solved model to solve the wired connection topology, and obtaining a current wired connection scheme corresponding to the current optimized congested base station;

[0035] integrating all the base stations included in the current limited connection scheme into a wired connection body, and substituting the wired connection body as a surplus base station into a process of solving the wired connection topology of a next congested base station until the solving of the wired connection topology of all the congested base stations is completed, and obtaining the wired connection optimization result.

[0036] According to another aspect of the present application, a design device of a wired and wireless hybrid network is provided, comprising:

[0037] a rate matrix construction module, configured to obtain transmission rates between users and base stations and between base stations in the system, and construct a transmission rate matrix based on the transmission rates;

[0038] a first optimization module, configured to set a connection mode between all the base stations as a wireless connection, and construct a wireless optimization objective function based on the transmission rate matrix;

[0039] a first solving module, configured to perform optimization solution on the wireless optimization objective function, and obtain an unbalanced base station under the wireless connection; the unbalanced base station includes a congested base station and a surplus base station;

[0040] a second optimization module, configured to establish a wired connection between the congested base station and the surplus base station, and establish a wired optimization objective function with the minimum wired connection path as the target;

[0041] a second solving module, configured to perform successive optimization solution on the wired optimization objective function according to an order of the traffic in and out difference of the congested base station from small to large, and obtain a wired connection optimization result.

[0042] Further, the rate matrix construction module is further configured to:

[0043] obtain spatial positions of base stations and distribution positions of users in the system, and determine straight-line distances between ends to ends based on the spatial positions of the base stations and the determined distribution positions of the users;

[0044] calculate received signal power and interference power based on the straight-line distances between the ends to ends and channel conditions;

[0045] determine transmission rates between the ends to ends in the system by using Shannon formula based on the received signal power and the interference power, and construct the transmission rate matrix based on the transmission rates between all the ends to ends in the system.

[0046] Further, the first optimization module is further configured to:

[0047] establish a wireless connection relationship between the user equipment and a base station with the highest transmission rate within a preset range;

[0048] determine the output flow and the input flow corresponding to each base station in the system based on the transmission rate matrix;

[0049] calculate the flow in-out difference between the output flow and the input flow corresponding to each base station;

[0050] build the wireless optimization objective function with the minimum system flow in-out difference as the target.

[0051] Further, the first solving module is further configured to:

[0052] configure a first constraint condition for the wireless optimization objective function, the first constraint condition including a half-duplex communication constraint, a user next-hop connection number constraint, and a base station next-hop connection number constraint;

[0053] perform a relaxation processing on the connection state parameters in the wireless optimization objective function and the first constraint condition, and add a penalty term in the wireless optimization objective function to obtain a first to-be-solved model;

[0054] perform an iterative solving on the first to-be-solved model until the tolerance is less than a preset value or the maximum iteration number is reached to obtain a wireless optimization solving result; and determine the unbalanced base station under the wireless connection condition in the system based on the wireless optimization solving result.

[0055] Further, the second optimization module is further configured to:

[0056] configure a second constraint condition for the wired optimization objective function, the second constraint condition including a wired connection symmetry constraint, a wired connectivity body selectivity constraint, a wired connectivity body internal base station number constraint, a wired connection edge number constraint, a selected base station number constraint, a wired connectivity body flow in-out constraint, and a wired connectivity aggregation constraint.

[0057] Further, the wired connectivity aggregation constraint in the second optimization module is constructed based on a single commodity flow model, including:

[0058] setting an auxiliary variable Z i,j ;

[0059] setting the output flow of the congested base station to each rich base station i as Z 1,i , and setting the input flow of each rich base station i to the congested base station as Z i,1 ; and based on the output flow Z 1,iand the input flow Z i,1 a wired connectivity body flow constraint is set;

[0060] based on the auxiliary variable Z i,j a flow conservation constraint and a connectivity constraint are constructed;

[0061] the wired connectivity body flow constraint, the flow conservation constraint and the connectivity constraint jointly constitute the wired connectivity aggregation constraint.

[0062] Further, the second solving module is further used for:

[0063] relaxing the 0-1 variable in the wired optimization objective function and the second constraint condition, and adding a penalty term in the wired optimization objective function to obtain a second to-be-solved model;

[0064] sorting all the congested base stations according to the flow in-out difference from small to large, and determining the order of the sorted congested base stations as the order of the successive optimization solving;

[0065] obtaining a current optimized congested base station from the order of the successive optimization solving, substituting the current optimized congested base station and all the surplus base stations into the second to-be-solved model to solve the wired connection topology, and obtaining a current wired connection scheme corresponding to the current optimized congested base station;

[0066] integrating all the base stations included in the current wired connection scheme into a wired connectivity body, and substituting the wired connectivity body as a surplus base station into the process of solving the wired connection topology of the next congested base station until the solving of the wired connection topology of all the congested base stations is completed, and obtaining the wired connection optimization result.

[0067] According to another aspect of the present application, a storage medium is provided, and at least one executable instruction is stored in the storage medium, which makes a processor execute operations corresponding to the design method of the wired and wireless hybrid network.

[0068] According to another aspect of the present application, a device is provided, which comprises a processor, a memory, a communication interface and a communication bus, and the processor, the memory and the communication interface complete communication with each other through the communication bus;

[0069] The memory is used for storing at least one executable instruction, and the executable instruction makes the processor execute operations corresponding to the design method of the wired and wireless hybrid network.

[0070] By means of the above technical solutions, the technical solutions provided by the embodiments of the present application have at least the following advantages:

[0071] The application provides a design method and device of a wired and wireless hybrid network, a storage medium and equipment.

[0072] The above description is only a summary of the technical scheme of the application, in order to more clearly understand the technical means of the application, the specific embodiments of the application can be implemented according to the content of the specification, and in order to make the above and other purposes, characteristics and advantages of the application more obvious and easy to understand, the following specifically describes the specific embodiments of the application. BRIEF DESCRIPTION OF DRAWINGS

[0073] Various other advantages and benefits will become apparent to those of ordinary skill in the art, upon reading the following detailed description of the preferred embodiments. The accompanying drawings are intended to depict only preferred embodiments of the application, and therefore should not be considered to narrow the scope of the present application. Additionally, like reference numerals are intended to denote like parts throughout the various drawings. In the drawings:

[0074] Figure 1 A flowchart of a design method of a wired and wireless hybrid network provided by an embodiment of the application is shown;

[0075] Figure 2 A flowchart of another design method of a wired and wireless hybrid network provided by an embodiment of the application is shown;

[0076] Figure 3 A flowchart of still another design method of a wired and wireless hybrid network provided by an embodiment of the application is shown;

[0077] Figure 4 A flowchart of yet another design method of a wired and wireless hybrid network provided by an embodiment of the application is shown;

[0078] Figure 5 Fig. 1 shows a structural schematic diagram of a design device of a wired and wireless hybrid network according to an embodiment of the present application;

[0079] Figure 6 Fig. 2 shows a structural schematic diagram of a device according to an embodiment of the present application. DETAILED DESCRIPTION

[0080] Exemplary embodiments of the present disclosure will be described in detail with reference to the drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure can be more thoroughly understood and so that the scope of the present disclosure can be completely conveyed to those skilled in the art.

[0081] An embodiment of the present application provides a design method of a wired and wireless hybrid network, as shown in the figure, the method comprises: Figure 1

[0082] 101, obtaining transmission rate conditions between users and base stations, and between base stations in the system, and constructing a transmission rate matrix based on the transmission rate conditions;

[0083] In an embodiment of the present application, the current execution end obtains transmission rate conditions between users and base stations, and between base stations in the system, wherein the transmission rate refers to the amount of data that can be transmitted per unit time, usually expressed in bits per second (bps), and a higher transmission rate indicates faster information transmission capability. The current execution end also constructs a transmission rate matrix based on the obtained transmission rate conditions, wherein the transmission rate matrix is used to describe the rate distribution of data transmission in a wireless communication system, and the transmission rate matrix directly depends on the characteristics of the channel matrix. The statistical characteristics (such as channel gain, signal-to-noise ratio, etc.) of the channel matrix will affect the transmission rate, which is not limited in the embodiment of the present application.

[0084] It should be noted that the base station in the present application includes a macro base station and a micro base station. Since the invention is for the maximum user input rate, only the uplink rate from the user to the base station is considered in the present application, i.e. it is considered that the user only does the wireless link transmitting end and does not do the wireless link receiving end. Since the macro base station is directly connected to the core network through a wired optical fiber for rate output, it is considered that the macro base station only does the receiving end and does not do the transmitting end in the wireless link network.

[0085] 102, setting the connection mode between all base stations as a wireless connection, and constructing a wireless optimization objective function based on the transmission rate matrix;

[0086] ​In the embodiment of the present application, the current execution end sets the connection mode between each base station in the system as wireless connection, and constructs a wireless optimization objective function based on the rate distribution of data transmission in the system, that is, based on the transmission rate matrix. The wireless optimization objective function is mainly used for the optimization design of the wireless link in the system, and the wireless optimization objective function is used to reduce the occurrence of congested base stations in the system as much as possible.

[0087] 103. The wireless optimization objective function is optimized and solved to obtain the unbalanced base station under the wireless connection condition; the unbalanced base station includes the congested base station and the surplus base station;

[0088] In the embodiment of the present application, when the user traffic demand is too much, the wireless connection alone cannot solve the resource imbalance between the congested base station and the surplus base station due to the limited wireless channel transmission rate. The current execution end optimizes and solves the wireless optimization objective function constructed in step 102 to obtain the unbalanced base station under the wireless connection condition. The unbalanced base station includes the congested base station and the surplus base station. The congested base station represents the base station with input traffic greater than output traffic, which is represented by the formula R in >R out , wherein R in represents the input traffic, and R out represents the output traffic; the surplus base station represents the base station with input traffic less than output traffic, which is represented by the formula R in <R out .

[0089] 104. A wired connection is established between the congested base station and the surplus base station, and a wired optimization objective function is constructed with the minimum wired connection path as the target;

[0090] In the embodiment of the present application, since the wireless link alone cannot solve the imbalance in the system, a wired link needs to be built in the system to integrate the resources of the unbalanced base station, and the wired link needs to be optimized and designed when the wired link is built. The current execution end establishes a wired connection between the congested base station and the surplus base station determined in step 103, and constructs a wired optimization objective function with the minimum wired connection path as the target. The minimum wired connection path represents that the connection path between the selected surplus base station and the current to-be-optimized congested base station in the system is minimum, and the specific formula is as follows:

[0091]

[0092] , wherein x i,j represents whether there is a wired connection between the base station and the base station or between the base station and the aggregated base station, d i,j represents the distance between the base station and the base station or between the base station and the aggregated base station. The aggregated base station is the wired connection body of the congested base station and the surplus base station. represents the number of surplus base stations; N represents that the congested base station k (one base station) and the surplus base stations form a wired communication body, that is, the number of independent base stations contained in the wired communication body is N.

[0093] 105. The wired optimization objective function is solved by successive optimization according to the traffic in-out difference value of the congested base station from small to large, and a wired connection optimization result is obtained.

[0094] In the embodiment of the application, the current execution end optimizes and designs the wired communication of the congested base stations one by one according to the congestion severity of the congested base stations. Specifically, the current execution end can judge the congestion severity of the congested base stations according to the traffic in-out difference value. The traffic in-out difference value ΔR = R out -R in When ΔR < 0, it represents a congested base station, and when ΔR > 0, it represents a surplus base station. Since the traffic in-out difference value of the congested base station is negative, the smaller the traffic in-out difference value of the congested base station, the more serious the congestion degree.

[0095] In the embodiment, the current execution end optimizes and designs the wired links corresponding to the congested base stations in the system one by one according to the traffic in-out difference value of the congested base stations from small to large. Therefore, the current execution end needs to solve the wired optimization objective function by successive optimization to obtain a wired connection optimization result, which is not limited in the embodiment of the application.

[0096] Further, as a refinement and expansion of the specific implementation of the above embodiment, in order to better represent the rate distribution of data transmission in the system, another design method of a wired and wireless hybrid network is provided, as shown in the following table. Figure 2 The step of constructing a transmission rate matrix based on the transmission rate situation includes:

[0097] 201. Obtain the spatial positions of base stations and the distribution positions of users in the system, and determine the straight-line distance between the end-to-end based on the spatial positions of the base stations and the determined distribution positions of the users.

[0098] The straight-line distance between the end-to-end can be represented by d ij , which can represent the straight-line distance between the transmitting end i and the receiving end j, or the straight-line distance between the receiving end i and the transmitting end j, which is not limited in the embodiment of the application.

[0099] 202. Calculate the received signal power and interference power based on the straight-line distance between the end-to-end and the channel condition.

[0100] ​​In the embodiment of the present application, the current executing end calculates the received signal power and the interference power based on the straight-line distance and the channel condition between the end-to-end, and the specific calculation is as follows:

[0101] The calculation formula of the received signal power is as follows:

[0102]

[0103] Wherein, P jir is the signal power received by the j base station from the i base station / user, P ijt is the signal power sent by the i base station / user to the j base station, h is the small-scale fading gain in the channel, G t , G r are the transmitting antenna gain and the receiving antenna gain respectively, and λ is the signal wavelength.

[0104] The calculation formula of the interference power is as follows:

[0105]

[0106] Wherein, I ij represents the interference power received by the j base station from the non-i base station. jkr

[0107] 203, based on the received signal power and the interference power, the transmission rate between the end-to-end in the system is determined by using the Shannon formula, and the transmission rate matrix is constructed based on the transmission rate between all the end-to-end in the system.

[0108] In the embodiment of the present application, the current executing end determines the transmission rate between the end-to-end in the system by using the Shannon formula based on the received signal power P jir and the interference power I ij obtained by the above step 202, and the specific calculation formula is as follows:

[0109]

[0110] Wherein, B is the signal bandwidth, N is the noise power, R ij represents the transmission rate of the wireless link ij. The current executing end integrates all the transmission rates R ij of the wireless links in the system to form the transmission rate matrix R.

[0111] Further, as a refinement and expansion of the specific implementation manner of the above embodiment, in order to reduce the congestion of each base station as much as possible under the condition of wireless link connection, another design method of the wired and wireless hybrid network is provided, as shown in the following steps: Figure 3 The steps include: ​

[0112] 301. Establish a wireless connection between the user equipment and the base station with the highest transmission rate within the preset range;

[0113] In this embodiment of the invention, the current execution end adopts This represents the set of user devices within the system. For any user i in the set, there exists a maximum connection range r. th There are two requirements for user i to establish a wireless connection with the base station:

[0114] (1) User i can only be less than r away from it. th The base station must establish an access link; otherwise, a connection cannot be established due to the signal being too weak.

[0115] (2) User i can only establish an access link with the base station with the highest communication quality.

[0116] Due to the above two conditions, the following judgment is made regarding whether user i establishes an access link with base station j:

[0117]

[0118] in, This indicates that the distance between base station j and user i is less than r. th Furthermore, the transmission rate of the link formed by these two elements is the highest within this range (the link quality is the best). Therefore, under these conditions, x can be... ij Assign a value of 1 if the value is 1, otherwise assign 0. Since the transmission rate matrix, the distribution locations of users, and the distribution locations of base stations are all known, the aforementioned constraints on x... ij (That is, all access links) can be determined based on known conditions, without increasing the complexity of solving the optimization problem.

[0119] 302. Determine the corresponding output and input traffic of each base station in the system based on the transmission rate matrix;

[0120] In this embodiment of the invention, the current execution terminal determines the corresponding output and input traffic of each base station in the system based on the transmission rate matrix R, specifically:

[0121] Input traffic R of base station i i，in It can be represented as:

[0122]

[0123] in, Let I represent the set of all base stations (including micro base stations and macro base stations), and let I represent the set of user equipment and micro base stations. It can be used as a micro base station or a macro base station, because both can serve as the receiving end of a wireless link.j,i Rij represents the connection status of the user equipment / micro base station j and the base station i j,i Rji represents the transmission rate of the user equipment / micro base station j to the base station i

[0124] Ri represents the output flow of the base station i i，out Ri can be represented as:

[0125]

[0126] wherein, Xi represents the set of micro base stations, x i,j Rij represents the connection status of the micro base station i and the user equipment / micro base station j i,j Rji represents the transmission rate of the micro base station i to the user equipment / micro base station j. Herein, Only the micro base station, because the output end of the macro base station is directly connected with the core network through a wired optical fiber, and cannot be the transmitting end of a wireless link.

[0127] 303, calculating the flow in-out difference between the output flow and the input flow corresponding to each base station;

[0128] 304, constructing the wireless optimization objective function with the minimum system flow in-out difference as the target.

[0129] In the embodiment of the present application, the current execution end calculates the flow in-out difference between the output flow and the input flow corresponding to each base station, which can be represented by the formula: i，out Ri i，in ; then, the wireless optimization objective function is constructed with the minimum system flow in-out difference as the target, which is specifically as follows:

[0130]

[0131] In the embodiment, after the wireless optimization objective function is constructed, the current execution end also needs to optimize and solve the constructed wireless optimization objective function to obtain the unbalanced base station under the wireless connection, which specifically includes:

[0132] 305, configuring the wireless optimization objective function with a first constraint condition, and the first constraint condition includes a half-duplex communication constraint, a user next-hop connection number constraint and a base station next-hop connection number constraint;

[0133] In the embodiment of the present application, the current execution end also configures the wireless optimization objective function constructed in step 304 with a first constraint condition, and the first constraint condition includes a half-duplex communication constraint, a user next-hop connection number constraint and a base station next-hop connection number constraint. The half-duplex communication constraint is specifically described by the following formula:

[0134]

[0135] The above-mentioned half-duplex communication constraint represents the restriction of half-duplex communication in a wireless backhaul link (a wireless link between base stations), that is, only a one-way transmission link is allowed to exist.

[0136] The user next-hop connection quantity constraint is constructed based on the technical features of step 301, and specifically:

[0137]

[0138] The base station next-hop connection quantity constraint is specifically shown in the following formula:

[0139]

[0140] The above-mentioned constraint condition limits the number of next wireless links allowed to be established by the base station i, and M represents the maximum number of next-hop links allowed to exist with the micro base station as the starting node.

[0141] 306, the connection state parameters in the wireless optimization objective function and the first constraint condition are relaxed, and a penalty term is added to the wireless optimization objective function to obtain a first to-be-solved model;

[0142] In the embodiment of the application, in order to enhance the effect of optimization solving, the current execution end relaxes the connection state parameters in the wireless optimization objective function and the first constraint condition, that is, the 0-1 variable x i,j is relaxed to an interval value variable. At the same time, the current execution end also needs to add a penalty term to the wireless optimization objective function to obtain a first to-be-solved model, and the specific formula is as follows:

[0143]

[0144] Wherein, x i，j，prev is the result generated by the last round of optimization, and the initial value of x i，j，prev is set to zero.

[0145] 307, the first to-be-solved model is iteratively solved until the tolerance is less than a preset value or the maximum number of iterations is reached, and a wireless optimization solving result is obtained; and the unbalanced base station in the system under the wireless connection condition is determined based on the wireless optimization solving result.

[0146] In the embodiment of the application, the current execution end can use CVX (Convex Optimization Solver) to iteratively solve the above-mentioned first to-be-solved model until the tolerance is less than a preset value or the maximum number of iterations is reached, and a wireless optimization solving result is obtained. The current execution end also needs to determine R in > Rout congested base stations, and R in <R out surplus base stations.

[0147] Further, as a refinement and extension of the above embodiment, in order to design a wired link adjustment for a congested base station, another method for designing a hybrid wired and wireless network is provided, after establishing a wired connection between the congested base station and the surplus base station and establishing a wired optimization objective function with the goal of minimizing the wired connection path, the method further comprises:

[0148] configuring a second constraint condition for the wired optimization objective function, the second constraint condition comprising a wired connection symmetry constraint, a wired connected component selectivity constraint, a wired connected component internal base station number constraint, a wired connection edge number constraint, a selected base station number constraint, a wired connected component flow in and out constraint, and a wired connected component aggregation constraint.

[0149] wherein the wired connection symmetry constraint is specifically shown in the following formula:

[0150]

[0151] The wired connection symmetry constraint can effectively prevent self-loop connection (connecting oneself).

[0152] wherein the wired connected component selectivity constraint is specifically shown in the following formula:

[0153]

[0154] The wired connected component selectivity constraint means that only when both base stations are selected to form a wired connected component, there is a possibility of wired connection between the two base stations. Specifically:

[0155] (1) If one of the base station i or the base station j is not selected, taking the base station i as an example, p(i) = 0, p(j) = 1, the constraint condition becomes:

[0156]

[0157] Since x is a 0-1 binary variable, it can only take 0, and there is no connection between the base station i and the base station j. This is even more true when both base stations are not selected.

[0158] (2) If both the base station i and the base station j are selected, p(i) = 1, p(j) = 1, the constraint condition becomes:

[0159]

[0160] This is equivalent to an invalid constraint, and whether to connect depends on the connected condition constraint.

[0161] The number of internal base stations of the wired communication body is constrained by the following formula:

[0162] p(1) = 1

[0163]

[0164] Wherein, p(1) = 1 indicates that the congested base station must be selected. N represents the number of internal independent base stations of the final generated wired communication body (because the minimum case is one congested base station and one rich base station; the maximum case is one congested base station and all rich base stations).

[0165] The number of wired connection edges is constrained by the following formula:

[0166]

[0167] The number of wired connection edges indicates that the number of wired connection edges should be N-1, so that the minimum spanning tree can be generated.

[0168] The number of selected base stations is constrained by the following formula:

[0169]

[0170] The number of selected base stations indicates that the number of all selected base stations should be the same as the number of independent base stations inside the wired communication body.

[0171] The wired communication body flow in and out constraint is constrained by the following formula:

[0172]

[0173] The wired communication body flow in and out constraint indicates that the final determined wired communication body should not be congested.

[0174] The wired communication aggregation constraint is constructed based on a single commodity flow model, including:

[0175] (1) Set auxiliary variable Z i,j ;

[0176] In the embodiment of the application, there is already a variable x in the wired optimization objective function to represent whether there is a wired connection between two base stations. However, if only the variable x is used for optimization design, the generated wired communication body cannot be avoided to be divided, so the auxiliary variable Z i,j can ensure that the finally generated wired communication body is a complete whole.

[0177] In the present embodiment, for the convenience of description, the value of the auxiliary variable (0-1 variable) can be referred to as a connected flow. Since all the selected redundant base stations can be connected with the congested base station, the congested base station can be regarded as a water source, and water can flow from the congested base station (water source) to the connected redundant base stations through the wired connection. Therefore, the following constraint condition is intended to make the water flow from the source (congested base station) to all the selected redundant base stations, so as to ensure that the finally generated is a connected whole.

[0178] (2) setting the output flow of the congested base station to each redundant base station i as Z 1,i , and setting the input flow of each redundant base station i to the congested base station as Z i,1 ; and setting the wired connected flow constraint based on the output flow Z 1,i and the input flow Z i,1 , which is specifically shown in the following formula:

[0179]

[0180] The wired connected flow constraint is that the congested base station k is regarded as a water source, Z 1,i , and the subscript 1 is the congested base station, which represents the water flow from the congested base station to the redundant base station i, and the cumulative items are the total output flow of the congested base station, and the latter cumulative item is the total input flow of the congested base station.

[0181] It should be noted that in the above constraint condition, the second formula indicates that if the redundant base station i is selected, then obviously according to the previous definition p(i) = 1, so the water flow into the redundant base station i must be greater than or equal to 1 (the value of z is 0 or 1), and since the congested base station is regarded as a source, the base station i can only have a flow path with the congested base station, either directly connected or connected through an intermediate base station. This constraint can ensure that all the selected redundant base stations i have a connected path with the congested base station.

[0182] (3) constructing the flow conservation constraint and the connected constraint based on the auxiliary variable Z i,j ;

[0183] The flow conservation constraint is specifically shown in the following formula:

[0184]

[0185] When the base station i is selected, p(i) = 1, and the constraint becomes:

[0186]

[0187] For the intermediate base station in the connected body, the total water flow input into it is equal to the total water flow output from it, so the inequality will be automatically taken as equality in the solving process. For the non-intermediate base station in the connected body, there is only input but no output, so the total output flow in the constraint is less than or equal to the total input flow.

[0188] The connected constraint is specifically as shown in the following formula:

[0189]

[0190] The above connected constraint is used to force the water flow to exist only in the wired connection.

[0191] (4) The wired connected body flow constraint, the flow conservation constraint and the connected constraint jointly constitute the wired connected aggregation constraint.

[0192] Further, as a refinement and expansion of the above embodiment, in order to enhance the effect of optimization solving, another design method of a wired and wireless mixed network is provided, as shown in the following steps: Figure 4 The wired optimization target function is sequentially optimized and solved in the order of the traffic input and output difference of the congested base station from small to large, to obtain a wired connection optimization result, including:

[0193] 401. Relaxing the 0-1 variables in the wired optimization target function and the second constraint condition, and adding a penalty term in the wired optimization target function to obtain a second to-be-solved model;

[0194] In the embodiment of the application, the current execution end relaxes the 0-1 variables in the wired optimization target function and the second constraint condition, that is, the 0-1 variables are relaxed to interval-valued variables. At the same time, the current execution end also needs to add a penalty term in the wired optimization target function to obtain a second to-be-solved model, and the specific formula is as follows:

[0195]

[0196]

[0197] Wherein, x i，j，prev and p prev (i) is the result generated by the last round of optimization, and the initial value is set to zero.

[0198] 402. All the congested base stations are sorted in the order of the traffic input and output difference from small to large, and the order of the sorted congested base stations is determined as the order of the sequential optimization and solving;

[0199] In this embodiment of the invention, since the inflow / outflow difference of congested base stations is negative, the smaller the inflow / outflow difference, the more severe the congestion. The current execution terminal sorts all congested base stations in ascending order of inflow / outflow difference, thus obtaining congested base stations sorted by congestion severity. The current execution terminal determines the order of the sorted congested base stations as the order of the successive optimization solution, that is, it starts the wired connection optimization process from the most congested base station until the least congested base station is reached.

[0200] 403. Obtain the currently optimized congested base station from the order of successive optimization solutions, substitute the currently optimized congested base station and all redundant base stations into the second solution model to solve for the wired connection topology, and obtain the current wired connection scheme corresponding to the currently optimized congested base station.

[0201] In this embodiment of the invention, the current execution terminal obtains the currently optimized congested base station from the successive optimization solution order, and substitutes the currently optimized congested base station and all redundant base stations into the second solution model to solve for the wired connection topology. In this embodiment, CVX (Convex Optimization Solver) is preferably used to iteratively solve the above-mentioned second solution model to obtain the current wired connection scheme corresponding to the currently optimized congested base station.

[0202] 404. Integrate all base stations included in the current limited connection scheme into a wired connected entity; and substitute the wired connected entity as a surplus base station into the process of solving the wired connection topology of the next congested base station, until the wired connection topology of all the congested base stations is solved, and obtain the wired connection optimization result.

[0203] In this embodiment of the invention, before the current execution terminal performs the wired connection topology optimization solution for the next congested base station, it is also necessary to integrate all base stations included in the current limited connection scheme into a wired connected entity; and substitute the wired connected entity as a surplus base station into the process of solving the wired connection topology for the next congested base station.

[0204] It should be noted that when a wired connected entity is substituted as a surplus base station into the wired connection topology solution for the next congested base station, the distance d between the congested base station and the aggregation base station (wired connected entity) is calculated. i,jWhen the congestion base station i is found, the Euclidean distance between the congestion base station i and several sub-base stations included in the wired communication body needs to be calculated, the smallest distance is selected as the effective distance between the congestion base station i and the wired communication body, and the independent base station j which produces the smallest distance with the congestion base station is recorded, and then if the wired communication body is subsequently selected to be directly connected with the congestion base station i, the independent base station j which is closest to the wired communication body can be directly connected with the congestion base station i.

[0205] Therefore, by continuously repeating the above solving process until all the congestion base stations are successfully solved, the wired connection optimization result is obtained.

[0206] The embodiment of the present application provides a design method of a wired and wireless hybrid network, compared with the prior art, the present application obtains the transmission rate between users and base stations and between base stations in the system, and constructs a transmission rate matrix based on the transmission rate; sets the connection mode between all base stations as wireless connection, and constructs a wireless optimization objective function based on the transmission rate matrix; the wireless optimization objective function is optimized and solved to obtain the unbalanced base stations under the wireless connection; the unbalanced base stations include congestion base stations and surplus base stations, the optimization design of the wireless connection in the system is realized, and the appearance of the congestion base stations in the system is reduced as much as possible. Then, the wired connection between the congestion base stations and the surplus base stations is established, and a wired optimization objective function is established with the minimum wired connection path as the target; the wired optimization objective function is sequentially optimized and solved according to the traffic in and out difference of the congestion base stations from small to large, and the wired connection optimization result is obtained, the resource imbalance problem which cannot be solved by relying on the wireless link optimization is solved, and the wired link after optimization meets the resource integration condition while the line layout is the shortest. In summary, the present application realizes the resource integration of the load imbalance nodes in the way of wired and wireless fusion.

[0207] As an implementation of the method shown in the above Figure 1 , the embodiment of the present application provides a design device of a wired and wireless hybrid network, as shown in the above Figure 5 , the device comprises:

[0208] The rate matrix construction module 51 is used for obtaining the transmission rate between users and base stations and between base stations in the system, and constructing a transmission rate matrix based on the transmission rate;

[0209] The first optimization module 52 is used for setting the connection mode between all base stations as wireless connection, and constructing a wireless optimization objective function based on the transmission rate matrix;

[0210] The first solving module 53 is configured to solve the wireless optimization objective function to obtain an unbalanced base station in a wireless connection, wherein the unbalanced base station includes a congested base station and a surplus base station.

[0211] The second optimization module 54 is configured to establish a wired connection between the congested base station and the surplus base station, and establish a wired optimization objective function with a minimum wired connection path as an objective.

[0212] The second solving module 55 is configured to solve the wired optimization objective function in a descending order of a traffic in-out difference of the congested base station to obtain a wired connection optimization result.

[0213] Further, the rate matrix construction module 51 is further configured to:

[0214] obtain spatial positions of base stations and user distribution positions in a system, and determine a straight-line distance between end-to-end based on the spatial positions of the base stations and the determined user distribution positions;

[0215] calculate a received signal power and an interference power based on the straight-line distance between the end-to-end and a channel condition;

[0216] determine a transmission rate between the end-to-end in the system based on the received signal power and the interference power by using a Shannon formula, and construct the transmission rate matrix based on the transmission rates between all the end-to-end in the system.

[0217] Further, the first optimization module 52 is further configured to:

[0218] establish a wireless connection relationship between a user equipment and a base station with a highest transmission rate in a preset range;

[0219] determine an output traffic and an input traffic corresponding to each base station in the system based on the transmission rate matrix;

[0220] calculate a traffic in-out difference between the output traffic and the input traffic corresponding to each base station;

[0221] construct the wireless optimization objective function with a minimum system traffic in-out difference as an objective.

[0222] Further, the first solving module 53 is further configured to:

[0223] configure a first constraint condition for the wireless optimization objective function, wherein the first constraint condition includes a half-duplex communication constraint, a user next-hop connection number constraint, and a base station next-hop connection number constraint;

[0224] relaxing the connection state parameters in the wireless optimization objective function and the first constraint condition, and adding a penalty term in the wireless optimization objective function to obtain a first to-be-solved model;

[0225] iteratively solving the first to-be-solved model until a tolerance is less than a preset value or a maximum iteration number is reached to obtain a wireless optimization solving result; and determining the unbalanced base station under a system internal wireless connection condition based on the wireless optimization solving result.

[0226] Further, the second optimization module 54 is further configured to:

[0227] configure a second constraint condition for the wired optimization objective function, the second constraint condition including a wired connection symmetry constraint, a wired connectivity body selectivity constraint, a wired connectivity body internal base station number constraint, a wired connection edge number constraint, a selected base station number constraint, a wired connectivity body flow in-out constraint, and a wired connectivity aggregation constraint.

[0228] Further, the wired connectivity aggregation constraint in the second optimization module 54 is constructed based on a single commodity flow circulation model, including:

[0229] setting an auxiliary variable Z i,j ;

[0230] setting an output flow of the congested base station to each rich base station i as Z 1,i , and setting an input flow of each rich base station i to the congested base station as Z i,1 ; and setting a wired connectivity body flow constraint based on the output flow Z 1,i and the input flow Z i,1 ;

[0231] constructing a flow conservation constraint and a connectivity constraint based on the auxiliary variable Z i,j ;

[0232] The wired connectivity body flow constraint, the flow conservation constraint, and the connectivity constraint jointly constitute the wired connectivity aggregation constraint.

[0233] Further, the second solving module 55 is further configured to:

[0234] relaxing the 0-1 variable in the wired optimization objective function and the second constraint condition, and adding a penalty term in the wired optimization objective function to obtain a second to-be-solved model;

[0235] sorting all the congested base stations in ascending order of the flow in-out difference, and determining the order of the sorted congested base stations as the order of the successive optimization solving;

[0236] The currently optimized congested base station is obtained from the successive optimization solution order. The currently optimized congested base station and all redundant base stations are substituted into the second solution model to solve the wired connection topology, and the current wired connection scheme corresponding to the currently optimized congested base station is obtained.

[0237] The current limited connection scheme integrates all base stations into a wired connected entity; and the wired connected entity is used as a surplus base station in the process of solving the wired connection topology of the next congested base station, until the wired connection topology of all the congested base stations is solved, and the wired connection optimization result is obtained.

[0238] This invention provides a design apparatus for a hybrid wired and wireless network. Compared with existing technologies, this invention obtains the transmission rate information between users and base stations, and between base stations, and constructs a transmission rate matrix based on this information. It sets the connection method between all base stations to wireless and constructs a wireless optimization objective function based on the transmission rate matrix. The invention then optimizes the wireless optimization objective function to obtain unbalanced base stations under wireless connection conditions. These unbalanced base stations include congested base stations and redundant base stations, thus optimizing the wireless connection design within the system and minimizing the occurrence of congested base stations. Next, wired connections are established between the congested and redundant base stations, and a wired optimization objective function is established with the goal of minimizing the wired connection path. The wired optimization objective function is then successively optimized according to the increasing traffic difference between the congested base stations to obtain the optimized wired connection result. This solves the resource imbalance problem that cannot be addressed by wireless link optimization alone, and ensures that the optimized wired links meet resource integration conditions while minimizing line deployment. In summary, this invention achieves resource integration for nodes with unbalanced loads through a combination of wired and wireless methods.

[0239] According to one embodiment of the present invention, a storage medium is provided, the storage medium storing at least one executable instruction, the computer-executable instruction being capable of executing the design method of the wired and wireless hybrid network in any of the above method embodiments.

[0240] Figure 6 The diagram shows a structural schematic of a device according to an embodiment of the present invention. The specific implementation of the device is not limited by the specific embodiments of the present invention.

[0241] like Figure 6 As shown, the device may include: a processor 602, a communications interface 604, a memory 606, and a communications bus 608.

[0242] The processor 602, the communication interface 604, and the memory 606 communicate with each other through a communication bus 608.

[0243] The communication interface 604 is configured to communicate with network elements such as clients or other servers.

[0244] The processor 602 is configured to execute the program 610, and in particular, execute the steps of the method for designing a hybrid wired and wireless network.

[0245] In particular, the program 610 can include program codes including computer operation instructions.

[0246] The processor 602 can be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present application. The one or more processors included in the device can be of the same type, such as one or more CPUs, or can be of different types, such as one or more CPUs and one or more ASICs.

[0247] The memory 606 is configured to store the program 610. The memory 606 can include a high-speed RAM memory, and can also include a non-volatile memory such as at least one disk memory.

[0248] The program 610 can be specifically configured to cause the processor 602 to perform the following operations:

[0249] Obtain transmission rate conditions between users and base stations, and between base stations in the system, and construct a transmission rate matrix based on the transmission rate conditions;

[0250] Set the connection mode between all base stations to wireless connection, and construct a wireless optimization objective function based on the transmission rate matrix;

[0251] Optimize and solve the wireless optimization objective function to obtain unbalanced base stations in the wireless connection; the unbalanced base stations include congested base stations and surplus base stations;

[0252] Establish a wired connection between the congested base stations and the surplus base stations, and establish a wired optimization objective function with the objective of minimizing the wired connection path;

[0253] Optimize and solve the wired optimization objective function in sequence according to the flow in-out difference of the congested base stations from small to large to obtain a wired connection optimization result.

[0254] It should be apparent to those skilled in the art that the modules or steps of the application described above can be implemented with a general purpose computing device, which can be centralized on a single computing device or distributed over a network of multiple computing devices, and optionally implemented with program code executable by a computing device, which can be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described can be performed in a different order than shown, or made into individual integrated circuit modules, or multiple modules or steps made into a single integrated circuit module. Thus, the application is not limited to any particular combination of hardware and software.

[0255] The preferred embodiments of the application described above are intended to be merely illustrative, and numerous modifications and adaptations will be apparent to those skilled in the art. Such modifications and adaptations do not depart from the spirit and scope of the application as set forth in the following claims.

Claims

1. A method of designing a hybrid wired and wireless network, characterized by, The method comprises the following steps: acquiring transmission rate conditions between users and base stations, and between base stations in a system, and constructing a transmission rate matrix based on the transmission rate conditions; setting a connection mode between all base stations as a wireless connection, and constructing a wireless optimization objective function based on the transmission rate matrix; optimizing and solving the wireless optimization objective function to obtain unbalanced base stations in a wireless connection condition; the unbalanced base stations comprise congested base stations and surplus base stations; establishing a wired connection between the congested base stations and the surplus base stations, and establishing a wired optimization objective function with the objective of minimizing a wired connection path; optimizing and solving the wired optimization objective function in sequence according to a flow in-out difference value of the congested base stations from small to large to obtain a wired connection optimization result; the step of constructing the wireless optimization objective function based on the transmission rate matrix comprises the following steps: establishing a wireless connection relationship between a user equipment and a base station with the highest transmission rate within a preset range; determining output flow and input flow corresponding to each base station in the system based on the transmission rate matrix; calculating a flow in-out difference value between the output flow and the input flow corresponding to each base station; constructing the wireless optimization objective function with the objective of minimizing a system flow in-out difference value.

2. The method of claim 1, wherein, the step of constructing the transmission rate matrix based on the transmission rate conditions comprises the following steps: acquiring spatial positions of base stations and user distribution positions in the system, and determining a straight-line distance between end-to-end based on the spatial positions of the base stations and the user distribution positions; calculating received signal power and interference power based on the straight-line distance between end-to-end and channel conditions; determining transmission rate between end-to-end in the system by using a Shannon formula based on the received signal power and the interference power, and constructing the transmission rate matrix based on transmission rates between all end-to-end in the system.

3. The method of claim 1, wherein, the step of optimizing and solving the wireless optimization objective function to obtain unbalanced base stations in a wireless connection condition comprises the following steps: configuring a first constraint condition for the wireless optimization objective function, the first constraint condition comprising a half-duplex communication constraint, a user next-hop connection quantity constraint, and a base station next-hop connection quantity constraint; performing relaxation processing on connection state parameters in the wireless optimization objective function and the first constraint condition, and adding a penalty term in the wireless optimization objective function to obtain a first to-be-solved model; iteratively solving the first to-be-solved model until a tolerance is less than a preset value or a maximum iteration number is reached to obtain a wireless optimization solving result, and determining the unbalanced base stations in a wireless connection condition in the system based on the wireless optimization solving result.

4. The method of claim 1, wherein, after the step of establishing a wired connection between the congested base stations and the surplus base stations, and establishing a wired optimization objective function with the objective of minimizing a wired connection path, the method further comprises the following steps: configuring a second constraint condition for the wired optimization objective function, the second constraint condition comprising a symmetry constraint of a wired connection, a wired connectivity body selective constraint, a wired connectivity body internal base station quantity constraint, an edge number constraint of the wired connection, a selected base station quantity constraint, a wired connectivity body flow in-out constraint, and a wired connectivity aggregation constraint.

5. The method of claim 4, wherein, The wired communication aggregation constraint is constructed based on a single commodity circulation model, and includes: Setting an auxiliary variable Z i,j ; setting the output flow from the congested base station to each of the surplus base stations i to Z 1,i , and setting the input flow from each of the surplus base stations i to the congested base station to Z i,1 ; and setting a wired connectivity volume constraint based on the output flow Z 1,i and the input flow Z i,1 ​ based on the auxiliary variable Z i,j constructing flow conservation constraints and connectivity constraints; The wired communication body flow constraint, the flow conservation constraint, and the communication constraint jointly constitute the wired communication aggregation constraint.

6. The method of claim 5, wherein, The wired optimization objective function is sequentially optimized and solved in the order of the traffic in-out difference values of the congested base stations from small to large, to obtain a wired connection optimization result, including: The 0-1 variables in the wired optimization objective function and the second constraint condition are relaxed, and a penalty term is added to the wired optimization objective function, to obtain a second to-be-solved model; All the congested base stations are sorted in the order of the traffic in-out difference values from small to large, and the order of the sorted congested base stations is determined as the order of the sequential optimization and solution; A current optimized congested base station is obtained from the order of the sequential optimization and solution, the current optimized congested base station and all the surplus base stations are substituted into the second to-be-solved model to solve the wired connection topology, to obtain a current wired connection scheme corresponding to the current optimized congested base station; All the base stations included in the current wired connection scheme are integrated into a wired communication body, and the wired communication body is substituted into the process of solving the wired connection topology of the next congested base station as a surplus base station, until the solving of the wired connection topology of all the congested base stations is completed, to obtain the wired connection optimization result.

7. A design device for a hybrid wired and wireless network, characterized in that, including: a rate matrix construction module, configured to acquire transmission rate conditions between users and base stations and between base stations in a system, and construct a transmission rate matrix based on the transmission rate conditions; a first optimization module, configured to set a connection mode between all the base stations as a wireless connection, and construct a wireless optimization objective function based on the transmission rate matrix; a first solving module, configured to optimize and solve the wireless optimization objective function, to obtain unbalanced base stations in a wireless connection state; the unbalanced base stations include congested base stations and surplus base stations; a second optimization module, configured to establish a wired connection between the congested base stations and the surplus base stations, and establish a wired optimization objective function with the minimum wired connection path as a target; a second solving module, configured to sequentially optimize and solve the wired optimization objective function in the order of traffic in-out difference values of the congested base stations from small to large, to obtain a wired connection optimization result; The first optimization module is further configured to: establish a wireless connection relationship between a user equipment and a base station with the highest transmission rate within a preset range; determine output traffic and input traffic corresponding to each base station in the system based on the transmission rate matrix; calculate traffic in-out difference values between the output traffic and the input traffic corresponding to each base station; construct the wireless optimization objective function with the minimum system traffic in-out difference value as a target.

8. A storage medium, characterized by The storage medium stores at least one executable instruction, and the executable instruction performs operations corresponding to the design method of the wired and wireless hybrid network in any one of claims 1-6. The storage medium stores at least one executable instruction, and the executable instruction performs operations corresponding to the design method of the wired and wireless hybrid network in any one of claims 1-6.

9. An apparatus, comprising: comprising a processor, a memory, a communication interface and a communication bus, which enable mutual communication among the processor, the memory and the communication interface; the memory is configured to store at least one executable instruction, which enables the processor to perform operations corresponding to the design method of the wired and wireless hybrid network according to any one of claims 1-6.

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