CN112788688A

CN112788688A - Vertical switching method, device, equipment and storage medium between heterogeneous networks

Info

Publication number: CN112788688A
Application number: CN202110033109.5A
Authority: CN
Inventors: 邓宏贵; 王书敏; 刘刚
Original assignee: Central South University
Current assignee: Central South University
Priority date: 2021-01-11
Filing date: 2021-01-11
Publication date: 2021-05-11
Anticipated expiration: 2041-01-11
Also published as: CN112788688B

Abstract

The invention discloses a vertical switching method, a vertical switching device, vertical switching equipment and a vertical switching storage medium among heterogeneous networks. Wherein, the method comprises the following steps: determining prior switching probability of the UE to each base station in the heterogeneous network based on TOPSIS; solving the state transition probability of each base station based on the prior switching probability; determining the current state value of each base station based on the set judgment attribute; obtaining the conditional probability of switching the UE to each base station based on the state value; and determining a target base station switched by the UE based on the prior switching probability and the conditional probability. In the process of determining the target base station, the embodiment of the invention not only considers the current state of the base station, but also comprehensively considers the user service quality requirement, thereby effectively improving the resource utilization rate of the heterogeneous network system and ensuring the user service quality requirement.

Description

Vertical switching method, device, equipment and storage medium between heterogeneous networks

Technical Field

The present invention relates to the field of wireless communications technologies, and in particular, to a method, an apparatus, a device, and a storage medium for vertical handover between heterogeneous networks.

Background

With the rapid development of wireless network technologies, heterogeneous networks with different network characteristics and adopting different access technologies, such as WiFi networks, 4G networks, 5G networks, etc., are emerging continuously. In order to better utilize access technologies of various heterogeneous networks and meet the requirement of a user on network service quality, researchers design various heterogeneous network convergence technical schemes. In the convergence technical solution of the heterogeneous network, mobility management is the most important issue, and mainly includes location management and handover management. Handover between heterogeneous networks, also referred to as vertical handover, is a hot spot of current research.

The vertical handover process between heterogeneous networks can be divided into three stages of network discovery, handover decision and handover execution. Among them, the handover decision is a very important link in the whole handover process. In the aspect of handover decision, when designing a vertical handover algorithm, the complexity of the algorithm, the quality of service requirements of users, and the network performance of each base station need to be considered comprehensively. Common vertical switching algorithms can be roughly divided into four types, the first type is a vertical switching algorithm based on received signal strength, the algorithm has single judgment attribute and too simple design, the characteristic difference of networks of all systems cannot be reflected, and the ping-pong effect is easily caused; the second type is a multi-attribute decision algorithm which selects various terminal decision attributes and constructs corresponding effect functions or cost functions in a mode of weighting the attributes so as to determine the optimal network for access, and the vertical switching algorithm is simple in design and low in operation complexity, so that the vertical switching algorithm is largely used and researched, but the flexibility is poor, and the dynamic change characteristic of the network state is not considered; the third type is a switching algorithm based on an intelligent System, which inputs the decision attribute of the network into a Fuzzy Inference System (FIS) or a neural network for processing, and performs a switching decision according to the System output. The algorithm has high accuracy, high operation complexity and poor coordination of switching users; the fourth type is a vertical switching algorithm based on a Markov decision process, and the algorithm quantizes the network states at different times by introducing a cost function, so that a switching user can master the dynamic change characteristic of the network state in real time, the user is well ensured to access to a network with low blocking rate and low time delay, but the service requirement of the user side is not considered.

Disclosure of Invention

In view of this, embodiments of the present invention provide a method, an apparatus, a device, and a storage medium for vertical handover between heterogeneous networks, which aim to improve resource utilization of a heterogeneous network system and ensure a service quality requirement of a user.

The technical scheme of the embodiment of the invention is realized as follows:

the embodiment of the invention provides a vertical switching method between heterogeneous networks, which comprises the following steps:

determining prior switching probability of User Equipment (UE) switching to each base station in a heterogeneous network based on a Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS);

solving the state transition probability of each base station based on the prior switching probability;

determining the current state value of each base station based on the set judgment attribute;

obtaining the conditional probability of switching the UE to each base station based on the state value;

and determining a target base station switched by the UE based on the prior switching probability and the conditional probability.

An embodiment of the present invention further provides a device for vertical handover between heterogeneous networks, where the device includes:

the first probability obtaining module is used for determining prior switching probability of the UE switched to each base station in the heterogeneous network based on TOPSIS;

a second probability calculating module, configured to calculate a state transition probability of each base station based on the prior handover probability;

the state value solving module is used for determining the current state value of each base station based on the set judgment attribute;

a third probability calculating module, configured to calculate a conditional probability of switching the UE to each base station based on the state value;

and the switching decision module is used for determining a target base station switched by the UE based on the prior switching probability and the conditional probability.

An embodiment of the present invention further provides a vertical handover device between heterogeneous networks, including: a processor and a memory for storing a computer program capable of running on the processor, wherein the processor, when running the computer program, is configured to perform the steps of the method according to an embodiment of the invention.

The embodiment of the present invention further provides a storage medium, where a computer program is stored on the storage medium, and when the computer program is executed by a processor, the steps of the method according to the embodiment of the present invention are implemented.

The technical scheme provided by the embodiment of the invention is based on the prior switching probability of UE switched to each base station in the TOPSIS heterogeneous network, the state transition probability of each base station is obtained based on the prior switching probability, the current state value of each base station is determined, the corresponding conditional probability of UE switching is obtained based on the current state value of each base station, and the target base station switched by the UE is determined based on the prior switching probability and the conditional probability. In the process of determining the target base station, the embodiment of the invention not only considers the current state of the base station, but also comprehensively considers the user service quality requirement, thereby effectively improving the resource utilization rate of the heterogeneous network system and ensuring the user service quality requirement.

Drawings

Fig. 1 is a flowchart illustrating a vertical handover method between heterogeneous networks according to an embodiment of the present invention;

FIG. 2 is a diagram illustrating a base station distribution during simulation in an exemplary application of the present invention;

FIG. 3 is a diagram illustrating a comparative simulation of a conventional vertical handover algorithm and a vertical handover algorithm proposed in the present invention on a system transmission rate;

FIG. 4 is a diagram illustrating a comparative simulation of a conventional vertical handover algorithm and a vertical handover algorithm proposed in the present invention on a system blocking rate;

fig. 5 is a schematic structural diagram of a vertical handover device between heterogeneous networks according to an embodiment of the present invention;

fig. 6 is a schematic structural diagram of a vertical handover device between heterogeneous networks according to an embodiment of the present invention.

Detailed Description

The present invention will be described in further detail with reference to the accompanying drawings and examples.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

An embodiment of the present invention provides a method for vertical handover between heterogeneous networks, where the heterogeneous networks may include at least two different networks, for example, including but not limited to at least two of the following: a WiFi network, a 3G network, a 4G network, a 5G network, etc. The UE may be a mobile terminal such as a smart phone, a tablet computer, and an intelligent wearable device, which is not specifically limited in this embodiment of the present invention. As shown in fig. 1, the method includes:

step 101, determining prior switching probability of UE switching to each base station in a heterogeneous network based on TOPSIS;

here, TOPSIS is an intra-group comprehensive evaluation method that can make full use of information of raw data, and the result can accurately reflect the gap between evaluation schemes. The basic process is based on the normalized original data matrix, the optimal scheme and the worst scheme in the limited schemes are found out by adopting a cosine method, then the distance between each evaluation object and the optimal scheme and the worst scheme is respectively calculated, and the relative approach degree of each evaluation object and the optimal scheme is obtained to be used as the basis for evaluating the quality. The method has no strict limitation on data distribution and sample content, and data calculation is simple and easy to implement.

Here, the a priori handover probability taking into account the user side requirements can be determined based on TOPSIS. Illustratively, step 101 may include:

obtaining a decision attribute for reflecting the service quality requirement of a user;

and solving the prior switching probability of the UE to each base station based on the TOPSIS and the decision attribute.

The decision attributes may include, but are not limited to: received signal strength, bit error rate, throughput, etc. Assuming that the decision attribute includes K attributes and the heterogeneous network includes M base stations, the attribute matrix a of M × K order can be obtained after the homologation and normalization processing of each attribute.

Wherein, the syntropy formula is as follows:

the normalized formula is as follows:

in the formula A_(：，l)And the matrix Z is a normalized matrix after being syntropized and normalized.

Then, solving the positive and negative ideal solutions of each attribute:

calculating the distance between each candidate network and the positive and negative ideal solutions:

next, the closeness of each candidate network to the optimal solution is calculated:

in the TOPSIS algorithm, the greater the proximity degree of the candidate network j and the optimal scheme is, the greater the probability of switching the user to the candidate network j is, and the sticking of each candidate network and the optimal scheme is carried outThe proximity normalization is the probability of switching to each base station without considering the overall switching strategy:

in the formula, c_ijRepresenting the proximity of user i to base station j.

The number of users switched to each base station j can be estimated according to the calculated closeness degree

The blocking rate of the base station can be further calculated and further corrected, and the blocking rate of the base station is calculated by the following formula:

wherein λ_jIs the user access rate, mu, of base station j_jIs the base station service rate, eta_jIs the base station capacity.

The final prior handover probability calculation formula is derived as follows:

wherein, BR_kIs the blocking rate of base station k, c_ikIndicating the proximity of user i to base station k.

102, solving the state transition probability of each base station based on the prior switching probability;

illustratively, step 102 may include:

counting the number of users of each base station based on the prior switching probability, and solving the user arrival rate and the user leaving rate of each base station;

and solving the state transition probability of each base station based on the user arrival rate and the user leaving rate.

In an application example, the prior switching probability of user switching is firstly utilized as the prejudgment of the userA decision stage, counting the number U of users of each base station_jThereby obtaining the user rate lambda of the base station_j＝U_j(t)/τ. Then, according to the queuing theory, the probability (i.e. user arrival rate) that each base station reaches k users in unit time can be calculated as:

when the service rate mu of each base station_jWhen it is known that the probability that a base station leaves k users in a unit time (i.e., user leaving rate) is:

the state transition probability of each base station is obtained as follows:

in the formula, c_jIndicates the number of persons currently accessed in the base station j, c_j′Indicates the possible number of people, p, accessed to the base station j after the decision period is finished_aIs the user arrival rate, p, of the base station_bIs the user leaving rate of the base station.

103, determining the current state value of each base station based on the set decision attribute;

illustratively, step 103 may include:

determining a state cost function representing the current state of the base station based on the set decision attribute;

determining the current state value of each base station based on the state value function;

wherein the set decision attribute comprises at least one of: average access bandwidth of the base station and network delay of the base station.

In an application example, the average access bandwidth of the base station and the network delay of the base station are selected as decision attributes for solving the state values of the base station in different states, and the state values of the base station can visually reflect the current state characteristics of the base station. The state cost function design may be as follows:

in the formula, s_j(t +1) is the state of the base station j at the next moment, β is the depreciation factor, and R is the corresponding instant reward under different states. Therefore, the state value of the corresponding state of all the base stations can be obtained by using a dynamic programming algorithm.

Here, the calculation of the instantaneous reward is related to the decision attributes of the selected network side, i.e. to the average access bandwidth of the base station and the network delay of the base station.

The average access bandwidth of the base station is a benefit type attribute (namely, a forward attribute), and the cost function of the base station is r_b(s_j(t)，j)＝(b(s_j(t)，j)-b_mmin)/(b_max-b_min)，b_maxAnd b_minIs the maximum and minimum bandwidth requirement, b(s), required for the connection_j(t), j) is the base station j in state s_jActual remaining bandwidth at (t), when b(s)_j(t)，j)＜b_min， r_b(s_j(t), j) is 0, when b(s)_j(t)，j)＞b_maxWhen r is_b(s_j(t)，j)＝1。

The network delay of the base station is of a loss type (namely, a negative attribute), and the cost function of the network delay is r_d(s_j(t)，j)＝(d_max-d(s_j(t)，j))/(d_max-d_min)；d_maxAnd d_minIs the maximum and minimum delay requirement, d(s), required for the connection_j(t), j) is the base station j in state s_jActual network delay at (t) when d(s)_j(t)，j)＜d_min， r_d(s_j(t, j) is 1, whend(s_j(t)，j)＞d_maxWhen r is_d(s_j(t)，j)＝0。

Let w_bAnd w_dRespectively, the weights of the remaining available bandwidth and the network delay, the total instantaneous reward of the base station j at time t is:

sheet(s)_j(t)，j)＝w_br_b(s_j(t)，j)+w_dr_d(s_j(t)，j)。

104, obtaining the conditional probability of switching the UE to each base station based on the state value;

here, the obtaining of the conditional probability of the UE switching to each base station based on the state value includes:

and determining the conditional probability corresponding to each base station based on the ratio of the state value of each base station to the sum of the state values of all base stations in the heterogeneous network.

Illustratively, the conditional probability for each base station is as follows:

wherein v is_ijAnd the state value of the base station j at the moment when the user i accesses the base station j is shown.

And 105, determining a target base station switched by the UE based on the prior switching probability and the conditional probability.

Illustratively, step 105 may include:

solving the posterior switching probability of the UE switched to each base station for the prior switching probability and the conditional probability based on a Bayesian formula;

and selecting the base station with the maximum posterior switching probability as the target base station.

Illustratively, the bayesian for determining the posterior handover probability is as follows:

wherein, p (u)_ij) A priori handover probability for user i to base station j, p (B)_j|u_ij) Conditional probability, p (u), for user i to switch to base station j_ij|B_j) The posterior handover probability for the user i to handover to the base station j, oc indicates a positive ratio.

In an application example, a heterogeneous network system is built, which is composed of three base stations, namely 3G, 4G and 5G, and the distribution of the three base stations is as shown in fig. 2, each base station is placed in a matrix space of 500m × 500m, wherein the 3G base station is located at a coordinate point (250, 500), the 4G base station is located at a coordinate point (0, 0), and the 5G base station is located at a coordinate point (500, 0). The number of channels of the three base stations is 10, 20 and 16 respectively.

After the number of channels is determined, the state of the base station can be determined. Then, the transition probability of each state is solved according to the queuing theory, and at this time, the state transition matrix of three base stations can be obtained by combining the number of channels as long as the service rate of the user is known, and the service rate μ is set to be 0.5.

In this application example, the total bandwidths of the three base stations are set to 5MHz, 20MHz, and 24MHz, respectively, and the maximum allowable time delays are: 300ms, 800ms and 320ms, and the average bandwidth is respectively set as: 0.5MHz, 1MHz, 1.5MHz, the average time delay is respectively: 30ms, 40ms, 20ms, U_B＝4MHz，L_B＝1MHz， U_D＝300ms，L_DWhen the time is 60ms, the cost function of each state can be obtained by the above equation.

In this application example, when solving the prior handover probability, the transmission rate, the bit error rate, and the received signal strength are selected as the decision attribute, and the calculation formula of the received signal strength is as follows:

RSS_ij(l)＝ρ-10*κln(l)+h；

in this application example, there are three base stations, and the transmission powers ρ of the three base stations 3G, 4G, and 5G are: the path loss factors of 10watts, 20watts and 30watts, and the path loss factors of the three base stations are 0.7, 1, 1 and h respectively, which are white noises satisfying (0, 1) gaussian distribution. The interference signal strengths are: -22, -8, -7.

The transmission rate is calculated by the formula: transmission rate:

the calculation formula of the bit error rate is as follows:

wherein

When the position of a user is determined, the signal-to-noise ratio of the user relative to each base station can be obtained according to the calculation formula and conditions, the signal-to-noise ratio can be determined, the error rate and the transmission rate can be calculated, 3 base stations are assumed, when the number of users is N, an N x 3-order error rate matrix and a transmission rate matrix can be formed, the value of each element in the matrix is known, N is 10-100, and the interval is 10, so that the change of the system performance along with the increase of the number of users can be observed.

The experimental parameter settings are shown in table 1, and the experimental results obtained according to the above procedure are shown in fig. 3 and 4.

TABLE 1

Parameter(s)	Value of
		Number of base stations	3
Name of base station	3G，4G，5G
		Coverage area of base station	7km，50km，25km
Number of base station channels	10，20，16
		Bandwidth of base station	5MHz，20MHz，24MHz
Base station transmission power	10watts，20watts，30watts
		Average received bandwidth	0.5MHz、1MHz、1.5MHz
Maximum time delay	300ms、800ms、320ms
		Average time delay	30ms、40ms、20ms
White gaussian noise of the channel	h～N(0，1)
		Measuring white gaussian noise	ξ²～N(0，10)
Decision gap	10second

FIG. 3 shows the maximum throughput curve obtained by the system when 100 access users are randomly generated in a 500 × 500 matrix and the users access the heterogeneous network at an arrival rate of 1-10. As can be seen from fig. 3, compared to the conventional vertical handover algorithm, for example, the dobby algorithm and the decision tree algorithm, the vertical handover algorithm used in the present invention can effectively increase the throughput of the system, thereby improving the overall performance of the heterogeneous network.

FIG. 4 shows a congestion rate curve obtained by a system when 100 access users are randomly generated in a 500 × 500 matrix and the users access a heterogeneous network at an arrival rate of 1-10. As can be seen from fig. 4, compared with the conventional vertical handover algorithm, for example, the dobby-based algorithm and the decision tree-based algorithm, the vertical handover algorithm used in the present invention can effectively reduce the blocking rate of the system, thereby improving the overall performance of the heterogeneous network.

In order to implement the method according to the embodiment of the present invention, an embodiment of the present invention further provides a vertical handover apparatus between heterogeneous networks, where as shown in fig. 5, the apparatus includes: a first probability calculating module 501, a second probability calculating module 502, a state value calculating module 503, a third probability calculating module 504 and a switching decision module 505. The first probability solution module 501 is configured to determine, based on TOPSIS, a priori handover probability of the UE to each base station in the heterogeneous network; the second probability obtaining module 502 is configured to obtain a state transition probability of each base station based on the prior handover probability; the state value calculating module 503 is configured to determine the current state value of each base station based on the set decision attribute; the third probability obtaining module 504 is configured to obtain a conditional probability that the UE is switched to each base station based on the state value; the handover decision module 505 is configured to determine a target base station for handover of the UE based on the prior handover probability and the conditional probability.

In some embodiments, the first probability derivation module 501 is specifically configured to:

In some embodiments, the calculation formula for determining the a priori handover probability is as follows:

wherein, c_ijRepresenting the proximity of a user i to a base station j, M being the number of base stations in the heterogeneous network, BR_jFor the blocking rate of the base station, BR_kIs the blocking rate of base station k, c_ikIndicating the proximity of user i to base station k.

In some embodiments, the second probability solution module 502 is specifically configured to:

In some embodiments, the state value calculation module 503 is specifically configured to:

In some embodiments, the third probability solution module 504 is specifically configured to:

In some embodiments, the handover decision module 505 is specifically configured to:

In practical applications, the first probability calculating module 501, the second probability calculating module 502, the state value calculating module 503, the third probability calculating module 504, and the handover decision module 505 may be implemented by a processor in a vertical handover device between heterogeneous networks. Of course, the processor needs to run a computer program in memory to implement its functions.

It should be noted that: in the vertical handover device between heterogeneous networks according to the above embodiment, when performing vertical handover between heterogeneous networks, only the division of the program modules is illustrated, and in practical applications, the above processing may be distributed to different program modules according to needs, that is, the internal structure of the device is divided into different program modules to complete all or part of the above-described processing. In addition, the vertical handover device between heterogeneous networks and the vertical handover method between heterogeneous networks provided in the foregoing embodiments belong to the same concept, and specific implementation processes thereof are described in detail in the method embodiments and are not described herein again.

Based on the hardware implementation of the program module, and in order to implement the method according to the embodiment of the present invention, an embodiment of the present invention further provides a vertical handover device between heterogeneous networks. Fig. 6 shows only an exemplary structure of the apparatus and not the entire structure, and a part of or the entire structure shown in fig. 6 may be implemented as necessary.

As shown in fig. 6, an apparatus 600 provided in an embodiment of the present invention includes: at least one processor 601, memory 602, user interface 603, and at least one network interface 604. The various components of the vertical switching device 600 between heterogeneous networks are coupled together by a bus system 605. It will be appreciated that the bus system 605 is used to enable communications among the components. The bus system 605 includes a power bus, a control bus, and a status signal bus in addition to a data bus. For clarity of illustration, however, the various buses are labeled as bus system 605 in fig. 6.

The user interface 603 may include, among other things, a display, a keyboard, a mouse, a trackball, a click wheel, a key, a button, a touch pad, or a touch screen.

The memory 602 in the embodiment of the present invention is used for storing various types of data to support the operation of the vertical handover device between heterogeneous networks. Examples of such data include: any computer program for operating on a vertical handover device between heterogeneous networks.

The vertical handover method between heterogeneous networks disclosed in the embodiment of the present invention may be applied to the processor 601, or implemented by the processor 601. The processor 601 may be an integrated circuit chip having signal processing capabilities. In the implementation process, the steps of the vertical handover method between heterogeneous networks may be implemented by an integrated logic circuit of hardware or an instruction in the form of software in the processor 601. The Processor 601 may be a general purpose Processor, a Digital Signal Processor (DSP), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. Processor 601 may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed by the embodiment of the invention can be directly implemented by a hardware decoding processor, or can be implemented by combining hardware and software modules in the decoding processor. The software module may be located in a storage medium located in the memory 602, and the processor 601 reads information in the memory 602, and completes the steps of the method for vertical handover between heterogeneous networks provided in the embodiment of the present invention in combination with hardware thereof.

In an exemplary embodiment, the vertical switching Device between heterogeneous networks may be implemented by one or more Application Specific Integrated Circuits (ASICs), DSPs, Programmable Logic Devices (PLDs), Complex Programmable Logic Devices (CPLDs), FPGAs, general purpose processors, controllers, Micro Controllers (MCUs), microprocessors (microprocessors), or other electronic components for performing the aforementioned methods.

It will be appreciated that the memory 602 can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic random access Memory (FRAM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical disk, or a Compact Disc Read-Only Memory (CD-ROM); the magnetic surface storage may be disk storage or tape storage. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Enhanced Synchronous Dynamic Random Access Memory (Enhanced DRAM), Synchronous Dynamic Random Access Memory (SLDRAM), Direct Memory (DRmb Access), and Random Access Memory (DRAM). The described memory for embodiments of the present invention is intended to comprise, without being limited to, these and any other suitable types of memory.

In an exemplary embodiment, an embodiment of the present invention further provides a storage medium, that is, a computer storage medium, which may specifically be a computer-readable storage medium, for example, including a memory 602 storing a computer program, where the computer program is executable by a processor 601 of a vertical handover device between heterogeneous networks, so as to complete the steps described in the method of the embodiment of the present invention. The computer readable storage medium may be a ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface Memory, optical disk, or CD-ROM, among others.

It should be noted that: "first," "second," and the like are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.

In addition, the technical solutions described in the embodiments of the present invention may be arbitrarily combined without conflict.

The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for vertical handover between heterogeneous networks is characterized by comprising the following steps:

determining prior switching probability of switching User Equipment (UE) to each base station in a heterogeneous network based on a good-bad solution distance method (TOPSIS);

2. The method of claim 1, wherein the determining the a priori handover probabilities of the UE handing over to the base stations in the heterogeneous network based on TOPSIS comprises:

3. The method of claim 2, wherein the prior handover probability is determined by the following equation:

wherein, c_ijRepresenting the proximity of a user i to a base station j, M being the number of base stations in the heterogeneous network, BR_jFor the blocking rate of base station j, BR_kIs the blocking rate of base station k, c_ikIndicating the proximity of user i to base station k.

4. The method of claim 1, wherein the determining the state transition probability for each base station based on the a priori handover probabilities comprises:

5. The method of claim 1, wherein determining the current state value of each base station based on the determined decision attributes comprises:

6. The method of claim 1, wherein the obtaining the conditional probability of the UE switching to each base station based on the state value comprises:

7. The method of claim 1, wherein the determining the target base station for the handover of the UE based on the a priori handover probability and the conditional probability comprises:

8. An apparatus for vertical handover between heterogeneous networks, comprising:

the state value calculating module is used for determining the current state value of each base station based on the set judgment attribute;

9. An apparatus for vertical handover between heterogeneous networks, comprising: a processor and a memory for storing a computer program capable of running on the processor, wherein,

the processor, when executing the computer program, is adapted to perform the steps of the method of any of claims 1 to 7.

10. A storage medium having a computer program stored thereon, the computer program, when executed by a processor, implementing the steps of the method of any one of claims 1 to 7.