Interoperability method and apparatus

Abstract

This invention provides an interoperability method and apparatus. The method includes: constructing an initial solution space for a differential adaptive evolutionary algorithm based on the value range of interoperability-related configuration parameters; determining a solution vector at the fitness of the optimal individual using the differential adaptive evolutionary algorithm based on historical interoperability-related data; and performing interoperation based on the solution vector at the fitness of the optimal individual. The interoperability method and apparatus provided by this invention construct the initial solution space of the differential adaptive evolutionary algorithm based on the value range of interoperability-related configuration parameters and determine the optimal solution for the interoperability-related configuration parameters using the differential adaptive evolutionary algorithm, thereby improving the success rate of interoperation.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and more specifically to an interoperability method and apparatus. Background Technology

[0002] Currently, Voice over NR (VoNR) is a fifth-generation (5G) voice solution based on the Internet Protocol Multimedia Subsystem (IMS) network. With full 5G network coverage, VoNR can achieve continuous handover within the 5G network. However, in situations where 5G and 4G networks provide supplementary coverage, VoNR will experience inter-system interoperability between the 5G and 4G networks, reverting to 4G voice. This interoperability includes handover and redirection; whether handover or redirection is used depends on radio guidelines and the availability of the N26 interface.

[0003] Existing VoNR inter-system handover or redirection mainly involves the A2 threshold, B1 threshold, B2 threshold, and redirection threshold. Under VoNR service, when the level value triggers the A2 threshold, the base station sends B1 or B2 event measurements to the terminal / user equipment (UE) or directly triggers voice redirection.

[0004] However, in existing VoNR inter-system handover methods, once the measurement and handover thresholds are configured, they are not real-time. Furthermore, the reconfiguration of thresholds often requires on-site testing, signaling tracing, and finally, manual setting of threshold values ​​based on optimization experience. This consumes a lot of resources and is highly dependent on the experience of the optimization personnel. The response to fluctuations in handover indicators is not real-time, which leads to a low success rate of VoNR inter-system handover. Summary of the Invention

[0005] This invention provides a switching method and apparatus to solve the technical problem of low success rate of VoNR inter-system switching.

[0006] In a first aspect, the present invention provides an interoperability method, comprising:

[0007] The initial solution space of the differential adaptive evolution algorithm is constructed based on the value range of interoperability-related configuration parameters.

[0008] Based on historical data related to interoperability, the solution vector under the fitness of the optimal individual is determined using the differential adaptive evolution algorithm.

[0009] Interoperation is performed based on the solution vectors under the fitness of the optimal individual.

[0010] In one embodiment, based on interoperability-related historical data, the differential adaptive evolutionary algorithm is used to determine the solution vector at the fitness of the optimal individual, including:

[0011] A fitness function is constructed based on the interoperability-related historical data.

[0012] Perform solution space mutation;

[0013] Perform solution space crossover;

[0014] The solution vector corresponding to the larger fitness function value is taken as the individual for the next iteration;

[0015] At the end of the iteration, the solution vector with the fitness of the optimal individual is output.

[0016] In one embodiment, the fitness function is expressed as follows:

[0017]

[0018] Among them, f i (g) Let be the fitness function value corresponding to the i-th solution vector in the g-th iteration. The preset adjustment coefficient, The switching success rate is calculated when using the i-th solution vector in the g-th iteration. The retargeting success rate is calculated when using the i-th solution vector in the g-th iteration. The access delay is when the i-th solution vector in the g-th iteration is used.

[0019] In one embodiment, the expression for the adaptive mutation operator in the solution space mutation process is as follows:

[0020]

[0021] Among them, F i (g) Let F be the adaptive mutation operator corresponding to the i-th solution vector in the g-th iteration. u F is the upper bound of the mutation operator. l This is the lower bound of the mutation operator. Let be the fitness function values ​​corresponding to the three solution vectors selected from the solution space.

[0022] In one embodiment, the initial solution space is expressed as follows:

[0023]

[0024] in, For the initial solution space, The value of the nth dimension parameter in the mth solution vector of the initial solution space is selected from the range of values ​​of the corresponding interoperability-related configuration parameters, where m is the population size and n is the dimension of the solution.

[0025] In one embodiment, the interoperability-related configuration parameters include at least one of the following:

[0026] A2 threshold;

[0027] B1 threshold;

[0028] B2 threshold;

[0029] Redirection threshold.

[0030] In one embodiment, the interoperability-related historical data includes at least one of the following:

[0031] Switching success rate;

[0032] Redirect ratio;

[0033] Access latency.

[0034] In a second aspect, the present invention provides an interoperable device, comprising:

[0035] The building module is used to construct the initial solution space of the differential adaptive evolution algorithm based on the range of values ​​of interoperability-related configuration parameters;

[0036] The determination module is used to determine the solution vector at the fitness of the optimal individual based on the interoperability-related historical data and using the differential adaptive evolution algorithm.

[0037] The processing module is used to perform interoperation based on the solution vectors under the fitness of the optimal individual.

[0038] Thirdly, the present invention provides an electronic device including a processor and a memory storing a computer program, wherein the processor executes the computer program to implement the steps of the interoperability method described in the first aspect.

[0039] Fourthly, the present invention provides a processor-readable storage medium storing a computer program for causing the processor to perform the steps of the interoperability method described in the first aspect.

[0040] The interoperability method and apparatus provided by this invention construct an initial solution space for a differential adaptive evolutionary algorithm based on the value range of interoperability-related configuration parameters, and use the differential adaptive evolutionary algorithm to determine the optimal solution of the interoperability-related configuration parameters, thereby improving the success rate of interoperability. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0042] Figure 1 This is a flowchart illustrating the interoperability method provided by the present invention;

[0043] Figure 2 This is a schematic diagram of the interoperability logic flow provided by the present invention;

[0044] Figure 3 This is a schematic diagram of the interoperability device provided by the present invention;

[0045] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0046] Existing VoNR inter-system handover or redirection mainly involves the A2 threshold, B1 threshold, B2 threshold, and redirection threshold. Under VoNR service, when the level value triggers the A2 threshold, the base station sends B1 and B2 event measurements to the UE or directly triggers voice redirection.

[0047] However, in existing VoNR inter-system handover methods, once the measurement and handover thresholds are configured, they are not real-time. Furthermore, the reconfiguration of thresholds often requires on-site testing, signaling tracing, and finally, manual setting of threshold values ​​based on optimization experience. This consumes a lot of resources and is highly dependent on the experience of the optimization personnel. The response to fluctuations in handover indicators is not real-time, which leads to a low success rate of VoNR inter-system handover.

[0048] Furthermore, existing VoNR inter-system handover methods trigger a handover decision as long as the voltage levels of the local (serving cell) and the peer (target neighbor cell) meet the thresholds set by A2, B1, or B2. This ignores the service continuity issue after the UE hands over to the target neighbor cell, only aiming to find an inter-system cell that meets the conditions, regardless of whether it is the optimal cell for the current handover.

[0049] Furthermore, the existing VoNR inter-system handover threshold configuration still does not make full use of historical data and cannot perform fine-grained configuration of NR-LTE neighbor cell handover based on the current network situation. The threshold setting is too strict for some cells and too lenient for others, which will cause the VoNR handover success rate to reach a certain bottleneck and make it difficult to improve further.

[0050] To address the aforementioned technical problems, this invention provides an interoperability method based on a differential adaptive evolutionary algorithm. An initial solution space for the differential adaptive evolutionary algorithm is constructed based on the value range of interoperability-related configuration parameters. The optimal solution for the interoperability-related configuration parameters is then determined using the differential adaptive evolutionary algorithm, thereby improving the success rate of interoperability.

[0051] For example, for VoNR inter-system handover, an evaluation function is constructed using historical VoNR handover data of NR-LTE (handover success rate, redirection ratio, access latency, etc.). The A1 threshold (test threshold), A2 threshold (decision threshold), B1 threshold, B2 threshold, and redirection threshold of NR-LTE inter-system handover are used as optimization parameters. An improved differential adaptive evolutionary algorithm is used to gradually obtain the optimal combination of handover thresholds, thereby achieving self-optimization of VoNR inter-system handover.

[0052] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0053] Figure 1 This is a flowchart illustrating the interoperability method provided by the present invention, as shown below. Figure 1 As shown, this invention provides an interoperability method, the executing entity of which can be a network-side device, such as a base station. The method includes:

[0054] Step 101: Construct the initial solution space of the differential adaptive evolution algorithm based on the value range of the interoperability-related configuration parameters.

[0055] Specifically, in the embodiments of this application, interoperability includes switching, reselection, redirection, etc.

[0056] Optionally, the interoperability-related configuration parameters include at least one of the following:

[0057] A2 threshold;

[0058] B1 threshold;

[0059] B2 threshold;

[0060] Redirection threshold.

[0061] For example, interoperability-related configuration parameters include the A2 threshold, B1 threshold, B2 threshold, and redirection threshold, which are used to randomly initialize the initial solution space of the differential adaptive evolutionary algorithm.

[0062] Initial solution space using a matrix express, The expression is as follows:

[0063]

[0064] in, For the initial solution space, The value of the nth dimension parameter in the mth solution vector of the initial solution space is selected from the range of values ​​of the corresponding interoperability-related configuration parameters, where m is the population size and n is the dimension of the solution.

[0065] For VoNR inter-system handover, four sets of parameters are usually required, so the value of n is 4, and m can be determined according to the specific situation. For example, the value of m can be set to 10 here.

[0066] Taking n=4 and m=10 as an example, the first column of the initial solution space matrix is: The first column of the initial solution space matrix corresponds to the A2 threshold for interoperability between NR systems, with a value range (upper and lower bounds) of [-141, -43] and a step size of 1.

[0067] The second column of the initial solution space matrix is The second column of the initial solution space matrix corresponds to the B1 threshold for interoperability between NR systems, with a value range of [-140, -43] and a step size of 1.

[0068] The third column of the initial solution space matrix is The third column of the initial solution space matrix corresponds to the B2 threshold for interoperability between NR systems, with a value range of [-156, -31] and a step size of 1.

[0069] The fourth column of the initial solution space matrix is The fourth column in the initial solution space matrix corresponds to the redirection threshold for interoperability between NR systems, with a value range of [-156, -31] and a step size of 1.

[0070] The initialization formula for the element values ​​in the initial solution space matrix is ​​as follows:

[0071]

[0072] Among them, [L jU j ]for The corresponding value range (upper and lower bounds), g is the number of iterations, and the initial value is 0.

[0073] Step 102: Based on the historical data related to interoperability, use the differential adaptive evolution algorithm to determine the solution vector under the fitness of the optimal individual.

[0074] Specifically, in the embodiments of this application, the interoperability-related historical data includes at least one of the following:

[0075] Switching success rate;

[0076] Redirect ratio;

[0077] Access latency.

[0078] The redirection ratio represents the success rate of redirection. The access latency represents the average access latency.

[0079] Figure 2 This is a schematic diagram of the interoperability logic flow provided by the present invention, such as... Figure 2 As shown, the specific steps for determining the solution vector under the fitness of the optimal individual include:

[0080] 1. Construct a fitness function based on historical data related to interoperability.

[0081] The fitness function is expressed as follows:

[0082]

[0083] Among them, f i (g) Let be the fitness function value corresponding to the i-th solution vector in the g-th iteration. The preset adjustment coefficient, The switching success rate is calculated when using the i-th solution vector in the g-th iteration. The retargeting success rate is calculated when using the i-th solution vector in the g-th iteration. The access delay is when the i-th solution vector in the g-th iteration is used.

[0084] Used to control different selections for VoNR inter-system handover and redirection. It can be set between 0.5 and 0.8.

[0085] 2. Perform solution space mutation.

[0086] For example, three solution vectors are randomly selected from a space of m solution vectors, denoted as follows: The fitness function values ​​corresponding to the three solution vectors are sorted from best to worst (from largest to smallest). The expression for the mutation vector is as follows:

[0087]

[0088] The principle for generating the solution is as follows: In the g-th iteration, three solution vectors are randomly selected from the m solution spaces and recombined according to the adaptive mutation operator.

[0089] The formula for calculating the adaptive mutation operator is as follows:

[0090]

[0091] Among them, F i (g) Let F be the adaptive mutation operator corresponding to the i-th solution vector in the g-th iteration. u F is the upper bound of the mutation operator. l This is the lower bound of the mutation operator. Three solution vectors selected from the solution space The corresponding fitness function values, F l and F u The value can be configured according to the actual situation, for example, F l =0.2, F u =0.8.

[0092] F i (g) The value of adapts to the two individuals of the generated difference vector, balancing the global search and the local search. This ensures that the optimal switching threshold is found quickly while avoiding getting trapped in local extrema.

[0093] 3. Perform solution space crossover.

[0094] For each solution vector elements According to probability CR i,j Perform cross-substitution to obtain a new solution vector. The formula is as follows:

[0095]

[0096] Among them, rand i,j (0,1) represents the probability of randomly generating a 0-1, and j = rand(j) indicates that the generated random index is j. Therefore, when the random function is less than the crossover probability cr i,j When the corresponding solution vector element is replaced with the corresponding element of the mutated vector, the other element remains unchanged.

[0097] Crossover probability cri,j The calculation formula is as follows:

[0098]

[0099] Among them, f i It is an individual (a solution vector for an individual). The fitness function value, f min and f max These are the fitness scores of the worst and best individuals in the current population, respectively. It is the average value of the threshold space fitness. l and cr u These represent the upper and lower bounds of the crossover probability cr, respectively. For example, cr l =0.1,cr u =0.6.

[0100] cr i,j Calculations show that for fitness f i For solutions with good fitness, a smaller cr is chosen to preserve the structure of the original solution as much as possible, increasing the chance of the threshold combination entering the next iteration. Conversely, for solutions with poor fitness, a larger cr is chosen to accelerate the change of the individual's structure, causing the threshold solution vector to be eliminated.

[0101] 4. Select the solution vector corresponding to the larger fitness function value as the individual for the next iteration.

[0102] Compare separately and Given the fitness function value, select the threshold solution vector with a better (larger) fitness function value as the individual for the next iteration.

[0103]

[0104] As can be seen from the above formula, for each individual, Better than or equal to And it will definitely converge to the optimal solution space. The new solution vectors obtained by mutation and cross-operation help to break through the local optimum and reach the global optimum switching threshold.

[0105] 5. At the end of the iteration, output the solution vector with the fitness of the optimal individual.

[0106] Repeat the above steps until the preset number of iterations is reached, or until the current optimal fitness function value has no substantial increase compared to the historical optimal fitness function value, then stop iterating.

[0107]

[0108] in, f is the fitness function value corresponding to the i-th solution vector in the g-th iteration. max The value of the fitness function is the historical best value, and Δ is the convergence threshold, which can generally be a very small number, such as 0.001.

[0109] Based on the above steps, the solution space vector under the fitness of the optimal individual is determined, which is the current VoNR inter-system handover optimal threshold to be found, and the expression is as follows:

[0110]

[0111] When the iteration stops, the output results correspond to the four parameter thresholds for VoNR inter-system handover.

[0112] Step 103: Perform interoperation based on the solution vectors under the fitness of the optimal individual.

[0113] Specifically, after determining the solution vector under the fitness of the optimal individual, interoperation is performed based on the solution vector under the fitness of the optimal individual.

[0114] For example, in the above example, the configuration parameters related to VoNR inter-system handover include the A2 threshold, B1 threshold, B2 threshold, and redirection threshold. The optimal solutions for these four parameters are determined using a differential adaptive evolutionary algorithm, and the corresponding parameters are configured according to these four optimal solutions to execute the VoNR inter-system handover.

[0115] The interoperability method provided by this invention constructs an initial solution space for a differential adaptive evolutionary algorithm based on the value range of interoperability-related configuration parameters, and uses the differential adaptive evolutionary algorithm to determine the optimal solution of the interoperability-related configuration parameters, thereby improving the success rate of interoperability.

[0116] Figure 3 This is a schematic diagram of the interoperability device provided by the present invention, as shown below. Figure 3 As shown, the present invention provides an interoperable device, comprising:

[0117] The construction module 301 is used to construct the initial solution space of the differential adaptive evolutionary algorithm based on the value range of the interoperability-related configuration parameters; the determination module 302 is used to determine the solution vector under the fitness of the optimal individual based on the interoperability-related historical data and the differential adaptive evolutionary algorithm; the processing module 303 is used to perform interoperation based on the solution vector under the fitness of the optimal individual.

[0118] It should be noted that the interoperability device provided in this embodiment of the invention can implement all the method steps implemented in the above method embodiments and achieve the same technical effect. Therefore, the parts and beneficial effects that are the same as those in the method embodiments will not be described in detail here.

[0119] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 4 As shown, the electronic device may include a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other via the communication bus 440. The processor 410 can call a computer program in the memory 430 to execute steps of an interoperability method, such as:

[0120] The initial solution space of the differential adaptive evolution algorithm is constructed based on the value range of interoperability-related configuration parameters.

[0121] Based on historical data related to interoperability, the solution vector under the fitness of the optimal individual is determined using the differential adaptive evolution algorithm.

[0122] Interoperation is performed based on the solution vectors under the fitness of the optimal individual.

[0123] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0124] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, which, when executed by a computer, enable the computer to perform the steps of the interoperability methods provided by the above methods, for example including:

[0125] The initial solution space of the differential adaptive evolution algorithm is constructed based on the value range of interoperability-related configuration parameters.

[0126] Based on historical data related to interoperability, the solution vector under the fitness of the optimal individual is determined using the differential adaptive evolution algorithm.

[0127] Interoperation is performed based on the solution vectors under the fitness of the optimal individual.

[0128] On the other hand, embodiments of this application also provide a processor-readable storage medium storing a computer program for causing the processor to perform the steps of the interoperability methods provided in the above embodiments, such as including:

[0129] The initial solution space of the differential adaptive evolution algorithm is constructed based on the value range of interoperability-related configuration parameters.

[0130] Based on historical data related to interoperability, the solution vector under the fitness of the optimal individual is determined using the differential adaptive evolution algorithm.

[0131] Interoperation is performed based on the solution vectors under the fitness of the optimal individual.

[0132] The processor-readable storage medium can be any available medium or data storage device that the processor can access, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO)), optical memory (e.g., CD, DVD, BD, HVD), and semiconductor memory (e.g., ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)).

[0133] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0134] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0135] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An interoperability method, characterized in that, include: The initial solution space of the differential adaptive evolution algorithm is constructed based on the value range of interoperability-related configuration parameters. Based on interoperability-related historical data, the differential adaptive evolution algorithm is used to determine the solution vector under the fitness of the optimal individual, including: constructing a fitness function based on the interoperability-related historical data; performing solution space mutation; performing solution space crossover; taking the solution vector corresponding to the larger fitness function value as the individual for the next iteration; and at the end of the iteration, outputting the solution vector under the fitness of the optimal individual. Interoperation is performed based on the solution vectors under the fitness of the optimal individual; The fitness function is expressed as follows: Among them, f i (g) Let be the fitness function value corresponding to the i-th solution vector in the g-th iteration. The preset adjustment coefficient, The switching success rate is calculated when using the i-th solution vector in the g-th iteration. The retargeting success rate is calculated when using the i-th solution vector in the g-th iteration. The access delay is when the i-th solution vector in the g-th iteration is used.

2. The interoperability method according to claim 1, characterized in that, The expression for the adaptive mutation operator in the solution space mutation process is as follows: Among them, F i (g) Let F be the adaptive mutation operator corresponding to the i-th solution vector in the g-th iteration. u F is the upper bound of the mutation operator. l This is the lower bound of the mutation operator. Let be the fitness function values ​​corresponding to the three solution vectors selected from the solution space.

3. The interoperability method according to claim 1, characterized in that, The expression for the initial solution space is as follows: in, For the initial solution space, The value of the nth dimension parameter in the mth solution vector of the initial solution space is selected from the range of values ​​of the corresponding interoperability-related configuration parameters, where m is the population size and n is the dimension of the solution.

4. The interoperability method according to claim 1, characterized in that, The interoperability-related configuration parameters include at least one of the following: A2 threshold; B1 threshold; B2 threshold; Redirection threshold.

5. The interoperability method according to claim 1, characterized in that, The interoperability-related historical data includes at least one of the following: Switching success rate; Redirect ratio; Access latency.

6. An interoperable device, characterized in that, include: The building module is used to construct the initial solution space of the differential adaptive evolution algorithm based on the range of values ​​of interoperability-related configuration parameters; The determination module is used to determine the solution vector with the fitness of the optimal individual based on the interoperability-related historical data and using the differential adaptive evolution algorithm. The determination module includes: constructing a fitness function based on the interoperability-related historical data; performing solution space mutation; performing solution space crossover; taking the solution vector with the larger fitness function value as the individual for the next iteration; and outputting the solution vector with the fitness of the optimal individual at the end of the iteration. The processing module is used to perform interoperation based on the solution vector under the fitness of the optimal individual; The fitness function is expressed as follows: Among them, f i (g) Let be the fitness function value corresponding to the i-th solution vector in the g-th iteration. The preset adjustment coefficient, The switching success rate is calculated when using the i-th solution vector in the g-th iteration. The retargeting success rate is calculated when using the i-th solution vector in the g-th iteration. The access delay is when the i-th solution vector in the g-th iteration is used.

7. An electronic device comprising a processor and a memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the interoperability method according to any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the interoperability method as described in any one of claims 1 to 5.

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