CN113709754A - Clustering algorithm based wireless broadband communication system station arrangement networking method and system - Google Patents
Clustering algorithm based wireless broadband communication system station arrangement networking method and system Download PDFInfo
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Abstract
The invention discloses a method and a system for arranging stations and networking a wireless broadband communication system based on a clustering algorithm. Multiple iteration simulation calculations show that the aim of improving the coverage rate can be achieved by each iteration step, and the final algorithm converges to a better result. The method can closely combine the physical significance of the scene to finally obtain a result which is not inferior to that of the traditional site optimization method, but the operation speed is superior to that of the traditional optimization method.
Description
Technical Field
The invention belongs to the technical field of communication, and particularly relates to a clustering algorithm-based station arrangement and networking method and system for a wireless broadband communication system.
Background
In conventional mobile communication networks, a conventional cellular network structure is mostly used, and the cellular structure is considered as an optimal topology covering a two-dimensional plane. However, in special situations such as disaster relief, military operations, etc., the base station deployment at this time is required to reach mobility, real-time performance, high efficiency, and the limitation of topographic factors in station deployment, so that the conventional cellular network structure cannot be used for station deployment. Based on the above problems, it is very important to provide an efficient base station deployment method under these special situations.
In fact, site planning of a wireless broadband communication system is an optimization problem, and an optimized index is maximized to meet communication requirements of a scene, wherein signal coverage is often used as an optimized index. In consideration of the fact that in the actual station arrangement process, a single base station but a plurality of base stations are deployed simultaneously, the optimization problem is a non-convex optimization problem. The academic world of the non-convex optimization problem does not have a general theory for solving the optimal solution, and the methods such as carrying out convex processing on the non-convex problem and using optimization algorithms such as genetic algorithms are used for solving the optimal solution in much more engineering, but the solving process can only obtain one optimal solution and cannot ensure that the global optimal solution can be obtained.
Scholars at home and abroad carry out a lot of work on the problem of site planning, and the most representative scheme based on the genetic algorithm has the greatest defect that the optimization direction needs to be continuously searched in iteration, so that a great amount of time and computing resources are consumed. In the actual physical context of site planning, this optimized direction is the moving direction of the base station that can improve the coverage of map signals. The base station can obviously improve the signal coverage rate of the map when moving from a place with stronger signal coverage to a place with weaker signal coverage, so that the movement of the base station to the area with weaker signal coverage in the map is the direction of optimizing the position of the base station. Based on the map signal coverage condition, a clustering algorithm can be used for calculating a clustering center with weak signal coverage, and the calculated clustering centers of a plurality of weak signal coverage points indicate the position optimization direction of the base station. Because the clustering algorithm with lower computational complexity can directly indicate the direction of the base station position optimization, the method is more efficient than the genetic algorithm. In addition, most studies are too ideal for the actual physical environment assumption and cannot reflect the influence of the surrounding terrain on the communication quality exactly. Based on the above consideration, a networking scheme for site layout of the wireless broadband communication system based on the clustering algorithm, which has strong real-time performance and can well reflect terrain influence, can be developed.
Further analysis of the application of clustering algorithms to the present problem has shown that base stations tend to spread out and move towards areas of poor coverage during the optimization process. Based on this finding, it is considered that the clustering algorithm directly indicates the optimization direction in the iterative process, so that a lot of time and waste of computing resources caused by trial and error can be saved.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a method and a system for arranging stations and networking of a wireless broadband communication system based on a clustering algorithm, so as to achieve the purpose of improving the signal coverage rate when a base station site is deployed.
The invention adopts the following technical scheme:
a wireless broadband communication system station arrangement networking method based on a clustering algorithm comprises the following steps:
s1, randomly initializing to generate a base station layout meeting the requirements, and calculating the coverage condition of a map in the initial base station layout through channel modeling;
s2, calculating the cluster centers of a plurality of uncovered areas by using a k-means clustering algorithm according to the coverage condition of the map obtained in the step S1, and determining the cluster center priority of the uncovered areas according to the descending order of the points classified into the uncovered points of the cluster centers;
s3, traversing each cluster center in sequence according to the priority determined in the step S2, calculating the distances from all base stations to the corresponding cluster center in sequence to determine the moving priority for traversing to a certain cluster center, and traversing all the base stations in sequence according to the priorities;
s4, for traversing a certain base station, the base station moves to the cluster center traversed in the step S3, and under the condition that the layout condition of the base station is met, the maximum new coverage rate obtained in the process of moving the base station is calculated;
s5, judging the maximum new coverage rate obtained in the step S4, if the maximum new coverage rate is larger than the current coverage rate, updating the position of the base station, ending traversal, and ending one iteration;
s6, after the step S5 is finished, calculating new cluster centers of a plurality of uncovered areas, starting next iteration until the coverage rate is not improved any more, and when the expected coverage rate is reached or the maximum iteration times are reached, outputting the position of the base station as the final position of the base station;
and S7, calculating the received power of each space point of the map according to the final base station position output in the step S6, calculating the final signal coverage rate, and outputting the position of the deployed base station.
Specifically, step S2 specifically includes:
s201, randomly selecting k coordinates from the input coordinates of the uncovered area as initial values of cluster centers;
s202, calculating Euclidean distances between each point in the uncovered area and k cluster centers, and selecting the closest cluster center as a mark type for each point;
s203, after the clustering centers of all points are marked, calculating new center points of all clusters again;
and S204, stopping iteration and outputting the clustering result if the sum of the absolute value differences of the newly calculated cluster center position and the old cluster center position reaches a threshold value or the iteration frequency reaches an expected value.
Further, in step S201, the number k of cluster centers of the k-means clusters is the same as the number of base stations.
Further, in step S202, the distance D between the ith uncovered point coordinate and the current jth cluster centerijComprises the following steps:
wherein x isiAnd yiIs the abscissa and ordinate, X, of the i uncovered pointsjAnd YjIs the abscissa and ordinate of the current jth cluster center.
Further, in step S203, the abscissa X 'of the jth cluster center of the new center point of each cluster is recalculated'jAnd Y'jComprises the following steps:
wherein x isiAnd yiIs the abscissa and ordinate of the i-th signal uncovered point classified into the j-th cluster center, njThe number of signal uncovered points classified into the jth cluster center.
Further, in step S204, if the sum of the absolute differences between the newly calculated cluster center position and the old cluster center position does not reach the threshold value, or the number of iterations does not reach the expected value, the process continues to step S202.
Specifically, in step S4, the base station moves to the traversed cluster center with 1/6 of the distance from the base station to the cluster center as a step length, and when the base station layout condition is satisfied, the coverage of the base station after each movement is calculated, and the maximum coverage is regarded as the maximum new coverage.
Specifically, in step S6, the condition for terminating the iteration is that the coverage of all the cluster cores is not increased after traversing in a certain iteration, or the specified number of iterations is reached.
Specifically, in step S7, the signal coverage obtained from the final position of the base station obtained in step S6 is used as the final signal coverage.
Another technical solution of the present invention is a wireless broadband communication system site deployment networking system based on a clustering algorithm, comprising:
the calculation module randomly initializes and generates a base station layout meeting the requirements, and calculates the coverage condition of a map in the initial base station layout through channel modeling;
the sorting module is used for calculating the cluster centers of a plurality of uncovered areas by using a k-means clustering algorithm according to the coverage condition of the map obtained by the calculating module, and determining the cluster center priority of the uncovered areas according to the descending sorting of the points classified into the uncovered points of the cluster centers;
the traversing module sequentially traverses each cluster center according to the priority determined by the sequencing module, sequentially calculates the distances from all the base stations to the corresponding cluster centers to determine the moving priority for traversing to a certain cluster center, and then sequentially traverses all the base stations according to the priority;
the moving module is used for moving the base station to the cluster center traversed by the traversing module for traversing to a certain base station, and calculating the maximum new coverage rate obtained in the process of moving the base station under the condition of meeting the layout condition of the base station;
the judging module is used for judging the maximum new coverage rate obtained by the mobile module, updating the position of the base station and ending traversal if the maximum new coverage rate is greater than the current coverage rate, and ending one-time iteration;
the iteration module is used for calculating new cluster centers of a plurality of uncovered areas after the module is judged to be ended, starting next iteration until the coverage rate is not improved any more, and outputting the base station position as the final base station position when the expected coverage rate is reached or the maximum iteration times are reached;
and the deployment module is used for calculating the receiving power of each space point of the map according to the final base station position output by the iteration module, calculating the final signal coverage rate and outputting the position of the deployment base station.
Compared with the prior art, the invention has at least the following beneficial effects:
the invention discloses a wireless broadband communication system station arrangement networking method based on a clustering algorithm, and application of the clustering algorithm in the problem can be found out that base stations tend to disperse gradually and move towards a weak coverage area in the optimization process. Based on this finding, it is considered that the clustering algorithm directly indicates the optimization direction in the iterative process, so that a lot of time and waste of computing resources caused by trial and error can be saved.
Further, based on a common k-means clustering algorithm, the cluster center of a signal uncovered area in the map in each iterative calculation is calculated through the k-means clustering algorithm, and based on the fact that the signal coverage of the uncovered area can be enhanced by moving a base station to the cluster center of the uncovered area, the position of only one base station is moved in each iterative calculation by an agreed moving rule so as to achieve the purpose of improving the signal coverage rate. Multiple iteration simulation calculations show that the aim of improving the coverage rate can be achieved by each iteration step, and the final algorithm converges to a better result. The algorithm can be closely combined with the physical significance of a scene, and can finally obtain a result which is not inferior to that of the traditional station address optimization algorithm, but the operation speed is superior to that of the traditional optimization algorithm, which is the greatest innovation point of the invention.
Further, the number of cluster cores of the k-means clustering algorithm in step S201 cannot be generated by the algorithm itself and needs to be given in advance. Because the base station determines the moving priority according to the cluster centers, the number of the cluster centers should be positively correlated with the number of the base stations, so that the requirement of the algorithm is met by selecting the cluster center number k of the k-means cluster to be the same as the number of the base stations.
Further, in step S202, the clustering algorithm needs to measure a clustering distance criterion, and in this scenario, the physical distance D between the i-th uncovered point coordinate and the current j-th cluster center is setijThe criterion set as the clustering distance is optimal.
Further, in step S203, the abscissa and the ordinate of the jth cluster center of the new center point of each cluster are recalculated, and the calculated new cluster center coordinates can be subjected to the next iteration.
Further, in step S204, if the sum of the absolute differences between the newly calculated cluster center position and the old cluster center position does not reach the threshold value, or the number of iterations does not reach the expected value, the iteration is stopped to output the result. The purpose of the setting is to avoid invalid or not greatly improving the result of the iterative computation, and improve the efficiency of the computation.
Further, in step S4, the traversed current base station is moved to the corresponding cluster center according to the step length, a new signal coverage rate after each movement is calculated, and finally, the largest signal coverage rate is selected as the result of the current iteration.
Further, in step S6, until the coverage is not further improved, the expected coverage is reached, or the number of iterations is reached, the base station position is output as the final base station position. The purpose of this is that these conditions are termination conditions for terminating the iteration.
Further, the setting of step S7 is to output the result after the iteration is completed, and output the stationing position of the base station and the current signal coverage.
In conclusion, the invention fully considers the actual physical meaning of the problem, rather than blindly using an algorithm with higher design requirements, and can keep a better result while greatly saving the calculation time. .
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
FIG. 1 is a schematic view of a scene;
FIG. 2 is a schematic diagram of the algorithm proposed by the method of the present invention at an initial time;
FIG. 3 is a diagram of a base station after one iteration of its location;
FIG. 4 is a schematic diagram of a secondary base station after position iteration;
FIG. 5 is a block flow diagram of the present invention;
fig. 6 is a simulation result diagram of the algorithm of the present invention under different signal receiving sensitivities.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be understood that the terms "comprises" and/or "comprising" indicate the presence of the stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that 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. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
Various structural schematics according to the disclosed embodiments of the invention are shown in the drawings. The figures are not drawn to scale, wherein certain details are exaggerated and possibly omitted for clarity of presentation. The shapes of various regions, layers and their relative sizes and positional relationships shown in the drawings are merely exemplary, and deviations may occur in practice due to manufacturing tolerances or technical limitations, and a person skilled in the art may additionally design regions/layers having different shapes, sizes, relative positions, according to actual needs.
The invention provides a clustering algorithm-based wireless broadband communication system station arrangement networking method, which comprises the steps of initializing the positions of a plurality of base stations needing station arrangement, modeling and simulating the signal coverage condition of each point in a map through signals, clustering the centers of a plurality of uncovered areas by using a clustering algorithm on the simulated signal coverage areas, moving the base stations according to a certain priority, continuously iterating the algorithm until the coverage rate cannot be improved, and finishing iteration.
Referring to fig. 1, the present invention is applied in a scenario that a plurality of base stations are arranged in a known map information area, each base station works in different frequency bands to provide telecommunication services for users, and an optimal base station layout is obtained through an algorithm, so that the signal coverage rate in the area can be optimal.
Selecting a proper channel model in site planning is extremely important, firstly, a used channel model needs to be determined, link loss of a channel is divided into large-scale fading and small-scale fading, large-scale average path loss is used for measuring average fading of signals between a transmitter and a receiver and is defined as a difference value between effective transmitting power and average receiving power, and small-scale fading refers to fading in a short term, particularly to rapid fluctuation of received signals in the short term when a mobile station moves a small distance.
The method selects a more common Okumura-Hata model; the empirical formula is shown as (1):
Lm＝69.55+26.16lg(f)-13.82lg(hte)-a(hre)+[44.9-6.55lg(hte)lg(d)] (1)
where f is the carrier frequency (unit: MHZ), hteIs the finite height (unit: m), h, of the transmitting antennareIs the finite height of the receiving antenna (unit: m), d is the distance between the transmitter and the receiver (unit: km), a (h)re) Is a mobile antenna correction factor whose value depends on the environment.
If the threshold value of the known signal coverage is gamma, n base stations need to be deployed at the same time, and the base stations work in different frequency bands without co-channel interference. The signal coverage condition of the mth signal receiving point on the map is judged by the formula (2):
aiming at the problem to be solved, the positions of a plurality of base stations are optimized through the iterative algorithm based on the clustering algorithm, so that the signal coverage rate of the coverage area of the base stations under the layout is optimal.
The invention selects an Okumura-Hata model which is commonly used in the industry as a channel model to calculate the received signal strength of each point in the map, and the same frequency interference among all base stations does not need to be considered because the invention mainly aims at the base stations working at different frequency bands. And selecting the base station with the highest received signal strength to access each point on the map, and if the received signal strength is higher than a threshold value, considering that the signal of the point is covered.
The method provided by the invention is based on a common k-means clustering algorithm, calculates the cluster center of the area where the signal is not covered in the map in each iterative calculation through the k-means clustering algorithm, and moves the position of only one base station in each iterative calculation by an agreed moving rule based on the fact that the signal coverage of the uncovered area can be enhanced by moving the base station to the cluster center of the uncovered area so as to achieve the purpose of improving the signal coverage rate. Multiple iteration simulation calculations show that the aim of improving the coverage rate can be achieved by each iteration step, and the final algorithm converges to a better result. The method can closely combine the physical significance of the scene, and can finally obtain the result which is not inferior to that of the traditional station address optimization algorithm, but the operation speed is superior to that of the traditional optimization algorithm, which is the greatest innovation point of the method.
Referring to fig. 5, the method for networking a wireless broadband communication system based on a clustering algorithm in the invention obtains the position coordinates of all uncovered areas after obtaining the signal coverage of each point of a map, and obtains the cluster center of the uncovered area as the optimization direction of an iterative algorithm by using a k-means clustering algorithm. The method comprises the following specific steps:
s1, randomly initializing to generate a base station layout meeting the requirements, and calculating the coverage condition of the map in the process of channel modeling according to the initial base station layout;
s2, clustering according to the coverage condition of the map by using k-means to calculate cluster centers of a plurality of uncovered areas, and determining the priorities of the cluster centers according to the descending order of the points of the uncovered points classified into the cluster centers (the more the classified points are, the higher the priority is);
s201, randomly selecting k coordinates from input coordinates of an uncovered area as initial values of cluster centers, wherein the number k of the cluster centers of k-means clusters is the same as the number of base stations;
s202, calculating Euclidean distances between each point in the uncovered area and k cluster centers according to a formula (3), and selecting the closest cluster center as a mark category for each point;
wherein D isijDenotes the distance, x, of the ith uncovered point coordinate with respect to the current jth cluster centeriAnd yiIs the abscissa and ordinate, X, of the i uncovered pointsjAnd YjIs the abscissa and ordinate of the current jth cluster center.
S203, after the clustering centers of all points are marked, calculating new center points of all clusters again through a formula (4);
wherein, X'jAnd Y'jIs the updated abscissa, x, of the jth cluster centeriAnd yiIs the abscissa and ordinate of the i-th signal uncovered point classified into the j-th cluster center, njThe number of signal uncovered points classified into the jth cluster center.
And S204, if the sum of the absolute value differences of the newly calculated cluster center position and the old cluster center position reaches a threshold value or the iteration frequency reaches an expected value, stopping iteration and outputting a clustering result, otherwise, continuing to the step S202.
S3, traversing each cluster center in sequence according to the priority, calculating the distances from all base stations to the cluster center in sequence to determine the moving priority (the closer the distance is, the higher the priority is), and traversing all the base stations in sequence according to the priority;
s4, for traversing to a certain base station, the base station is moved to the traversed cluster center by using 1/6 of the distance between the base station and the cluster center as a step length, under the condition of meeting the layout condition of the base stations which can communicate with each other, the coverage rate of the base station after each movement is calculated, and the maximum coverage rate is the maximum new coverage rate;
s5, judging the maximum new coverage rate of the step S4, if the maximum new coverage rate is larger than the current coverage rate, updating the position of the base station and ending the traversal till the end of the iteration;
s6, calculating new cluster centers of a plurality of uncovered areas to start next iteration, wherein the condition of iteration termination is that the coverage rate of all the cluster centers is not improved after traversing in a certain iteration, or the specified iteration times are reached;
and S7, finally, calculating the receiving power of each space point of the map according to the final base station position through a channel modeling formula and the engineering parameter of the base station, judging whether the space point is covered by the signal according to whether the receiving power of each space point on the map reaches the receiving sensitivity, thereby calculating the final signal coverage rate of the map and outputting the position of the deployed base station.
In another embodiment of the present invention, a clustering algorithm based wireless broadband communication system site deployment networking system is provided, which can be used for implementing the above clustering algorithm based wireless broadband communication system site deployment networking method, and specifically, the clustering algorithm based wireless broadband communication system site deployment networking system includes a computing module, a sorting module, a traversing module, a moving module, a judging module, an iteration module, and a deployment module.
The calculation module randomly initializes and generates a base station layout meeting the requirements, and calculates the coverage condition of a map in the initial base station layout through channel modeling;
the sorting module is used for calculating the cluster centers of a plurality of uncovered areas by using a k-means clustering algorithm according to the coverage condition of the map obtained by the calculating module, and determining the cluster center priority of the uncovered areas according to the descending sorting of the points classified into the uncovered points of the cluster centers;
the traversing module sequentially traverses each cluster center according to the priority determined by the sequencing module, sequentially calculates the distances from all the base stations to the corresponding cluster centers to determine the moving priority for traversing to a certain cluster center, and then sequentially traverses all the base stations according to the priority;
the moving module is used for moving the base station to the cluster center traversed by the traversing module for traversing to a certain base station, and calculating the maximum new coverage rate obtained in the process of moving the base station under the condition of meeting the layout condition of the base station;
the judging module is used for judging the maximum new coverage rate obtained by the mobile module, updating the position of the base station and ending traversal if the maximum new coverage rate is greater than the current coverage rate, and ending one-time iteration;
the iteration module is used for calculating new cluster centers of a plurality of uncovered areas after the module is judged to be ended, starting next iteration until the coverage rate is not improved any more, and outputting the base station position as the final base station position when the expected coverage rate is reached or the maximum iteration times are reached;
and the deployment module is used for calculating the receiving power of each space point of the map according to the final base station position output by the iteration module, calculating the final signal coverage rate and outputting the position of the deployment base station.
In yet another embodiment of the present invention, a terminal device is provided that includes a processor and a memory for storing a computer program comprising program instructions, the processor being configured to execute the program instructions stored by the computer storage medium. The Processor may be a Central Processing Unit (CPU), or may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable gate array (FPGA) or other Programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc., which is a computing core and a control core of the terminal, and is adapted to implement one or more instructions, and is specifically adapted to load and execute one or more instructions to implement a corresponding method flow or a corresponding function; the processor of the embodiment of the invention can be used for the operation of a station arrangement networking method of a wireless broadband communication system based on a clustering algorithm, and comprises the following steps:
randomly initializing to generate a base station layout meeting the requirements, and calculating the coverage condition of a map in the initial base station layout through channel modeling; calculating the cluster centers of a plurality of uncovered areas by using a k-means clustering algorithm according to the coverage condition of the obtained map, and determining the cluster center priority of the uncovered areas according to the descending order of the points classified into the uncovered points of the cluster centers; sequentially traversing each cluster center according to the determined priority, sequentially calculating the distances from all base stations to the corresponding cluster center for traversing to a certain cluster center to determine the moving priority, and then sequentially traversing all the base stations according to the priority; for traversing a certain base station, the base station is moved to the traversed cluster center, and under the condition of meeting the layout condition of the base station, the maximum new coverage rate obtained in the process of moving the base station is calculated; judging the obtained maximum new coverage rate, if the maximum new coverage rate is larger than the current coverage rate, updating the position of the base station and ending traversal, and ending one-time iteration; calculating new cluster centers of a plurality of uncovered areas, starting the next iteration until the coverage rate is not improved any more, and outputting the base station position as the final base station position when the expected coverage rate is reached or the maximum iteration times are reached; and calculating the receiving power of each space point of the map according to the output final base station position, calculating the final signal coverage rate, and outputting the position of the deployed base station.
In still another embodiment of the present invention, the present invention further provides a storage medium, specifically a computer-readable storage medium (Memory), which is a Memory device in a terminal device and is used for storing programs and data. It is understood that the computer readable storage medium herein may include a built-in storage medium in the terminal device, and may also include an extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space storing an operating system of the terminal. Also, one or more instructions, which may be one or more computer programs (including program code), are stored in the memory space and are adapted to be loaded and executed by the processor. It should be noted that the computer-readable storage medium may be a high-speed RAM memory, or may be a non-volatile memory (non-volatile memory), such as at least one disk memory.
The processor can load and execute one or more instructions stored in the computer readable storage medium to implement the corresponding steps of the method for setting up a station and networking of the wireless broadband communication system based on the clustering algorithm in the above embodiments; one or more instructions in the computer-readable storage medium are loaded by the processor and perform the steps of:
randomly initializing to generate a base station layout meeting the requirements, and calculating the coverage condition of a map in the initial base station layout through channel modeling; calculating the cluster centers of a plurality of uncovered areas by using a k-means clustering algorithm according to the coverage condition of the obtained map, and determining the cluster center priority of the uncovered areas according to the descending order of the points classified into the uncovered points of the cluster centers; sequentially traversing each cluster center according to the determined priority, sequentially calculating the distances from all base stations to the corresponding cluster center for traversing to a certain cluster center to determine the moving priority, and then sequentially traversing all the base stations according to the priority; for traversing a certain base station, the base station is moved to the traversed cluster center, and under the condition of meeting the layout condition of the base station, the maximum new coverage rate obtained in the process of moving the base station is calculated; judging the obtained maximum new coverage rate, if the maximum new coverage rate is larger than the current coverage rate, updating the position of the base station and ending traversal, and ending one-time iteration; calculating new cluster centers of a plurality of uncovered areas, starting the next iteration until the coverage rate is not improved any more, and outputting the base station position as the final base station position when the expected coverage rate is reached or the maximum iteration times are reached; and calculating the receiving power of each space point of the map according to the output final base station position, calculating the final signal coverage rate, and outputting the position of the deployed base station.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 2, a plurality of base station layouts are generated by random initialization, a k-means clustering algorithm is used to cluster signal uncovered areas to obtain cluster center points, and the priority of the cluster centers is determined in a descending order according to the number of various types in a clustering result (i.e., the higher the number of clusters is, the higher the priority is). For each cluster center, the priority of moving the base station for the cluster center is determined according to the ascending order of the distance from each base station to the cluster center, and the base station is moved in a certain step length according to the priority (namely, the closer the distance is, the higher the priority is). The cluster centers of the clusters and the moving priorities of the base stations are determined in the initial layout. Firstly, determining the moving direction with the highest priority as cluster center 1, determining the base station with the highest moving priority as BS4, wherein the arrow direction is the moving direction of BS4, and the BS4 moves to the position of the cluster center 1 in a certain step length according to the moving direction and calculates the new coverage rate of each movement in sequence. The calculation finds that the maximum new coverage during the move is higher than the original coverage, at which point the location of BS4 is updated.
Referring to fig. 3, the location and priority of each cluster center and the priority of the corresponding base station are updated according to the updated new location. The cluster center point with the highest priority changes the position, but the base station BS4 with the highest priority is moved without help to improve the coverage, so the position of the base station BS4 is not changed to select the base station BS3 with the second priority. Moving the base station BS3 in the direction of the arrow according to the rules, it can be found that the coverage can be improved while recording the base station BS3 location of the maximum coverage and updating the location of the base station BS 3.
Referring to fig. 4, the above algorithm is repeated according to the updated positions of the base stations. The coverage rate cannot be improved until all base stations are traversed, and the convergence condition of the algorithm is achieved. The flow chart of the algorithm is shown in the schematic diagram 5.
Computer simulation simulations were performed using MATLAB R2020a according to the clustering algorithm mentioned above, the computer being configured to: processors Intel i5-8250U 1.60GHz and memory 8 GB. The simulated environment is as follows:
table 1 simulation parameter description
Referring to fig. 6, a graph of simulation results at different signal reception sensitivities is shown. From the results, it can be seen that the map signal coverage rate is gradually reduced with the increase of the receiving sensitivity, because the increase of the receiving sensitivity reduces the coverage of the base station, and the map signal coverage rate is reduced under the condition that other conditions are not changed. It is further found that the algorithm running time has a certain volatility, since the convergence result of the algorithm depends on the initial random state and thus has a certain randomness.
In summary, the station arrangement and networking method and system for the wireless broadband communication system based on the clustering algorithm fully consider the actual physical significance of the problem, but not blindly use the algorithm with higher design requirements, thereby greatly saving the calculation time and simultaneously maintaining a better result.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned contents are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical idea of the present invention falls within the protection scope of the claims of the present invention.
Claims (10)
1. A wireless broadband communication system station arrangement networking method based on a clustering algorithm is characterized by comprising the following steps:
s1, randomly initializing to generate a base station layout meeting the requirements, and calculating the coverage condition of a map in the initial base station layout through channel modeling;
s2, calculating the cluster centers of a plurality of uncovered areas by using a k-means clustering algorithm according to the coverage condition of the map obtained in the step S1, and determining the cluster center priority of the uncovered areas according to the descending order of the points classified into the uncovered points of the cluster centers;
s3, traversing each cluster center in sequence according to the priority determined in the step S2, calculating the distances from all base stations to the corresponding cluster center in sequence to determine the moving priority for traversing to a certain cluster center, and traversing all the base stations in sequence according to the priorities;
s4, for traversing a certain base station, the base station moves to the cluster center traversed in the step S3, and under the condition that the layout condition of the base station is met, the maximum new coverage rate obtained in the process of moving the base station is calculated;
s5, judging the maximum new coverage rate obtained in the step S4, if the maximum new coverage rate is larger than the current coverage rate, updating the position of the base station, ending traversal, and ending one iteration;
s6, after the step S5 is finished, calculating new cluster centers of a plurality of uncovered areas, starting next iteration until the coverage rate is not improved any more, and when the expected coverage rate is reached or the maximum iteration times are reached, outputting the position of the base station as the final position of the base station;
and S7, calculating the received power of each space point of the map according to the final base station position output in the step S6, calculating the final signal coverage rate, and outputting the position of the deployed base station.
2. The method according to claim 1, wherein step S2 is specifically:
s201, randomly selecting k coordinates from the input coordinates of the uncovered area as initial values of cluster centers;
s202, calculating Euclidean distances between each point in the uncovered area and k cluster centers, and selecting the closest cluster center as a mark type for each point;
s203, after the clustering centers of all points are marked, calculating new center points of all clusters again;
and S204, stopping iteration and outputting the clustering result if the sum of the absolute value differences of the newly calculated cluster center position and the old cluster center position reaches a threshold value or the iteration frequency reaches an expected value.
3. The method of claim 2, wherein in step S201, the number k of cluster centers of k-means clusters is the same as the number of base stations.
4. The method according to claim 2, wherein in step S202, the distance D between the ith uncovered point coordinate and the current jth cluster centerijComprises the following steps:
wherein x isiAnd yiIs the abscissa and ordinate, X, of the i uncovered pointsjAnd YjIs the abscissa and ordinate of the current jth cluster center.
5. The method according to claim 2, wherein in step S203, the abscissa X 'of the jth cluster center of the new center point of each cluster is recalculated'jAnd Yj' is:
wherein x isiAnd yiIs the abscissa and ordinate of the i-th signal uncovered point classified into the j-th cluster center, njThe number of signal uncovered points classified into the jth cluster center.
6. The method of claim 2, wherein in step S204, if the sum of the absolute differences between the new calculated cluster center position and the old cluster center position does not reach a threshold value or the number of iterations does not reach an expected value, step S202 is continued.
7. The method of claim 1, wherein in step S4, the base station moves to the traversed cluster center with 1/6 steps of distance from the cluster center to the base station, and if the base station layout condition is satisfied, the coverage of the base station after each movement is calculated, and the maximum new coverage is determined as the maximum new coverage.
8. The method of claim 1, wherein in step S6, the condition for the end of the iteration is that the coverage of all the cluster cores is not increased after the traversal of a certain iteration or a specified number of iterations is reached.
9. The method of claim 1, wherein in step S7, the signal coverage obtained from the final position of the base station obtained in step S6 is used as the final signal coverage.
10. A wireless broadband communication system site layout networking system based on a clustering algorithm is characterized by comprising:
the calculation module randomly initializes and generates a base station layout meeting the requirements, and calculates the coverage condition of a map in the initial base station layout through channel modeling;
the sorting module is used for calculating the cluster centers of a plurality of uncovered areas by using a k-means clustering algorithm according to the coverage condition of the map obtained by the calculating module, and determining the cluster center priority of the uncovered areas according to the descending sorting of the points classified into the uncovered points of the cluster centers;
the traversing module sequentially traverses each cluster center according to the priority determined by the sequencing module, sequentially calculates the distances from all the base stations to the corresponding cluster centers to determine the moving priority for traversing to a certain cluster center, and then sequentially traverses all the base stations according to the priority;
the moving module is used for moving the base station to the cluster center traversed by the traversing module for traversing to a certain base station, and calculating the maximum new coverage rate obtained in the process of moving the base station under the condition of meeting the layout condition of the base station;
the judging module is used for judging the maximum new coverage rate obtained by the mobile module, updating the position of the base station and ending traversal if the maximum new coverage rate is greater than the current coverage rate, and ending one-time iteration;
the iteration module is used for calculating new cluster centers of a plurality of uncovered areas after the module is judged to be ended, starting next iteration until the coverage rate is not improved any more, and outputting the base station position as the final base station position when the expected coverage rate is reached or the maximum iteration times are reached;
and the deployment module is used for calculating the receiving power of each space point of the map according to the final base station position output by the iteration module, calculating the final signal coverage rate and outputting the position of the deployment base station.
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