WO2022052489A1 - 无线访问接入点部署方法和装置、存储介质 - Google Patents

无线访问接入点部署方法和装置、存储介质 Download PDF

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Publication number
WO2022052489A1
WO2022052489A1 PCT/CN2021/091758 CN2021091758W WO2022052489A1 WO 2022052489 A1 WO2022052489 A1 WO 2022052489A1 CN 2021091758 W CN2021091758 W CN 2021091758W WO 2022052489 A1 WO2022052489 A1 WO 2022052489A1
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wireless access
access point
access points
target area
deployment
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PCT/CN2021/091758
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English (en)
French (fr)
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吴端坡
严军荣
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三维通信股份有限公司
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/22—Traffic simulation tools or models
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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  • the present invention relates to the field of communications, and in particular, to a wireless access point deployment method and device, and a storage medium.
  • the embodiments of the present invention provide a wireless access point deployment method and device, and a storage medium, so as to meet more user needs, improve service quality, and reduce operating costs while ensuring lower energy consumption and operating costs .
  • a method for deploying wireless access points including: estimating a first number of wireless access points to be deployed in a target area; deploying the first number of wireless access points to maximize the average energy efficiency and/or total transmit power of the first number of wireless access points within the target area when a preset deployment policy is met minimum.
  • a wireless access point deployment device including: an estimation unit, configured to estimate a first number of wireless access points to be deployed in a target area; a deployment unit, It is set to deploy the first number of wireless access points in the target area based on the multi-target particle swarm algorithm, so that when the preset deployment strategy is satisfied, the first number of wireless access points in the target area are The point of entry has the highest average energy efficiency and/or the lowest total transmit power.
  • a computer-readable storage medium is also provided, where a computer program is stored in the computer-readable storage medium, wherein the computer program is configured to execute the above-mentioned wireless access when running. Access point deployment method.
  • an electronic device including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the above-mentioned computer program through the computer program Wireless access point deployment method.
  • the first number of wireless access points to be deployed in the target area is estimated; based on the multi-target particle swarm algorithm, the first number of wireless access points are deployed in the target area, so that the The first number of wireless access points in the target area have a maximum average energy efficiency and/or a minimum total transmit power when a preset deployment policy is satisfied.
  • a preset deployment strategy can be satisfied during deployment, so as to maximize the average energy efficiency and/or minimize the total transmit power of multiple wireless access points, thereby ensuring lower energy consumption and lower operating costs. meet more user needs, improve service quality, and reduce operating costs.
  • the wireless access point capacity limit should be designed based on the number of people distributed in the current area during deployment, and it is required that the total number of users served by all wireless access points should be greater than or equal to the total number of people in the current area.
  • the maximum transmit power of the wireless access point is limited, and it is stipulated that the transmit power of each wireless access point cannot be higher than this threshold.
  • the present application adopts the multi-objective particle swarm algorithm, which has fast convergence speed and high efficiency, and has many measures to avoid falling into local optimum, and can quickly reach the maximum average energy efficiency and/or total transmit power of wireless access points minimal purpose.
  • FIG. 1 is a schematic diagram of an application scenario of wireless access point deployment provided by an embodiment of the present application
  • FIG. 2A is a schematic diagram of a flow of a wireless access point deployment method provided by an embodiment of the present application
  • 2B is a schematic diagram of establishing a target area-user model provided by an embodiment of the present application.
  • 3A is a schematic flowchart of a multi-target deployment algorithm provided by an embodiment of the present application.
  • 3B is a schematic flowchart of judging whether a preset deployment strategy is satisfied according to an embodiment of the present application
  • FIG. 4 is a schematic structural diagram of an optional wireless access point deployment apparatus according to an embodiment of the present invention.
  • FIG. 5 is a schematic structural diagram of an optional electronic device according to an embodiment of the present invention.
  • PSO particle swarm optimization algorithm
  • PSO bird flock foraging algorithm
  • J. Kennedy and RCEberhart Kernel- EA
  • the PSO algorithm is a kind of evolutionary algorithm. Similar to the simulated annealing algorithm, it also starts from a random solution and finds the optimal solution through iteration. It also evaluates the quality of the solution through fitness, but it is simpler than the genetic algorithm rules. It does not have the "Crossover” (Crossover) and "Mutation” (Mutation) operations of the genetic algorithm, it finds the global optimum by following the current searched optimum value.
  • This algorithm has attracted the attention of academia because of its advantages of easy implementation, high precision and fast convergence, and it has shown its superiority in solving practical problems.
  • Wireless Access Point is the HUB in the traditional wired network, and it is also the most commonly used device when building a small wireless local area network.
  • AP is equivalent to a bridge connecting wired network and wireless network. Its main function is to connect various wireless network clients together, and then connect the wireless network to Ethernet.
  • FIG. 1 is a schematic diagram of an application scenario of wireless access point deployment provided by an embodiment of the present application. As shown in FIG. 1 , it includes: multiple wireless access points AP101 and multiple users 102 .
  • the wireless access point AP101 can be a HUB in a traditional wired network, and is also the most commonly used device when building a small wireless local area network.
  • AP is equivalent to a bridge connecting wired network and wireless network. Its main function is to connect various wireless network clients together, and then connect the wireless network to Ethernet. It is also a wireless switch in a wireless network, and it is the access point for mobile terminal users to enter the wired network.
  • the indoor coverage of an AP is generally 30m to 100m.
  • the AP products of many manufacturers can be interconnected to increase the WLAN coverage area. It is also because the coverage of each AP has certain limitations. Just as mobile phones can roam between base stations, wireless LAN clients can also roam between APs. Therefore, in order to realize wireless Internet access in a large range, it is necessary to deploy multiple APs to ensure that multiple terminal devices in a large range can access the Ethernet through the multiple APs.
  • the user 102 is set to refer to a terminal device that can access the Internet through an AP, and the terminal device can be an input and output device, a device that inputs programs and data to a computer or receives a computer output processing result via a communication facility.
  • Terminal equipment is usually set in a convenient place where communication facilities can be used to connect with a remote computer to work. It is mainly composed of a communication interface control device and a dedicated or selected input and output device. For example: computers, notebooks, smart phones, only watches, smart bracelets, Bluetooth speakers and other terminal devices that can access the Internet through AP.
  • the application scenario of wireless access point deployment in FIG. 1 is only an exemplary implementation in the embodiment of the present invention, and the application scenario of wireless access point deployment in the embodiment of the present invention includes but It is not limited to the above application scenarios of wireless access point deployment.
  • FIG. 2A is a schematic diagram of a flow of a method for deploying a wireless access point provided by an embodiment of the present application. It can be set up as the system in FIG. 1 described above, which will be described below in conjunction with FIG. 2A to deploy the device from one side of the wireless access point.
  • the method may include the following steps S1-S3.
  • Step S1 Establish a target area-user model.
  • the user distribution law corresponding to the target area is obtained, and the target area-user model is established.
  • the number of users in different areas is different, and thus the user density in different areas is different, and the number of terminals held by corresponding users is also different. Therefore, before deploying the wireless access point, it is necessary to obtain the user distribution rule corresponding to the target area, so as to deploy the wireless access point.
  • FIG. 2B is a schematic diagram of establishing a target area-user model provided by an embodiment of the present application.
  • multiple APs are deployed in the target area to ensure that terminal devices held by multiple users in the target area can access the Internet through the deployed APs.
  • a target area with an area of AT may be divided into N subarea sub-areas, and the sub-areas may be divided according to actual conditions.
  • the area of each area is A(k)
  • the user density of each sub-area is A(k).
  • Step S2 estimating the first number of wireless access points to be deployed in the target area.
  • the target area-user model After establishing the target area-user model, it is necessary to estimate the number of wireless access points to be deployed in the target area (ie, the first number), so as to reasonably deploy multiple wireless access points in the target area . For example, given the range of association between access points and users (the range of connections from users to access points), estimate the maximum number of users served by a single access point.
  • the estimating the first number of wireless access points waiting to be deployed in the target area includes: acquiring a second number corresponding to each wireless access point, where the second number is the maximum number of terminal devices allowed to be accessed by the wireless access point; obtain the total number of the terminal devices in the target area; estimate the first number according to the second number and the total number.
  • the method for estimating the maximum number of services of a single wireless access point can be a deployment method based on a random geometric model, which can estimate the maximum service rate that a single access point can provide according to the distance from the user to the access point, and Based on this rate, estimate the maximum number of users that can be served.
  • the estimating the first number of wireless access points waiting to be deployed in the target area includes: acquiring the coverage of each wireless access point, where the coverage is the wireless access point The access point allows the terminal device to access the distance range; the area range of the target area is obtained, and the first number is estimated according to the coverage area of each wireless access point and the area range.
  • the estimating the number of wireless access points waiting to be deployed in the target area includes: acquiring a third number corresponding to each wireless access point, where the third number is the The maximum number of wireless access points allowed to access the terminal devices; obtain the total number of terminal devices in the target area; obtain the coverage of each wireless access point, where the coverage is the wireless access point The distance range that terminal equipment is allowed to access; according to the third number, the total number and the coverage of each wireless access point, estimate the number of wireless access points waiting to be deployed in the target area.
  • the method of joint deployment of coverage area and number of serving persons can be adopted, wherein, the coverage area estimation is to divide the coverage area of the whole AP by the AP coverage of a single access point.
  • the service user estimate is the number of users active in the area divided by the maximum number of service users for a single access point AP.
  • the method of joint deployment of coverage and service population means that the final estimated number is the maximum of the two estimation methods.
  • Step S2 of the present invention is implemented: first, a random geometric model can be used to model a single access point, and the total throughput of a single access point can be calculated, and the calculation formula is as follows:
  • Formulas (1), (2) and (3) represent the wireless access point AP-user signal-to-noise ratio, where P b is the transmit power of the wireless access point AP, g i , g j are the wireless access Rayleigh fading factor for AP i and AP j. r is the distance from the user to the wireless access point serving it, and Rj is the distance from the interfering wireless access point to the user.
  • Formula (2) is actually the signal gain obtained by the user
  • formula (3) is the interference obtained by the user.
  • Equation (4) represents the total throughput that the access point can provide, which is modeled using a random geometric model as follows:
  • R th is the coverage of a single AP.
  • Formula (7) is the number of wireless access points estimated according to the number of people served, N is the number of people in the entire area, and N user is the maximum number of users that a single wireless access point can serve.
  • the calculation formula is as follows:
  • ⁇ th is the minimum throughput threshold that a user can receive.
  • the final estimated number of wireless access points deployed is:
  • Step S3 based on the multi-target particle swarm algorithm, deploy a first number of wireless access points in the target area.
  • the first number of wireless access points are deployed in the target area, so that the first number of wireless access points in the target area meet the preset deployment strategy
  • the access point has the highest average energy efficiency and/or the lowest total transmit power.
  • the deploying the first number of wireless access points in the target area based on the multi-target particle swarm algorithm includes: initializing the location variables of each wireless access point and speed variable, and determine the objective function corresponding to each wireless access point; based on the multi-objective particle swarm algorithm, iteratively update the position variable and speed variable of each wireless access point, so that the The first quantity of wireless access points satisfies the preset deployment policy; the first quantity of wireless access points is deployed in the target area according to the updated position variable and the updated speed variable.
  • the preset deployment strategy includes one or more of the following strategies: the total number of users served by the strategy for the first number of wireless access points is greater than the total number of users in the target area ; the strategy is that the total number of terminal devices covered by the first number of wireless access points is greater than or equal to a first preset threshold, and the first preset threshold corresponds to the number of all terminal devices in the target area; The strategy is that the transmission power of each wireless access point in the first number of wireless access points is less than the maximum preset transmission threshold.
  • the capacity limit should be designed based on the number of people distributed in the current area during deployment, and it is required that the total number of users served by all access points should be greater than or equal to the total number of people in the current area.
  • the present invention considers that the coverage requirement is met.
  • the present invention limits the maximum transmit power of the access point, and stipulates that the transmit power of each access point cannot be higher than the threshold.
  • FIG. 3A is a schematic flowchart of a multi-target deployment algorithm provided by an embodiment of the present application. It should be noted that the particles in the multi-target deployment algorithm mentioned in the embodiments of the present application and the accompanying drawings are wireless access points. As shown in FIG. 3A , based on the multi-target particle swarm algorithm, deploying the first number of wireless access points in the target area may include the following steps:
  • Step S31 Determine the number of particle populations and initialize the position variable and particle velocity variable of each wireless access point according to the pre-deployed number of wireless access points. For example: determine the particle population number L and initialize the position variable W (l) and particle velocity variable V (l) of each AP according to the estimated number of pre-deployed access points (the first number) .
  • x and y are the AP position coordinates
  • p represents the emission power
  • l is the particle swarm to which it belongs.
  • Step S32 Calculate the objective function (overall power and user average energy efficiency) corresponding to each wireless access point, and put some of these wireless access points into an external set. (It can be random or according to preset rules).
  • Step S33 Determine the optimal solution corresponding to each wireless access point, which is called the local optimal solution W( l,local ).
  • Step S34 Divide the target area into many grids, and determine the coordinates of the grid where the target area is located according to the coordinates corresponding to the wireless access point.
  • Step S35 Define an adaptation value for a grid containing at least one wireless access point AP in the external set, select a grid based on the roulette method, and randomly select a wireless access point AP in the external set as the grid.
  • the global optimal solution W global
  • Step S36 Update the position variables and speed variables of all wireless access points. Among them, the formula is as follows:
  • Step S37 Recalculate the objective function value, and update the local optimal solution of the wireless access point.
  • the outer set is updated using the adaptive mesh method.
  • Step S38 Determine whether the wireless access point satisfies the preset deployment policy restrictions, and if not, jump back to step S36 again until the conditions are satisfied.
  • FIG. 3B is a schematic flowchart of judging whether a preset deployment strategy is satisfied according to an embodiment of the present application.
  • step S381 after initializing the variables, determine whether the current deployment meets the capacity limitation requirements, if not, perform location update and power adjustment on the access point and re-determine the capacity limitation, if the requirements are met, proceed to step S382, and do not If satisfied, repeat the above steps.
  • Step S382 Determine whether the current deployment satisfies the coverage requirements, if not, perform location update and power adjustment on the access point and perform coverage limitation judgment again, if the requirements are satisfied, perform step S383, otherwise, repeat the above steps. Determine whether the current deployment meets the requirements of the transmit power threshold. If not, perform location update and power adjustment on the access point and re-determine the transmit power threshold. If the requirements are met, the deployment is completed. If not, repeat the above steps.
  • the conditions for judging whether to preset the deployment strategy can be processed according to the following formula: whether
  • Formula (14) indicates that the serviceable user capacity when the access point is deployed is greater than the number of users existing in the current area, where ⁇ m,k represents the percentage of the current access point coverage area in the entire area, ⁇ represents the adjustment factor,
  • the present invention takes 1.
  • ⁇ n represents the number of users actually served by the access point.
  • Equation (17) indicates that the transmit power of each access point cannot exceed a defined threshold P threshold .
  • Step S4 Based on the greedy algorithm, cancel the deployment of the target wireless access point in the first number of wireless access points.
  • the target wireless access point does not change the first number of wireless access points
  • the total capacity of the access points, the total coverage of the first number of wireless access points, and/or the transmit power of the first number of wireless access points are all access points that do not affect the capacity, coverage and transmission power limitations, ie. After the access point is eliminated, the above formulas (14), (15) and (17) are all established.
  • the average energy efficiency of multiple wireless access points can be maximized, that is, the energy consumption is small, and the total transmission power is minimized, which can satisfy more users while ensuring low energy consumption and operation cost. demand, improve service quality and reduce operating costs.
  • FIG. 4 is a schematic diagram of an optional wireless access point deployment apparatus according to an embodiment of the present invention. Schematic. As shown in Figure 4, the device includes:
  • Estimating unit 401 configured to estimate the first number of wireless access points to be deployed in the target area
  • the deployment unit 402 is configured to deploy the first number of wireless access points in the target area based on the multi-target particle swarm algorithm, so that the first number of wireless access points in the target area is satisfied when the preset deployment strategy is satisfied.
  • the average energy efficiency of each wireless access point is maximum and/or the total transmit power is minimum.
  • first estimate the first number of wireless access points to be deployed in the target area; based on the multi-target particle swarm algorithm, deploy the first number of wireless access points in the target area , so as to maximize the average energy efficiency and/or minimize the total transmit power of the first number of wireless access points in the target area when a preset deployment strategy is met.
  • a preset deployment strategy can be satisfied during deployment, so as to maximize the average energy efficiency and/or minimize the total transmit power of multiple wireless access points, thereby ensuring lower energy consumption and lower operating costs. meet more user needs, improve service quality, and reduce operating costs.
  • the wireless access point capacity limit should be designed based on the number of people distributed in the current area during deployment, and it is required that the total number of users served by all wireless access points should be greater than or equal to the total number of people in the current area.
  • the maximum transmit power of the wireless access point is limited, and it is stipulated that the transmit power of each wireless access point cannot be higher than this threshold.
  • the present application adopts the multi-objective particle swarm algorithm, which has fast convergence speed and high efficiency, and has many measures to avoid falling into local optimum, and can quickly reach the maximum average energy efficiency and/or total transmit power of wireless access points minimal purpose.
  • the estimating unit 401 is specifically configured to: obtain a second quantity corresponding to each wireless access point, where the second quantity is the access point allowed by the wireless access point the maximum number of terminal devices; obtain the total number of the terminal devices in the target area; estimate the first number according to the second number and the total number.
  • the estimating unit 401 is specifically configured to: acquire the coverage of each wireless access point, where the coverage is that the wireless access point allows the terminal device to access The distance range of the target area is obtained; the area range of the target area is obtained, and the first number is estimated according to the coverage area of each wireless access point and the area range.
  • the estimating unit 401 is specifically configured to: obtain a third quantity corresponding to each wireless access point, where the third quantity is the access point allowed by the wireless access point. obtaining the maximum number of the terminal equipment; obtaining the total number of the terminal equipment in the target area; obtaining the coverage of each wireless access point, the coverage being the distance range that the wireless access point allows the terminal equipment to access; According to the third number, the total number, and the coverage of each wireless access point, the number of wireless access points waiting to be deployed in the target area is estimated.
  • the deployment unit 402 is specifically set to: initialize the position variable and speed variable of each wireless access point, and determine the objective function corresponding to each wireless access point ; Based on the multi-objective particle swarm algorithm, iteratively update the position variable and speed variable of each wireless access point, so that the first number of wireless access points meet the preset deployment strategy; According to the updated The location variable and the updated velocity variable are deployed in the target area with the first number of wireless access points.
  • the preset deployment strategy includes one or more of the following strategies: the total number of users served by the strategy for the first number of wireless access points is greater than the total number of users in the target area ; the strategy is that the total number of terminal devices covered by the first number of wireless access points is greater than or equal to a first preset threshold, and the first preset threshold corresponds to the number of all terminal devices in the target area; The strategy is that the transmission power of each wireless access point in the first number of wireless access points is less than the maximum preset transmission threshold.
  • the apparatus further includes: a canceling unit 403, configured to, based on the multi-target particle swarm algorithm, cancel the Deployment of target wireless access points in the first number of wireless access points, the target wireless access point is not to change the total capacity of the first number of wireless access points, the The total coverage of the first number of wireless access points and/or the transmission power of the first number of wireless access points.
  • a canceling unit 403 configured to, based on the multi-target particle swarm algorithm, cancel the Deployment of target wireless access points in the first number of wireless access points, the target wireless access point is not to change the total capacity of the first number of wireless access points, the The total coverage of the first number of wireless access points and/or the transmission power of the first number of wireless access points.
  • a computer-readable storage medium where a computer program is stored in the computer-readable storage medium, wherein the computer program is configured to execute any one of the above when running steps in a method embodiment.
  • the above-mentioned computer-readable storage medium may be configured to store a computer program configured to perform the following steps:
  • a first number of wireless access points to be deployed in the target area is estimated.
  • the multi-target particle swarm algorithm Based on the multi-target particle swarm algorithm, deploy the first number of wireless access points in the target area, so that the first number of wireless access points in the target area meet the preset deployment strategy
  • the average energy efficiency is maximum and/or the total transmitted power is minimum.
  • the storage medium may include: a flash disk, a ROM (Read-Only Memory, read-only memory), a RAM (Random Access Memory, a random access device), a magnetic disk or an optical disk, and the like.
  • FIG. 5 is an optional electronic device according to an embodiment of the present invention.
  • the electronic device includes a memory 502 and a processor 505, the memory 502 stores a computer program, and the processor 504 is configured to execute any one of the above method embodiments through the computer program. A step of.
  • the above-mentioned electronic apparatus may be located in at least one network device among multiple network devices of a computer network.
  • the above-mentioned processor may be configured to execute the following steps through a computer program:
  • Estimate the first number of wireless access points to be deployed in the target area based on the multi-objective particle swarm algorithm, deploy the first number of wireless access points in the target area, so as to meet the preset deployment strategy when the average energy efficiency of the first number of wireless access points in the target area is maximum and/or the total transmit power is minimum.
  • FIG. 5 is for illustration only, and the electronic device may also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a handheld computer, and a mobile Internet device (Mobile Internet device). Internet Devices, MID), PAD and other terminal equipment.
  • FIG. 5 does not limit the structure of the above electronic device.
  • the electronic device may also include more or less components than those shown in FIG. 5 (eg, network interfaces, etc.), or have a different configuration than that shown in FIG. 5 .
  • the memory 502 may be configured to store software programs and modules, such as program instructions/modules corresponding to the over-temperature power automatic adjustment method and device in the embodiment of the present invention, and the processor 504 executes the software programs and modules stored in the memory 502 by running the software programs and modules. , so as to perform various functional applications and transmission of original data information, that is, to realize the above-mentioned automatic adjustment method of over-temperature power.
  • Memory 502 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, memory 502 may further include memory located remotely from processor 504, and these remote memories may be connected to the terminal through a network.
  • the memory 502 may be specifically, but not limited to, be set to store information such as the target height of the target object.
  • the foregoing memory 502 may include, but is not limited to, the estimation unit 402 , the deployment unit 404 and the elimination unit 403 in the foregoing wireless access point deployment apparatus.
  • it may also include but not be limited to other module units in the above-mentioned over-temperature power automatic adjustment device, which will not be repeated in this example.
  • the above-mentioned transmission device 506 is configured to receive or send data via a network.
  • Specific examples of the above-mentioned networks may include wired networks and wireless networks.
  • the transmission device 506 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices and routers through a network cable so as to communicate with the Internet or a local area network.
  • the transmission device 506 is a radio frequency (RF) module, which is configured to communicate with the Internet in a wireless manner.
  • RF radio frequency
  • the above-mentioned electronic device further includes: a connection bus 508 configured to connect various module components in the above-mentioned electronic device.
  • the above-mentioned terminal or server may be a node in a distributed system, wherein the distributed system may be a blockchain system, and the blockchain system may be communicated by the multiple nodes through a network A distributed system formed by formal connections.
  • a peer-to-peer (P2P, Peer To Peer) network can be formed between nodes, and any form of computing equipment, such as servers, terminals and other electronic devices can become a node in the blockchain system by joining the peer-to-peer network.
  • the storage medium may include: a flash disk, a read-only memory (Read-Only Memory, ROM), a random access device (Random Access Memory, RAM), a magnetic disk or an optical disk, and the like.
  • the integrated units in the above-mentioned embodiments are implemented in the form of software functional units and sold or used as independent products, they may be stored in the above-mentioned computer-readable storage medium.
  • the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium,
  • Several instructions are included to cause one or more computer devices (which may be personal computers, servers, or network devices, etc.) to perform all or part of the steps of the methods of various embodiments of the present invention.
  • the disclosed client terminal may be implemented in other manners.
  • the device embodiments described above are only illustrative, for example, the division of units is only a logical function division. In actual implementation, there may be other division methods, for example, multiple units or components may be combined or integrated into Another system, or some features can be ignored, or not implemented.
  • the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of units or modules, and may be in electrical or other forms.
  • Units described as separate components may or may not be physically separated, and components shown as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.
  • the above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.
  • a wireless access point deployment method, device, and storage medium provided by the embodiments of the present invention have the following beneficial effects: the multi-objective particle swarm algorithm is adopted, which has fast convergence speed and high efficiency, and there are many measures to avoid Falling into a local optimum can quickly achieve the goal of maximizing the average energy efficiency of the wireless access point and/or minimizing the total transmit power.

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Abstract

本发明公开了无线访问接入点部署方法和装置、存储介质。该方法包括：预估目标区域内待部署的无线访问接入点的第一数量；基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点，以使在满足预设部署策略时所述目标区域内的所述第一数量个无线访问接入点的平均能源效率最大和/或发射总功率最小。以在保证较低的能耗和运营成本的情况下，满足更多的用户需求，提高服务质量，降低运营成本。

Description

无线访问接入点部署方法和装置、存储介质 技术领域
本发明涉及通信领域，具体而言，涉及一种无线访问接入点部署方法和装置、存储介质。
背景技术
当前移动数据的爆炸式增长对运营商提出了更高的要求。在此背景下，运营商应不得不提供更高的通信系统容量，以满足用户日益增长的需求，并为用户带来更好的用户体验。当前已有多种技术被用来提高通信系统容量，减少系统运营压力，如频段复用、数据卸载等方式都可以提高通信系统容量，提升用户服务质量，满足用户需求。但是上述方法较为复杂，且限制性较大，不能从根源性解决问题。一种更为简单且高效的解决方案是部署足够多的接入点，为用户提供足够多的通信服务。但是，该方式往往带来更高的能耗和运营成本。
因此如何在保证较低的能耗和运营成本的情况下，满足更多的用户需求，提高服务质量，降低运营成本，是亟待解决的问题。
发明内容
本发明实施例提供了一种无线访问接入点部署方法和装置、存储介质，以在保证较低的能耗和运营成本的情况下，满足更多的用户需求，提高服务质量，降低运营成本。
根据本发明实施例的一个方面，提供了无线访问接入点部署方法，包括：预估目标区域内待部署的无线访问接入点的第一数量；基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点，以使在满足预设部署策略时所述目标区域内的所述第一数量个无线访问接入点的平均能源效率最大和/或发射总功率最小。
根据本发明实施例的另一方面，还提供了无线访问接入点部署装置，包括：预估单元，设置为预估目标区域内待部署的无线访问接入点的第一数量；部署单元，设置为基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点，以使在满足预设部署策略时所述目标区域内的所述第一数量个无线访问接入点的平均能源效率最大和/或发射总功率最小。
根据本发明实施例的又一方面，还提供了一种计算机可读的存储介质，该计算机可读的存储介质中存储有计算机程序，其中，该计算机程序被设置为运行时执行上述过无线访问接入点部署方法。
根据本发明实施例的又一方面，还提供了一种电子装置，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其中，上述处理器通过计算机程序执行上述的无线访问接入点部署方法。
通过本发明，首先，预估目标区域内待部署的无线访问接入点的第一数量；基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点，以使在满足预设部署策略时所述目标区域内的所述第一数量个无线访问接入点的平均能源效率最大和/或发射总功率最小。采用上述技术方案，可以在部署时，满足预设部署策略，以使的多个无线访问接入点的平均能源效率最大和/或发射总功率最小，保证了较低的能耗和运营成本的情况下，满足更多的用户需求，提高服务质量，降低运营成本。例如：在部署时应以当前区域内分布人数来设计无线访问接入点容量限制，要求所有无线访问接入点服务用户的总数应大于或等于当前区域内的总人数。当区域内95％用户都达到服务速率要求时，在接入点服务用户过程中，限定无线访问接入点的最大发射功率，并规定每个无线访问接入点的发射功率都不能高于该阈值。而且本申请采用多目标粒子群算法，其收敛速度快，效率高，且有很多措施可以避免陷入局部最优，可以很快的达到无线访问接入点的平均能源效率最大和/或发射总功率最小的目的。
附图说明
此处所说明的附图用来提供对本发明的进一步理解，构成本申请的一部分，本发明的示意性实施例及其说明设置为解释本发明，并不构成对本发明的不当限定。在附图中：
图1是本申请实施例提供的一种无线访问接入点部署的应用场景示意图；
图2A是本申请实施例提供的一种无线访问接入点部署方法流程的示意图；
图2B是本申请实施例提供的一种建立目标区域-用户模型的示意图；
图3A是本申请实施例提供的一种多目标部署算法流程示意图；
图3B是本申请实施例提供的一种判断是否满足预设部署策略的流程示意图；
图4是根据本发明实施例的一种可选的无线访问接入点部署装置的结构示意图；
图5是根据本发明实施例的一种可选的电子装置的结构示意图。
具体实施方式
为了使本技术领域的人员更好地理解本发明方案，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分的实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都应当属于本发明保护的范围。
需要说明的是，本发明的说明书和权利要求书及上述附图中的术语“第一”、“第二”和“第三”等是设置为区别类似的对象，而不必设置为描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的本发明的实施例能够以除了在这里图示或描述的那些以外的顺序实施。此外，术语“包括”和“具有”以及他们的任何变形，意图在 于覆盖不排他的包含，例如，包含了一系列步骤或单元的过程、方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
首先，对本申请中的部分用语进行解释说明，以便于本领域技术人员理解。
(1)粒子群算法，也称粒子群优化算法或鸟群觅食算法(Particle Swarm Optimization)，缩写为PSO，是由J.Kennedy和R.C.Eberhart等开发的一种新的进化算法(Evolutionary Algorithm-EA)。PSO算法属于进化算法的一种，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover)和“变异”(Mutation)操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。
(2)无线访问接入点(Wireless Access Point，AP)就是传统有线网络中的HUB，也是组建小型无线局域网时最常用的设备。AP相当于一个连接有线网和无线网的桥梁，其主要作用是将各个无线网络客户端连接到一起，然后将无线网络接入以太网。
一个高效合理的AP部署方案可以在保证服务用户质量的同时，减少AP部署数量，并降低整个AP部署环境的能耗，对降低运营成本是十分必要的。下面对本申请实施例所基于的其中一种无线访问接入点AP部署场景进行描述。请参考附图1，图1是本申请实施例提供的一种无线访问接入点部署的应用场景示意图，如图1所示包括：多个无线访问接入点AP101，多个用户102。
其中，无线访问接入点AP101可以是传统有线网络中的HUB，也是组建小型无线局域网时最常用的设备。AP相当于一个连接有线网和无线网的桥梁，其主要作用是将各个无线网络客户端连接到一起，然后将无线网络接入以太网。也是无线网络中的无线交换机，它是移动终端用户进入 有线网络的接入点。AP的室内覆盖范围一般是30m～100m，不少厂商的AP产品可以互联，以增加WLAN覆盖面积。也正因为每个AP的覆盖范围都有一定的限制，正如手机可以在基站之间漫游一样，无线局域网客户端也可以在AP之间漫游。因此，若想实现在一个较大的范围内实现无线上网，需要部署多个AP，以保证在一个较大的范围内的多个终端设备可以通过该多AP接入以太网。
用户102设置为指代终端设备，该终端设备可以通过AP接入互联网，该终端设备可以是输入输出设备，经由通信设施向计算机输入程序和数据或接收计算机输出处理结果的设备。终端设备通常设置在能利用通信设施与远处计算机联接工作的方便场所，它主要由通信接口控制装置与专用或选定的输入输出装置组合而成。例如：电脑、笔记本、智能手机、只能手表、智能手环、蓝牙音箱等等可以通过AP接入互联网的终端设备。
可以理解的是，图1中的无线访问接入点部署的应用场景只是本发明实施例中的一种示例性的实施方式，本发明实施例中的无线访问接入点部署的应用场景包括但不仅限于以上无线访问接入点部署的应用场景。
参考附图2A，图2A是本申请实施例提供的一种无线访问接入点部署方法流程的示意图。可应设置为上述图1中的系统，下面将结合图2A从无线访问接入点部署装置的单侧进行描述。该方法可以包括以下步骤S1-步骤S3。
步骤S1：建立目标区域-用户模型。
具体的，给定部署目标区域的区域范围，得出所述目标区域对应的用户分布规律，建立所述目标区域-用户模型。不同区域内用户的数量不同，进而不同区域的用户密度不同，对应的用户所持有的终端数目也不同。所以在部署无线访问接入点之前，需要获取所述目标区域对应的用户分布规律，以便部署无线访问接入点。
例如：参考附图2B，图2B是本申请实施例提供的一种建立目标区域-用户模型的示意图。如图2B所示，将目标区域内部署多个AP，以保证目标区域内多个用户持有的终端设备可以通过部署的AP接入互联网。其中， 本申请实施例可以将面积为A T的目标区域划分成N subarea个子区域，子区域的划分可以根据实际情况自主划分，每个区域的面积为A(k)，每个子区域的用户密度为D(k)，k＝1,……,N subarea，以便部署无线访问接入点。
步骤S2、预估目标区域内待部署的无线访问接入点的第一数量。
具体的，在建立目标区域-用户模型后，需要预估目标区域内待部署的无线访问接入点的数量(即，第一数量)，以便在目标区域内合理部署多个无线访问接入点。例如：给定接入点到用户的关联范围(用户到接入点的连接范围)，估算单个接入点的最大服务用户数。
作为一种可选的方案，所述预估目标区域内等待部署的无线访问接入点的第一数量，包括：获取每个无线访问接入点对应的第二数量，所述第二数量为所述无线访问接入点允许接入的终端设备的最大数量；获取目标区域内所述终端设备的总数量；根据所述第二数量和所述总数量，预估所述第一数量。其中，估算单个无线访问接入点的最大服务数量的方法可以为基于随机几何模型的部署方法，该方法可以根据用户到接入点的距离估算单个接入点所能提供的最大服务速率，并根据该速率估算能服务的最大用户数。
作为一种可选的方案，所述预估目标区域内等待部署的无线访问接入点的第一数量，包括：获取每个无线访问接入点的覆盖范围，所述覆盖范围为所述无线访问接入点允许所述终端设备接入的距离范围；获取目标区域的区域范围根据所述每个无线访问接入点的覆盖范围和所述区域范围，预估所述第一数量。
作为一种可选的方案，所述预估目标区域内等待部署的无线访问接入点的数量，包括：获取每个无线访问接入点对应的第三数量，所述第三数量为所述无线访问接入点允许接入所述终端设备的最大数量；获取目标区域内所述终端设备的总数量；获取每个无线访问接入点的覆盖范围，所述覆盖范围为无线访问接入点允许终端设备接入的距离范围；根据所述第三数量、所述总数量以及所述每个无线访问接入点的覆盖范围，预估目标区 域内等待部署的无线访问接入点的数量。
例如：可采用覆盖范围与服务人数联合部署的方法，其中，覆盖范围估算是用整体AP的覆盖范围除以单个接入点AP覆盖发内。服务用户估算是用活动在该区域的用户人数除以单个接入点AP的最大服务用户数。而采用覆盖范围与服务人数联合部署的方法是指最终估算数量为两种估算方法的最大值。实施本发明步骤S2：可以首先采用随机几何模型对单个接入点进行建模，计算出单个接入点的总吞吐量，其计算公式如下：
Figure PCTCN2021091758-appb-000001
Figure PCTCN2021091758-appb-000002
Figure PCTCN2021091758-appb-000003
公式(1)，(2)和(3)表示无线访问接入点AP-用户的信噪比，式中P b是无线访问接入点AP的发射功率，g i,g j是无线访问接入点i和无线访问接入点j的瑞利衰落因子。r为用户到为其提供服务的无线访问接入点的距离，Rj为干扰无线访问接入点到该用户的距离。公式(2)实际上为用户获得的信号增益，公式(3)为用户获得的干扰。
Figure PCTCN2021091758-appb-000004
公式(4)表示接入点可提供的总吞吐量，其利用随机几何模型建模后如下：
Figure PCTCN2021091758-appb-000005
公式(5)中
Figure PCTCN2021091758-appb-000006
和
Figure PCTCN2021091758-appb-000007
是
Figure PCTCN2021091758-appb-000008
和
Figure PCTCN2021091758-appb-000009
为拉普拉斯变换。
估算接入点的部署数量计算公式如(6),(7)和(8)所示：
Figure PCTCN2021091758-appb-000010
Figure PCTCN2021091758-appb-000011
为根据覆盖范围估算的无线访问接入点数量，R th是单个无线访问接入点的覆盖范围。
Figure PCTCN2021091758-appb-000012
公式(7)为根据服务人数估算的无线访问接入点数量，N为整个区域人数，N user是单个无线访问接入点能服务的最大用户数，计算公式如下：
Figure PCTCN2021091758-appb-000013
τ th是用户可以接收的最小吞吐量阈值。
最终预估的无线访问接入点部署数量为：
Figure PCTCN2021091758-appb-000014
步骤S3、基于多目标粒子群算法，在目标区域内部署第一数量个无线访问接入点。
具体的，基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点，以使在满足预设部署策略时所述目标区域内的所述第一数量个无线访问接入点的平均能源效率最大和/或发射总功率最小。
作为一种可选的方案，所述基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点，包括：初始化所述每个无线访问接入点的位置变量和速度变量，并确定所述每个无线访问接入点对应的目标函数；基于所述多目标粒子群算法，迭代更新所述每个无线访问接入点的位置变量和速度变量，以使所述第一数量个无线访问接入点满足预设部署策略；根据更新后的位置变量和更新后速度变量，在目标区域内部署所述第一数量个无线访问接入点。
作为一种可选的方案，所述预设部署策略包括以下策略中的一个或多 个：所述策略为所述第一数量个无线访问接入点服务的用户总数大于目标区域内用户的总数；所述策略为所述第一数量个无线访问接入点覆盖的终端设备的总数量大于或等于第一预设阈值，所述第一预设阈值与目标区域内所有终端设备数量对应；所述策略为所述第一数量个无线访问接入点中每个无线访问接入点的发射功率小于最大预设发射阈值。即，可以理解的是，在部署时应以当前区域内分布人数来设计容量限制，要求所有接入点服务用户的总数应大于或等于当前区域内的总人数。当区域内95％用户都达到服务速率要求时，本发明认为达到了覆盖要求。在接入点服务用户过程中，本发明限定接入点的最大发射功率，并规定每个接入点的发射功率都不能高于该阈值。
作为一种可选的方案，请参考附图3A，图3A是本申请实施例提供的一种多目标部署算法流程示意图。需要说明的是，本申请实施例和附图中所提及的多目标部署算法中的粒子为无线访问接入点。如图3A所示，基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点，可以包括以下步骤：
步骤S31：确定粒子种群数量并根据预部署的无线访问接入点数量，初始化每个无线访问接入点位置变量和粒子速度变量。例如：确定粒子种群数量L并根据估算的预部署接入点数量(第一数量)，初始化每个AP的位置变量W (l)和粒子速度变量V (l)。
Figure PCTCN2021091758-appb-000015
Figure PCTCN2021091758-appb-000016
上(10)式中x，y为AP位置坐标，p代表发射功率，l为所属粒子群。
步骤S32：计算每个无线访问接入点对应的目标函数(整体功率与用户平均能源效率效),并将这些无线访问接入点中的部分无线访问接入点放入外部集合中。(可以随机或者按照预设规则)。
步骤S33：确定每个无线访问接入点对应的最优解，称为局部最优解 W( l,local)。
步骤S34：将目标区域分割成许多格子，并根据无线访问接入点所对应的坐标确定所在格子的坐标。
步骤S35：为至少包含一个外部集合中无线访问接入点AP的格子定义适应值，基于轮盘赌方法选定一个格子，从上述格子中随机选择一个在外部集合的无线访问接入点AP作为全局最优解W (global)。
步骤S36：更新所有无线访问接入点的位置变量和速度变量。其中，公式如下：
Figure PCTCN2021091758-appb-000017
上述(12)式中
Figure PCTCN2021091758-appb-000018
为0.8，c1＝c2＝2，φ 1和φ 2是正数。
Figure PCTCN2021091758-appb-000019
步骤S37：重新计算目标函数值，更新无线访问接入点的局部最优解。利用自适应网格法更新外部集合。
步骤S38：判断无线访问接入点是否满足预设部署策略限制，若不满足则重新跳回到步骤S36，直到满足条件为止。
例如：请参考附图3B，图3B是本申请实施例提供的一种判断是否满足预设部署策略的流程示意图。如图3B所示，步骤S381：初始化变量后，判定当前部署是否满足容量限制要求，不满足则对接入点进行位置更新和功率调整并重新进行容量限制判断，若满足要求进行步骤S382，不满足则重复上述步骤。步骤S382：判定当前部署是否满足覆盖要求，不满足则对接入点进行位置更新和功率调整并重新进行覆盖限制判断，若满足要求进行步骤S383，不满足则重复上述步骤。判定当前部署是否满足发射功率阈值要求，不满足则对接入点进行位置更新和功率调整并重新进行发射功率阈值判断，若满足要求完成部署，不满足则重复上述步骤。
其中，判断是否预设部署策略的条件可以按照如下公式处理：是否
策略1：
Figure PCTCN2021091758-appb-000020
公式(14)表示接入点部署时的可服务的用户容量要大于当前区域存在的用户数，式中ρ m,k表示当前接入点覆盖区域占当整个区域的百分比，η表示调节因子，本发明取1。
策略2：
Figure PCTCN2021091758-appb-000021
公式(15)表示接入点实际服务的用户数应达到总人数的σ％，即N ref＝σN。此外：
Figure PCTCN2021091758-appb-000022
式中γ n表示接入点实际服务的用户数。
策略3：
Figure PCTCN2021091758-appb-000023
公式(17)表示每个接入点的发射功率都不能超过限定阈值P threshold。
需要说明的是，本发明中容量限制的判断切换条件按步骤S481,S482，S483执行。
步骤S4：基于贪婪算法，取消第一数量个无线访问接入点中的目标无线访问接入点的部署。
具体的，基于贪婪算法，取消所述第一数量个无线访问接入点中的目标无线访问接入点的部署，所述目标无线访问接入点为不改变所述第一数量个无线访问接入点的总容量、所述第一数量个无线访问接入点的总覆盖范围和/或所述第一数量个无线访问接入点的传输功率。可以理解的是：在进行无线访问接入点冗余消除时，所消除的无线访问接入点均为不影响容量、覆盖范围和传输功率限制的接入点，即。将该接入点消除后上述公式(14)，(15)和(17)均成立。
通过本实施例，可以使得多个无线访问接入点的平均能源效率最大，即能耗较小，发射总功率最小，保证了较低的能耗和运营成本的情况下，满足更多的用户需求，提高服务质量，降低运营成本。
需要说明的是，对于前述的各方法实施例，为了简单描述，故将其都表述为一系列的动作组合，但是本领域技术人员应该知悉，本发明并不受所描述的动作顺序的限制，因为依据本发明，某些步骤可以采用其他顺序或者同时进行。其次，本领域技术人员也应该知悉，说明书中所描述的实施例均属于优选实施例，所涉及的动作和模块并不一定是本发明所必须的。
根据本发明实施例的又一方面，还提供了过无线访问接入点部署装置，请参考附图4，图4是根据本发明实施例的一种可选的无线访问接入点部署装置的结构示意图。如图4所示，该装置包括：
预估单元401，设置为预估目标区域内待部署的无线访问接入点的第一数量；
部署单元402，设置为基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点，以使在满足预设部署策略时所述目标区域内的所述第一数量个无线访问接入点的平均能源效率最大和/或发射总功率最小。
在本申请实施例中，首先，预估目标区域内待部署的无线访问接入点的第一数量；基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点，以使在满足预设部署策略时所述目标区域内的所述第一数量个无线访问接入点的平均能源效率最大和/或发射总功率最小。采用上述技术方案，可以在部署时，满足预设部署策略，以使的多个无线访问接入点的平均能源效率最大和/或发射总功率最小，保证了较低的能耗和运营成本的情况下，满足更多的用户需求，提高服务质量，降低运营成本。例如：在部署时应以当前区域内分布人数来设计无线访问接入点容量限制，要求所有无线访问接入点服务用户的总数应大于或等于当前区域内的总人数。当区域内95％用户都达到服务速率要求时，在接入点服务用户过程中，限定无线访问接入点的最大发射功率，并规定每个无线访问接入点的发射功 率都不能高于该阈值。而且本申请采用多目标粒子群算法，其收敛速度快，效率高，且有很多措施可以避免陷入局部最优，可以很快的达到无线访问接入点的平均能源效率最大和/或发射总功率最小的目的。
作为一种可选的方案，所述预估单元401，具体设置为：获取每个无线访问接入点对应的第二数量，所述第二数量为所述无线访问接入点允许接入的终端设备的最大数量；获取目标区域内所述终端设备的总数量；根据所述第二数量和所述总数量，预估所述第一数量。
作为一种可选的方案，所述预估单元401，具体设置为：获取每个无线访问接入点的覆盖范围，所述覆盖范围为所述无线访问接入点允许所述终端设备接入的距离范围；获取目标区域的区域范围根据所述每个无线访问接入点的覆盖范围和所述区域范围，预估所述第一数量。
作为一种可选的方案，所述预估单元401，具体设置为：获取每个无线访问接入点对应的第三数量，所述第三数量为所述无线访问接入点允许接入所述终端设备的最大数量；获取目标区域内所述终端设备的总数量；获取每个无线访问接入点的覆盖范围，所述覆盖范围为无线访问接入点允许终端设备接入的距离范围；根据所述第三数量、所述总数量以及所述每个无线访问接入点的覆盖范围，预估目标区域内等待部署的无线访问接入点的数量。
作为一种可选的方案，所述部署单元402，具体设置为：初始化所述每个无线访问接入点的位置变量和速度变量，并确定所述每个无线访问接入点对应的目标函数；基于所述多目标粒子群算法，迭代更新所述每个无线访问接入点的位置变量和速度变量，以使所述第一数量个无线访问接入点满足预设部署策略；根据更新后的位置变量和更新后速度变量，在目标区域内部署所述第一数量个无线访问接入点。
作为一种可选的方案，所述预设部署策略包括以下策略中的一个或多个：所述策略为所述第一数量个无线访问接入点服务的用户总数大于目标区域内用户的总数；所述策略为所述第一数量个无线访问接入点覆盖的终端设备的总数量大于或等于第一预设阈值，所述第一预设阈值与目标区域 内所有终端设备数量对应；所述策略为所述第一数量个无线访问接入点中每个无线访问接入点的发射功率小于最大预设发射阈值。
作为一种可选的方案，所述装置，还包括：消除单元403，设置为基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点之后基于贪婪算法，取消所述第一数量个无线访问接入点中的目标无线访问接入点的部署，所述目标无线访问接入点为不改变所述第一数量个无线访问接入点的总容量、所述第一数量个无线访问接入点的总覆盖范围和/或所述第一数量个无线访问接入点的传输功率。
根据本发明的实施例的又一方面，还提供了一种计算机可读的存储介质，该计算机可读的存储介质中存储有计算机程序，其中，该计算机程序被设置为运行时执行上述任一项方法实施例中的步骤。
可选地，在本实施例中，上述计算机可读的存储介质可以被设置为存储设置为执行以下步骤的计算机程序：
预估目标区域内待部署的无线访问接入点的第一数量。
基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点，以使在满足预设部署策略时所述目标区域内的所述第一数量个无线访问接入点的平均能源效率最大和/或发射总功率最小。
可选地，在本实施例中，本领域普通技术人员可以理解上述实施例的各种方法中的全部或部分步骤是可以通过程序来指令终端设备相关的硬件来完成，该程序可以存储于一计算机可读存储介质中，存储介质可以包括：闪存盘、ROM(Read-Only Memory，只读存储器)、RAM(Random Access Memory，随机存取器)、磁盘或光盘等。
根据本发明实施例的又一个方面，还提供了一种设置为实施上述无线访问接入点部署的电子装置，请参考附图5，图5是根据本发明实施例的一种可选的电子装置的结构示意图，如图5所示，该电子装置包括存储器502和处理器505，该存储器502中存储有计算机程序，该处理器504被 设置为通过计算机程序执行上述任一项方法实施例中的步骤。
可选地，在本实施例中，上述电子装置可以位于计算机网络的多个网络设备中的至少一个网络设备。
可选地，在本实施例中，上述处理器可以被设置为通过计算机程序执行以下步骤：
预估目标区域内待部署的无线访问接入点的第一数量；基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点，以使在满足预设部署策略时所述目标区域内的所述第一数量个无线访问接入点的平均能源效率最大和/或发射总功率最小。
可选地，本领域普通技术人员可以理解，图5所示的结构仅为示意，电子装置也可以是智能手机(如Android手机、iOS手机等)、平板电脑、掌上电脑以及移动互联网设备(Mobile Internet Devices，MID)、PAD等终端设备。图5其并不对上述电子装置的结构造成限定。例如，电子装置还可包括比图5中所示更多或者更少的组件(如网络接口等)，或者具有与图5所示不同的配置。
其中，存储器502可设置为存储软件程序以及模块，如本发明实施例中的过温功率自动调整方法和装置对应的程序指令/模块，处理器504通过运行存储在存储器502内的软件程序以及模块，从而执行各种功能应用以及原始数据信息传输，即实现上述的过温功率自动调整方法。存储器502可包括高速随机存储器，还可以包括非易失性存储器，如一个或者多个磁性存储装置、闪存、或者其他非易失性固态存储器。在一些实例中，存储器502可进一步包括相对于处理器504远程设置的存储器，这些远程存储器可以通过网络连接至终端。上述网络的实例包括但不限于互联网、企业内部网、局域网、移动通信网及其组合。其中，存储器502具体可以但不限于设置为存储目标对象的目标高度等信息。作为一种示例，如图5所示，上述存储器502中可以但不限于包括上述过无线访问接入点部署装置中的预估单元402、部署单元404和消除单元403。此外，还可以包括但不限 于上述过温功率自动调整装置中的其他模块单元，本示例中不再赘述。
可选地，上述的传输装置506设置为经由一个网络接收或者发送数据。上述的网络具体实例可包括有线网络及无线网络。在一个实例中，传输装置506包括一个网络适配器(Network Interface Controller，NIC)，其可通过网线与其他网络设备与路由器相连从而可与互联网或局域网进行通讯。在一个实例中，传输装置506为射频(Radio Frequency，RF)模块，其设置为通过无线方式与互联网进行通讯。
此外，上述电子装置还包括：连接总线508，设置为连接上述电子装置中的各个模块部件。
在其他实施例中，上述终端或者服务器可以是一个分布式系统中的一个节点，其中，该分布式系统可以为区块链系统，该区块链系统可以是由该多个节点通过网络通信的形式连接形成的分布式系统。其中，节点之间可以组成点对点(P2P，Peer To Peer)网络，任意形式的计算设备，比如服务器、终端等电子设备都可以通过加入该点对点网络而成为该区块链系统中的一个节点。
可选地，在本实施例中，本领域普通技术人员可以理解上述实施例的各种方法中的全部或部分步骤是可以通过程序来指令终端设备相关的硬件来完成，该程序可以存储于一计算机可读存储介质中，存储介质可以包括：闪存盘、只读存储器(Read-Only Memory，ROM)、随机存取器(Random Access Memory，RAM)、磁盘或光盘等。
上述本发明实施例序号仅仅为了描述，不代表实施例的优劣。
上述实施例中的集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在上述计算机可读取的存储介质中。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在存储介质中，包括若干指令用以使得一台或多台计算 机设备(可为个人计算机、服务器或者网络设备等)执行本发明各个实施例方法的全部或部分步骤。
在本发明的上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述的部分，可以参见其他实施例的相关描述。
在本申请所提供的几个实施例中，应该理解到，所揭露的客户端，可通过其它的方式实现。其中，以上所描述的装置实施例仅仅是示意性的，例如单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，单元或模块的间接耦合或通信连接，可以是电性或其它的形式。
作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本发明各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
以上仅是本发明的优选实施方式，应当指出，对于本技术领域的普通技术人员来说，在不脱离本发明原理的前提下，还可以做出若干改进和润饰，这些改进和润饰也应视为本发明的保护范围。
工业实用性
如上所述，本发明实施例提供的一种无线访问接入点部署方法和装置、存储介质具有以下有益效果：采用多目标粒子群算法，其收敛速度快，效 率高，且有很多措施可以避免陷入局部最优，可以很快的达到无线访问接入点的平均能源效率最大和/或发射总功率最小的目的。

Claims (10)

  1. 一种无线访问接入点部署方法，包括：
    预估目标区域内待部署的无线访问接入点的第一数量；
    基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点，以使在满足预设部署策略时所述目标区域内的所述第一数量个无线访问接入点的平均能源效率最大和/或发射总功率最小。
  2. 根据权利要求1所述的方法，其中，所述预估目标区域内等待部署的无线访问接入点的第一数量，包括：
    获取每个无线访问接入点对应的第二数量，所述第二数量为所述无线访问接入点允许接入的终端设备的最大数量；
    获取目标区域内所述终端设备的总数量；
    根据所述第二数量和所述总数量，预估所述第一数量。
  3. 根据权利要求1所述的方法，其中，所述预估目标区域内等待部署的无线访问接入点的第一数量，包括：
    获取每个无线访问接入点的覆盖范围，所述覆盖范围为所述无线访问接入点允许终端设备接入的距离范围；
    获取目标区域的区域范围；
    根据所述每个无线访问接入点的覆盖范围和所述区域范围，预估所述第一数量。
  4. 根据权利要求1所述的方法，其中，所述预估目标区域内等待部署的无线访问接入点的数量，包括：
    获取每个无线访问接入点对应的第三数量，所述第三数量为所述无线访问接入点允许接入终端设备的最大数量；
    获取目标区域内所述终端设备的总数量；
    获取每个无线访问接入点的覆盖范围，所述覆盖范围为无线访问接入点允许终端设备接入的距离范围；
    根据所述第三数量、所述总数量以及所述每个无线访问接入点的覆盖 范围，预估目标区域内等待部署的无线访问接入点的数量。
  5. 根据权利要求1至4任一项中所述的方法，其中，所述基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点，包括：
    初始化所述每个无线访问接入点的位置变量和速度变量，并确定所述每个无线访问接入点对应的目标函数；
    基于所述多目标粒子群算法，迭代更新所述每个无线访问接入点的位置变量和速度变量，以使所述第一数量个无线访问接入点满足预设部署策略；
    根据更新后的位置变量和更新后速度变量，在目标区域内部署所述第一数量个无线访问接入点。
  6. 根据权利要求5所述的方法，其中，所述预设部署策略包括以下策略中的一个或多个：
    所述策略为所述第一数量个无线访问接入点服务的用户总数大于目标区域内用户的总数；
    所述策略为所述第一数量个无线访问接入点覆盖的终端设备的总数量大于或等于第一预设阈值，所述第一预设阈值与目标区域内所有终端设备数量对应；
    所述策略为所述第一数量个无线访问接入点中每个无线访问接入点的发射功率小于最大预设发射阈值。
  7. 根据权利要求1所述的方法，其中，所述基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点之后，还包括：
    基于贪婪算法，取消所述第一数量个无线访问接入点中的目标无线访问接入点的部署，所述目标无线访问接入点为不改变所述第一数量个无线访问接入点的总容量、所述第一数量个无线访问接入点的总覆盖范围和/或所述第一数量个无线访问接入点的传输功率。
  8. 一种无线访问接入点部署装置，包括：
    预估单元，设置为预估目标区域内待部署的无线访问接入点的第一数量；
    部署单元，设置为基于多目标粒子群算法，在目标区域内部署所述第一数量个无线访问接入点，以使在满足预设部署策略时所述目标区域内的所述第一数量个无线访问接入点的平均能源效率最大和/或发射总功率最小。
  9. 一种计算机可读的存储介质，所述计算机可读的存储介质包括存储的程序，其中，所述程序运行时执行上述权利要求1至7任一项中所述的方法。
  10. 一种电子装置，包括存储器和处理器，所述存储器中存储有计算机程序，所述处理器被设置为通过所述计算机程序执行所述权利要求1至7任一项中所述的方法。
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