WO2022011750A1 - 基于聚类算法的毫米波移动基站在线频谱共享方法及系统 - Google Patents

基于聚类算法的毫米波移动基站在线频谱共享方法及系统 Download PDF

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WO2022011750A1
WO2022011750A1 PCT/CN2020/105610 CN2020105610W WO2022011750A1 WO 2022011750 A1 WO2022011750 A1 WO 2022011750A1 CN 2020105610 W CN2020105610 W CN 2020105610W WO 2022011750 A1 WO2022011750 A1 WO 2022011750A1
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base station
target
target base
user
base stations
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PCT/CN2020/105610
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English (en)
French (fr)
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谢宁
李卓远
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深圳大学
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/023—Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G06F18/232—Non-hierarchical techniques
    • G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
    • G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
    • 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
    • H04W16/14—Spectrum sharing arrangements between different networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/025—Services making use of location information using location based information parameters

Definitions

  • the present disclosure relates to the technical field of wireless communication, and in particular, to a method and system for online spectrum sharing of a millimeter-wave mobile base station based on a clustering algorithm.
  • Non-Patent Document 1 discloses a spectrum sharing method in millimeter-wave cellular networks through cell association, coordination and beamforming.
  • the combined beamforming design and base station association optimization framework reduces higher multi-user interference due to spectrum sharing.
  • Non-patent document 1 Spectrum Sharing in mmWave Cellular Networks via Cell Association, Coordination, and Beamforming. Hossein Shokri-Ghadikolaei November, 2016.
  • the present disclosure is proposed in view of the above situation, and its purpose is to provide an online spectrum sharing method for millimeter-wave mobile base stations based on a clustering algorithm, which reduces the coordination overhead and computational complexity of spectrum sharing in a millimeter-wave cellular network system. system.
  • a first aspect of the present disclosure provides an online spectrum sharing method for a millimeter-wave mobile base station based on a clustering algorithm, which is a spectrum sharing method for a millimeter-wave cellular network system with multiple base stations and multiple user terminals, and is characterized in that , including: the plurality of base stations receive the position signals transmitted by each user terminal to obtain the position information of the user terminal, and determine a plurality of cluster center points based on a clustering algorithm, and then move several base stations based on the plurality of cluster center points.
  • the clustering algorithm obtains multiple initial center points based on the number of the user terminals and the number of radio frequency links of the multiple base stations, and based on the multiple initial center points, the multiple The number and location information of the user terminals and the number of radio frequency links of each base station obtain a plurality of cluster center points corresponding to the plurality of user terminals, and each of the target base stations and the corresponding user terminals respectively perform signal transmission, wherein , each cluster center point corresponds to a target base station respectively, and the multiple base stations share the spectrum with the multiple user terminals. If the user terminal moves or a new user terminal appears, the user terminal is connected by the nearest target base station.
  • the multiple target base stations remain unchanged; if the target base station adds clients, the number of radio frequency links is less than For the number of user terminals served by the target base station, the number of initial center points is increased and the multiple target base stations are re-determined based on the location information of each user terminal, the clustering algorithm and each base station.
  • multiple base stations determine multiple cluster center points based on the location information of multiple user terminals and a clustering algorithm, and then move the base station based on the multiple cluster center points to obtain multiple target base stations.
  • Signal transmission is performed between users, and multiple base stations share spectrum with multiple users. If the user terminal moves or a new user terminal appears, the user terminal is served by the target base station with the closest distance. The target base station remains unchanged. If the number of radio frequency links of the target base station is less than the number of users served by the target base station after adding the user terminal, the number of initial center points will be increased and based on the location information of each user terminal, clustering algorithm and each base station Redetermine multiple target base stations. In this case, the coordination overhead and computational complexity of spectrum sharing of the millimeter-wave cellular network system can be effectively reduced.
  • the clustering algorithm is a K-means clustering algorithm.
  • the cluster center point can be better obtained.
  • each user terminal can obtain its corresponding location information. Thereby, the location information of each user terminal can be obtained.
  • base stations other than the multiple target base stations among the multiple base stations are turned off. Thereby, it can contribute to reduction of energy consumption.
  • the multiple user terminals are divided into multiple clusters, and the number of user terminals in any one cluster does not exceed the cluster The number of RF links of the corresponding target base station. Therefore, the base station and the user terminal can work better.
  • a second aspect of the present disclosure provides an online spectrum sharing system for a millimeter-wave mobile base station based on a clustering algorithm, which is a millimeter-wave cellular network system for spectrum sharing with multiple transmitting devices and multiple user devices, and is characterized in that it includes: : The plurality of transmitting devices receive the position signals transmitted by each user device to obtain the position information of the user device, and determine a plurality of cluster center points based on a clustering algorithm, and then move a number of transmitters based on the plurality of cluster center points The device obtains multiple target transmitting devices, the clustering algorithm obtains multiple initial center points based on the number of the user devices and the number of radio frequency links of the multiple transmitting devices, and based on the multiple initial center points, The number and location information of the multiple user equipment and the number of radio frequency links of each transmitting device obtain multiple cluster center points corresponding to the multiple user equipment; wherein, each cluster center point corresponds to a target transmission device, the plurality of transmitting devices and the plurality of user devices share spectrum
  • the user device moves or a new user device appears, the user device is served by the target transmitter device with the closest distance. If the target transmitter device adds a user device, the number of radio frequency links is not less than the user device served by the target transmitter device. The number of target transmitters remains unchanged. If the number of radio frequency links of the target transmitter is less than the number of user devices served by the target transmitter, the number of initial center points is increased and based on the The location information of the user device, the clustering algorithm, and the respective transmitting devices re-determine the plurality of target transmitting devices.
  • a plurality of transmitting devices determine a plurality of cluster center points based on the location information of a plurality of user devices and a clustering algorithm, and then move the transmitting device based on the plurality of cluster center points to obtain a plurality of target transmitting devices, and each target transmits
  • the devices respectively perform signal transmission with the corresponding user devices, and the multiple transmitting devices share the spectrum with the multiple user devices. If the user device moves or a new user device appears, the user device is served by the target transmitting device with the closest distance. If the target transmitting device adds a user device, the number of radio frequency links is not less than the number of user devices served by the target transmitting device. , then the multiple target transmitters remain unchanged.
  • the number of radio frequency links after the target transmitter is added to the user terminal is less than the number of user devices served by the target transmitter, the number of initial center points is increased and based on the number of user devices.
  • the location information, clustering algorithm, and individual transmitters re-determine multiple target transmitters. In this case, the coordination overhead and computational complexity of spectrum sharing of the millimeter-wave cellular network system can be effectively reduced.
  • the clustering algorithm is a K-means clustering algorithm.
  • the cluster center point can be better obtained.
  • each user equipment can obtain its corresponding location information. Thereby, the location information of each user apparatus can be obtained.
  • the transmitting devices other than the multiple target transmitting devices among the multiple transmitting devices are turned off. Thereby, it can contribute to reduction of energy consumption.
  • the multiple user devices are divided into multiple clusters, and the number of user devices in any cluster does not exceed the cluster The number of RF links of the corresponding target transmitter.
  • the transmitting apparatus and the user apparatus can be made to work better.
  • FIG. 1 is a schematic diagram illustrating an application scenario of an online spectrum sharing method for a millimeter-wave mobile base station based on a clustering algorithm according to an example of the present disclosure.
  • FIG. 2 is a flowchart illustrating a method of determining a target base station involved in an example of the present disclosure.
  • FIG. 3 is a flowchart illustrating a method of determining a cluster center point involved in an example of the present disclosure.
  • FIG. 4 is a schematic flowchart illustrating a performance detection method for an online spectrum sharing method involved in an example of the present disclosure.
  • FIG. 5 is a waveform diagram illustrating the variation of the target total rate of the UE involved in the example of the present disclosure with the signal-to-noise ratio.
  • FIG. 6 is a waveform diagram illustrating the variation of the target total rate of the UE according to the example of the present disclosure with the number of antennas of the target base station.
  • FIG. 7 is a waveform diagram illustrating the variation of the target total rate of the UE according to the example of the present disclosure with the number of antennas of the UE.
  • FIG. 8 is a waveform diagram illustrating the variation of the K value with the number of user terminals involved in the example of the present disclosure.
  • FIG. 9 is a waveform diagram illustrating the variation of the target total rate of the UEs involved in the example of the present disclosure with the number of UEs.
  • FIG. 10 is a waveform diagram illustrating the variation of the K value with the number of radio frequency chains involved in an example of the present disclosure.
  • FIG. 11 is a waveform diagram illustrating the target total rate as a function of the number of radio frequency chains involved in an example of the present disclosure.
  • FIG. 12 is a bar graph showing the target total rate of the UE involved in the example of the present disclosure as a function of carrier frequency.
  • FIG. 13 is a bar graph showing the target total rate of the UE involved in the example of the present disclosure as a function of the UE.
  • FIG. 14 is a block diagram illustrating an online spectrum sharing system for a millimeter-wave mobile base station based on a clustering algorithm according to an example of the present disclosure.
  • the present disclosure provides a method and system for online spectrum sharing of a millimeter-wave mobile base station based on a clustering algorithm.
  • the method and system for online spectrum sharing of millimeter-wave mobile base stations based on a clustering algorithm can be applied to a millimeter-wave cellular network system, which can realize spectrum sharing in a millimeter-wave cellular network system, and can significantly reduce the millimeter-wave cellular network.
  • FIG. 1 is a schematic diagram illustrating an application scenario of an online spectrum sharing method for a millimeter-wave mobile base station based on a clustering algorithm according to an example of the present disclosure.
  • the online spectrum sharing method for millimeter-wave mobile base stations (“online spectrum sharing method” for short) is an online spectrum sharing method for a millimeter-wave cellular network system with multiple base stations and multiple users.
  • multiple target base stations (described later) among the multiple base stations can perform signal transmission with multiple corresponding UEs.
  • the base station and the UE can share spectrum and can operate on a millimeter-wave cellular network system (or "millimeter-wave cellular network").
  • the number of base stations may be multiple.
  • the number of antennas of each base station may be multiple.
  • the number of clients can be multiple.
  • the number of antennas for each UE may be multiple.
  • the location of the base station may be mobile.
  • the location of the client can be mobile.
  • the number of radio frequency links per base station may be multiple.
  • a millimeter wave cellular network system may include 4 base stations (eg, base station 101, base station 102, etc.) and 13 user terminals (eg, user terminal 200, user terminal 201, etc.).
  • one user terminal is a newly added user terminal (for example, the user terminal 212, which will be described later), and each base station may have three radio frequency lines (for example, the radio frequency link 400 and the radio frequency link 401 of the base station 101). and RF link 402).
  • the mmWave cellular network system may be in a low load state, ie N b
  • M ⁇ is the set of all UEs
  • B ⁇ is the set of all target base stations (described later)
  • is the number of all target base stations, that is, the number of base stations serving multiple UEs
  • N b represents the number of UEs serving the target base station b (that is, the target base station numbered as b).
  • a base station may refer to a device in an access network that communicates with wireless terminals over an air interface through one or more sectors.
  • the base station may be used to interconvert received air frames to IP frames, acting as a router between the wireless terminal and the rest of the access network, which may include an Internet Protocol (IP) network.
  • IP Internet Protocol
  • the base station may also coordinate attribute management of the air interface.
  • the base station may be a base station (BTS, Base Transceiver Station) in GSM or CDMA, a base station (NodeB) in WCDMA, or an evolved base station (NodeB or eNB or e-NodeB, evolutional Node) in LTE. B).
  • BTS Base Transceiver Station
  • NodeB base station
  • eNB evolved base station
  • e-NodeB evolutional Node
  • the client terminal may be a user.
  • the user may include, but is not limited to, user equipment.
  • User equipment may include, but is not limited to, smart phones, notebook computers, personal computers (Personal Computer, PC), personal digital assistants (Personal Digital Assistant, PDA), mobile Internet devices (Mobile Internet Device, MID), wearable devices (such as smart watches) , smart bracelets, smart glasses) and other electronic devices, wherein, the operating system of the user equipment may include but not limited to Android operating system, IOS operating system, Symbian (Symbian) operating system, BlackBerry (Blackberry) operating system , Windows Phone8 operating system, etc.
  • each UE can obtain its own location information, and can send a location signal containing the respective location information to the base station.
  • respective base stations may obtain respective location information. Thereby, the location information of the UE and the base station can be obtained.
  • multiple base stations can use a clustering algorithm to determine the target base station according to the location information of each UE.
  • the target base station may be a determined base station for serving multiple UEs, that is, the target base station is in a working state in a subsequent service process.
  • base stations other than the multiple target base stations among the multiple base stations may be shut down, that is, other base stations among the multiple base stations that are not target base stations may be shut down. Thereby, it can contribute to reduction of energy consumption.
  • a K-means clustering algorithm ie, an unsupervised clustering algorithm
  • multiple base stations can use the K-means clustering algorithm, the respective location information of the base stations, the location information of the user terminal, and the radio frequency chain of the base station.
  • the number of roads determines multiple cluster center points. Thereby, the cluster center point can be better obtained.
  • other clustering algorithms such as K-center point clustering algorithm, may also be selected in the implementation.
  • FIG. 2 is a flowchart illustrating a method of determining a target base station involved in an example of the present disclosure.
  • the method for determining a target base station using a clustering algorithm may include the following steps: obtaining multiple initial center points based on the number of UEs and the number of radio frequency links of the base station (step S110 ); Multiple initial center points, the number and location information of multiple user terminals, and the number of radio frequency links of each base station are obtained to obtain multiple cluster center points corresponding to multiple user terminals (step S120 ); each base station obtains multiple target base stations (step S130).
  • step S110 multiple initial center points may be obtained based on the number of UEs and the number of radio frequency links of the base station.
  • the number of UEs may not be greater than the number of radio frequency links of the corresponding base station. Therefore, the base station and the user terminal can work better.
  • the number of radio frequency links of the base station may be N r , and the base station can serve N r user terminals at the same time, that is, the base station can simultaneously perform signal transmission with N r user terminals.
  • multiple initial center points may be obtained based on the number of UEs and the number of radio frequency links of the base station.
  • the number K of initial center points can satisfy: Among them, M ⁇ represents the set of all user terminals,
  • K points may be randomly selected as initial center points.
  • K user terminals may be randomly selected and their corresponding positions may be used as initial center points.
  • the number of initial center points can be obtained as 4, where the base station is The user terminal 212 in FIG. 1 can be moved, and a new user terminal (described later) is added later. . In this case, 4 clients can be randomly selected and their positions are taken as the initial center points.
  • step S120 multiple cluster center points corresponding to the multiple user terminals can be obtained based on the multiple initial center points, the number and location information of the multiple user terminals, and the number of radio frequency links of each base station.
  • FIG. 3 is a flowchart illustrating a method of determining a cluster center point involved in an example of the present disclosure.
  • the method for determining the cluster center point in step S120 may include the following steps: taking the initial center point as the initial cluster center point (step S121 ); Clustering and dividing each client by the class center point (step S122); obtaining the center point of each cluster according to the divided clusters (step S123); judging whether the elements in each cluster are not changing (step S124) If there is a change, then the center point of each cluster is used as the initial cluster center point (step S125); If there is no change, then judge whether the number of corresponding user terminals in each cluster is not greater than the radio frequency link of any base station (step S126); if it is greater than, then increase the number of initial center points by one, and the increased initial center point can also be randomly selected (step S127); if not greater than, then use the center point of each cluster as the cluster center point (step S128).
  • the initial center point may be used as the initial cluster center point.
  • step S122 each user terminal is clustered based on the location information of each user terminal and the initial cluster center point.
  • the distance between the user terminal and each initial cluster center point may be calculated according to the location information of the user terminal.
  • each user terminal may correspond to an initial cluster center point.
  • an initial cluster center point with a smaller distance from each user terminal may be used as the corresponding initial cluster center point of the user terminal. Thereby, it is possible to perform cluster division for all the user terminals.
  • each initial cluster center point may correspond to one or more user terminals.
  • step S123 the center point of each cluster is obtained according to the divided clusters.
  • center points corresponding to each cluster may be obtained according to each cluster.
  • the center point corresponding to each cluster where, is represented as the kth cluster, It is expressed as the number of users in the kth cluster, (x MT,m ,y MT,m ) is expressed as the location information of the mth user end, and m can be the user end in the cluster.
  • elements of each cluster may include the corresponding client and center point.
  • step S124 it is determined whether the elements in each cluster are not changing.
  • the currently obtained cluster may be compared with the previously obtained cluster to determine whether the elements in each cluster are not changing, for example, it is determined that the currently obtained kth cluster corresponds to Whether the center point and the user end of , and the center point and the user end corresponding to the kth cluster obtained previously are the same. If there is a change, it can continue to step S125. If there is no change, proceed to step S126.
  • the objective function can be calculated according to the location information of the user terminal and the center point corresponding to the cluster, and the objective function satisfies:
  • (x MT,m , y MT,m ) is the location information of the mth user terminal
  • ⁇ k is the center point (or mean) corresponding to the kth cluster
  • K represents the center number of points.
  • the number of center points can be the same as the number of initial center points. It is judged by formula (2) whether the objective function corresponding to each cluster will not change significantly.
  • step S125 it can be judged whether the result of the objective function corresponding to each cluster will not change significantly by comparing the currently obtained cluster with the previously obtained cluster, for example, judging whether the currently obtained kth cluster and Whether the result of the objective function corresponding to the kth cluster obtained previously has changed significantly. If there is a significant change, step S125 can be continued. If no obvious change occurs, step S126 can be continued.
  • the present embodiment may employ a K-means clustering algorithm.
  • the goal of the K-means clustering algorithm may be to minimize the value of the objective function for all clusters, which may satisfy: In this case, each user terminal can be divided into more appropriate clusters.
  • step S125 if there is a change, that is, if the element in each cluster or the corresponding objective function changes, then step S125 can be continued, that is, the center point of each cluster is taken as the initial cluster center point. Steps S122 to S124 may be repeated thereafter. In this case, it is convenient to obtain more suitable cluster center points in the future.
  • step S126 if there is no change, that is, if the elements in each cluster or the corresponding objective function does not change, then step S126 can be continued, that is, the currently obtained number of corresponding user terminals and base stations in each cluster Compare the number of radio frequency links in each cluster, and determine whether the number of corresponding UEs in each cluster is not greater than the number of radio frequency links of any base station. If it is greater than that, then proceed to step S127. If it is not greater than that, then proceed to step S128. In step S127, if it is greater than the number of initial center points, the number of initial center points may be increased by one, and the increased initial center points may also be randomly selected.
  • the added initial center point may be selected in the same manner as the previous initial center point, for example, a UE is randomly selected and its location is used as the added initial center point. Steps S121 to S126 may be repeated after step S127 is performed. In this way, the target base station obtained subsequently can transmit signals to the corresponding user terminal at the same time.
  • step S1208 if it is not greater than that, the currently obtained center point of each cluster may be used as the cluster center point. Thereby, the cluster center point can be obtained.
  • the number of center points may be the same as the number of cluster center points.
  • the target base station may be determined in step S130 based on the plurality of cluster center points obtained in the above-mentioned step S120.
  • multiple target base stations may be obtained by moving several base stations based on multiple cluster center points.
  • several base stations may be selected from multiple base stations and moved to positions corresponding to the respective cluster center points as target base stations.
  • the number of target base stations may be the same as the number of cluster center points, that is, each cluster center point may correspond to one target base station respectively.
  • the positions of each cluster center point and any user terminal are different, several base stations are selected from the multiple base stations, and can be moved to each cluster center point as target base station.
  • 12 client terminals are divided into 4 clusters (cluster 300, cluster 310, cluster 320, cluster 330), corresponding to 4 clusters respectively
  • the center point (not shown)
  • four base stations (base station 101, base station 102, base station 103, and base station 104) are selected and moved to the positions corresponding to the four cluster center points as four target base stations.
  • the base station can be moved to the vicinity of the cluster center point as the target base station.
  • the base station may be moved to a location within ten meters (eg, one meter away) of the cluster center point. Thereby, several base stations can be moved to obtain multiple target base stations.
  • the base station 101 , the base station 102 , the base station 103 , and the base station 104 may be moved to positions corresponding to the center points of each cluster as the target base stations, respectively.
  • a clustering algorithm may be utilized to divide the plurality of clients into a plurality of clusters, wherein each cluster may contain one or more clients.
  • each cluster may correspond to a target base station.
  • 12 client terminals can be divided into 4 clusters, wherein cluster 300 can include client 200, client 201, and client 202, and cluster 310 can include client 203, user For client 204 and client 205, cluster 320 may include client 206, client 207, and client 208, and cluster 330 may include client 209, client 210, and client 211.
  • the number of radio frequency links of the target base station corresponding to each cluster may not be less than the number of UEs in the cluster.
  • the target base station may simultaneously signal with the UEs in the corresponding cluster.
  • the cluster 300 includes a target base station (ie, base station 101 ), a user terminal 200, a user terminal 201 and a user terminal 202, wherein the number of radio frequency links of the base station 101 is 3, and the number of user terminals served by the base station 101 is less than or Equal to the number of radio frequency links of the base station 101 , the base station 101 can simultaneously transmit signals to its corresponding UEs (ie, UE 200 , UE 201 , and UE 202 ).
  • an existing user terminal may be moved or a new user terminal (eg, the user terminal 212 in FIG. 1 ) may be moved, and the corresponding user terminal may be determined based on the location information of the user terminal and each cluster center point.
  • Clustering so as to determine the target base station corresponding to the user terminal.
  • the cluster corresponding to the user terminal can be determined according to the distance between the user terminal and each cluster center point, thereby determining the target base station corresponding to the cluster, and the user terminal can be served by the target base station.
  • the cluster corresponding to the cluster center point closest to the user terminal may be used as the cluster corresponding to the user terminal. For example, by Obtain the cluster center point with the smallest distance from the user terminal m among the multiple cluster center points, thereby obtaining the cluster corresponding to the user terminal m, that is, the target base station corresponding to the cluster can serve the user terminal.
  • the target base station (the target base station closest to the mobile or new user terminal) increases the number of radio frequency links after the user terminal is added, the number of radio frequency links is not less than the number of user terminals currently corresponding to the target base station, then the current aggregation may not be changed. class, that is, the existing target base station can be maintained (that is, the determined multiple target base stations can be unchanged). In some examples, if the number of radio frequency links of the target base station is less than the number of UEs currently corresponding to the target base station, the current cluster may be changed, and the target base station may be re-determined. For example, as shown in FIG.
  • a new user terminal eg, user terminal 212
  • the user terminal 212 is closest to the target base station (base station 103 )
  • the number of radio frequency links of the base station 103 is 3 (for example, the radio frequency link 403, the radio frequency link 404, the radio frequency link 405), and at this time, the number of users corresponding to the target base station (the base station 103) is 4 (for example, the user terminal 206, user terminal 207, user terminal 208, and user terminal 212), the current clustering can be changed, that is, the target base station can be re-determined, so that the base station and the user terminal can work better normally.
  • multiple new cluster center points may be determined based on the clustering algorithm and the location information of each user terminal, and then the mobile base station may re-determine the target base station. That is to say, if an existing user terminal is moved or a new user terminal is added, so that the number of radio frequency links corresponding to the target base station is smaller than the number of user terminals corresponding to the target base station, the number of initial center points can be increased.
  • the target base station may be re-determined based on the clustering algorithm.
  • the cluster center point can be determined according to the clustering algorithm and the location information of the user terminal.
  • each base station can receive the location information of the user terminal and can determine the cluster center point through a clustering algorithm.
  • the coordination overhead can be effectively reduced.
  • the computational complexity of the base station can be determined according to a clustering algorithm, wherein each iteration of the clustering algorithm can be divided into three types to obtain the computational complexity: (1) In step S124, the computational complexity can be obtained by formula (2) to determine whether the objective function has changed significantly. Among them, 5 operations are required for one user terminal, then for all user terminals operations.
  • step S122 the user terminals may be clustered according to the location information of the user terminals and the initial clustering center point, wherein, for all the user terminals required operations.
  • step S123 the center point of each cluster can be obtained by formula (1), wherein, for all clusters, it is necessary to operations.
  • the user terminal can be moved or a new user terminal can be added, and the target base station corresponding to the user terminal can be determined by comparing the distances between the user terminal and each cluster center point. Wherein, K operations are required for the user terminal.
  • multiple target base stations may be obtained by moving the base station according to the cluster center point, and several base stations may be selected from the multiple base stations and moved to positions corresponding to each cluster center point as the target base station.
  • T 1 is assumed clustering algorithm iteration in step S125, the T 2 iterations performed in step S127, the can be obtained to determine the total number of calculations by the target base station of the present disclosure.
  • the total number of operations can satisfy: In this case, the computational complexity of the base station can be effectively reduced.
  • all base stations and UEs (including newly added UEs) need to be updated. the user end) re-clustering and re-determining the target base station (that is, re-determining a new target base station).
  • step S127 may be re-entered to re-determine the target base station based on the clustering algorithm.
  • the total number of operations can satisfy: (4). It can be seen from this that the present embodiment can effectively reduce the computational complexity of the base station.
  • the online spectrum sharing method may include that multiple base stations may determine one or more target base stations based on a clustering algorithm, location information of each user terminal, etc.; the target base station may perform signal transmission with the corresponding user terminals; The target base station can share spectrum with the user terminal, etc.
  • performance testing may be performed for the online spectrum sharing method described above.
  • FIG. 4 is a schematic flowchart illustrating a performance detection method for an online spectrum sharing method involved in an example of the present disclosure.
  • the performance detection method may include the following steps: each target base station transmits a signal to a corresponding user terminal through several paths, the signal obtains a second signal through a wireless channel, and the user terminal receives the second signal, Based on the corresponding target base station, the user terminal and the channel state information, the signal matrix, the combined weight vector and the precoding weight vector between the target base station and the user terminal are obtained (step S10); based on the combined weight vector, the precoding weight vector, the signal The matrix and the average transmission power of the target base station obtain the interference signal and the target signal, and then obtain the average rate at which the user terminal receives the second signal based on the noise signal and the bandwidth of the shared spectrum (step S20); The corresponding relationship between each target base station and the user terminal obtains the total rate of the user terminal, and the total rate of each user terminal is summed to obtain the target total rate, and then the performance of the millimeter wave cellular network system is detected based on the target total rate (step S30).
  • each target base station can transmit signals to the corresponding user terminal through several paths, the signal obtains the second signal through the wireless channel, the user terminal receives the second signal, and obtains the second signal based on the corresponding target base station, the user terminal and the channel state information Signal matrix, combined weight vector and precoding weight vector between the target base station and the UE.
  • each target base station transmits a signal to the corresponding user terminal through several paths, and the signal obtains a second signal through a wireless channel.
  • the second signal includes the target signal, the interference signal and the noise signal.
  • the location information and channel state information of the target base station and the user terminal obtain the angle of arrival and departure angle corresponding to several paths, and based on the number of antennas of the target base station and the number of antennas of the user terminal, the steering vector of the angle of arrival and the steering vector of the departure angle are obtained, Based on the number of paths between the target base station and the user terminal, the channel gain corresponding to each path, the number of antennas of the target base station and the number of antennas of the user terminal, the signal matrix between the target base station and the user terminal is obtained.
  • the number of links, the angle of arrival of the target path, and the guidance vector of the angle of arrival of the target path obtain the combined weighting vector between the target base station and the user terminal, and obtain the combined weighting vector and signal matrix based on the combined weighting vector and the signal matrix between the target base station and the user terminal
  • the precoding weight vector between the target base station and the UE obtain the combined weighting vector between the target base station and the user terminal.
  • the target base station may share spectrum with the UE.
  • the target base station and the UE may share a frequency band with a bandwidth of W.
  • the target base station and the UE may obey independent Poisson distributions in the same area.
  • each target base station may transmit signals to the corresponding user terminal through several paths, that is, the target base station is associated with the user terminal.
  • the user terminal is in the cluster corresponding to the target base station.
  • the target base station does not transmit signals to UEs in other clusters other than the corresponding cluster, that is, the target base station is not associated with the UEs.
  • a binary variable can be used to represent the association state of the target base station and the UE.
  • the number of paths between each target base station and the corresponding UE may be one or more.
  • the target base station can transmit signals to the corresponding UE through any path.
  • each path may correspond to the same or different channel gains.
  • the channel gain of the lth path is denoted as h bml .
  • the channel gain may be assumed to be a complex Gaussian random variable with zero mean and satisfy in, is the distance-dependent large-scale lognormal path fading, can satisfy where ⁇ d is the path loss index, satisfying ⁇ d ⁇ 2.
  • d bm is the distance between the base station b and the mobile terminal m
  • c 3 ⁇ 10 8 m/s
  • f c is the carrier frequency of the signal.
  • the number of antennas of the target base station may be one or more.
  • the number of antennas of the target base station may be N BS
  • the number of antennas of the UE may be one or more.
  • the number of antennas at the UE may be N MT .
  • the signal obtains the second signal via the wireless channel, and the UE can receive the second signal.
  • the angle of arrival and the angle of departure respectively corresponding to several paths may be obtained based on the location information and channel state information of the corresponding target base station, the UE.
  • the angle of arrival and the angle of departure may be determined by the target base station, the spatial distribution of the UE, and the scattering in the communication environment.
  • the spatial distribution of the target base station and the user terminal may be obtained from the location information of the target base station and the user terminal. Scattering in the communication environment can be obtained from channel state information.
  • the angle of arrival and the angle of departure can be independent random variables that follow a uniform distribution [0, 2 ⁇ ].
  • the arrival angle and departure angle of the lth path between the target base station b and the user terminal m can be expressed as ⁇ MT,bml and ⁇ BS,bml respectively
  • the target base station and the user terminal can obey an independent homogeneous Poisson point process , where ⁇ MT,bml and ⁇ BS,bml can be independent random variables that follow a uniform distribution [0,2].
  • the UE may obtain the steering vector of the angle of arrival and the steering vector of the departure angle based on the number of antennas of the target base station and the number of antennas of the UE.
  • the steering vector for the angle of arrival may satisfy: (5), wherein, the angle of arrival ⁇ MT, bml can be substituted into, thus the guidance vector of the angle of arrival of the lth path between the target base station b and the user terminal m can be obtained, and the guidance vector of the departure angle can satisfy:
  • the departure angle ⁇ BS,bml can be substituted into, so that the guidance vector of the departure angle of the 1 th path between the target base station b and the user terminal m can be obtained.
  • the user terminal may obtain the signal between the target base station and the user terminal based on the number of paths between the target base station and the user terminal, the channel gain corresponding to each path, the number of antennas of the target base station and the number of antennas of the user terminal matrix.
  • the signal matrix between the target base station b and the mobile terminal m can satisfy:
  • the UE may obtain a combined weighting vector between the target base station and the UE based on the number of radio frequency links of the target base station, the angle of arrival of the target path, and the guidance vector of the angle of arrival of the target path.
  • the UE may obtain the precoding weight vector between the target base station and the UE based on the combined weight vector and the signal matrix between the target base station and the UE.
  • the number of radio frequency links of the target base station may be one or more.
  • the number of radio frequency links of the target base station may be N r , that is, the target base station may transmit signals to N r users simultaneously at most. If the number of UEs corresponding to the target base station is greater than the number of radio frequency links, the target base station will be overloaded and cause problems with the target base station.
  • the number of radio frequency links of each target base station may be only one, and each UE can obtain an accurate angle of arrival.
  • the user terminal m can obtain the accurate arrival angle ⁇ MT,bml of the l-th path.
  • the target path may be the path with the largest channel gain among several paths between the target base station and the UE. Therefore, it is convenient to obtain the combined weighting vector between the user terminal and the base station subsequently.
  • a combined weight vector between the target base station b and the user terminal m can be obtained based on the formula (5).
  • the combined weight vector w MT,bm can satisfy: in, It is expressed as the angle of arrival corresponding to the path l* (that is, the target path) with the largest channel gain.
  • the precoding weight vector w BS,bm between the target base station b and the UE m may satisfy
  • the user terminal may obtain the interference signal and the target signal based on the combined weighting vector, the precoding weighting vector, the signal matrix, and the average transmission power of the target base station, and then obtain the second receiving second signal based on the noise signal and the bandwidth of the shared spectrum.
  • the average rate of the signal may be obtained by the user terminal.
  • the user terminal may obtain the interference signal and the target signal based on the signal matrix, the combined weight vector, the precoding weight vector, and the corresponding average transmission power of the target base station.
  • the user terminal may obtain an average rate at which the user terminal receives the second signal based on the interference signal, the target signal, the noise signal, and the bandwidth of the shared spectrum between the target base station and the user terminal.
  • the target base station may transmit a signal to the corresponding UE.
  • the signal can obtain the second signal via the wireless channel.
  • the user terminal can receive the second signal.
  • the second signal may include an interference signal, a target signal and a noise signal.
  • the UE may obtain the target signal received by the UE based on the signal matrix, the combined weight vector, the precoding weight vector and the average transmission power of the target base station between the UE and the corresponding target base station.
  • the average transmission power of the target base station b can be P BS , and normalizing the average transmission power can satisfy: (9), when the target base station b transmits a signal to the user terminal m, the target signal received by the user terminal can be obtained based on equations (6) to (9), which can satisfy:
  • multiple target base stations in the working state may correspond to the same operator or correspond to multiple operators.
  • any target base station may correspond to one operator.
  • Multiple UEs may correspond to the same operator or correspond to multiple operators.
  • any user terminal may correspond to one operator.
  • multiple target base stations may correspond to z operators.
  • any target base station may serve one or more UEs.
  • the target base station b may serve multiple UEs.
  • the set of all UEs served by the target base station b can be represented as A b .
  • any target base station can transmit signals to multiple UEs simultaneously.
  • the user terminal may receive the second signal.
  • the interference signal in the second signal may include a first interference signal generated by the same target base station transmitting signals to other corresponding user terminals and a second interference signal generated by other target base stations of the same operator transmitting signals to their corresponding user terminals.
  • the first interference signal can satisfy:
  • the second interference signal can satisfy:
  • the third interference signal can satisfy:
  • the user terminal may receive the second signal, the noise signal in the second signal may be a complex Gaussian variable with zero mean, and the noise signal in the second signal may satisfy: in, is the variance.
  • the average rate R bm at which the user terminal m receives information (eg, the second signal) from the target base station b can be obtained according to equations (10) to (14), Can satisfy:
  • W can be expressed as the shared bandwidth when the target base station and the user end share the spectrum, can be the signal-to-interference noise ratio.
  • the user terminal may obtain the total rate of the user terminal based on the average rate, the multiple target base stations and the corresponding relationship between the multiple target base stations and the user terminal, and the total rate of each user terminal is summed to obtain the target total rate, and then based on the target total rate Check the performance of mmWave cellular network systems.
  • the target base station b transmits a signal to the user terminal m
  • the target base station b corresponds to the zth operator
  • the formula ( 15) The total rate at which the user terminal m receives information (for example, the second signal) from all target base stations corresponding to the operator z can be obtained, and the total rate R m can satisfy:
  • the user terminal can receive the signal transmitted by the corresponding target base station in the corresponding operator, and the total target rate can be obtained by summing the total rates corresponding to all the user terminals, and the target total rate R ⁇ can satisfy: Thereby, the target total rate can be obtained, and the performance of the target base station and the user-end spectrum sharing (ie, the millimeter-wave cellular network system) can be detected according to the target total rate (described later).
  • Fig. 5 to Fig. 12 by analyzing the curve of the target total rate of the user terminal with different system parameters by analyzing the present disclosure and the conventional solution (ie the solution disclosed in Non-Patent Document 1) Detect the performance of the millimeter-wave cellular network system, where A is the variation curve (or histogram) of the target total rate of the user terminal of the traditional scheme with different system parameters, and B is the target total rate of the user terminal of the present disclosure with different system parameters.
  • the number of radio frequency links of each user terminal is one, that is, each user terminal can only receive information sent by one target base station.
  • FIG. 5 is a waveform diagram illustrating the variation of the target total rate of the UE involved in the example of the present disclosure with the signal-to-noise ratio.
  • the signal-to-noise ratio satisfies
  • the distribution frequency of mobile terminals is There are 100 per square kilometer
  • the total target rate of the UE of the present disclosure and the traditional solution increases with the increase of the signal-to-noise ratio, and it is linear
  • the scheme of the present disclosure has better performance. For example, when the total rate reaches 10 ⁇ 2 bits/s/Hz, the required signal-to-noise ratio of the scheme of the present disclosure is 19 dB lower than that of the traditional scheme.
  • FIG. 6 is a waveform diagram illustrating the variation of the target total rate of the UE according to the example of the present disclosure with the number of antennas of the target base station.
  • FIG. 7 is a waveform diagram illustrating the variation of the target total rate of the UE according to the example of the present disclosure with the number of antennas of the UE.
  • the signal-to-noise ratio is 30dB
  • the distribution frequency of mobile terminals is 100 per square kilometer
  • the target total rate of the UE in the present disclosure and the conventional solution both increases with the increase of the number of antennas of each target base station, and increases in a logarithmic form.
  • the number of antennas of the target base station required by the scheme of the present disclosure is less than that of the traditional scheme, that is, the scheme of the present disclosure has better performance.
  • the signal-to-noise ratio is 30dB
  • the distribution frequency of mobile terminals is 100 per square kilometer
  • the solution of the present disclosure requires fewer antennas at the UE than the traditional solution, that is, the solution of the present disclosure has better performance. According to Fig. 6 and Fig.
  • the target total rate increases as the number of N BS or N MT increases, because with the increase of the number of antennas, the gain of the antenna increases and the interfering signal decreases, wherein the target total rate is equal to
  • the increase in the number form shows that under the signal-to-interference-noise ratio, adding more antenna elements has little effect on improving the target total rate.
  • the total bandwidth can be increased or parallel data can be transmitted for the client side, thereby further increasing the target total rate.
  • the increase in the number of antennas at each UE has a greater impact on the target total rate than the increase in the number of antennas at each target base station. In order to achieve the same target total rate, more antennas need to be added at the target base station than at the UE.
  • the size and power of the UE has more constraints than the target base station.
  • FIG. 8 is a waveform diagram illustrating the variation of the K value with the number of user terminals involved in the example of the present disclosure.
  • FIG. 9 is a waveform diagram illustrating the variation of the target total rate of the UEs involved in the example of the present disclosure with the number of UEs.
  • the signal-to-noise ratio is 30dB
  • the number of radio frequency links of each target base station is 5.
  • A is a waveform diagram of the K value changing with the number of UEs in the solution of the present disclosure, wherein the K value increases with the increase of the number of UEs and increases linearly. In this case, it is helpful to predict the number of target base stations required by the scheme of the present disclosure.
  • the target total rate of the UEs of the present disclosure and the conventional solution both increases with the increase of the number of UEs, and increases logarithmically.
  • the solution of the present disclosure requires less user terminals than the traditional solution, that is, the solution of the present disclosure has better performance. It can be seen from Figure 9 that as the number of UEs increases, the target total rate of the two schemes increases in logarithmic form, because increasing the number of UEs has a greater contribution to the target total rate, but at the same time it will also increase the interference signal. .
  • FIG. 10 is a waveform diagram illustrating the variation of the K value with the number of radio frequency chains involved in an example of the present disclosure.
  • FIG. 11 is a waveform diagram illustrating the target total rate as a function of the number of radio frequency chains involved in an example of the present disclosure.
  • the signal-to-noise ratio is 30dB
  • the distribution frequency of mobile terminals is per square kilometer. 100.
  • A is a waveform diagram of the variation of K value with the number of radio frequency links in the scheme of the present disclosure, wherein the K value decreases with the increase of the number of radio frequency links of each target base station small. In this case, the number of target base stations required by the scheme of the present disclosure can be reduced.
  • the target total rate of the UE of the present disclosure and the conventional solution decreases with the increase of the number of radio frequency links of each target base station, wherein the solution of the present disclosure is more affected big. It can be seen from FIG. 10 and FIG. 11 that as the number of radio frequency links of each target base station increases, the number of base stations can be reduced, but the interference signal increases, resulting in a decrease in the total target rate.
  • FIG. 12 is a bar graph showing the target total rate of the UE involved in the example of the present disclosure as a function of carrier frequency.
  • the signal-to-noise ratio is 30dB
  • the distribution frequency of mobile terminals is 100 per square kilometer
  • the target total rate of the UE of the present disclosure and the conventional solution both decreases with the increase of the carrier frequency.
  • FIG. 13 is a bar graph showing the target total rate of the UE involved in the example of the present disclosure as a function of the UE.
  • A is the target total rate corresponding to the scheme of the present disclosure when no new user terminal is added
  • B is the target total rate corresponding to the scheme of the present disclosure when a new user terminal is added at any time.
  • the location of the user terminal and other user terminals may not change. Except for the different number of users, other parameters can be the same as in Figure 9.
  • a and B are the histograms of the total target rate corresponding to the number of users per square kilometer being 50, 51, and 52, respectively. It can be seen from FIG.
  • the target total rate is the same when a new user terminal is added at any time and when no new user terminal is added, that is, the new user terminal added at any time of the present disclosure can have the same performance as when no new user terminal is added. . And as the number of clients increases, the target total rate increases.
  • the present embodiment has better performance than the traditional solution, and can also reduce the computational complexity and coordination overhead of the base station when determining the target base station. Therefore, according to the present disclosure, it is possible to provide an online spectrum sharing method for millimeter-wave mobile base stations based on a clustering algorithm that reduces the coordination overhead and computational complexity of spectrum sharing in a millimeter-wave cellular network system.
  • the present disclosure relates to an online spectrum sharing system for a millimeter-wave mobile base station based on a clustering algorithm.
  • the millimeter-wave mobile base station online spectrum sharing system is a millimeter-wave cellular network system including multiple transmitting devices and multiple user devices.
  • the transmitting device in the online spectrum sharing system of the millimeter-wave mobile base station can be analogous to the above-mentioned base station, and the user device can be analogous to the above-mentioned user terminal.
  • FIG. 14 is a block diagram illustrating a clustering algorithm-based millimeter-wave mobile base station online spectrum sharing system 1 involved in an example of the present disclosure.
  • the millimeter-wave mobile base station online spectrum sharing system 1 may include multiple transmitting devices and multiple user devices.
  • multiple target transmitting apparatuses eg, transmitting apparatus 10, transmitting apparatus 11
  • transmitting device and the user device may share spectrum and operate on a mmWave cellular network.
  • a plurality of transmitting devices may receive a location including location information transmitted by various user devices (eg, user device 20, user device 21, user device 22, user device 23)
  • the signal obtains the location information of the user equipment, and determines multiple cluster center points based on the clustering algorithm, and then moves several base stations as target base stations (eg, transmitter 10, transmitter 11) based on the multiple cluster centers.
  • the clustering algorithm may include obtaining a plurality of initial center points based on the number of user devices and the number of radio frequency links of the transmitting devices.
  • the clustering algorithm may obtain multiple cluster center points corresponding to the multiple user equipments based on the multiple initial center points, the number and location information of the multiple user equipments, and the number of radio frequency links of each transmitting equipment.
  • each cluster center point corresponds to a target transmitting device respectively, and multiple transmitting devices and multiple user devices share spectrum.
  • For the acquisition of the target launch device reference may be made to the above steps S110 to S130.
  • each transmitting device can receive the position signal transmitted by the user device to obtain the position information of the user device, and the cluster center point can be determined through a clustering algorithm. Thereby, the coordination overhead can be effectively reduced.
  • the specific process refer to the above-mentioned online spectrum sharing method.
  • an existing user device may be moved or a new user device may be added.
  • the target transmitting device corresponding to the user device is determined by calculating the distance between the user device and each cluster center point, wherein , the cluster center point corresponding to the target transmitting device may have the smallest distance from the user device.
  • the current clustering may not be changed, that is, the existing target transmitting device may be maintained. device.
  • the current cluster can be changed, and the target transmitting device can be re-determined, that is, a new one can be re-determined.
  • Target launcher For the specific process, refer to the above-mentioned online spectrum sharing method. .
  • the total number of operations required by the launcher to determine the target launcher in different situations can be obtained from equations (3) and (4). Computational complexity.
  • transmitters other than the plurality of target transmitters of the plurality of transmitters may be turned off. Thereby, it can contribute to reduction of energy consumption.
  • the online spectrum sharing system 1 for the millimeter-wave mobile base station can perform performance detection on it as the above-mentioned online spectrum sharing method.
  • the solution of the present disclosure has better performance than the traditional solution, and can also reduce the computational complexity and coordination overhead of the transmitting device when determining the target transmitting device. Therefore, according to the present disclosure, an online spectrum sharing system 1 of a millimeter-wave mobile base station based on a clustering algorithm can be provided, which reduces the coordination overhead and computational complexity of spectrum sharing of a millimeter-wave cellular network system.

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Abstract

本公开涉及一种基于聚类算法的毫米波移动基站在线频谱共享方法，其包括：多个基站基于多个用户端的位置信息和聚类算法确定多个聚类中心点，进而基于多个聚类中心点移动基站获得多个目标基站，各个目标基站分别与对应的用户端之间进行信号传输，多个基站与多个用户端频谱共享，若用户端移动或出现新的用户端，则该用户端由距离最近的目标基站服务，若该目标基站增加用户端后射频链路的数量不小于该目标基站服务的用户端的数量，则多个目标基站不变，若该目标基站增加用户端后射频链路的数量小于该目标基站服务的用户端的数量，则将初始中心点的数量增加并重新确定目标基站。由此能够有效地减小毫米波蜂窝网系统的频谱共享的协调开销和计算复杂度。

Description

基于聚类算法的毫米波移动基站在线频谱共享方法及系统 技术领域
本公开涉及无线通信技术领域，具体涉及一种基于聚类算法的毫米波移动基站在线频谱共享方法及系统。
背景技术
在现代无线通信中，频谱资源作为非可再生资源，非常宝贵。在传统通信协议中的频谱资源的分配是独占且专用的，为了提高频谱利用率，出现了频谱共享技术，即允许多个网络运营商访问相同的频谱资源。毫米波蜂窝网系统的工作频率达到了10-300GHz，相对于传统电磁波具有超大带宽，可以大幅度解决频谱资源紧张的问题。在现有技术中可以利用毫米波蜂窝网系统实现频谱共享，毫米波蜂窝网系统的频谱共享是指允许多个网络运营商访问相同的频谱资源。
目前，已有科研团队实现了毫米波蜂窝网系统的频谱共享，例如非专利文献1公开了一种通过小区关联、协调和波束成形在毫米波蜂窝网中进行频谱共享，其通过提出一种基于联合波束成形设计和基站关联的优化框架，减小了因频谱共享所导致的更高的多用户干扰。
然而，在上述现有技术中，毫米波蜂窝网系统的频谱共享往往存在两个问题：(1)多个基站之间交换大量信息会导致非常高的协调开销；(2)寻找多个基站的最优预编码加权矩阵的计算复杂度很高。
[参考文献]
非专利文献1：Spectrum Sharing in mmWave Cellular Networks via Cell Association,Coordination,and Beamforming.Hossein Shokri-Ghadikolaei November,2016。
发明内容
本公开是有鉴于上述的状况而提出的，其目的在于提供一种减小毫米波蜂窝网系统的频谱共享的协调开销和计算复杂度的基于聚类算法的毫米波移动基站在线频谱共享方法及系统。
为此，本公开的第一方面提供了一种基于聚类算法的毫米波移动基站在线频谱共享方法，是具有多个基站和多个用户端的毫米波蜂窝网系统的频谱共享方法，其特征在于，包括：所述多个基站接收各个用户端发射的位置信号以获得用户端的位置信息，并基于聚类算法确定多个聚类中心点，进而基于所述多个聚类中心点移动若干个基站获得多个目标基站，所述聚类算法基于所述用户端的数量和所述多个基站的射频链路的数量获得多个初始中心点，并基于所述多个初始中心点、所述多个用户端的数量与位置信息以及各个基站的射频链路的数量获得与所述多个用户端对应的多个聚类中心点，各个所述目标基站分别与对应的用户端之间进行信号传输，其中，各个聚类中心点分别对应一个目标基站，所述多个基站和所述多个用户端频谱共享，若所述用户端移动或出现新的用户端，则该用户端由距离最近的目标基站服务，若该目标基站增加用户端后射频链路的数量不小于该目标基站服务的用户端的数量，则所述多个目标基站不变，若该目标基站增加用户端后射频链路的数量小于该目标基站服务的用户端的数量，则将初始中心点的数量增加并基于所述各个用户端的位置信息、所述聚类算法和所述各个基站重新确定所述多个目标基站。
在本公开中，多个基站基于多个用户端的位置信息和聚类算法确定多个聚类中心点，进而基于多个聚类中心点移动基站获得多个目标基站，各个目标基站分别与对应的用户端之间进行信号传输，多个基站与多个用户端频谱共享。若用户端移动或出现新的用户端，则该用户端由距离最近的目标基站服务，若该目标基站增加用户端后射频链路的数量不小于该目标基站服务的用户端的数量，则多个目标基站不变，若该目标基站增加用户端后射频链路的数量小于该目标基站服务的用户端的数量，则将初始中心点的数量增加并基于各个用户端的位置信息、聚类算法和各个基站重新确定多个目标基站。在这种情况下，能够有效地减小毫米波蜂窝网系统的频谱共享的协调开销和计算复杂度。
本公开的第一方面所涉及的毫米波移动基站在线频谱共享方法中，可选地，所述聚类算法为K均值聚类算法。由此，能够更好地获得聚类中心点。
本公开的第一方面所涉及的毫米波移动基站在线频谱共享方法中，可选地，各个用户端均能获得各自对应的位置信息。由此，能够获得各个用户端的位置信息。
本公开的第一方面所涉及的毫米波移动基站在线频谱共享方法中，可选地，将所述多个基站中的所述多个目标基站外的基站关闭。由此，能够有助于降低能量的消耗。
本公开的第一方面所涉及的毫米波移动基站在线频谱共享方法中，可选地，所述多个用户端划分为多个聚类，任一聚类中的用户端数量不超过该聚类对应的目标基站的射频链路的数量。由此，能够使基站和用户端更好地工作。
本公开的第二方面提供了一种基于聚类算法的毫米波移动基站在线频谱共享系统，是具有多个发射装置和多个用户装置的频谱共享的毫米波蜂窝网系统，其特征在于，包括：所述多个发射装置接收各个用户装置发射的位置信号以获得用户装置的位置信息，并基于聚类算法确定多个聚类中心点，进而基于所述多个聚类中心点移动若干个发射装置获得多个目标发射装置，所述聚类算法基于所述用户装置的数量和所述多个发射装置的射频链路的数量获得多个初始中心点，并基于所述多个初始中心点、所述多个用户装置的数量与位置信息以及各个发射装置的射频链路的数量获得与所述多个用户装置对应的多个聚类中心点；其中，各个聚类中心点分别对应一个目标发射装置，所述多个发射装置和所述多个用户装置频谱共享。若所述用户装置移动或出现新的用户装置，则该用户装置由距离最近的目标发射装置服务，若该目标发射装置增加用户装置后射频链路的数量不小于该目标发射装置服务的用户装置的数量，则所述多个目标发射装置不变，若该目标发射装置的射频链路的数量小于该目标发射装置服务的用户装置的数量，则将初始中心点的数量增加并基于所述各个用户装置的位置信息、所述聚类算法和所述各个发射装置重新确定所述多个目标发射装置。
在本公开中，多个发射装置基于多个用户装置的位置信息和聚类算法确定多个聚类中心点，进而基于多个聚类中心点移动发射装置获得多个目标发射装置，各个目标发射装置分别与对应的用户装置之间 进行信号传输，多个发射装置与多个用户装置频谱共享。若用户装置移动或出现新的用户装置，则该用户装置由距离最近的目标发射装置服务，若该目标发射装置增加用户装置后射频链路的数量不小于该目标发射装置服务的用户装置的数量，则多个目标发射装置不变，若该目标发射装置增加用户端后射频链路的数量小于该目标发射装置服务的用户装置的数量，则将初始中心点的数量增加并基于各个用户装置的位置信息、聚类算法和各个发射装置重新确定多个目标发射装置。在这种情况下，能够有效地减小毫米波蜂窝网系统的频谱共享的协调开销和计算复杂度。
本公开的第二方面所涉及的毫米波移动基站在线频谱共享系统中，可选地，所述聚类算法为K均值聚类算法。由此，能够更好地获得聚类中心点。
本公开的第二方面所涉及的毫米波移动基站在线频谱共享系统中，可选地，各个用户装置均能获得各自对应的位置信息。由此，能够获得各个用户装置的位置信息。
本公开的第二方面所涉及的毫米波移动基站在线频谱共享系统中，可选地，将所述多个发射装置中的所述多个目标发射装置外的发射装置关闭。由此，能够有助于降低能量的消耗。
本公开的第二方面所涉及的毫米波移动基站在线频谱共享系统中，可选地，所述多个用户装置划分为多个聚类，任一聚类中的用户装置数量不超过该聚类对应的目标发射装置的射频链路的数量。由此，能够使发射装置和用户装置更好地工作。
根据本公开，能够提供一种减小毫米波蜂窝网系统的频谱共享的协调开销和计算复杂度的基于聚类算法的毫米波移动基站在线频谱共享方法及系统。
附图说明
图1是示出了本公开的示例所涉及的基于聚类算法的毫米波移动基站在线频谱共享方法的应用场景示意图。
图2是示出了本公开的示例所涉及的确定目标基站的方法流程图。
图3是示出了本公开的示例所涉及的确定聚类中心点的方法流程图。
图4是示出了本公开的示例所涉及的针对在线频谱共享方法的性能检测方法的流程示意图。
图5是示出了本公开的示例所涉及的用户端的目标总速率随信噪比变化的波形图。
图6是示出了本公开的示例所涉及的用户端的目标总速率随目标基站的天线数量变化的波形图。
图7是示出了本公开的示例所涉及的用户端的目标总速率随用户端的天线数量变化的波形图。
图8是示出了本公开的示例所涉及的K值随用户端的数量变化的波形图。
图9是示出了本公开的示例所涉及的用户端的目标总速率随用户端的数量变化的波形图。
图10是示出了本公开的示例所涉及的K值随射频链路的数量变化的波形图。
图11是示出了本公开的示例所涉及的目标总速率随射频链路的数量变化的波形图。
图12是示出了本公开的示例所涉及的用户端的目标总速率随载波频率变化的柱形图。
图13是示出了本公开的示例所涉及的用户端的目标总速率随用户端变化的柱形图。
图14是示出了本公开的示例所涉及的基于聚类算法的毫米波移动基站在线频谱共享系统的框图。
具体实施方式
以下，参考附图，详细地说明本公开的优选实施方式。在下面的说明中，对于相同的部件赋予相同的符号，省略重复的说明。另外，附图只是示意性的图，部件相互之间的尺寸的比例或者部件的形状等可以与实际的不同。
本公开提供一种基于聚类算法的毫米波移动基站在线频谱共享方 法及系统。在本公开中，基于聚类算法的毫米波移动基站在线频谱共享方法及系统可以应用在毫米波蜂窝网系统，能够实现毫米波蜂窝网系统的频谱共享，并能够较为明显地减小毫米波蜂窝网系统的频谱共享的协调开销和计算复杂度。以下结合附图进行详细描述本公开。
图1是示出了本公开的示例所涉及的基于聚类算法的毫米波移动基站在线频谱共享方法的应用场景示意图。如图1所示，毫米波移动基站在线频谱共享方法(简称“在线频谱共享方法”)是具有多个基站和多个用户端的毫米波蜂窝网系统的在线频谱共享方法。其中，多个基站中的多个目标基站(稍后描述)可以与对应的多个用户端之间进行信号传输。在一些示例中，基站和用户端可以频谱共享且可以工作于毫米波蜂窝网系统(或称“毫米波蜂窝网”)。
在一些示例中，基站的数量可以是多个。每个基站的天线数量可以是多个。用户端的数量可以是多个。每个用户端的天线数量可以是多个。在一些示例中，基站的位置可以是移动的。用户端的位置可以是移动的。在一些示例中，每个基站的射频链路的数量可以是多个。例如，如图1所示，毫米波蜂窝网系统可以包含4个基站(例如基站101、基站102等)和和13个用户端(例如用户端200、用户端201等)。其中，一个用户端为之后新增加的用户端(例如，用户端212，稍后描述)，每个基站可以都具有3个射频线路(例如，基站101具有的射频链路400、射频链路401和射频链路402)。在一些示例中，毫米波蜂窝网系统可以处于低负荷状态，即N b|B ∑|＞＞|M ∑|。其中，M ∑表示为所有用户端的集合，B ∑表示为所有目标基站(稍后描述)的集合，|B ∑|表示为所有目标基站的数量，也即服务于多个用户端的基站的数量，N b表示为目标基站b(即编号为b的目标基站)服务的用户端的个数。
在本公开中，基站(例如接入点)可以是指接入网中在空中接口上通过一个或多个扇区与无线终端通信的设备。基站可用于将收到的空中帧与IP帧进行相互转换，作为无线终端与接入网的其余部分之间的路由器，其中，接入网的其余部分可包括网际协议(IP)网络。基站还可以协调对空中接口的属性管理。例如，基站可以是GSM或CDMA中的基站(BTS，Base Transceiver Station)，也可以是WCDMA中的基站(NodeB)，还可以是LTE中的演进型基站(NodeB或eNB 或e-NodeB，evolutional Node B)。
在本公开中，用户端可以是用户。其中，用户可以包括但不限于用户设备。用户设备可以包括但不限于智能手机、笔记本电脑、个人计算机(Personal Computer，PC)、个人数字助理(Personal Digital Assistant，PDA)、移动互联网设备(Mobile Internet Device，MID)、穿戴设备(如智能手表、智能手环、智能眼镜)等各类电子设备，其中，该用户设备的操作系统可包括但不限于Android操作系统、IOS操作系统、Symbian(塞班)操作系统、Black Berry(黑莓)操作系统、Windows Phone8操作系统等等。
在一些示例中，各个用户端可以获得各自的位置信息，并可以将包含各自的位置信息的位置信号发送给基站。在一些示例中，各个基站可以获得各自的位置信息。由此，能够获得用户端和基站的位置信息。
在一些示例中，多个基站可以利用聚类算法根据各个用户端的位置信息确定目标基站。在一些示例中，目标基站可以是确定出的用于服务多个用户端的基站，也就是说，目标基站在后续服务过程中处于工作状态。在一些示例中，可以将多个基站中的多个目标基站外的基站关闭，也即可以将多个基站中并非作为目标基站的其他基站关闭。由此，能够有助于降低能量的消耗。
在一些示例中，聚类算法可以选用K均值聚类算法(即非监督聚类算法)，多个基站可以根据K均值聚类算法、基站各自的位置信息、用户端的位置信息和基站的射频链路的数量确定多个聚类中心点。由此，能够更好地获得聚类中心点。但本公开的示例不限于此，在一些示例中，在实施方式中也可以选用其它的聚类算法，例如，K中心点聚类算法。
图2是示出了本公开的示例所涉及的确定目标基站的方法流程图。
在一些示例中，如图2所示，使用聚类算法确定目标基站的方法可以包括以下步骤：基于用户端的数量和基站的射频链路的数量获得多个初始中心点(步骤S110)；基于多个初始中心点、多个用户端的数量与位置信息以及各个基站的射频链路的数量获得与多个用户端对应的多个聚类中心点(步骤S120)；基于多个聚类中心点移动若干个基站 获得多个目标基站(步骤S130)。
在步骤S110中，可以基于用户端的数量和基站的射频链路的数量获得多个初始中心点。
在一些示例中，用户端的数量可以不大于相应的基站的射频链路的数量。由此，能够使基站和用户端更好地工作。例如，基站的射频链路的数量可以是N r个，则该基站可以同时服务N r个用户端，即该基站可以同时与N r个用户端进行信号传输。
在一些示例中，可以基于用户端的数量和基站的射频链路的数量获得多个初始中心点。初始中心点的数量K可以满足：
Figure PCTCN2020105610-appb-000001
其中，M ∑表示为所有用户端的集合，|M ∑|表示为用户端的数量，N r表示为基站的射频链路的数量。在一些示例中，可以随机选取K个点作为初始中心点。例如，可以随机选取K个用户端并将其对应的位置作为初始中心点。例如，基于图1所示的4个基站、12个用户端(除了用户端212)以及每个基站可以都具有3个射频链路，可以获得初始中心点的数量为4个，其中，基站是可以移动的，图1中的用户端212为之后增加新的用户端(稍后描述)。。在这种情况下，可以随机选择选取4个用户端并将其位置作为初始中心点。
在步骤S120中，基于多个初始中心点、多个用户端的数量与位置信息以及各个基站的射频链路的数量可以获得与多个用户端对应的多个聚类中心点。
图3是示出了本公开的示例所涉及的确定聚类中心点的方法流程图。
在一些示例中，如图3所示，步骤S120中确定聚类中心点的方法可以包括以下步骤：将初始中心点作为初始聚类中心点(步骤S121)；基于各个用户端的位置信息和初始聚类中心点对各个用户端进行聚类划分(步骤S122)；根据划分的多个聚类获得各个聚类的中心点(步骤S123)；判断各个聚类中的元素是否不在发生变化(步骤S124)；若发生变化，则将各个聚类的中心点作为初始聚类中心点(步骤S125)；若不发生变化，则判断各个聚类中对应的用户端的数量是否不大于任一基站的射频链路的数量(步骤S126)；若大于，则将初始中心点的数量 增加一个，该增加的初始中心点也可以随机选取(步骤S127)；若不大于，则将各个聚类的中心点作为聚类中心点(步骤S128)。
在一些示例中，在步骤S121中，可以将初始中心点作为初始聚类中心点。
在步骤S122中，基于各个用户端的位置信息和初始聚类中心点对各个用户端进行聚类划分。
在一些示例中，在步骤S122中，可以根据用户端的位置信息计算该用户端与各个初始聚类中心点的距离。在一些示例中，各个用户端可以对应一个初始聚类中心点。例如，可以将各个用户端距离更小的初始聚类中心点作为该用户端的对应的初始聚类中心点。由此，能够对所有的用户端进行聚类划分。在一些示例，各个初始聚类中心点可以对应一个或多个用户端。
在步骤S123中，根据划分的多个聚类获得各个聚类的中心点。
在一些示例中，在步骤S123中，可以根据各个聚类获得分别与各个聚类对应的中心点。在一些示例中，可以根据
Figure PCTCN2020105610-appb-000002
来确定各个聚类对应的中心点，其中，
Figure PCTCN2020105610-appb-000003
表示为第k个聚类，
Figure PCTCN2020105610-appb-000004
表示为第k个聚类中的用户端的数量，(x MT,m,y MT,m)表示为第m个用户端的位置信息，m可以为该聚类中的用户端。在一些示例中，各个聚类的元素可以包括对应的用户端和中心点。
在步骤S124中，判断各个聚类中的元素是否不在发生变化。
在一些示例中，在步骤S124中，可以将当前获得的聚类和前一次获得的聚类进行比较，判断各个聚类中的元素是否不在发生变化，例如判断当前获得的第k个聚类对应的中心点和用户端和前一次获得的第k个聚类对应的中心点和用户端是否相同。若发生变化，则可以继续步骤S125。若未发生变化，则可以继续步骤S126。
但本公开的示例不限于此，在一些示例中，可以根据用户端的位置信息和聚类对应的中心点计算目标函数，目标函数满足：
Figure PCTCN2020105610-appb-000005
其中，k＝1,2,...,K，m∈M ∑，
Figure PCTCN2020105610-appb-000006
表示为第k个聚类，(x MT,m,y MT,m)表示为第m个用户端的位置信息，μ k表示为第k个聚类对应的中心点(或均值)，K表示中心点的数量。中心点的数量可以和初始中心点的数量相同。通过式(2)判断各个聚类对应的目标函数是否不会发生明显变化。在一些示例中，可以通过当前获得的聚类和前一次获得的聚类进行比较，判断各个聚类对应的目标函数的结果是否不会发生明显变化，例如判断当前获得的第k个聚类和前一次获得的第k个聚类对应的目标函数的结果是否发生明显变化。若发生明显变化，则可以继续步骤S125。若未发生明显变化，则可以继续步骤S126。
在一些示例中，如上所述，本实施方式可以采用K均值聚类算法。在一些示例中，K均值聚类算法的目标可以是将所有聚类的目标函数的值最小化，可以满足：
Figure PCTCN2020105610-appb-000007
在这种情况下，可以将各个用户端划分为较为合适的聚类。
在步骤S125中，若发生变化，也即若各个聚类中的元素或对应的目标函数发生变化，则可以继续步骤S125，也即将各个聚类的中心点作为初始聚类中心点。之后可以重复步骤S122至步骤S124。在这种情况下，能够便于后续获得更加适合的聚类中心点。
在步骤S126中，若不发生变化，也即若各个聚类中的元素或对应的目标函数未发生变化，则可以继续步骤S126，也即将当前获得的各个聚类中对应的用户端的数量和基站的射频链路的数量进行比较，判断各个聚类中对应的用户端的数量是否不大于任一基站的射频链路的数量。若大于，则可以继续步骤S127。若不大于，则可以继续步骤S128。在步骤S127中，若大于，则可以将初始中心点的数量增加一个，该增加的初始中心点也可以随机选取。在一些示例中，增加的初始中心点可以和之前的初始中心点的选择方式相同，例如随机选择一个用户端并将其位置作为增加的初始中心点。在执行完步骤S127后可以重复步骤S121至步骤S126。由此，能够使后续获得的目标基站可以同时向对应的用户端发射信号。
在步骤S128中，若不大于，则可以将当前获得的各个聚类的中心点作为聚类中心点。由此能够获得聚类中心点。在一些示例中，中心点的数量可以和聚类中心点的数量相同。
在一些示例中，基于上述的步骤S120获得的多个聚类中心点可以在步骤S130中确定目标基站。
在一些示例中，在步骤S130中，可以基于多个聚类中心点移动若干个基站获得多个目标基站。在一些示例中，可以从多个基站中选取若干个基站分别移动到各个聚类中心点对应的位置作为目标基站。在一些示例中，目标基站的数量可以和聚类中心点的数量相同，也就是说，各个聚类中心点可以分别对应一个目标基站。在一些示例中，若各个聚类中心点和任一用户端的位置均不相同，则将若干个基站从多个基站中选出若干个基站，并可以将其分别移动到各个聚类中心点作为目标基站。例如，如图1所示，12个用户端(未包括用户端212)被划分为4个聚类(聚类300、聚类310、聚类320、聚类330)，分别对应4个聚类中心点(未图示)，选取4个基站(基站101、基站102、基站103、基站104)分别移动到4个聚类中心点对应的位置作为4个目标基站。在一些示例中，若聚类中心点和任一用户端的位置相同，则可以将基站移动到该聚类中心点的附近作为目标基站。在一些示例中，可以将基站移动到该聚类中心点的周围十米内(例如周围一米远)的位置。由此，能够移动若干个基站获得多个目标基站。例如，如图1所示，可以分别将基站101、基站102、基站103、基站104分别移动到各个聚类中心点对应的位置作为目标基站。
在一些示例中，可以利用聚类算法将多个用户端划分为多个聚类，其中，每个聚类可以包含一个或多个用户端。在一些示例中，每个聚类可以对应一个目标基站。例如，如图1所示，可以将12个用户端划分为4个聚类，其中，聚类300可以包含用户端200、用户端201和用户端202，聚类310可以包含用户端203、用户端204和用户端205，聚类320可以包含用户端206、用户端207和用户端208，聚类330可以包含用户端209、用户端210和用户端211。在一些示例中，各个聚类对应的目标基站的射频链路的数量可以不小于该聚类中的用户端的数量。由此，能够使基站和用户端更好地工作。在一些示例中，目标 基站可以同时与对应的聚类中的用户端进行信号传输。例如，聚类300包含目标基站(即基站101)、用户端200、用户端201和用户端202，其中，基站101的射频链路的数量为3个，基站101服务的用户端的数量为小于或等于基站101的射频链路的数量，基站101可以同时向其对应的用户端(即用户端200、用户端201和用户端202)发射信号。
在一些示例中，可以将现有的用户端移动或增加新的用户端(例如，图1中的用户端212)，可以基于该用户端的位置信息和各个聚类中心点确定该用户端对应的聚类，从而确定该用户端对应的目标基站。具体而言，可以根据该用户端与各个聚类中心点之间的距离确定该用户端对应的聚类，从而确定该聚类对应的目标基站，该用户端可以由该目标基站服务。在一些示例中，可以将距离该用户端最近的聚类中心点对应的聚类作为该用户端对应的聚类。例如，可以通过
Figure PCTCN2020105610-appb-000008
获得多个聚类中心点中与该用户端m的距离最小的聚类中心点，由此能够获得该用户端m对应的聚类，即该聚类对应的目标基站可以服务于该用户端。
在一些示例中，若该目标基站(距离移动或新的用户端最近的目标基站)增加用户端后射频链路的数量不小于该目标基站当前对应的用户端的数量，则可以不改变当前的聚类，即可以保持现有的目标基站(即确定的多个目标基站可以不变)。在一些示例中，若该目标基站的射频链路的数量小于该目标基站当前对应的用户端的数量，则可以改变当前的聚类，可以重新确定目标基站。例如，如图1所示，若增加新的用户端(例如用户端212)，用户端212距离目标基站(基站103)最近，则可以确定用户端212对应目标基站(基站103)，目标基站(基站103)的射频链路的数量为3个(例如射频链路403、射频链路404、射频链路405)，且此时目标基站(基站103)对应的用户端的数量为4个(例如用户端206、用户端207、用户端208、用户端212)，则可以改变当前的聚类，即可以重新确定目标基站，从而能够使基站和用户端更好地正常工作。在一些示例中，可以基于聚类算法、各个用户端的位置信息确定多个新的聚类中心点，进而移动基站重新确定目标基站。也就是说，若将现有的用户端移动或增加新的用户端， 使其对应的目标基站的射频链路的数量小于该目标基站对应的用户端的数量，则可以将初始中心点的数量增加一个(例如重新进入步骤S127)，可以基于聚类算法重新确定目标基站。
在本实施方式中，可以根据聚类算法和用户端的位置信息确定聚类中心点。具体而言，每个基站可以接收用户端的位置信息并通过聚类算法可以确定聚类中心点。在这种情况下，能够有效地减小协调开销。在一些示例中，可以根据聚类算法确定基站的计算复杂度，其中，可以将聚类算法的每次迭代分为三种类型来获得计算复杂度：(1)在步骤S124中可以通过计算式(2)来判断目标函数是否明显变化，其中，对应一个用户端需要5次运算，则对于所有的用户端需要
Figure PCTCN2020105610-appb-000009
次运算。(2)在步骤S122中，可以通过用户端的位置信息和初始聚类中心点对用户端进行聚类划分，其中，对于所有的用户端需要
Figure PCTCN2020105610-appb-000010
次运算。(3)在步骤S123中，可以通过式(1)获得各个聚类的中心点，其中，对于所有的聚类需要
Figure PCTCN2020105610-appb-000011
次运算。在本实施方式中，可以将用户端移动或增加新的用户端，可以通过比较该用户端到各个聚类中心点的距离确定该用户端对应的目标基站。其中，对于该用户端需要K次运算。
在本实施方式中，可以根据聚类中心点移动基站获得多个目标基站，可以从多个基站中选取若干个基站分别移动到各个聚类中心点对应的位置作为目标基站。
在一些示例中，假设聚类算法在步骤S125进行T 1次迭代，在步骤S127进行T 2次迭代，则可以获得通过本公开来确定目标基站的总运算次数。总运算次数可以满足：
Figure PCTCN2020105610-appb-000012
在这种情况下，能够有效地减小基站的计算复杂度。在一些示例中，若新增加的用户端对应的目标基站的射频链路的数量小于服务的用户端(包括新增加的用户端)的数量，则需要对所有的基站和用户端(包括新增加的用户端)重新进行聚类划分和重新确定目标基站(即重新确定新的目标基站)。在一些示例中，可以重新进入步骤S127，基于聚类算法重新确定目标基站。在这种情况下，总运算次数可以满足：
Figure PCTCN2020105610-appb-000013
(4)。由此可知，本实施方式能够有效地减小基站的计算复杂度。
在本实施方式中，在线频谱共享方法可以包括多个基站可以基于聚类算法、各个用户端的位置信息等确定出一个或多个目标基站；目标基站可以与对应的用户端之间进行信号传输；目标基站可以和用户端频谱共享等。
在一些示例中，针对上述的在线频谱共享方法可以进行性能检测。
图4是示出了本公开的示例所涉及的针对在线频谱共享方法的性能检测方法的流程示意图。
在本实施方式中，如图4所示，性能检测方法可以包括以下步骤：各个目标基站通过若干路径向对应的用户端发射信号，信号经无线信道获得第二信号，用户端接收第二信号，基于对应的目标基站、该用户端和信道状态信息获得目标基站与该用户端之间的信号矩阵、组合加权向量和预编码加权向量(步骤S10)；基于组合加权向量、预编码加权向量、信号矩阵、该目标基站的平均传输功率获得干扰信号和目标信号，进而基于噪声信号和共享频谱的带宽获得用户端接收第二信号的平均速率(步骤S20)；基于平均速率、多个目标基站和多个目标基站与用户端的对应关系获得用户端的总速率，对各个用户端的总速率求和获得目标总速率，进而基于目标总速率检测毫米波蜂窝网系统的性能(步骤S30)。
在步骤S10中，各个目标基站可以通过若干路径向对应的用户端发射信号，信号经无线信道获得第二信号，用户端接收第二信号，基于对应的目标基站、该用户端和信道状态信息获得目标基站与该用户端之间的信号矩阵、组合加权向量和预编码加权向量。
具体而言，各个目标基站通过若干路径向对应的用户端发射信号，信号经无线信道获得第二信号，第二信号包括目标信号和干扰信号以及噪声信号，用户端接收第二信号，基于对应的目标基站、用户端的位置信息和信道状态信息获得与若干路径对应的到达角和离场角，基于该目标基站的天线数量和用户端的天线数量获得到达角的指导向量和离场角的指导向量，基于该目标基站与用户端之间的路径数量、各路径对应的信道增益、该目标基站的天线数量和用户端的天线数量获得该目标基站与用户端之间的信号矩阵，基于该目标基站的射频链路的数量、目标路径的到达角和目标路径的到达角的指导向量获得该目 标基站与用户端之间的组合加权向量，基于该目标基站与用户端之间的组合加权向量和信号矩阵获得该目标基站与用户端之间的预编码加权向量。
在一些示例中，目标基站可以和用户端频谱共享。例如，目标基站和用户端可以共享带宽为W的频段。在一些示例中，目标基站和用户端可以在相同的区域内服从独立的泊松分布。
在一些示例中，在步骤S10中，各个目标基站可以通过若干路径向对应的用户端发射信号，即该目标基站和该用户端相关联。其中，该用户端在该目标基站对应的聚类中。在一些示例中，目标基站不向对应的聚类外的其他聚类中的用户端发射信号，即该目标基站和该用户端不关联。在一些示例中，可以利用二元变量表示目标基站和用户端的关联状态。例如，利用二元变量a bm表示基站b与移动终端m的关联状态，如果基站b可以向移动终端m发射信号，则a bm＝1；否则，a bm＝0。
在一些示例中，各个目标基站与对应的用户端之间的路径数量可以是一个或多个。目标基站可以通过任一路径向对应的用户端发射信号。其中，每条路径可以对应相同或不同的信道增益。在一些示例中，可以假设目标基站b与移动终端m之间的路径数量为L bm。其中，第l条路径的信道增益表示为h bml。在一些示例中，可以假设信道增益为零均值的复杂高斯随机变量，且满足
Figure PCTCN2020105610-appb-000014
其中，
Figure PCTCN2020105610-appb-000015
是与距离相关的大规模对数正态路径衰落，
Figure PCTCN2020105610-appb-000016
可以满足
Figure PCTCN2020105610-appb-000017
其中，α d是路径损失指数，满足α d≥2。d bm是基站b和移动终端m之间距离，λ是信号的波长，满足λ＝c/f c。c＝3×10 8m/s，f c是信号的载波频率。
在一些示例中，目标基站的天线数量可以是一个或多个。例如，目标基站的天线数量可以是N BS，用户端的天线数量可以是一个或多个。例如，用户端的天线数量可以是N MT。
在一些示例中，信号经无线信道获得第二信号，用户端可以接收第二信号。在一些示例中，可以基于对应的目标基站、用户端的位置信息和信道状态信息获得与若干路径分别对应的到达角和离场角。在一些示例中，到达角和离场角可以由目标基站、用户端的空间分布和通信环境中的散射决定。其中，目标基站、用户端的空间分布可以由 目标基站、用户端的位置信息获得。通信环境中的散射可以由信道状态信息获得。在一些示例中，若目标基站和用户端可以服从独立的齐次泊松分布，则到达角和离场角可以是遵循均匀分布[0,2π]的独立随机变量。例如，目标基站b与用户端m的第l条路径的到达角和离场角可以分别表示为θ MT,bml和θ BS,bml，目标基站和用户端可以服从独立的齐次泊松点过程，其中，θ MT,bml和θ BS,bml可以是遵循均匀分布[0,2]的独立随机变量。
在一些示例中，用户端可以基于该目标基站的天线数量和用户端的天线数量获得到达角的指导向量和离场角的指导向量。在一些示例中，到达角的指导向量可以满足：
Figure PCTCN2020105610-appb-000018
(5)，其中，可以将到达角θ MT,bml代入，由此能够获得目标基站b与用户端m的第l条路径的到达角的指导向量，离场角的指导向量可以满足：
Figure PCTCN2020105610-appb-000019
其中，可以将离场角θ BS,bml代入，由此能够获得目标基站b与用户端m的第l条路径的离场角的指导向量。
在一些示例中，用户端可以基于该目标基站与用户端之间的路径数量、各路径对应的信道增益、该目标基站的天线数量和用户端的天线数量获得该目标基站与用户端之间的信号矩阵。例如，目标基站b与移动终端m之间的信号矩阵可以满足：
Figure PCTCN2020105610-appb-000020
在一些示例中，用户端可以基于该目标基站的射频链路的数量、目标路径的到达角和目标路径的到达角的指导向量获得该目标基站与用户端之间的组合加权向量。用户端可以基于该目标基站与用户端之间的组合加权向量和信号矩阵获得该目标基站与用户端之间的预编码加权向量。在一些示例中，目标基站的射频链路的数量可以是一个或多个。例如，目标基站的射频链路的数量可以N r个，即该目标基站可以最多同时向N r个用户端发射信号。如果目标基站对应的用户端的数 量大于射频链路的数量，会使目标基站出现过载情况导致目标基站出现问题。
在一些示例中，各个目标基站的射频链路的数量可以只有一个，并且各个用户端可以获得准确的到达角。例如，用户端m可以获得准确的第l条路径的到达角θ MT,bml。在一些示例中，目标路径可以为目标基站与用户端之间的若干路径中信道增益最大的路径。由此，能够便于后续获得该用户端和该基站之间的组合加权向量。在一些示例中，当目标基站b向用户端m发射信号，可以基于式(5)获得目标基站b与用户端m之间的组合加权向量，组合加权向量w MT,bm可以满足：
Figure PCTCN2020105610-appb-000021
其中，
Figure PCTCN2020105610-appb-000022
表示为信道增益最大的路径l *(即目标路径)对应的到达角。在一些示例中，目标基站b与用户端m之间的预编码加权向量w BS,bm可以满足
Figure PCTCN2020105610-appb-000023
在步骤S20中，用户端可以基于组合加权向量、预编码加权向量、信号矩阵、该目标基站的平均传输功率获得干扰信号和目标信号，进而基于噪声信号和共享频谱的带宽获得用户端接收第二信号的平均速率。
具体而言，用户端可以基于信号矩阵、组合加权向量、预编码加权向量和对应的目标基站的平均传输功率获得干扰信号和目标信号。用户端可以基于干扰信号、目标信号、噪声信号以及该目标基站与用户端的共享频谱的带宽获得用户端接收第二信号的平均速率。
在一些示例中，目标基站可以向对应的用户端发射信号。信号经无线信道可以获得第二信号。用户端可以接收第二信号。其中，第二信号可以包含干扰信号、目标信号和噪声信号。
在一些示例中，用户端可以基于用户端和对应的目标基站之间的信号矩阵、组合加权向量、预编码加权向量以及该目标基站的平均传输功率获得用户端接收到的目标信号。例如，目标基站b的平均传输功率可以为P BS，对平均传输功率进行归一化可以满足：
Figure PCTCN2020105610-appb-000024
(9)，当目标基站b向用户端m发射信号，可以基于式(6)至式(9)获得用户端接收到的目标信号，可以满足：
Figure PCTCN2020105610-appb-000025
在一些示例中，处于工作状态的多个目标基站可以对应同一个运营商或对应多个运营商。其中，任一目标基站可以对应一个运营商。多个用户端可以对应同一个运营商或对应多个运营商。其中，任一用户端可以对应一个运营商。在一些示例中，多个目标基站可以对应z个运营商。其中，第i个运营商可以具有多个目标基站，第i个运营商对应的所有目标基站的集合可以表示为B i，则z个运营商对应的所有目标基站的集合可以表示为B ∑＝B 1∪B 2∪...∪B Z。第i个运营商可以服务多个用户端，第i个运营商服务的所有用户端的集合可以表示为M i，则z个运营商对应的所有用户端的集合可以表示为M ∑＝M 1∪M 2∪...∪M Z。
在一些示例中，任一目标基站可以服务一个或多个用户端。例如，目标基站b可以服务多个用户端。目标基站b服务的所有用户端的集合可以表示为A b。
在一些示例中，可以有多个目标基站处于工作状态。任一目标基站可以同时向多个用户端发射信号。在一些示例中，用户端可以接收第二信号。第二信号中的干扰信号可以包括由同一个目标基站向其他对应的用户端发射信号产生的第一干扰信号和由同一个运营商的其他目标基站向各自对应的用户端发射信号产生的第二干扰信号以及由不同运营商对应的目标基站向各自对应的用户端发射信号产生的第三干扰信号。在一些示例中，当目标基站b向用户端m发射信号，假设目标基站b对应第z个运营商，则第一干扰信号可以满足：
Figure PCTCN2020105610-appb-000026
第二干扰信号可以满足：
Figure PCTCN2020105610-appb-000027
第三干扰信号可以满足：
Figure PCTCN2020105610-appb-000028
在一些示例中，由于毫米波蜂窝网系统的覆盖范围较小，可以不需要在长距离的基站之间进行协调，并且第二干扰信号和第三干扰信号可以忽略不计。
在一些示例中，用户端可以接收第二信号，第二信号中的噪声信号可以为零均值的复杂高斯变量，第二信号中的噪声信号可以满足：
Figure PCTCN2020105610-appb-000029
其中，
Figure PCTCN2020105610-appb-000030
是方差。
在一些示例中，当目标基站b向用户端m发射信号，可以根据式(10)至式(14)获得用户端m从目标基站b接收信息(例如，第二信号)的平均速率R bm，可以满足：
Figure PCTCN2020105610-appb-000031
其中，W可以表示为目标基站和用户端频谱共享时的共享带宽，
Figure PCTCN2020105610-appb-000032
可以为信号干扰噪声比。
在步骤S30中，用户端可以基于平均速率、多个目标基站和多个目标基站与用户端的对应关系获得用户端的总速率，对各个用户端的总速率求和获得目标总速率，进而基于目标总速率检测毫米波蜂窝网系统的性能。
在一些示例中，当目标基站b向用户端m发射信号，假设目标基站b对应第z个运营商，可以根据第z个运营商中的其他目标基站与用户端m的对应关系，由式(15)可以获得用户端m从运营商z对应的所有目标基站处接收到信息(例如，第二信号)的总速率，总速率R m可以满足：
Figure PCTCN2020105610-appb-000033
在一些示例中，用户端可以接收对应的运营商中的对应目标基站发射的信号，对所有用户端对应的总速率进行求和可以获得目标总速率，目标总速率R ∑可以满足：
Figure PCTCN2020105610-appb-000034
由此，能够获得目标总速率，并可以根据目标总速率检测目标基站和用户端频谱共享(即毫米波蜂窝网系统)的性能(稍后描述)。
在一些示例中，如图5至图12所示(除了图8和图10)，通过分析本公开和传统方案(即非专利文献1公开的方案)用户端的目标总速率随不同系统参数变化曲线检测毫米波蜂窝网系统的性能，其中，A为传统方案的用户端的目标总速率随不同系统参数变化曲线(或柱状图)，B为本公开的用户端的目标总速率随不同系统参数变化曲线(或柱状图)。如图5至图12中，系统参数满足总带宽为2GHz、f c＝32GHz和α d＝2。另外，每个用户端的射频链路的数量为1个，即每个用户端仅能收到一个目标基站发送的信息。
图5是示出了本公开的示例所涉及的用户端的目标总速率随信噪 比变化的波形图。其中，信噪比满足
Figure PCTCN2020105610-appb-000035
在一些示例中，如图5所示，每个目标基站的天线数量为20个，即N BS＝20，每个用户端的天线数量为5个，即N MT＝5，移动终端的分布频率为每平方公里100个，每个目标基站的射频链路的数量为5个，即N r＝5，本公开和传统方案的用户端的目标总速率均随着信噪比增加而增加，且呈线性增加，由图5可知，本公开的方案具有更好的性能，例如当总速率达到10 -2bits/s/Hz时，本公开的方案所需的信噪比比传统方案低19dB。
图6是示出了本公开的示例所涉及的用户端的目标总速率随目标基站的天线数量变化的波形图。图7是示出了本公开的示例所涉及的用户端的目标总速率随用户端的天线数量变化的波形图。
在一些示例中，如图6所示，信噪比为30dB、每个用户端的天线数量为5个，即N MT＝5，移动终端的分布频率为每平方公里100个，每个目标基站的射频链路的数量为5个，即N r＝5，本公开和传统方案的用户端的目标总速率均随着每个目标基站的天线数量的增加而增加，且呈对数形式增加。由图6可知，两种方案为了达到相同的目标总速率，本公开的方案所需的目标基站的天线数量比传统方案少，即本公开的方案具有更好的性能。
在一些示例中，如图7所示，信噪比为30dB、每个目标基站的天线数量为20个，即N BS＝20，移动终端的分布频率为每平方公里100个，每个目标基站的射频链路的数量为5个，即N r＝5，本公开和传统方案的用户端的目标总速率均随着用户端的天线数量的增加而增加，且呈对数形式增加。由图7可知，两种方案为了达到相同的目标总速率，本公开的方案所需的用户端的天线数量比传统方案少，即本公开的方案具有更好的性能。根据图6和图7所知，目标总速率随着N BS或N MT的数量增加而增加，因为随着天线数量的增加，天线的增益增高，使干扰信号降低，其中，目标总速率以对数形式的上升，说明在信号干扰噪声比下，增加更多的天线单元对于提升目标总速率的影响不大。在这种情况下，可以增加总带宽或为用户端传输并行数据，由此能够进一步提高目标总速率。每个用户端的天线数量增加对目标总速率的影响比每个目标基站的天线数量增加对目标总速率的影响大。为了达到 相同的目标总速率，需要在目标基站上增加的天线数量比在用户端增加的天线数量更多。比如当目标总速率达到10 -3bits/s/Hz时，图6中需要N BS＝40和N MT＝5，图7中需要N BS＝20和N MT＝9。但对于大型天线元件，用户端的尺寸和电量比目标基站有更多的限制。
图8是示出了本公开的示例所涉及的K值随用户端的数量变化的波形图。图9是示出了本公开的示例所涉及的用户端的目标总速率随用户端的数量变化的波形图。其中，信噪比为30dB、每个目标基站的天线数量为20个，即N BS＝20，每个用户端的天线数量为5个，即N MT＝5，每个目标基站的射频链路的数量为5个，即N r＝5，用户端的数量由每平方公里20个变化到每平方公里100。
在一些示例中，如图8所示，A为本公开的方案中K值随用户端的数量变化的波形图，其中，K值随用户端的数量的增加而增加，且呈线性增加。在这种情况下，有助于预测本公开的方案所需的目标基站的数量。
在一些示例中，如图9所示，本公开和传统方案的用户端的目标总速率均随着用户端的数量的增加而增加，且呈对数形式增加。由图9可知，两种方案为了达到相同的目标总速率，本公开的方案所需的用户端的数量比传统方案少，即本公开的方案具有更好的性能。由图9可知，随着用户端的数量的增加，两种方案的目标总速率以对数形式的上升，因为增加用户端的数量对目标总速率有更大的贡献，但同时也会使干扰信号增加。
图10是示出了本公开的示例所涉及的K值随射频链路的数量变化的波形图。图11是示出了本公开的示例所涉及的目标总速率随射频链路的数量变化的波形图。其中，信噪比为30dB、每个目标基站的天线数量为20个，即N BS＝20，每个用户端的天线数量为5个，即N MT＝5，移动终端的分布频率为每平方公里100个。
在一些示例中，如图10所示，A为本公开的方案中K值随射频链路的数量变化的波形图，其中，K值随每个目标基站的射频链路的数量的增加而减小。在这种情况下，能够减少本公开的方案所需的目标基站的数量。
在一些示例中，如图11所示，本公开和传统方案的用户端的目标 总速率均随着每个目标基站的射频链路的数量的增加而减小，其中本公开的方案受到的影响更大。由图10和图11可知，随着每个目标基站的射频链路的数量的增加可以减少基站数量，但使干扰信号增加，导致目标总速率降低。
图12是示出了本公开的示例所涉及的用户端的目标总速率随载波频率变化的柱形图。在一些示例中，如图10所示，信噪比为30dB、每个目标基站的天线数量为20个，即N BS＝20，每个用户端的天线数量为5个，即N MT＝5，移动终端的分布频率为每平方公里100个，每个目标基站的射频链路的数量为5个，即N r＝5。其中，本公开和传统方案的用户端的目标总速率均随着载波频率的增加而减小。由图12可知，随着载波频率的增加，目标总速率下降，因为载波频率的增加会使目标基站的覆盖率降低。对于高载波频率，可以在每个目标基站上布置数量更多的天线，由此，能够减少因目标基站的覆盖率降低导致的损失。
图13是示出了本公开的示例所涉及的用户端的目标总速率随用户端变化的柱形图。其中，A为本公开的方案未增加新的用户端时对应的目标总速率，B为本公开的方案随时增加新的用户端时对应的目标总速率，其中，在曲线B中除了新增加的用户端，其他用户端的位置可以不发生变化。除了用户端的数量不同，其他参数可以和图9相同，A、B分别为每平方公里用户端的数量为50、51、52时对应的目标总速率的柱状图。由图13可知，随时增加新的用户端时和未增加新的用户端时具有相同的目标总速率，即本公开的随时增加新的用户端可以和未增加新的用户端时具有相同的性能。并且随着用户端的数量的增加，目标总速率增加。
如上所述，本实施方式相比传统方案具有更好的性能，还可以在确定目标基站时减小基站的计算复杂度和协调开销。因此根据本公开，能够提供一种减小毫米波蜂窝网系统的频谱共享的协调开销和计算复杂度的基于聚类算法的毫米波移动基站在线频谱共享方法。
本公开涉及一种基于聚类算法的毫米波移动基站在线频谱共享系统。毫米波移动基站在线频谱共享系统是包括多个发射装置和多个用户装置的毫米波蜂窝网系统。在本公开中，毫米波移动基站在线频谱 共享系统中的发射装置可以类比上述基站，用户装置可以类比上述用户端。
图14是示出了本公开的示例所涉及的基于聚类算法的毫米波移动基站在线频谱共享系统1的框图。在一些示例中，如图14所示，毫米波移动基站在线频谱共享系统1可以包含多个发射装置和多个用户装置。在一些示例中，多个目标发射装置(例如发射装置10、发射装置11)可以与对应的多个用户装置之间进行信号传输。在一些示例中，发射装置和用户装置可以频谱共享且工作于毫米波蜂窝网。
在一些示例中，多个发射装置(例如发射装置10、发射装置11等)可以接收各个用户装置(例如用户装置20、用户装置21、用户装置22、用户装置23)发射的包含位置信息的位置信号以获得用户装置的位置信息，并基于聚类算法确定多个聚类中心点，进而基于多个聚类中心点移动若干个基站作为目标基站(例如发射装置10、发射装置11)。聚类算法可以包括基于用户装置的数量和发射装置的射频链路的数量获得多个初始中心点。聚类算法可以基于多个初始中心点、多个用户装置的数量与位置信息以及各个发射装置的射频链路的数量获得与多个用户装置对应的多个聚类中心点。其中，各个聚类中心点分别对应一个目标发射装置，多个发射装置和多个用户装置频谱共享。目标发射装置的获取可以参见上述步骤S110～S130。
在一些示例中，若各个聚类中心点和任一用户装置的位置均不相同，则将若干个发射装置分别移动到各个聚类中心点作为目标发射装置，若聚类中心点和任一用户装置的位置相同，则将发射装置移动到该聚类中心点的附近作为目标发射装置，目标发射装置和多个聚类中心点一一对应。多个发射装置和多个用户装置共享频谱。目标发射装置的获取可以参见上述性能检测方法中的步骤S10。其中，每个发射装置可以接收用户装置发射的位置信号以获得用户装置的位置信息通过聚类算法可以确定聚类中心点。由此，能够有效地减小协调开销。具体过程可以参见上述在线频谱共享方法。
在一些示例中，可以将现有的用户装置移动或增加新的用户装置，在这种情况下，通过计算该用户装置和各个聚类中心点的距离确定该用户装置对应的目标发射装置，其中，目标发射装置对应的聚类中心 点可以是与该用户装置距离最小的。在一些示例中，若该目标发射装置增加用户装置后射频链路的数量不小于该目标发射装置当前对应的用户装置的数量，则可以不改变当前的聚类，即可以保持现有的目标发射装置。在一些示例中，若该目标发射装置的射频链路的数量小于该目标发射装置当前对应的用户装置的数量，则可以改变当前的聚类，可以重新确定目标发射装置，即可以重新确定新的目标发射装置。具体过程可以参见上述在线频谱共享方法。。在本实施方式中，由式(3)和式(4)可以获得发射装置在不同情况下确定目标发射装置时所需的总运算次数，在这种情况下，能够有效地减小发射装置的计算复杂度。
在一些示例中，可以将多个发射装置中的多个目标发射装置外的发射装置关闭。由此，能够有助于降低能量的消耗。
在一些示例中，针对毫米波移动基站在线频谱共享系统1可以如同上述在线频谱共享方法对其进行性能检测。如上所述，本公开的方案相比传统方案具有更好的性能，还可以在确定目标发射装置时减小发射装置的计算复杂度和协调开销。因此根据本公开，能够提供一种减小毫米波蜂窝网系统的频谱共享的协调开销和计算复杂度的基于聚类算法的毫米波移动基站在线频谱共享系统1。
虽然以上结合附图和实施例对本公开进行了具体说明，但是可以理解，上述说明不以任何形式限制本公开。本领域技术人员在不偏离本公开的实质精神和范围的情况下可以根据需要对本公开进行变形和变化，这些变形和变化均落入本公开的范围内。

Claims (10)

  1. 一种基于聚类算法的毫米波移动基站在线频谱共享方法，是具有多个基站和多个用户端的毫米波蜂窝网系统的频谱共享方法，其特征在于，
    包括：
    所述多个基站接收各个用户端发射的位置信号以获得用户端的位置信息，并基于聚类算法确定多个聚类中心点，进而基于所述多个聚类中心点移动若干个基站获得多个目标基站，所述聚类算法基于所述用户端的数量和所述多个基站的射频链路的数量获得多个初始中心点，并基于所述多个初始中心点、所述多个用户端的数量与位置信息以及各个基站的射频链路的数量获得与所述多个用户端对应的多个聚类中心点，各个所述目标基站分别与对应的用户端之间进行信号传输，
    其中，各个聚类中心点分别对应一个目标基站，所述多个基站和所述多个用户端频谱共享，若所述用户端移动或出现新的用户端，则该用户端由距离最近的目标基站服务，若该目标基站增加用户端后射频链路的数量不小于该目标基站服务的用户端的数量，则所述多个目标基站不变，若该目标基站增加用户端后射频链路的数量小于该目标基站服务的用户端的数量，则将初始中心点的数量增加并基于所述各个用户端的位置信息、所述聚类算法和所述各个基站重新确定所述多个目标基站。
  2. 根据权利要求1所述的毫米波移动基站在线频谱共享方法，其特征在于：
    所述聚类算法为K均值聚类算法。
  3. 根据权利要求1所述的毫米波移动基站在线频谱共享方法，其特征在于：
    各个用户端均能获得各自对应的位置信息。
  4. 根据权利要求1所述的毫米波移动基站在线频谱共享方法，其特征在于：
    将所述多个基站中的所述多个目标基站外的基站关闭。
  5. 根据权利要求1所述的毫米波移动基站在线频谱共享方法，其特征在于：
    所述多个用户端划分为多个聚类，任一聚类中的用户端数量不超过该聚类对应的目标基站的射频链路的数量。
  6. 一种基于聚类算法的毫米波移动基站在线频谱共享系统，是具有多个发射装置和多个用户装置的频谱共享的毫米波蜂窝网系统，其特征在于，
    包括：
    所述多个发射装置接收各个用户装置发射的位置信号以获得用户装置的位置信息，并基于聚类算法确定多个聚类中心点，进而基于所述多个聚类中心点移动若干个发射装置获得多个目标发射装置，所述聚类算法基于所述用户装置的数量和所述多个发射装置的射频链路的数量获得多个初始中心点，并基于所述多个初始中心点、所述多个用户装置的数量与位置信息以及各个发射装置的射频链路的数量获得与所述多个用户装置对应的多个聚类中心点；
    其中，各个聚类中心点分别对应一个目标发射装置，所述多个发射装置和所述多个用户装置频谱共享，若所述用户装置移动或出现新的用户装置，则该用户装置由距离最近的目标发射装置服务，若该目标发射装置增加用户装置后射频链路的数量不小于该目标发射装置服务的用户装置的数量，则所述多个目标发射装置不变，若该目标发射装置的射频链路的数量小于该目标发射装置服务的用户装置的数量，则将初始中心点的数量增加并基于所述各个用户装置的位置信息、所述聚类算法和所述各个发射装置重新确定所述多个目标发射装置。
  7. 根据权利要求6所述的毫米波移动基站在线频谱共享系统，其特征在于：
    所述聚类算法为K均值聚类算法。
  8. 根据权利要求6所述的毫米波移动基站在线频谱共享系统，其特征在于：
    各个用户装置均能获得各自对应的位置信息。
  9. 根据权利要求6所述的毫米波移动基站在线频谱共享系统，其特征在于：
    将所述多个发射装置中的所述多个目标发射装置外的发射装置关闭。
  10. 根据权利要求6所述的毫米波移动基站在线频谱共享系统，其特征在于：
    所述多个用户装置划分为多个聚类，任一聚类中的用户装置数量不超过该聚类对应的目标发射装置的射频链路的数量。
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