CN111800737B

CN111800737B - Millimeter wave online spectrum sharing method and system based on clustering algorithm

Info

Publication number: CN111800737B
Application number: CN202010668769.6A
Authority: CN
Inventors: 谢宁; 李卓远
Original assignee: Shenzhen University
Current assignee: Shenzhen University
Priority date: 2020-07-13
Filing date: 2020-07-13
Publication date: 2021-10-12
Anticipated expiration: 2040-07-13
Also published as: CN111800737A

Abstract

The utility model relates to a millimeter wave online spectrum sharing method based on clustering algorithm, which comprises: the base stations determine a plurality of target base stations based on the position information and the clustering algorithm of a plurality of user terminals and a plurality of base stations, each target base station performs signal transmission with the corresponding user terminal, the base stations share the frequency spectrum with the user terminals, 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, if the number of radio frequency links after the user terminal is added by the target base station is not less than the number of the user terminals served by the target base station, the target base stations are unchanged, and if the number of radio frequency links after the user terminal is added by the target base station is less than the number of the user terminals served by the target base station, the number of initial central points is increased, and the target base stations are re-determined based on the position information and the clustering algorithm of each base station and each user terminal. Therefore, the coordination overhead and the calculation complexity of the frequency spectrum sharing of the millimeter wave cellular network system can be effectively reduced.

Description

Millimeter wave online spectrum sharing method and system based on clustering algorithm

Technical Field

The disclosure relates to the technical field of wireless communication, in particular to a millimeter wave online spectrum sharing method and system based on a clustering algorithm.

Background

In modern wireless communications, spectrum resources are at a premium as non-renewable resources. The allocation of spectrum resources in conventional communication protocols is exclusive and dedicated, and in order to improve spectrum utilization, spectrum sharing techniques have emerged, i.e. multiple network operators are allowed to access the same spectrum resources. The working frequency of the millimeter wave cellular network system reaches 10-300GHz, and compared with the traditional electromagnetic wave, the millimeter wave cellular network system has ultra-large bandwidth and can greatly solve the problem of frequency spectrum resource shortage. In the prior art, a millimeter wave cellular network system can be used to realize spectrum sharing, and spectrum sharing in the millimeter wave cellular network system means that multiple network operators are allowed to access the same spectrum resource.

At present, there are research teams that implement spectrum sharing of a millimeter wave cellular network system, for example, non-patent document 1 discloses spectrum sharing in a millimeter wave cellular network through cell association, coordination and beam forming, and an optimization framework based on a joint beam forming design and base station association is proposed to reduce higher multi-user interference caused by spectrum sharing.

However, in the above prior art, there are often two problems with spectrum sharing in the mm wave cellular network system: (1) exchanging large amounts of information between multiple base stations can result in very high coordination overhead; (2) the computational complexity of finding the optimal precoding weighting matrices for multiple base stations is high.

[ reference documents ]

Non-patent document 1: spectrum shading in mm wave Cellular network via Cell Association, coding, and Beamforming. Hossein Shokri-Ghadikolaei November, 2016.

Disclosure of Invention

The present disclosure has been made in view of the above circumstances, and an object thereof is to provide a millimeter wave online spectrum sharing method and system based on a clustering algorithm, which reduce the coordination overhead and computational complexity of spectrum sharing in a millimeter wave cellular network system.

To this end, a first aspect of the present disclosure provides a millimeter wave online spectrum sharing method based on a clustering algorithm, which is an online spectrum sharing method for a millimeter wave cellular network system having a plurality of base stations with fixed locations and a plurality of user terminals, and is characterized by including: the base stations receive position signals which are transmitted by the user terminals and contain position information to obtain the position information of the user terminals, a clustering algorithm and the position information of the base stations are used for determining a plurality of target base stations, the clustering algorithm obtains a plurality of initial central points based on the number of the user terminals and the number of radio frequency links of the base stations, and obtains a plurality of clustering central points corresponding to the user terminals based on the initial central points, the number and the position information of the user terminals and the number of the radio frequency links of the base stations; the method comprises the steps that each clustering center point corresponds to a target base station, the target base stations are base stations with the minimum distance to the clustering center points, a plurality of base stations and a plurality of user side frequency spectrums are shared, if the user side moves or a new user side appears, the user side is served by the target base station with the closest distance, if the number of radio frequency links after the user side is added to the target base station is not smaller than the number of the user sides served by the target base station, the target base stations are not changed, if the number of radio frequency links after the user side is added to the target base station is smaller than the number of the user sides served by the target base station, the number of the initial center points is increased, and the target base stations are determined again based on the position information of each base station and each user side and the clustering algorithm.

In the present disclosure, the base station determines a plurality of target base stations based on the location information of the user terminal and the base station and a clustering algorithm. And each target base station carries out signal transmission with the corresponding user terminal, and the plurality of base stations share the frequency spectrums of the plurality of user terminals. If the user terminal moves or a new user terminal appears, the user terminal is served by the nearest target base station, if the number of the radio frequency links after the user terminal is added by the target base station is not less than the number of the user terminals served by the target base station, a plurality of target base stations are unchanged, and if the number of the radio frequency links after the user terminal is added by the target base station is less than the number of the user terminals served by the target base station, the number of the initial central points is increased, and a plurality of target base stations are determined again based on the position information and the clustering algorithm of each base station and each user terminal. In this case, the coordination overhead and the computational complexity of spectrum sharing of the millimeter wave cellular network system can be effectively reduced.

In the millimeter wave online spectrum sharing method according to the first aspect of the present disclosure, optionally, the clustering algorithm is a K-means clustering algorithm. Thereby, the cluster center point can be obtained better.

In the millimeter wave online spectrum sharing method according to the first aspect of the present disclosure, optionally, each user side can obtain respective corresponding location information. Thereby, the location information of each user terminal can be obtained.

In the millimeter wave online spectrum sharing method according to the first aspect of the present disclosure, optionally, base stations other than the target base stations in the plurality of base stations are turned off. This can contribute to reduction in

The consumption of energy.

In the millimeter wave online spectrum sharing method according to the first aspect of the present disclosure, optionally, the plurality of user terminals are divided into a plurality of clusters, and the number of user terminals in any cluster does not exceed the number of radio frequency links of the target base station corresponding to the cluster. Therefore, the base station and the user terminal can work better.

A second aspect of the present disclosure provides a millimeter wave online spectrum sharing system based on a clustering algorithm, which is a millimeter wave cellular network system having a plurality of fixed-position transmitting devices and a plurality of user devices for online spectrum sharing, and includes: the plurality of transmitting devices receive position signals containing position information transmitted by each user device to obtain the position information of the user devices, and determine a plurality of target transmitting devices based on a clustering algorithm and the position information of the plurality of transmitting devices, wherein the clustering algorithm obtains a plurality of initial central points based on the number of the user devices and the number of radio frequency links of the transmitting devices, and obtains a plurality of clustering central points corresponding to the plurality of user devices based on the plurality of initial central points, the number and the position information of the plurality of user devices and the number of the radio frequency links of each transmitting device; wherein, each cluster center point corresponds to a target emitting device, the target emitting device is the emitting device with the minimum distance with the cluster center point, a plurality of emitting devices and a plurality of user devices share the frequency spectrum, if the user device moves or a new user device appears, the user device is served by the nearest target transmitting device, if the number of radio frequency links after the target transmitting device increases the user device is not less than the number of user devices served by the target transmitting device, the plurality of target transmitting devices are not changed, if the number of radio frequency links after the target transmitting device increases the user devices is less than the number of the user devices served by the target transmitting device, the number of initial center points is increased and the plurality of target transmitting devices is re-determined based on the location information of each of the transmitting devices and each of the user devices and the clustering algorithm.

In the disclosure, a transmitting device determines a plurality of target transmitting devices based on location information and a clustering algorithm of a user device and the transmitting device, each target transmitting device performs signal transmission with a corresponding user device, and the plurality of transmitting devices share a frequency spectrum with the plurality of user devices. If the user device moves or a new user device appears, the user device is served by a target transmitting device with the closest distance, if the number of radio frequency links after the target transmitting device increases the user device is not less than the number of the user devices served by the target transmitting device, a plurality of target transmitting devices are unchanged, if the number of radio frequency links after the target transmitting device increases the user side is less than the number of the user devices served by the target transmitting device, the number of initial central points is increased, and the plurality of target transmitting devices are re-determined based on the position information and the clustering algorithm of each transmitting device and each user device. In this case, the coordination overhead and the computational complexity of spectrum sharing of the millimeter wave cellular network system can be effectively reduced.

In the millimeter wave online spectrum sharing system according to the second aspect of the present disclosure, optionally, the clustering algorithm is a K-means clustering algorithm. Thereby, the cluster center point can be obtained better.

In the millimeter wave online spectrum sharing system according to the second aspect of the present disclosure, optionally, each user device can obtain the corresponding location information. This enables position information of each user apparatus to be obtained.

In the millimeter wave online spectrum sharing system according to the second aspect of the present disclosure, optionally, a transmitting device other than the target transmitting devices in the plurality of transmitting devices is turned off. This can contribute to reduction in energy consumption.

In the millimeter wave online spectrum sharing system according to the second aspect of the present disclosure, optionally, the plurality of user devices are divided into a plurality of clusters, and the number of user devices in any cluster does not exceed the number of radio frequency links of the target transmitting device corresponding to the cluster. This enables the transmitting device and the user device to function better.

According to the method and the system for sharing the millimeter wave online spectrum based on the clustering algorithm, the coordination overhead and the calculation complexity of spectrum sharing of the millimeter wave cellular network system can be reduced.

Drawings

Fig. 1 is a schematic view illustrating an application scenario of a millimeter wave online spectrum sharing method based on a clustering algorithm according to an example of the present disclosure.

Fig. 2 is a flow chart illustrating a method of determining a target base station in accordance with an example of the present disclosure.

Fig. 3 is a flow chart illustrating a method of determining a cluster center point in accordance with an example of the present disclosure.

Fig. 4 is a flow diagram illustrating a performance detection method for an online spectrum sharing method according to an example of the present disclosure.

Fig. 5 is a waveform diagram illustrating a target total rate as a function of a signal-to-noise ratio for a user terminal according to an example of the present disclosure.

Fig. 6 is a waveform diagram illustrating a target total rate of a user terminal as a function of the number of antennas of a target base station according to an example of the present disclosure.

Fig. 7 is a waveform diagram illustrating a target total rate of a user terminal as a function of the number of antennas of the user terminal according to an example of the present disclosure.

Fig. 8 is a waveform diagram illustrating a target total rate of the user terminals as a function of the number of user terminals according to an example of the present disclosure.

Fig. 9 is a waveform diagram illustrating a target total rate as a function of a number of radio frequency links to which examples of the present disclosure relate.

Fig. 10 is a bar graph illustrating target total rate of a user terminal as a function of carrier frequency in accordance with an example of the present disclosure.

Fig. 11 is a bar graph illustrating target total rate of a user terminal as a function of the user terminal according to an example of the present disclosure.

Fig. 12 is a block diagram illustrating a millimeter wave online spectrum sharing system based on a clustering algorithm according to an example of the present disclosure.

Detailed Description

Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In the following description, the same components are denoted by the same reference numerals, and redundant description thereof is omitted. The drawings are schematic and the ratio of the dimensions of the components and the shapes of the components may be different from the actual ones.

The disclosure provides a millimeter wave online spectrum sharing method and system based on a clustering algorithm. In the present disclosure, the millimeter wave online spectrum sharing method and system based on the clustering algorithm may be applied to a millimeter wave cellular network system, may implement spectrum sharing of the millimeter wave cellular network system, and may significantly reduce coordination overhead and computational complexity of spectrum sharing of the millimeter wave cellular network system. The present disclosure is described in detail below with reference to the attached drawings.

Fig. 1 is a schematic view illustrating an application scenario of a millimeter wave online spectrum sharing method based on a clustering algorithm according to an example of the present disclosure. As shown in fig. 1, the millimeter wave online spectrum sharing method (referred to as "online spectrum sharing method" for short) is an online spectrum sharing method of a millimeter wave cellular network system having a plurality of base stations at fixed locations and a plurality of user terminals. A plurality of target base stations (described later) in the plurality of base stations may perform signal transmission with a plurality of corresponding user terminals. The base station and the user terminal can share a frequency spectrum and can work in a millimeter wave cellular network system (or millimeter wave cellular network).

In some examples, the number of base stations may be multiple. The number of antennas per base station may be multiple. The number of the user terminals may be plural. The number of antennas at each user terminal may be multiple. In some examples, the location of the base station may be fixed. The location of the user terminal may be mobile. In some examples, the number of radio frequency links per base station may be multiple. For example, as shown in fig. 1, the mmwave cellular network system may include 12 fixed-location base stations (e.g., base station 100, base station 101, etc.) and 13 user terminals (e.g., user terminal 200, user terminal 201, etc.). Wherein one ue is a new ue (e.g., ue 212, described later), and each base station may have 3 uesRadio frequency links (e.g., radio frequency link 400, radio frequency link 401, and radio frequency link 402 that base station 101 has). In some examples, the mmwave cellular network system may be in a low load state, i.e., N_b|B_∑|＞＞|M_∑L. Wherein M is_∑Expressed as a set of all user terminals, B_∑Expressed as the set of all target base stations, | B_∑I is expressed as the number of all target base stations, i.e. the number of base stations serving a plurality of clients, N_bIndicating the number of ues serving target bs b (i.e. target bs numbered b).

In the present disclosure, a base station (e.g., access point) may refer to a device in an access network that communicates over the air-interface, through one or more sectors, with wireless terminals. The base station may be configured to interconvert received air frames and IP frames as a router between the wireless terminal and the rest of the access network, which may include an Internet Protocol (IP) network. The base station may also coordinate management of attributes for the air interface. For example, the Base Station may be a Base Transceiver Station (BTS) in GSM or CDMA, a Base Station (NodeB) in WCDMA, or an evolved Node B (NodeB or eNB or e-NodeB) in LTE.

In the present disclosure, the user terminal may be a user. The user may include, but is not limited to, a user device. The user Device may include, but is not limited to, various electronic devices such as a smart Phone, a notebook Computer, a Personal Computer (PC), a Personal Digital Assistant (PDA), a Mobile Internet Device (MID), a wearable Device (e.g., a smart watch, a smart bracelet, and smart glasses), wherein an operating system of the user Device may include, but is not limited to, an Android operating system, an IOS operating system, a Symbian operating system, a blackberry operating system, a Windows Phone8 operating system, and so on.

In some examples, each user terminal may obtain respective location information and may transmit a location signal containing the respective location information to the base station. In some examples, each base station may obtain respective location information. Thus, the position information of the user terminal and the base station can be obtained.

In some examples, the plurality of base stations may determine the target base station according to the location information of each user terminal and the location information of the base station using a clustering algorithm. In some examples, the target base station may be a base station determined to serve a plurality of user terminals, that is, the target base station is in an operating state during subsequent service. In some examples, base stations other than the target base stations in the plurality of base stations may be turned off, that is, other base stations in the plurality of base stations that are not the target base station may be turned off. This can contribute to reduction in energy consumption.

In some examples, the clustering algorithm may adopt a K-means clustering algorithm (i.e., an unsupervised clustering algorithm), and the plurality of base stations may determine the plurality of clustering center points according to the K-means clustering algorithm, respective location information of the base stations, location information of the user terminal, and the number of radio frequency links of the base stations. Thereby, the cluster center point can be obtained better. However, the examples of the present disclosure are not limited thereto, and in some examples, other clustering algorithms, for example, a K-center clustering algorithm, may also be used in the present embodiment.

In some examples, as shown in fig. 2, the method of determining a target base station using a clustering algorithm may include the steps of: obtaining a plurality of initial central points based on the number of the user terminals and the number of the radio frequency links of the base station (step S110); obtaining a plurality of cluster center points corresponding to the plurality of user terminals based on the plurality of initial center points, the number and location information of the plurality of user terminals, and the number of radio frequency links of each base station (step S120); a target base station is determined based on the plurality of cluster center points and the location information of the base station (step S130).

In step S110, a plurality of initial central points may be obtained based on the number of the user terminals and the number of the radio frequency links of the base station.

In some examples, the number of user terminals may be no greater than the number of radio frequency links of the corresponding base station. Thereby, the base station can be enabledAnd the user side works better. For example, the number of radio frequency links of a base station may be N_rThen the base station can serve N simultaneously_rA subscriber end, i.e. the base station can simultaneously communicate with N_rEach user terminal performs signal transmission.

In some examples, the plurality of initial center points may be obtained based on a number of user terminals and a number of radio frequency links of the base station. The number of initial center points K may satisfy:

wherein M is_∑Expressed as a set of all clients, | M_∑I is expressed as the number of clients, N_rExpressed as the number of radio frequency links of the base station. In some examples, K points may be chosen randomly as the initial center point. For example, K ues may be randomly selected and the corresponding positions thereof are used as the initial center points. For example, based on the 12 fixed-location base stations shown in fig. 1, 12 clients (except the client 212 in fig. 1), and each base station may have 3 rf links, the number of initial center points is 4, wherein the client 212 in fig. 1 is a new client (described later). In this case, 4 ues can be randomly selected and their positions can be used as the initial center point.

In step S120, a plurality of cluster center points corresponding to the plurality of ues may be obtained based on the plurality of initial center points, the number and location information of the plurality of ues, and the number of rf links of each base station.

In some examples, as shown in fig. 3, the method for determining the cluster center point in step S120 may include the following steps: taking the initial center point as an initial clustering center point (step S121); clustering division is carried out on each user side based on the position information of each user side and the initial clustering center point (step S122); obtaining a central point of each cluster from the divided clusters (step S123); judging whether the elements in each cluster are not changed (step S124); if the cluster center point is changed, taking the center point of each cluster as an initial cluster center point (step S125); if not, judging whether the number of the corresponding user sides in each cluster is not greater than the number of the radio frequency links of any base station (step S126); if so, increasing the number of the initial center points by one, wherein the increased initial center points can be randomly selected (step S127); if not, the center point of each cluster is used as the cluster center point (step S128).

In some examples, in step S121, the initial center point may be taken as the initial cluster center point.

In step S122, each ue is clustered based on the location information of each ue and the initial clustering center point.

In some examples, in step S122, the distance between the user terminal and each initial cluster center point may be calculated according to the location information of the user terminal. In some examples, each user terminal may correspond to an initial cluster center point. For example, the initial cluster center point with smaller distance of each user end may be used as the corresponding initial cluster center point of the user end. This makes it possible to perform cluster division for all the clients. In some examples, each initial cluster center point may correspond to one or more user terminals.

In step S123, the center point of each cluster is obtained from the divided clusters.

In some examples, in step S123, center points respectively corresponding to the respective clusters may be obtained from the respective clusters. In some examples, may be according to

To determine the center point corresponding to each cluster, wherein,

denoted as the k-th cluster, and,

expressed as the number of clients in the k-th cluster, (x)_MT,m,y_MT,m) Denoted as location information of the mth ue, m may be the ue in the cluster. In some examples, the elements of the respective clusters may include corresponding user ends and center points.

In step S124, it is determined whether or not the elements in each cluster are not changing.

In some examples, in step S124, the currently obtained cluster and the previously obtained cluster may be compared to determine whether elements in each cluster are not changed, for example, whether a central point corresponding to a k-th cluster and a central point corresponding to a user end and a user end corresponding to a k-th cluster obtained last time are the same. If so, step S125 may continue. If no change has occurred, step S126 may continue.

However, the examples of the present disclosure are not limited thereto, and in some examples, the objective function may be calculated according to the location information of the user terminal and the central point corresponding to the cluster, where the objective function satisfies:

wherein K is 1,2, K, M is in the middle of M_∑，

Denoted as the kth cluster, (x)_MT,m,y_MT,m) Expressed as location information, μ, of the mth subscriber terminal_kExpressed as the center point (or mean) corresponding to the kth cluster, and K represents the number of center points. The number of center points may be the same as the number of initial center points. And (4) judging whether the objective function corresponding to each cluster does not change obviously or not according to the formula (2). In some examples, whether the result of the objective function corresponding to each cluster does not change significantly may be determined by comparing the currently obtained cluster with the previously obtained cluster, for example, whether the result of the objective function corresponding to the k-th cluster obtained currently and the k-th cluster obtained previously changes significantly may be determined. If a significant change occurs, it can continueStep S125. If no significant change has occurred, step S126 may be continued.

In some examples, as described above, the present embodiment may employ a K-means clustering algorithm. In some examples, 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 ue can be divided into more suitable clusters.

In step S125, if there is a change, that is, if there is a change in the elements or corresponding objective functions in each cluster, step S125 may be continued, that is, the center point of each cluster is used as the initial cluster center point. Thereafter, steps S122 to S124 may be repeated. In this case, it is possible to facilitate the subsequent acquisition of a more suitable clustering center point.

In step S126, if no change occurs, that is, if the elements in each cluster or the corresponding objective function do not change, step S126 may be continued, that is, the number of the user terminals corresponding to each cluster and the number of the radio frequency links of the base station that are currently obtained are compared, and it is determined whether the number of the user terminals corresponding to each cluster is not greater than the number of the radio frequency links of any base station. If so, step S127 may continue. If not, step S128 may continue. In step S127, if it is greater than the predetermined threshold, the number of the initial center points may be increased by one, and the increased initial center points may be randomly selected. In some examples, the increased initial center point may be selected in the same manner as the previous initial center point, such as randomly selecting a user terminal and setting its location as the increased initial center point. Steps S121 to S126 may be repeated after step S127 is performed. Therefore, the target base station obtained subsequently can transmit signals to the corresponding user terminal at the same time.

In step S128, if not, the center points of the respective clusters currently obtained (e.g., the center point 301, the center point 311, the center point 321, and the center point 331 in fig. 1) may be taken as cluster center points. Thereby enabling to obtain a cluster center point. In some examples, the number of center points may be the same as the number of cluster center points.

In some examples, the target base station may be determined in step S130 based on the plurality of cluster center points and the location information of the base station obtained in step S120 described above.

In some examples, in step S130, the target base station may be determined among the plurality of base stations based on the plurality of cluster center points and the location information of the plurality of base stations. In some examples, the number of target base stations may be the same as the number of cluster center points. In some examples, each cluster center point may correspond to one target base station, and the target base station may be a base station having a minimum distance from the cluster center point. In some examples, the first and second images may be obtained by

And obtaining the base station with the minimum distance from the k-th clustering center point in the plurality of base stations, namely the base station can be used as the target base station. Wherein K is 1,2_∑，B_∑Expressed as the sum of all base stations, (x)_BS,b,y_BS,b) Expressed as position information of the b-th base station, mu_kIndicated as the cluster center point (or mean) corresponding to the kth cluster. For example, as shown in fig. 1, the distance from the base station 101 to the cluster center point 301 is the smallest compared to other base stations, and therefore the base station 101 can be the target base station. Then, for other cluster center points, the base station 102, the base station 103, and the base station 104 may be determined as target base stations, respectively. This enables the location of the target base station to be determined from a plurality of base stations at fixed locations.

In some examples, the plurality of user terminals may be divided into a plurality of clusters using a clustering algorithm, where each cluster may contain one or more user terminals. In some examples, each cluster may correspond to one target base station. For example, as shown in fig. 1, 12 user terminals can be divided into 4 clusters, wherein the cluster 300 can include the user terminal 200, the user terminal 201, and the user terminal 202, the cluster 310 can include the user terminal 203, the user terminal 204, and the user terminal 205, the cluster 320 can include the user terminal 206, the user terminal 207, and the user terminal 208, and the cluster 330 can include the user terminal 209, the user terminal 210, and the user terminal 211. In some examples, the number of radio frequency links of the target base station corresponding to each cluster may not be less than the number of the user terminals in the cluster. Therefore, the base station and the user terminal can work better. In some examples, the target base station may transmit signals to the user terminals in the corresponding cluster at the same time. For example, the cluster 300 includes the target base station (i.e., base station 101), the ue 200, the ue 201, and the ue 202, wherein the number of the radio links of the base station 101 is 3, the number of the ues served by the base station 101 is less than or equal to the number of the radio links of the base station 101, and the base station 101 can simultaneously transmit signals to its corresponding ues (i.e., the ue 200, the ue 201, and the ue 202).

In some examples, an existing ue may be moved or a new ue (e.g., the ue 212 in fig. 1) may be added, and the cluster corresponding to the ue may be determined based on the location information of the ue and the respective cluster center points, so as to determine the target base station corresponding to the ue. Specifically, the cluster corresponding to the ue can be determined according to the distance between the ue and each cluster center point, so as to determine the target base station corresponding to the cluster, where the ue can be served by the target base station. In some examples, the cluster corresponding to the cluster center point closest to the user end may be used as the cluster corresponding to the user end. For example, can be obtained by

And obtaining a cluster center point with the minimum distance with the user terminal m from the plurality of cluster center points, so as to obtain a cluster corresponding to the user terminal m, wherein the target base station corresponding to the cluster can serve the user terminal.

In some examples, if the number of radio frequency links after the target base station (i.e., the target base station closest to the mobile or new ue) is added to the ue is not less than the number of ues currently corresponding to the target base station, the current cluster may not be changed, i.e., the existing target base stations may be maintained (i.e., the determined target base stations may not be changed). In some examples, if the number of radio frequency links of the target base station is less than the number of the user terminals currently corresponding to the target base station, the current cluster may be changed, i.e., the target base station may be re-determined. For example, as shown in fig. 1, if a new user terminal (e.g., the user terminal 212) is added, and the user terminal 212 is closest to the target base station (the base station 103), it may be determined that the user terminal 212 corresponds to the target base station (the base station 103), the number of the radio frequency links of the target base station (the base station 103) is 3, and at this time, the number of the user terminals corresponding to the target base station (the base station 103) is 4, the current cluster may be changed, and the target base station may be re-determined, so that the base station and the user terminal may work better. In some examples, the target base station may be re-determined based on a clustering algorithm, location information of the respective base stations and the user terminals. In some examples, if an existing ue is moved or a new ue is added so that the number of radio frequency links of the target base station corresponding to the new ue is smaller than the number of ues corresponding to the target base station, the number of initial center points may be increased by one (for example, step S127 is re-entered), and the target base station may be re-determined based on the clustering algorithm.

In this embodiment, the clustering center point may be determined according to the clustering algorithm and the location information of the user terminal. Specifically, the base station may receive the location information of the user terminal and determine a cluster center point through a clustering algorithm. In this case, the coordination overhead can be effectively reduced. In some examples, the computational complexity of a base station may be determined from a clustering algorithm, where each iteration of the clustering algorithm may be divided into three types to obtain the computational complexity: (1) in step S124, it can be determined whether the objective function changes significantly by the calculation formula (2), where 5 operations are required for one ue, and all ues need to be operated

And (5) performing secondary operation. (2) In step S122, the ue can be clustered and divided according to the location information of the ue and the initial clustering center point, wherein all ues need to be clustered

And (5) performing secondary operation. (3) In step S123, the center point of each cluster may be obtained by equation (1), where all clusters need to be processed

And (5) performing secondary operation.

In this embodiment, the target base station may be determined from a plurality of base stations according to the clustering center points and the position information of the base stations, and the target base station may be determined by comparing the distances between each base station and each clustering center point. Wherein it is required for all base stations

And (5) performing secondary operation. In this embodiment, the ue can move or add a new ue, and the target bs corresponding to the ue can be determined by comparing the distances from the ue to the cluster center points. Wherein, K operations are required for the ue.

In some examples, assume that the clustering algorithm performs T at step S125₁A second iteration of T at step S127₂And performing iteration, so as to obtain the total operation times of the target base station determined by the method. The total operation times can satisfy:

in this case, the computational complexity of the base station can be effectively reduced.

In this embodiment, the online spectrum sharing method may include that the plurality of base stations may determine one or more target base stations based on a clustering algorithm, location information of each user terminal, and the like; the target base station can transmit signals with the corresponding user terminal; the target base station can share the frequency spectrum with the user terminal, and the like.

In some examples, performance detection may be performed for the online spectrum sharing methods described above.

In this embodiment, as shown in fig. 4, the performance detection method may include the following steps: each target base station transmits signals to a corresponding user terminal through a plurality of paths, the signals obtain second signals through a wireless channel, the user terminal receives the second signals, and a signal matrix, a combined weight vector and a precoding weight vector between the target base station and the user terminal are obtained based on the corresponding target base station, the user terminal and channel state information (step S10); obtaining an interference signal and a target signal based on the combined weight vector, the precoding weight vector, the signal matrix and the average transmission power of the target base station, and further obtaining an average rate of the user terminal receiving the second signal based on the noise signal and the bandwidth of the shared spectrum (step S20); the total rate of the user side is obtained based on the average rate, the plurality of target base stations, and the corresponding relationship between the plurality of target base stations and the user side, the total rates of the user sides are summed to obtain the target total rate, and the performance of the millimeter wave cellular network system is detected based on the target total rate (step S30).

In step S10, each target base station may transmit signals to a corresponding user end through multiple paths, the signals obtain second signals through a wireless channel, and the user end receives the second signals and obtains a signal matrix, a combined weight vector, and a precoding weight vector between the target base station and the user end based on the corresponding target base station, the user end, and channel state information.

Specifically, each target base station transmits signals to a corresponding user terminal through a plurality of paths, the signals obtain second signals through a wireless channel, the second signals comprise target signals, interference signals and noise signals, the user terminal receives the second signals, the arrival angles and departure angles corresponding to the plurality of paths are obtained based on the position information and channel state information of the corresponding target base station and the user terminal, the guide vector of the arrival angles and the guide vector of the departure angle are obtained based on 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 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 combined weighting vector between the target base station and the user terminal is obtained based on the number of radio frequency links of the target base station, the arrival angle of the target path and the guide vector of the arrival angle of the target path, and acquiring a precoding weighting vector between the target base station and the user terminal based on the combined weighting vector and the signal matrix between the target base station and the user terminal.

In some examples, the target base station may be shared with the user side spectrum. For example, the target base station and the user terminal may share a frequency band with a bandwidth W. In some examples, the target base station and the user terminal may be distributed from separate poisson within the same area.

In some examples, in step S10, 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. And the user side is in the cluster corresponding to the target base station. In some examples, the target base station does not transmit signals to the user terminal in other clusters outside the corresponding cluster, i.e., the target base station and the user terminal are not associated. In some examples, the association status of the target base station and the user terminal may be represented by a binary variable. For example, using a binary variable a_bmIndicating the association status of base station b with mobile terminal m, a if base station b can transmit signals to mobile terminal m_bm1 is ═ 1; otherwise, a_bm＝0。

In some examples, the number of paths between each target base station and the corresponding user terminal may be one or more. The target base station can transmit signals to the corresponding user terminal through any path. Wherein each path may correspond to the same or different channel gains. In some examples, it may be assumed that the number of paths between the target base station b and the mobile terminal m is L_bm. Wherein, the channel gain of the l path is represented as h_bml. In some examples, a complex gaussian random variable with zero mean channel gain may be assumed and satisfied

Wherein the content of the first and second substances,

is a large scale lognormal path fading related to distance,

can satisfy

Wherein alpha is_dIs a path loss index satisfying alpha_d≥2。d_bmIs the distance between the base station b and the mobile terminal m, λ is the wavelength of the signal, and λ is c/f_c。c＝3×10⁸m/s，f_cIs the carrier frequency of the signal.

In some examples, the number of antennas of the target base station may be one or more. For example, the number of antennas of the target base station may be N_BSThe number of antennas at the user end may be one or more. For example, the number of antennas at the user end may be N_MT。

In some examples, the signal is obtained as a second signal via a wireless channel, and the user terminal may receive the second signal. In some examples, the arrival angle and the departure angle respectively corresponding to the several paths may be obtained based on the location information and the channel state information of the corresponding target base station, the user terminal. In some examples, the angle of arrival and the angle of departure may be determined by the target base station, the spatial distribution of the user terminal, and scattering in the communication environment. The spatial distribution of the target base station and the user terminal can be obtained from the position information of the target base station and the user terminal. Scattering in a communication environment can be obtained from channel state information. In some examples, if the target base station and the user terminal may obey independent homogeneous poisson distribution, the arrival angle and departure angle may follow a uniform distribution [0,2 pi ]]Is used to determine the independent random variable of (1). For example, the arrival angle and departure angle of the l-th path between the target base station b and the user end m may be respectively represented as θ_MT,bmlAnd theta_BS,bmlThe target base station and the user terminal may be subjected to an independent homogeneous poisson point process, where θ_MT,bmlAnd theta_BS,bmlMay follow a uniform distribution [0,2 π]Is used to determine the independent random variable of (1).

In some examples, the user terminal may be based on the antenna of the target base stationAnd obtaining the guiding vector of the arrival angle and the guiding vector of the angle of departure field by the quantity and the quantity of the antennas at the user end. In some examples, the guideline vector for the angle of arrival may satisfy:

(4) wherein the angle of arrival θ can be determined_MT,bmlSubstituting, thereby obtaining a guidance vector of the arrival angle of the l-th path between the target base station b and the user end m, wherein the guidance vector of the angle of departure can satisfy:

wherein the angle of departure theta can be set_BS,bmlSubstituting, thereby obtaining a guidance vector of the departure angle of the l-th path between the target base station b and the user end m.

In some examples, the ue may obtain a signal matrix between the target base station and the ue based on the number of paths between the target base station and the ue, the channel gain corresponding to each path, the number of antennas of the target base station, and the number of antennas of the ue. For example, the signal matrix between the target base station b and the mobile terminal m may satisfy:

in some examples, the user terminal may obtain a combined weighting vector between the target base station and the user terminal based on the number of radio frequency links of the target base station, the arrival angle of the target path, and the guidance vector of the arrival angle of the target path. The ue can obtain a precoding weighting vector between the target base station and the ue based on the combined weighting vector and the signal matrix between the target base station and the ue. In some examples, the number of radio frequency links of the target base station may be one or more. For example, the number of radio frequency links of the target base station may be N_rI.e. the target base station can move to N at most simultaneously_rEach subscriber terminal transmits a signal. If the number of the user terminals corresponding to the target base station is greater than the number of the radio frequency links, the target base station is overloadedCausing problems at the target base station.

In some examples, the number of radio frequency links of each target base station may be only one, and each user terminal may obtain an accurate angle of arrival. For example, the user end m can obtain the accurate arrival angle θ of the ith path_MT,bml. In some examples, the target path may be a path with the largest channel gain among several paths between the target base station and the user terminal. Therefore, the combined weight vector between the ue and the base station can be obtained conveniently. In some examples, when the target base station b transmits a signal to the user terminal m, a combined weight vector between the target base station b and the user terminal m may be obtained based on equation (4), and the combined weight vector w_MT,bmCan satisfy the following conditions:

wherein the content of the first and second substances,

path l expressed as the maximum channel gain^*(i.e., the target path) corresponding angle of arrival. In some examples, precoding weight vector w between target base station b and user terminal m_BS,bmCan satisfy

In step S20, the ue may obtain the interference signal and the target signal based on the combined weight vector, the precoding weight vector, the signal matrix, and the average transmission power of the target base station, and further obtain the average rate at which the ue receives the second signal based on the noise signal and the bandwidth of the shared spectrum.

Specifically, the ue may obtain the interfering signal and the target signal based on the signal matrix, the combining weight vector, the precoding weight vector, and the average transmission power of the corresponding target base station. The ue can obtain an average rate at which the ue receives the second signal based on the interfering signal, the target signal, the noise signal, and the bandwidth of the shared spectrum of the target base station and the ue.

In some examples, the target base station may transmit a signal to the corresponding user terminal. The signal may be a second signal via a 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.

In some examples, the ue may obtain the target signal received by the ue based on a signal matrix between the ue and the corresponding target base station, the combining weight vector, the precoding weight vector, and an average transmission power of the target base station. For example, the average transmission power of the target base station b may be P_BSNormalizing the average transmission power may satisfy:

(9) when the target base station b transmits a signal to the user end m, the target signal received by the user end can be obtained based on equations (6) to (9), which can satisfy:

in some examples, multiple target base stations in an active state may correspond to the same operator or to multiple operators. Any target base station may correspond to one operator. The plurality of ues may correspond to the same operator or to a plurality of operators. Wherein, any user terminal can correspond to an operator. In some examples, the plurality of target base stations may correspond to z operators. Wherein, the ith operator may have a plurality of target base stations, and the set of all target base stations corresponding to the ith operator may be denoted as B_iThen the set of all target base stations corresponding to z operators can be represented as B_∑＝B₁∪B₂∪...∪B_Z. The ith operator may serve multiple ues, and the set of all ues served by the ith operator may be denoted as M_iThen the set of all the ue terminals corresponding to z operators can be represented as M_∑＝M₁∪M₂∪...∪M_Z。

In some examples, any target base station may serve one or more user terminals. For exampleThe target base station b can serve multiple ues. The set of all the user terminals served by the target base station b can be denoted as a_b。

In some examples, there may be multiple target base stations in operation. Any target base station can transmit signals to a plurality of user terminals at the same time. In some examples, the user terminal may receive the second signal. The interference signals in the second signals may include first interference signals generated by transmitting signals from the same target base station to other corresponding subscriber terminals, second interference signals generated by transmitting signals from other target base stations of the same operator to respective corresponding subscriber terminals, and third interference signals generated by transmitting signals from target base stations of different operators to respective corresponding subscriber terminals. In some examples, when the target base station b transmits a signal to the user terminal m, assuming that the target base station b corresponds to the z-th operator, the first interference signal may satisfy:

the second interfering signal may satisfy:

the third interfering signal may satisfy:

in some examples, since the coverage of the millimeter wave cellular network system is small, coordination between base stations at long distances may not be required, and the second interfering signal and the third interfering signal may be negligible.

In some examples, the user equipment may receive a second signal, the noise signal in the second signal may be a zero-mean complex gaussian variable, and the noise signal in the second signal may satisfy:

wherein the content of the first and second substances,

is the variance.

At one endIn some examples, when the target bs b transmits a signal to the ue m, the average rate R of the ue m receiving information (e.g., the second signal) from the target bs b can be obtained according to equations (10) to (14)_bmCan satisfy the following conditions:

wherein, W can be expressed as a shared bandwidth when the target base station and the user terminal spectrum are shared,

may be a signal to interference plus noise ratio.

In step S30, the ue may obtain a total rate of the ue based on the average rate, the multiple target base stations, and the corresponding relationship between the multiple target base stations and the ue, sum the total rates of the ues to obtain a target total rate, and further detect the performance of the mm wave cellular network system based on the target total rate.

In some examples, when the target bs b transmits a signal to the ue m, assuming that the target bs b corresponds to the z-th operator, the total rate of the ue m receiving information (e.g., the second signal) from all target bss corresponding to the operator z, the total rate R, can be obtained from equation (15) according to the corresponding relationship between the ue m and other target bss in the z-th operator_mCan satisfy the following conditions:

in some examples, the ue may receive signals transmitted from corresponding target base stations in corresponding operators, and sum total rates corresponding to all ues to obtain a target total rate, which is R_∑Can satisfy the following conditions:

thereby, a target total rate can be obtained, and the performance of spectrum sharing (i.e., millimeter wave cellular network system) of the target base station and the user terminal (described later) can be detected based on the target total rate.

In some examples, as in FIG. 5As shown in fig. 10, the performance of the millimeter wave cellular network system is detected by analyzing the target total rate variation curves of the ue according to the present disclosure and the conventional scheme (i.e., the scheme disclosed in non-patent document 1), where a is the target total rate variation curve (or histogram) of the ue according to the present disclosure, and B is the target total rate variation curve (or histogram) of the ue according to the conventional scheme. As shown in FIGS. 5 to 10, the system parameters satisfy the total bandwidth of 2GHz, f_c32GHz and alpha _d2. In addition, the number of the radio frequency links of each user terminal is 1, that is, each user terminal can only receive the information sent by one target base station.

Fig. 5 is a waveform diagram illustrating a target total rate as a function of a signal-to-noise ratio for a user terminal according to an example of the present disclosure. Wherein the signal-to-noise ratio is satisfied

In some examples, as shown in fig. 5, the number of antennas per target base station is 20, i.e., N_BSThe number of antennas per subscriber terminal is 5, i.e. N, 20_MTThe distribution frequency of the mobile terminal is 100 per square kilometer, and the number of radio frequency links of each target base station is 5, namely N_rAs 5, the total target rate of the ue in the present disclosure and the conventional scheme increases with the snr and has the same variation curve, which indicates that the present disclosure and the conventional scheme have the same performance under the condition that other system parameters are the same.

Fig. 6 is a waveform diagram illustrating a target total rate of a user terminal as a function of the number of antennas of a target base station according to an example of the present disclosure. Fig. 7 is a waveform diagram illustrating a target total rate of a user terminal as a function of the number of antennas of the user terminal according to an example of the present disclosure.

In some examples, as shown in fig. 6, the snr is 30dB, and the number of antennas per user end is 5, i.e., N_MTThe distribution frequency of the mobile terminal is 100 per square kilometer, and the number of radio frequency links of each target base station is 5, namely N_r5, the user end of the present disclosure and legacy scheme targetsThe total rate increases with the number of antennas per target base station, and because of the same variation curve, the disclosed and conventional schemes have the same performance with the same other system parameters.

In some examples, as shown in fig. 7, the signal-to-noise ratio is 30dB, and the number of antennas per target base station is 20, i.e., N_BSThe distribution frequency of the mobile terminal is 100 per square kilometer, and the number of radio frequency links of each target base station is 5, namely N_rAs 5, the total target rate of the ue in the present disclosure and the conventional scheme increases with the number of antennas in the ue, and has the same variation curve, which indicates that the present disclosure and the conventional scheme have the same performance under the condition that other system parameters are the same. From fig. 6 and 7, the target total rate varies with N_BSOr N_MTThe number of antennas is increased, because the gain of the antennas is increased and the interference signal is decreased as the number of antennas is increased, wherein the target total rate is raised in a logarithmic manner, which means that under the signal-to-interference-and-noise ratio, the effect of increasing more antenna units on raising the target total rate is not great. In this case, the total bandwidth may be increased or parallel data may be transmitted for the user side, thereby enabling a further increase in the target total rate. The increase in the number of antennas per user side has a greater effect on the target total rate than the increase in the number of antennas per target base station. To achieve the same target total rate, the number of antennas to be added at the target base station is required to be greater than the number of antennas to be added at the user terminal. For example, when the target total rate reaches 10^-3When bits/s/Hz, N is needed in FIG. 6_BS40 and N_MTN is required in fig. 7 as 5_BS20 and N _MT9. However, for large antenna elements, the size and power of the user terminal are more limited than those of the target base station.

In some examples, as shown in fig. 8, the signal-to-noise ratio is 30dB, and the number of antennas per target base station is 20, i.e., N_BSThe number of antennas per subscriber terminal is 5, i.e. N, 20_MTThe number of radio links per target base station is 5, i.e. N_rAs 5, the total target rate of the ue in the present disclosure and the conventional scheme increases with the number of the ue, wherein the number of the ue increases by changing the number of the ue per square kilometer and has the same variation curve, which indicates that the present disclosure and the conventional scheme have the same performance under the condition that other system parameters are the same. As can be seen from fig. 8, as the number of the ue increases, the target total rate rises logarithmically, because increasing the number of the ue contributes more to the target total rate, but also increases the interference signal.

Fig. 9 is a waveform diagram illustrating a target total rate as a function of a number of radio frequency links to which examples of the present disclosure relate. In some examples, as shown in fig. 9, the signal-to-noise ratio is 30dB, and the number of antennas per target base station is 20, i.e., N_BSThe number of antennas per subscriber terminal is 5, i.e. N, 20_MTThe distribution frequency of the mobile terminals is 100 per square kilometer, the total target rate of the user side of the present disclosure and the conventional scheme decreases with the increase of the number of radio frequency links of each target base station, and has the same variation curve, which shows that the present disclosure and the conventional scheme have the same performance under the condition that other system parameters are the same. As can be seen from fig. 9, as the number of radio frequency links per target base station increases, the target total rate decreases, because as the number of radio frequency links per target base station increases, the number of base stations may decrease, but the interfering signal increases, resulting in a decrease in the target total rate.

Fig. 10 is a bar graph illustrating target total rate of a user terminal as a function of carrier frequency in accordance with an example of the present disclosure. In some examples, as shown in fig. 10, the signal-to-noise ratio is 30dB, and the number of antennas per target base station is 20, i.e., N_BSThe number of antennas per subscriber terminal is 5, i.e. N, 20_MTThe distribution frequency of the mobile terminal is 100 per square kilometer, and the number of radio frequency links of each target base station is 5, namely N_rWherein a is as disclosedThe case where the target total rate of the user terminal varies with the carrier frequency and B is the case where the target total rate of the user terminal varies with the carrier frequency in the conventional scheme. The target total rate of the user terminal of the present disclosure and the conventional scheme both decrease with the increase of the carrier frequency and have the same variation curve, which indicates that the present disclosure and the conventional scheme have the same performance under the condition that other system parameters are the same. As can be seen from fig. 10, as the carrier frequency increases, the target total rate decreases, because the increase of the carrier frequency decreases the coverage of the target base station. For high carrier frequencies, more antenna elements may be arranged on each target base station, whereby losses due to a reduction in coverage of the target base station can be reduced.

Fig. 11 is a bar graph illustrating target total rate of a user terminal as a function of the user terminal according to an example of the present disclosure. Wherein, a is the corresponding target total rate when no new ue is added, and B is the corresponding target total rate when a new ue is added at any time, where the positions of other ues except the newly added ue in the curve B may not change. Other parameters than the number of clients may be the same as those in fig. 8, A, B being histograms of the target total rate for 50, 51, 52 clients per square kilometer, respectively. As can be seen from fig. 11, the new ue is added at any time and has the same target total rate as the new ue is not added, i.e., the new ue can be added at any time and has the same performance as the new ue is not added. And as the number of user terminals increases, the target total rate increases.

As described above, the present embodiment can reduce the computational complexity and coordination overhead of the base station when determining the target base station while maintaining the same performance as the conventional scheme. Therefore, according to the present disclosure, a millimeter wave online spectrum sharing method 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.

The disclosure relates to a millimeter wave online spectrum sharing system based on a clustering algorithm. The millimeter wave online spectrum sharing system is a millimeter wave cellular network system for online spectrum sharing that includes a plurality of fixed-location transmitting devices and a plurality of user devices. In the present disclosure, the transmitting device in the mm-wave online spectrum sharing system may be similar to the base station, and the user device may be similar to the user terminal.

Fig. 12 is a block diagram illustrating a millimeter wave online spectrum sharing system 1 based on a clustering algorithm according to an example of the present disclosure. In some examples, as shown in fig. 12, the millimeter wave online spectrum sharing system 1 may contain a plurality of transmitting devices and a plurality of user devices. In some examples, a plurality of target transmitting devices (e.g., transmitting devices 10, 12) of a plurality of transmitting devices (e.g., transmitting devices 10, 11, 12, etc.) may be in signal communication with a corresponding plurality of user devices. For example, the transmitting device 10 and the transmitting device 12 may determine as target transmitting devices, wherein the transmitting device 10 may transmit signals to the corresponding user device 20 and user device 21, and the transmitting device 12 may transmit signals to the corresponding user device 22 and user device 23. In some examples, the transmitting device and the user device may share a frequency spectrum and operate in a millimeter wave cellular network.

In some examples, a plurality of transmitting devices (e.g., transmitting device 10, transmitting device 11, transmitting device 12, etc.) may receive location signals containing location information transmitted by respective user devices (e.g., user device 20, user device 21, user device 22, user device 23) to obtain location information of the user devices, and determine a plurality of target transmitting devices (e.g., transmitting device 10, transmitting device 12) based on a clustering algorithm and the location information of the plurality of transmitting devices. 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 device. The clustering algorithm may obtain a plurality of cluster center points corresponding to the plurality of user devices based on the plurality of initial center points, the number and location information of the plurality of user devices, and the number of radio frequency links of each transmitting device. Each clustering central point corresponds to a target transmitting device respectively, the target transmitting device is the transmitting device with the minimum distance from the clustering central point, and the plurality of transmitting devices and the plurality of user devices share the frequency spectrum. The acquisition of the target transmission apparatus can be referred to the above step S110 to step S130. The plurality of transmitting devices can receive the position signals transmitted by the user devices to obtain the position information of the user devices, and the clustering center point can be determined through a clustering algorithm. This can effectively reduce the coordination overhead. The total number of operations required by the transmitting apparatus in determining the target transmitting apparatus can be obtained by equation (3), and in this case, the computational complexity of the transmitting apparatus can be effectively reduced.

In some examples, an existing user device may be moved or a new user device may be added, in which case, a target transmitting device corresponding to the user device may be determined by calculating a distance between the user device and each cluster center point, wherein the cluster center point corresponding to the target transmitting device may be the smallest distance from the user device. In some examples, if the number of radio frequency links after the target transmitting device adds the user devices is not less than the number of user devices currently corresponding to the target transmitting device, the current cluster may not be changed, i.e., the existing target transmitting device may be maintained. In some examples, if the number of radio frequency links of the target transmitting device is less than the number of user devices currently corresponding to the target transmitting device, the current cluster may be changed, that is, the target transmitting device may be re-determined, and the specific process may refer to the above online spectrum sharing method.

In some examples, a transmitting device outside of a plurality of targeted transmitting devices in the plurality of transmitting devices may be turned off. This can contribute to reduction in energy consumption.

In some examples, the millimeter wave online spectrum sharing system 1 may perform performance detection on it as with the online spectrum sharing method described above. As described above, the present embodiment can reduce the computational complexity and coordination overhead of the transmitting apparatus when determining the target transmitting apparatus while maintaining the same performance as the conventional scheme. Therefore, according to the present disclosure, it is possible to provide a millimeter wave online spectrum sharing system 1 based on a clustering algorithm that reduces the coordination overhead and computational complexity of spectrum sharing of a millimeter wave cellular network system.

While the present disclosure has been described in detail in connection with the drawings and examples, it should be understood that the above description is not intended to limit the disclosure in any way. Those skilled in the art can make modifications and variations to the present disclosure as needed without departing from the true spirit and scope of the disclosure, which fall within the scope of the disclosure.

Claims

1. A millimeter wave online spectrum sharing method based on a clustering algorithm is an online spectrum sharing method of a millimeter wave cellular network system with a plurality of base stations with fixed positions and a plurality of user terminals,

the method comprises the following steps:

the base stations receive position signals which are transmitted by the user terminals and contain position information to obtain the position information of the user terminals, the base stations determine a plurality of target base stations according to the position information of the user terminals and the position information of the base stations by using a clustering algorithm, the clustering algorithm obtains a plurality of initial central points based on the number of the user terminals and the number of radio frequency links of the base stations, obtains a plurality of clustering central points corresponding to the user terminals based on the initial central points, the number and the position information of the user terminals and the number of the radio frequency links of the base stations, and determines the target base stations based on the clustering central points and the position information of the base stations;

the method for determining the cluster center point comprises the following steps: taking the initial central point as an initial clustering central point, clustering and dividing each user terminal based on the position information of each user terminal and the initial clustering central point, obtaining the central point of each cluster according to a plurality of clusters which are divided, judging whether elements in each cluster are not changed, if so, taking the central point of each cluster as the initial clustering central point, if not, judging whether the number of the corresponding user terminals in each cluster is not more than the number of the radio frequency links of any base station, if so, increasing the number of the initial central points by one, randomly selecting the increased initial central point, and if not, taking the central point of each cluster as the clustering central point,

the method for determining the plurality of target base stations comprises the following steps: each cluster center point corresponds to a target base station respectively, the target base station is a base station with the minimum distance with the cluster center point, a plurality of base stations and a plurality of user side frequency spectrums are shared, if the user side moves or a new user side appears, the user side is served by the target base station with the closest distance, if the number of radio frequency links after the user side is added by the target base station is not less than the number of the user sides served by the target base station, the target base stations are not changed, if the number of radio frequency links after the user side is added by the target base station is less than the number of the user sides served by the target base station, the number of the initial center point is increased, and the target base stations are determined again based on the position information of each base station and each user side and the clustering algorithm.

2. The millimeter wave online spectrum sharing method according to claim 1, wherein:

the clustering algorithm is a K-means clustering algorithm.

3. The millimeter wave online spectrum sharing method according to claim 1, wherein:

each user side can obtain the corresponding position information.

4. The millimeter wave online spectrum sharing method according to claim 1, wherein:

turning off base stations other than the target base stations in the plurality of base stations.

5. The millimeter wave online spectrum sharing method according to claim 1, wherein:

the user terminals are divided into a plurality of clusters, and the number of the user terminals in any cluster is not more than the number of the radio frequency links of the target base station corresponding to the cluster.

6. A millimeter wave online spectrum sharing system based on a clustering algorithm is a millimeter wave cellular network system with a plurality of fixed-position transmitting devices and a plurality of user devices for online spectrum sharing,

the method comprises the following steps:

the plurality of transmitting devices receive position signals containing position information transmitted by the user devices to obtain the position information of the user devices, the plurality of transmitting devices determine a plurality of target transmitting devices according to the position information of the user devices and the position information of the transmitting devices by utilizing a clustering algorithm, the clustering algorithm obtains a plurality of initial central points based on the number of the user devices and the number of radio frequency links of the transmitting devices, obtains a plurality of clustering central points corresponding to the user devices based on the initial central points, the number and the position information of the user devices and the number of the radio frequency links of the transmitting devices, and determines the target transmitting devices based on the clustering central points and the position information of the transmitting devices;

the method for determining the cluster center point comprises the following steps: taking the initial central point as an initial clustering central point, clustering and dividing each user device based on the position information of each user device and the initial clustering central point, obtaining the central point of each cluster according to a plurality of clusters which are divided, judging whether elements in each cluster are not changed, if so, taking the central point of each cluster as the initial clustering central point, if not, judging whether the number of the corresponding user devices in each cluster is not more than the number of the radio frequency links of any transmitting device, if so, increasing the number of the initial central points by one, randomly selecting the increased initial central point, and if not, taking the central point of each cluster as the clustering central point,

the method of determining the plurality of target transmitting devices comprises the steps of: each cluster center point is respectively corresponding to a target transmitting device, the target transmitting device is the transmitting device with the minimum distance with the cluster center point, a plurality of transmitting devices and a plurality of user devices share the frequency spectrum, if the user devices move or new user devices appear, the user device is served by the nearest target transmitting device, if the number of radio frequency links after the target transmitting device increases the user device is not less than the number of user devices served by the target transmitting device, the plurality of target transmitting devices are not changed, if the number of radio frequency links after the target transmitting device increases the user devices is less than the number of the user devices served by the target transmitting device, the number of initial center points is increased and the plurality of target transmitting devices is re-determined based on the location information of each of the transmitting devices and each of the user devices and the clustering algorithm.

7. The millimeter wave online spectrum sharing system according to claim 6, wherein:

the clustering algorithm is a K-means clustering algorithm.

8. The millimeter wave online spectrum sharing system according to claim 6, wherein:

each user device can obtain the corresponding position information.

9. The millimeter wave online spectrum sharing system according to claim 6, wherein:

turning off a transmitting device outside the plurality of target transmitting devices in the plurality of transmitting devices.

10. The millimeter wave online spectrum sharing system according to claim 6, wherein:

the plurality of user devices are divided into a plurality of clusters, and the number of user devices in any cluster does not exceed the number of radio frequency links of the target transmitting device corresponding to the cluster.