CN113727414A - Dynamic base station deployment and backhaul method in ultra-dense network based on virtual base station - Google Patents

Dynamic base station deployment and backhaul method in ultra-dense network based on virtual base station Download PDF

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CN113727414A
CN113727414A CN202110944293.9A CN202110944293A CN113727414A CN 113727414 A CN113727414 A CN 113727414A CN 202110944293 A CN202110944293 A CN 202110944293A CN 113727414 A CN113727414 A CN 113727414A
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base station
virtual
communication equipment
communication
virtual base
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CN113727414B (en
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于银辉
初丽质
许泽萍
陈坚
郭思宇
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Jilin University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/22—Communication route or path selection, e.g. power-based or shortest path routing using selective relaying for reaching a BTS [Base Transceiver Station] or an access point
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/24—Multipath
    • H04L45/245—Link aggregation, e.g. trunking
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The invention discloses a dynamic base station deployment and return method in an ultra-dense network based on a virtual base station, which comprises the steps of using a modified affinity propagation clustering algorithm and selecting communication equipment UE which meets the conditions as the virtual base station; selecting a qualified virtual base station as a virtual relay node by using a multi-hop load balancing geographical path selection algorithm, and establishing a return communication path from the virtual base station to a mobile communication Base Station (BS); the present invention utilizes mobile devices densely distributed in a network environment to form a new dynamic, highly flexible and cost-effective virtual base station layer. Then, the virtual base station or the virtual relay node can be deployed and developed instantly at any time and any place according to the requirements, so that the communication efficiency and the network performance of the ultra-dense network are improved, the cost of a mobile network operator is reduced, the network throughput is increased, the time delay is reduced, and better service quality is provided in the whole cell.

Description

Dynamic base station deployment and backhaul method in ultra-dense network based on virtual base station
Technical Field
The invention relates to the technical field of wireless communication, in particular to a method for deploying a dynamic base station based on a virtual base station and transmitting data service back to an actual base station by the virtual base station in an ultra-dense network.
Background
With the development of economy and scientific technology, the living standard of people is continuously improved, communication requirements develop from initial voice communication to today's data, streaming media and other real-time services, application scenes relate to life and work of people, the traditional wireless network cannot meet the communication requirements of people, a novel technology is needed to promote the update of the network, and Ultra-Dense Networks (UDNs) are proposed as one of key technologies of a fifth-generation mobile communication system.
The UDN shortens the user access distance and realizes seamless coverage of cells by deploying a large number of low-power sites (Femtocell, Picocell and Microcell) in the traditional cellular network. Moreover, the low-power micro base stations provide the possibility of wide indoor and outdoor deployment, and the micro base stations can be deployed more specifically, for example, the micro base stations are deployed in a large number in shopping centers, stadiums, airports and train stations, so that the problem of limited network resources in densely populated areas is solved, and the transmission load of the macro base stations is reduced. The micro base stations enable the network to have higher data rate and throughput, the low price and the convenience of use of the micro base stations reduce the use cost, and the low transmission capacity of the micro base stations does not influence the established network. However, the current deployment of small base stations is static, and due to the movement of human factors, multi-function mobile traffic is asymmetrically delivered in the space and time domain, the static deployment of small base stations will not be flexible and cannot cope with dynamic mobile traffic.
At present, scholars at home and abroad introduce the concept of Virtual Base stations to solve the challenges faced by Base Station deployment, and communication Equipment (UE) of common people has enhanced functions through Base stations and relay nodes and is embedded into a multifunctional Base Station (VBS) to supplement infrastructure of mobile network operators. Then, according to the network requirements, a communication device with a UE-VBS function (called a qualified UE) is selected, and there are two types: (1) virtual Small Cell (VSC) for extended coverage/capacity/data rate in infrastructure weak strain hotspots: (2) as an intermediate Virtual Relay Node (VRN) in the communication path, facilitating efficient and effective flow of data within the radio access portion. The fusion of the existing ultra-dense network and the virtual base station has become a research hotspot of the current wireless communication.
Therefore, for the main problem that base station deployment is not flexible in the current ultra-dense network, how to provide a method for dynamic base station deployment based on a virtual base station and for the virtual base station to transmit data service back to an actual base station is a problem that needs to be solved by those skilled in the art.
Disclosure of Invention
In view of this, the present invention provides a method for deploying a dynamic base station based on a virtual base station and for the virtual base station to transmit data service back to an actual base station, so that the virtual base station can be deployed anytime and anywhere as required, thereby providing better service quality for users.
In order to achieve the purpose, the invention adopts the following technical scheme:
a dynamic base station deployment and backhaul method in an ultra-dense network based on a virtual base station comprises the following steps:
selecting qualified communication equipment UE as a virtual base station VBS according to an affinity propagation clustering algorithm MAPC, wherein the VBS specifically comprises an initial stage and a virtual base station forming stage;
the initial phase comprises: the BS of the mobile communication base station calculates a similarity matrix S according to the information exchanged between the total number N of the communication equipment in the cell and the total number M of the communication equipment which can be used as the base station in the cellN×MResponsibility matrix RN×MAnd availability matrix AN×M；
The responsibility matrix RN×MAnd the availability matrix AN×MAdding to construct a new matrix EN×MJudging a new matrix EN×MThe element E (i) in (b,j) if the number of the communication devices in the set is more than 0, i represents user communication equipment, j represents communication equipment capable of serving as a base station, i belongs to N, j belongs to M, if the number of the communication devices in the set is more than 0, the j belongs to the usable communication equipment UE, the usable communication equipment UE is taken as usable communication equipment UE, the usable communication equipment UE is recorded in the set L, an AUE list associated with each usable communication equipment UE is recorded, and the association between the communication equipment in the cell and the usable communication equipment is calculated through signal-to-noise preference;
the stage of forming the virtual base station comprises the following steps: determining available communication equipment UElCluster size of (d):
if the number of the available communication equipment UE is less than the preset minimum UE number minThreshold associated with the available communication equipment UE, the available communication equipment UE is determinedjDeleting the information from the set L, including the information in a communication list M which can be used as a base station, and waiting for the next information iteration;
if the number of the available communication equipment UE is larger than the preset maximum UE number maxThreshold associated with the available communication equipment UE, descending the order according to the signal-to-noise preference value and sequencing the user communication equipment in the cluster, adding the user communication equipment with the sequence number larger than maxThreshold into an unassociated set, waiting for being associated with the next available communication equipment meeting the conditions, and taking the available communication equipment in the cluster as a cluster head, namely a virtual base station;
for the user communication equipment without the available communication equipment UE nearby, the user communication equipment is directly associated with the BS of the mobile communication base station, and the operation is stopped when the unassociated set is known to be empty.
And establishing a backhaul communication path from the virtual base station to the mobile communication base station BS according to a multi-hop load balancing geographical path selection algorithm MLGP.
The method includes the steps of setting minThreshold and maxThreshold in the forming stage of the virtual base station, wherein the minThreshold represents the minimum number of users which are associated with available communication equipment UE meeting conditions so as to prove that the minimum number of users is reasonable when the communication equipment UE is activated as the virtual micro base station, and the maxThreshold represents the maximum number of the available communication equipment UE supported by the virtual base station and does not allow communication equipment with more resources than the virtual base station in terms of hardware and available bandwidth, and the purpose of ensuring the reliability of communication is achieved, so that the throughput is improved.
Preferably, the similarity matrix SN×MThe specific calculation process is as follows:
calculating the distance between the user communication equipment i and the communication equipment j which can be used as a base station:
Figure BDA0003216227540000031
Xi，Yicoordinates, X, representing the communication device ij，YjRepresenting the coordinates of a communication device j which can be used as a base station, wherein i belongs to N and j belongs to M;
storing the inverse of the distance into S (i, j), i.e. S (i, j) ═ dijMeans the possibility that a communication device which can be used as a base station is activated as a virtual base station, thereby obtaining a similarity matrix SN×MN denotes the total number of communication devices in the cell, and M denotes the number of communication devices in the cell that can serve as a base station.
Preferably, the responsibility matrix RN×MAnd availability matrix AN×MThe calculation formula is as follows:
R(i,j)＝S(i,j)-maxj'≠j{A(i,j')+S(i,j')}
Figure BDA0003216227540000041
wherein S (i, j) represents the inverse number of the distance between the user communication equipment i and the communication equipment j which can be used as the base station, and S (i, j ') represents the inverse number of the distance between the user communication equipment i and the communication equipment j' which can be used as the base station; r (i, j) is the information sent by the user communication equipment i to the communication equipment j which can be used as a base station, R (i ', j) is the information sent by the user communication equipment i' to the communication equipment j which can be used as a base station, and the R matrix reflects the user equipment which is more suitable to be synthesized into a virtual base station; a (i, j) is the information sent by the communication device j which can be used as a base station to the user communication device i, A (i, j ') is the information sent by the communication device j' which can be used as a base station to the user communication device i, and the A matrix reflects the possible cell clusters, namely indicates the user communication devices connected with the virtual base station.
Preferably, the signal-to-noise ratio preference calculation formula is:
SNRij＝TPij*Gij/σ
Figure BDA0003216227540000042
wherein, among them, SNRijRepresenting the signal-to-noise ratio, TP, of a user communication device i to a base station capable communication device jijIndicating the transmission power, G, of a user communication device i to a communication device j acting as a base stationijDenotes the channel gain from the base station-capable communication device j to the subscriber communication device i, sigma denotes the noise power, alpha denotes the attenuation factor, dijIndicating the distance of the user communication device i from the communication device j which can act as a base station.
Responsibility matrix RN×MReflecting the availability of qualified communication devices that are more suitable to become virtual base stations, availability matrix AN×MReflecting the possible clustering, it is indicated that some user communication devices may be connected to some UEs that may act as virtual base stations (i.e. cluster heads).
Preferably, the establishing of the backhaul communication path from the virtual base station to the BS of the mobile communication base station according to the multi-hop load balancing geographic path selection algorithm MLGP specifically includes:
inputting a virtual base station set S which is not in the effective communication range of the BS of the mobile communication base station and a virtual relay node set R which can be used as the virtual relay node set; the virtual relay node set R is a virtual base station obtained by the affinity propagation clustering algorithm, except a virtual base station which is not in the effective communication range of the BS of the mobile communication base station, and the virtual base station which is not in the effective communication range of the BS of the mobile communication base station is also called a virtual micro base station.
Computing the residual energy of a virtual relay node j
Figure BDA0003216227540000051
Whether the energy of the virtual base station k is larger than or equal to the energy of the virtual base station k, k belongs to S, if yes, the state of the virtual relay node j is in an opening mode, and if not, the state is in a closing mode;
drawing Euclidean lines between a kth virtual base station and a Base Station (BS) of the mobile communication base station, and calculating Euclidean distances between the kth virtual base station and communication equipment which can be used as the base station;
calculating Euclidean lines DE between a virtual relay node j and the mobile communication base station BSline；
Selecting the Euclidean line DElineThe virtual relay node of the starting mode is shortest and has the maximum Euclidean distance with the virtual base station;
and regarding the virtual relay node as a next hop from the virtual base station to the BS of the mobile communication base station, wherein the virtual relay node establishes a communication path with the BS of the mobile communication base station.
The MLGP algorithm of the present invention will dynamically set the efficient multi-hop communication path between the virtual base station and the BS. A plurality of eligible virtual base stations may be selected and activated as a virtual relay node through which aggregated mobile data traffic will flow (i.e., backhaul). Meanwhile, the data traffic load of the relay node in the candidate is considered, and the bottleneck of the BS in a return communication path passing through the relay node is avoided.
Preferably, the first and second liquid crystal materials are,
Figure BDA0003216227540000061
Figure BDA0003216227540000062
Figure BDA0003216227540000063
wherein the content of the first and second substances,
Figure BDA0003216227540000064
representing the total energy consumption of the virtual relay node l,
Figure BDA0003216227540000065
representing a minimum of virtual relay nodesOutput power, Δ p represents the load of the virtual relay node, Δ pkRepresents the load of the kth virtual base station, ReThe power remaining is represented by the power remaining,
Figure BDA0003216227540000066
represents the maximum power of the virtual relay node,
Figure BDA0003216227540000067
representing the total energy consumption of the virtual base station k,
Figure BDA0003216227540000068
represents the minimum output power of the virtual base station,
Figure BDA0003216227540000069
represents the maximum power, BW, of the virtual base stationPRBlog2(1+ SNR) represents the spectral efficiency of the signal at the virtual base station,
Figure BDA00032162275400000610
denotes the assignment of a virtual micro base station k to the N resource blocks of the signal, fnRepresenting the transmission rate of the signal on resource block N (N ∈ N).
Preferably, the Euclidean line DElineThe calculation formula is as follows:
DEline＝((Yl-Yk)Xl+(Xk-X1)Yl+X1Yk-Y1Xk)/dkl
wherein the content of the first and second substances,
Figure BDA00032162275400000611
wherein (X)1，Y1) Coordinates representing the actual base station BS, (X)k,Yk) Coordinates representing the user communication device k, (X)l,Yl) Coordinates representing a virtual base station l, dklRepresenting the distance of the user communication device k from the virtual base station l.
In conclusion, the invention has the following beneficial effects:
1. the invention is based on the concept of virtual base station, the functions of the smart phone of the common user can be enhanced through the base station and the relay node, and the smart phone is embedded into the component of the mobile network infrastructure and provides relief under the condition of stress or overload.
2. The invention adopts a Modified Affinity Propagation Clustering (MAPC) algorithm, selects user communication equipment which can be used as a base station as VSC (Virtual Small Cell) for capacity/data rate expansion in an area with weak infrastructure and needing more efficient and flexible network operation.
3. The invention adopts a multi-hop load balancing geographical path selection (MLGP) algorithm, selects the user communication equipment which can be used as a base station as a VRN (Virtual Relay Node) to provide more efficient backhaul of mobile data flow from a VSC to a BS.
4. The present invention improves network performance in terms of throughput, delay and jitter.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a block diagram of a deployment of virtual base stations in accordance with the present invention.
FIG. 2 is a flow chart of the present invention using the MAPC algorithm.
FIG. 3 is a flow chart of the present invention using the MLGP algorithm.
Fig. 4 is a Matlab simulation diagram in which MAPCs are used to deploy virtual base stations and form corresponding clusters in the present invention.
Fig. 5 is a Matlab simulation diagram for establishing a virtual BS and BS communication path using MLGP according to the present invention, fig. 5(1) shows a Matlab simulation diagram for establishing a virtual BS S1 and BS communication path using MLGP, and fig. 5(2) shows a Matlab simulation diagram for establishing a virtual BS S2 and BS communication path using MLGP.
FIG. 6 is a comparison of the UE-VBS numbers selected by the MAPC, APC, and KVF algorithms under different scenarios.
FIG. 7 is a comparison of throughput of MAPC, APC, and KVF algorithms under different scenarios.
FIG. 8 is a comparison of the average delays of the MAPC, APC, and KVF algorithms under different scenarios.
FIG. 9 is a comparison of average jitter of MAPC, APC, and KVF algorithms under different scenarios.
FIG. 10 is a comparison of the throughput of the MLGP, SBGR and NAR algorithms under different scenarios.
FIG. 11 is a comparison of the average delays of the MLGP, SBGR and NAR algorithms under different scenes.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Embodiment 1 the present invention is a process of forming a virtual base station using the MAPC algorithm.
The forming process of the virtual micro base station comprises an initial stage and a virtual base station forming stage.
Referring to fig. 4, the algorithm enters the Virtual Base Station (VBS) formation phase, the algorithm first checks each cluster created, the number of UEs associated with each cluster head (i.e., the available UEs selected in the initial phase), sets maxThreshold value to 12 in this embodiment, sets minThreshold value to 6, determines which available communication devices UEs are to be activated as virtual base stations with the proposed MAPC algorithm, and each virtual base station is to be associated with a UE.
It can be found that: in the virtual base station formation phase of these clusters, group 7 and group 2 were found to violate the above threshold limit.
1. The size of the group 7 clusters (15UEs) is larger than the maximum allowed threshold (i.e. 12 UEs). In this case, the UEs associated with the 7 th group of cluster heads (i.e., available UEs) would be sorted in descending order according to their SNR values. The first 12 user communication devices are selected and the available communication devices UE in the cluster are selected as virtual base stations. The remaining three user communication devices (highlighted as red circles in fig. 5) will be added to the "unassociated" set. These will try to associate with their next available communication device UE, but since these three user communication devices do not have any other available communication devices in their vicinity, they will associate directly with the BS.
2. The size of group 2 clusters (5UEs) is below the lowest allowed threshold (i.e., 6 UEs). In this case the cluster head of group 2 set will be removed from the available AUE list and the user equipments UEs associated with it will be added in the "unassociated set" (highlighted as a green circle). These common user equipments UEs are then associated with cluster heads whose next cluster size is smaller than a maximum threshold. Here, these UEs are associated with cluster headers No. 8 and No. 9.
At the end of the virtual micro base station formation phase, the selected available UEs are activated as virtual micro base stations for their associated UEs.
Embodiment 2 the present invention uses the multi-hop path selection process of the MLGP algorithm.
Referring to fig. 6, a set of virtual micro base stations not in "effective" communication range with a BS is denoted as SueWherein
Figure BDA0003216227540000091
The set of eligible UEs that can be selected as virtual relay nodes is denoted RueWherein
Figure BDA0003216227540000092
The circle in the figure represents SueThe red line represents the best path between the UE-VBS to the BS. Finding a source node using the proposed MLGP Algorithm
Figure BDA0003216227540000093
And BSThe best path in between.
1. The MLGP algorithm is in
Figure BDA0003216227540000094
A local search is performed within the transmission range and a qualified UE in "on state" is selected. Wherein the "on mode" and the "off mode" are based on RueResidual energy and S ofueThe energy required to offload the data is determined. In the present embodiment, the first and second electrodes are,
Figure BDA0003216227540000095
and
Figure BDA0003216227540000096
the modes are all 'on mode',
Figure BDA0003216227540000097
in that
Figure BDA0003216227540000098
Within the range covered, and
Figure BDA0003216227540000099
and
Figure BDA00032162275400000910
closer in euclidean distance
Figure BDA00032162275400000911
Euclidean distance from BS, and therefore, selecting
Figure BDA00032162275400000912
As the next relay node and adds it to the path list. From
Figure BDA00032162275400000913
Begin following the same procedure and select
Figure BDA00032162275400000914
As the next relay node in the path. Most preferablyAfter that, the air conditioner is started to work,
Figure BDA00032162275400000915
a local search is performed within its transmission range and a BS (destination) is found within its transmission range. Thus, the process is stopped and a communication path is established.
2. For the
Figure BDA00032162275400000916
Selecting
Figure BDA00032162275400000917
As
Figure BDA00032162275400000918
The next relay node of the communication path to the BS performs exactly the same procedure as described above. Then from
Figure BDA00032162275400000919
Initially, the algorithm performs a local search within its transmission range. In this case, it is preferable that the air conditioner,
Figure BDA0003216227540000101
are found. However, because
Figure BDA0003216227540000102
Has used in
Figure BDA0003216227540000103
Thus, it is possible to provide
Figure BDA0003216227540000104
Insufficient remaining energy/resources to offload
Figure BDA0003216227540000105
Will be
Figure BDA0003216227540000106
Is set to the "off mode". Thus, selecting
Figure BDA0003216227540000107
As the next relay node and adds it to the path list. Finally, the process is carried out in a batch,
Figure BDA0003216227540000108
a local search is performed within its transmission range, a BS (destination) is found within its transmission range, and finally a communication path is determined and established.
The correlation values for example 2 are given in table 3.
TABLE 3 symbols and values
Figure BDA0003216227540000109
Fig. 7, fig. 8, fig. 9, fig. 10, and fig. 11 are simulation results of the method of the present invention on a Matlab platform, and it can be seen from the simulation results that the overall network performance of a cell is improved by using the method of the present invention.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (7)

1. A dynamic base station deployment and backhaul method in a virtual base station-based ultra-dense network is characterized by comprising the following steps:
selecting qualified communication equipment UE as a virtual base station VBS according to an affinity propagation clustering algorithm MAPC, wherein the VBS specifically comprises an initial stage and a virtual base station forming stage;
the initial phase comprises: the BS of the mobile communication base station calculates a similarity matrix S according to the information exchanged between the total number N of the communication equipment in the cell and the total number M of the communication equipment which can be used as the base station in the cellN×MResponsibility matrix RN×MAnd availability matrix AN×M；
The responsibility matrix RN×MAnd the availability matrix AN×MAdding to construct a new matrix EN×MJudging a new matrix EN×MIf the element E (i, j) in the cell is greater than 0, i represents user communication equipment, j represents communication equipment which can be used as a base station, i belongs to N, j belongs to M, if the element E (i, j) is greater than M, the jth communication equipment which can be used as the base station is used as available communication equipment UE, the available communication equipment UE is recorded in a set L, an AUE list associated with each available communication equipment UE is recorded, and the association between the communication equipment in the cell and the available communication equipment is calculated through signal-to-noise preference;
the stage of forming the virtual base station comprises the following steps: determining available communication equipment UElCluster size of (d):
if the number of the available communication equipment UE is less than the preset minimum UE number minThreshold associated with the available communication equipment UE, the available communication equipment UE is determinedlDeleting the information from the set L, including the information in a communication list M which can be used as a base station, and waiting for the next information iteration;
if the number of the user communication equipment is greater than the preset maximum UE number maxThreshold associated with the available communication equipment UE, descending the order according to the signal-to-noise preference value and sequencing the user communication equipment in the cluster, adding the user communication equipment with the sequence number greater than maxThreshold into an unassociated set, and taking the available communication equipment in the cluster as a cluster head, namely a virtual base station;
and establishing a backhaul communication path from the virtual base station to the mobile communication base station BS according to a multi-hop load balancing geographical path selection algorithm MLGP.
2. The dynamic base station deployment and backhaul method in the super dense network based on virtual base stations as claimed in claim 1, wherein the similarity matrix SN×MThe specific calculation process is as follows:
calculating the distance between the user communication equipment i and the communication equipment j which can be used as a base station:
Figure FDA0003216227530000021
Xi，Yicoordinates, X, representing the communication device ij，YjRepresenting the coordinates of a communication device j which can be used as a base station, wherein i belongs to N and j belongs to M;
storing the inverse of the distance into S (i, j), i.e. S (i, j) ═ dijMeans the possibility that a communication device which can be used as a base station is activated as a virtual base station, thereby obtaining a similarity matrix SN×MN denotes the total number of communication devices in the cell, and M denotes the number of communication devices in the cell that can serve as a base station.
3. The dynamic base station deployment and backhaul method in the super dense network based on virtual base stations as claimed in claim 2, wherein the responsibility matrix R isN×MAnd availability matrix AN×MThe calculation formula is as follows:
R(i,j)＝S(i,j)-maxj's.t,j'≠j{A(i,j')+S(i,j')}
Figure FDA0003216227530000022
wherein, S (i, j) represents the inverse number of the distance between the user communication equipment i and the communication equipment j which can be used as the base station, and S (i, j ') represents the inverse number of the distance between the user communication equipment i and the communication equipment j' which can be used as the base station; r (i, j) is information sent by the user communication equipment i to the communication equipment j which can be used as a base station, R (i ', j) is information sent by the user communication equipment i' to the communication equipment j which can be used as a base station, and the R matrix reflects the user equipment which is more suitable to be used as a virtual base station; a (i, j) is the information sent by the communication device j which can be used as a base station to the user communication device i, A (i, j ') is the information sent by the communication device j' which can be used as a base station to the user communication device i, and the A matrix reflects the possible cell clusters, namely indicates the user communication devices connected with the virtual base station.
4. The method for dynamic base station deployment and backhaul in the super dense network based on the virtual base station as claimed in claim 1, wherein the snr preference calculation formula is:
SNRij＝TPij*Gij/σ
Figure FDA0003216227530000031
wherein the SNRijRepresenting the signal-to-noise ratio, TP, of a user communication device i to a base station capable communication device jijIndicating the transmission power, G, of a user communication device i to a communication device j acting as a base stationijDenotes the channel gain from the base station-capable communication device j to the subscriber communication device i, sigma denotes the noise power, alpha denotes the attenuation factor, dijIndicating the distance of the user communication device i from the communication device j which can act as a base station.
5. The dynamic base station deployment and backhaul method in the super-dense network based on the virtual base station as claimed in claim 1, wherein the establishing of the backhaul communication path from the virtual base station to the mobile communication base station BS according to the multi-hop load balancing geographical path selection algorithm MLGP specifically comprises:
inputting a virtual base station set S which is not in the effective communication range of the BS of the mobile communication base station and a virtual relay node set R which can be used as the virtual relay node set;
computing the residual energy of a virtual relay node j
Figure FDA0003216227530000032
Whether the energy of the virtual base station k is more than or equal to the energy of the virtual base station k, wherein k belongs to S, if yes, the state of the virtual relay node j is in an opening mode, otherwise, the state is in a closing mode;
drawing Euclidean lines between the kth virtual base station and the BS of the mobile communication base station, and calculating the Euclidean distance between the kth virtual base station and communication equipment which can be used as a base station;
calculating Euclidean lines DE between a virtual relay node j and the mobile communication base station BSline；
Selecting the Euclidean line DElineThe virtual relay node of the starting mode is shortest and has the maximum Euclidean distance with the virtual base station;
and regarding a virtual relay node as a next hop from a virtual base station to a BS of the mobile communication base station, wherein the virtual relay node establishes a communication path with the BS of the mobile communication base station.
6. The dynamic base station deployment and backhaul method in a virtual base station based super dense network as claimed in claim 5,
Figure FDA0003216227530000033
Figure FDA0003216227530000041
Figure FDA0003216227530000042
wherein, Pl RRepresenting the total energy consumption of the virtual relay node l,
Figure FDA0003216227530000043
represents the minimum output power of the virtual relay node, Δ p represents the load of the virtual relay node, Δ pkRepresents the load of the kth virtual base station, ReThe power remaining is represented by the power remaining,
Figure FDA0003216227530000044
to representThe maximum power of the virtual relay node is,
Figure FDA0003216227530000049
representing the total energy consumption of the virtual base station k,
Figure FDA0003216227530000045
represents the minimum output power of the virtual base station,
Figure FDA0003216227530000046
represents the maximum power, BW, of the virtual base stationPRBlog2(1+ SNR) represents the spectral efficiency of the signal at the virtual base station,
Figure FDA0003216227530000047
denotes the assignment of a virtual micro base station k to the N resource blocks of the signal, fnRepresenting the transmission rate of the signal on resource block N, N ∈ N.
7. The dynamic base station deployment and backhaul method in ultra-dense virtual base station-based network as claimed in claim 5, wherein the Euclidean line DElineThe calculation formula is as follows:
DEline＝((Yl-Yk)Xl+(Xk-X1)Yl+X1Yk-Y1Xk)/dkl
wherein the content of the first and second substances,
Figure FDA0003216227530000048
wherein (X)1，Y1) Coordinates representing the actual base station BS, (X)k,Yk) Coordinates representing the user communication device k, (X)l,Yl) Coordinates representing a virtual base station l, dklRepresenting the distance of the user communication device k from the virtual base station l.
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