CN113727414B - 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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CN113727414B
CN113727414B CN202110944293.9A CN202110944293A CN113727414B CN 113727414 B CN113727414 B CN 113727414B CN 202110944293 A CN202110944293 A CN 202110944293A CN 113727414 B CN113727414 B CN 113727414B
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base station
virtual
communication device
communication
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CN113727414A (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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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

Abstract

The invention discloses a dynamic base station deployment and backhaul method in an ultra-dense network based on a virtual base station, which comprises the steps of using a modified affinity propagation clustering algorithm to select communication equipment UE meeting the conditions as the virtual base station; selecting a virtual base station meeting the conditions as a virtual relay node by using a multi-hop load balancing geographic path selection algorithm, and establishing a backhaul 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 in real time 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 dynamic base station deployment based on a virtual base station and data service return of the virtual base station to an actual base station in an ultra-dense network.
Background
With the development of economy and science, the living standard of people is continuously improved, the communication requirement is developed from initial voice communication to today data, streaming media and other real-time services, the application scene relates to the life and work of people, the traditional wireless network cannot meet the communication requirement of people, new technology is required to promote the update of the network, and Ultra-Dense Networks (UDNs) are proposed as one of the key technologies of the fifth generation mobile communication system.
UDNs shorten the user access distance by deploying a large number of low power sites (Femtocell, picocell, microcell) in a conventional cellular network, enabling seamless coverage of cells. Moreover, low power micro base stations offer the possibility of wide deployment both indoors and outdoors, which can be deployed more targeted, such as by deploying micro base stations in large numbers in shopping malls, stadiums, airports and train stations, to alleviate the problem of limited network resources in densely populated areas, reducing the transmission load of macro base stations. The micro base stations provide higher data rates and throughput to the network, and their low price and ease of use reduce the cost of use, the low transmission capacity of the micro base stations does not affect the established network. However, at present, deployment of small-sized base stations is static, and due to movement of human factors, multifunctional mobile traffic is delivered asymmetrically in the space and time fields, the static deployment of small-sized base stations is inflexible and cannot cope with dynamic mobile traffic.
Currently, scholars at home and abroad introduce the concept of a virtual base station to solve the challenges of base station deployment, and communication Equipment (UE) of a common crowd is enhanced in function through the base station and a relay node and is embedded into a multifunctional virtual base station (Virtual Base Station, VBS) to supplement mobile network operator infrastructure. Communication devices with UE-VBS functionality (called qualified UEs) are then selected according to network requirements, mainly of two types: (1) Virtual small units (Virtual Small Cell, VSC) for extending coverage/capacity/data rate in strained hot spots of weak infrastructure: (2) As an intermediate virtual relay node (Virtual Relay Node, VRN) in the communication path, an effective and efficient flow of data within the radio access section is facilitated. The fusion of existing ultra-dense networks and virtual base stations has become a research hotspot for current wireless communications.
Therefore, aiming at the main problem of inflexible base station deployment in the current ultra-dense network, how to provide a dynamic base station deployment based on a virtual base station and a method for returning data service from the virtual base station to an actual base station is a problem to be solved by the skilled in the art.
Disclosure of Invention
In view of the above, the present invention provides 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, which can deploy the virtual base station at any time and any place according to the need, and provides better service quality for users.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a dynamic base station deployment and return method in a virtual base station-based ultra-dense network 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 method specifically comprises an initial stage and a virtual base station forming stage;
the initial stage comprises the following steps: the BS of the mobile communication base station calculates a similarity matrix S based on the messages exchanged between the total number N of communication devices in the cell and the total number M of communication devices available as base stations in the cell N×M Responsibility matrix R N×M And availability matrix A N×M ；
The responsibility matrix R N×M And the availability matrix A N×M Adding to build a new matrix E N×M Judging a new matrix E N×M If the element E (i, j) is larger than 0, i represents user communication equipment, j represents communication equipment capable of serving as a base station, i epsilon N, j epsilon M, and if the element E (i, j) is larger than 0, the j-th communication equipment capable of serving as a 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 of the communication equipment and the available communication equipment in a cell is calculated through signal-to-noise ratio preference;
the forming a virtual base station stage comprises: determining available communication devices UE l Cluster size of (c):
if the number of the available communication equipment UE is smaller than the preset minimum number of the UE associated with the available communication equipment UE, the available communication equipment UE is used for the communication j Deleting from the set L, and including the set L 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 larger than the preset maximum number maxThreshold associated with the available communication equipment UE, the user communication equipment in the cluster is ordered according to the signal-to-noise ratio preference value, the user communication equipment with the sequence number larger than maxThreshold is added into an unassociated set, the user communication equipment waits to be associated with the available communication equipment which meets the next condition, and the available communication equipment in the cluster is used as a cluster head, namely a virtual base station;
for user communication equipment which has no 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 BS of the mobile communication base station according to a multi-hop load balancing geographic path selection algorithm MLGP.
The method comprises the steps of setting minThreshold and maxThreshold in the formation stage of a virtual base station, wherein minThreshold represents the minimum number of users which should be associated with available communication equipment UE meeting the conditions so as to prove that the activation of the virtual base station as a virtual micro base station is reasonable, maxThreshold represents the maximum number of available communication equipment UE supported by the virtual base station, and communication equipment which is more than virtual base station resources in terms of hardware and available bandwidth is not allowed to be supported, so that the reliability of communication is ensured, and the throughput is improved.
Preferably, the similarity matrix S N×M The specific calculation process is as follows:
calculating the distance between the user communication equipment i and the communication equipment j capable of serving as a base station:X i ，Y i representing the coordinates, X, of the communication device i j ，Y j Representing the coordinates of the communication equipment j capable of serving as a base station, i epsilon N and j epsilon M;
storing the inverse of the distance into S (i, j), i.e. S (i, j) = -d ij Representing the likelihood that a communication device operable as a base station is activated as a virtual base station, thereby yielding a similarity matrix S N×M N represents the total number of communication devices in the cell, and M represents the number of communication devices in the cell that can act as base stations.
Preferably, the responsibility matrix R N×M And availability matrix A N×M The calculation formula is as follows:
R(i,j)＝S(i,j)-max j'≠j {A(i,j')+S(i,j')}
wherein S (i, j) represents the opposite number of distances between the user communication device i and the communication device j that can operate as a base station, and S (i, j ') represents the opposite number of distances between the user communication device i and the communication device j' that can operate as a base station; r (i, j) is information that the user communication device i transmits to the communication device j capable of serving as a base station, R (i ', j) is information that the user communication device i' transmits to the communication device j capable of serving as a base station, and R matrix reflects user devices more suitable to become virtual base stations; a (i, j) is the information that communication device j, which may act as a base station, transmits to user communication device i, a (i, j ') is the information that communication device j', which may act as a base station, transmits to user communication device i, and the a matrix reflects the possible cell clusters, i.e. indicates the user communication devices connected to the virtual base station.
Preferably, the signal to noise ratio preference calculation formula is:
SNR ij ＝TP ij *G ij /σ
wherein, SNR ij Representing the signal-to-noise ratio, TP, of a user communication device i to a communication device j operable as a base station ij Representing user communication device i to actionable baseTransmission power, G, of a station's communication device j ij Representing channel gain from communication device j, which can act as a base station, to user communication device i, σ represents noise power, α represents attenuation factor, d ij Indicating the distance of the user communication device i from the communication device j which can act as a base station.
Responsibility matrix R N×M Reflecting the qualified availability of communication devices more suitable for becoming a virtual base station, availability matrix A N×M Reflecting the possible clusters, it is indicated that certain user communication devices may be connected to certain UEs (i.e. cluster heads) that may act as virtual base stations.
Preferably, establishing a backhaul communication path from the virtual base station to the BS of the mobile communication base station according to the multi-hop load balancing geographical path selection algorithm MLGP specifically includes:
inputting a virtual base station set S which is not in the effective communication range of the mobile communication base station BS and a virtual relay node set R which can be used as a virtual relay node set; the virtual relay node set R is a virtual micro base station, which is obtained by an affinity propagation clustering algorithm, except for the remaining virtual base stations of the virtual base stations which are not in the BS effective communication range of the mobile communication base station.
Calculating the residual energy of the virtual relay node jWhether the energy of the virtual base station k is larger than or equal to that of the virtual base station k, wherein k epsilon S is satisfied, the j state of the virtual relay node is an on mode, and otherwise, the j state of the virtual relay node is an off mode;
drawing Euclidean lines between the kth virtual base station and the BS of the mobile communication base station, and calculating Euclidean distances between the kth virtual base station and communication equipment capable of serving as a base station;
calculating Euclidean line DE between a virtual relay node j and the BS of the mobile communication base station line ；
Selecting the Euclidean line DE line A virtual relay node of an on mode having a shortest and maximum euclidean distance from the virtual base station;
and regarding the virtual relay node as the next hop from the virtual base station to the mobile communication base station BS, wherein the virtual relay node establishes a communication path with the mobile communication base station BS.
The MLGP algorithm of the invention adopts the dynamic setting of the efficient multi-hop communication path between the virtual base station and the BS. Multiple eligible virtual base stations may be selected and activated as virtual relay nodes through which aggregated mobile data traffic will flow (i.e., backhaul). Meanwhile, considering the data traffic load of the relay node in the candidates, the BS is prevented from bottleneck in the backhaul communication path through the relay node.
Preferably, the method comprises the steps of,
wherein,representing the total energy consumption of the virtual relay node l +.>Representing the minimum output power of the virtual relay node, Δp representing the load of the virtual relay node, Δp k Representing the load of the kth virtual base station, R e Indicating the remaining power, +.>Representing maximum power of virtual relay node, +.>Representing the total energy consumption of virtual base station k +.>Representing the minimum output power of the virtual base station, +.>Representing maximum power, BW, of a virtual base station PRB log 2 (1 + snr) represents the spectral efficiency of the signal at the virtual base station,representing N resource blocks allocated to signals by virtual micro base station k, f n Representing the transmission rate (N e N) of the signal on resource block N.
Preferably, euclidean line DE line The calculation formula is as follows:
DE line ＝((Y l -Y k )X l +(X k -X 1 )Y l +X 1 Y k -Y 1 X k )/d kl
wherein,
wherein, (X 1 ，Y 1 ) Representing the coordinates of the actual base station BS, (X k ,Y k ) Representing the coordinates of the user communication device k, (X) l ,Y l ) Representing the coordinates, d, of the virtual base station l kl Indicating the distance of the user communication device k from the virtual base station l.
In summary, the invention has the following beneficial effects:
1. the invention is based on the concept of virtual base station, the smart phone of the common user can be enhanced by the functions of the base station and the relay node and is embedded as a component part of the mobile network infrastructure, and relief is provided under the condition of pressure or overload.
2. The present invention employs a Modified Affinity Propagation Clustering (MAPC) algorithm to select a user communication device that can act as a base station as a VSC (Virtual Small Cell, virtual micro base station) for capacity/data rate expansion in areas where the infrastructure is weak and more efficient and flexible network operation is required.
3. The present invention employs a multi-hop load balancing geographical path selection (MLGP) algorithm to select a user communication device that can act as a base station as a VRN (Virtual Relay Node ) to provide a more efficient backhaul of mobile data traffic from the VSC to the BS.
4. The invention improves network performance in terms of throughput, delay and jitter.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described below, it being obvious that the drawings in the description below are only embodiments of the present invention, and that other drawings can be obtained from the provided drawings without inventive effort for a person skilled in the art.
Fig. 1 is a frame diagram of a deployed virtual base station according to the present invention.
FIG. 2 is a flow chart of the present invention using MAPC algorithm.
Fig. 3 is a flowchart of the present invention using the MLGP algorithm.
Fig. 4 is a Matlab simulation diagram of a virtual base station deployed using MAPCs and forming a corresponding cluster in accordance with the present invention.
Fig. 5 is a Matlab simulation diagram of a communication path between a virtual base station and a BS using an MLGP according to the present invention, fig. 5 (1) is a Matlab simulation diagram of a communication path between a virtual base station S1 and a BS using an MLGP, and fig. 5 (2) is a Matlab simulation diagram of a communication path between a virtual base station S2 and a BS using an MLGP.
Fig. 6 is a comparison of the number of UE-VBS selected by the MAPC, APC, KVF three algorithms under different scenarios.
Fig. 7 is a comparison of the throughput of the MAPC, APC, KVF three algorithms under different scenarios.
Fig. 8 is a comparison of the average delay of the MAPC, APC, KVF algorithm under different scenarios.
Fig. 9 is a comparison of the average jitter of the MAPC, APC, KVF algorithm under different scenarios.
Fig. 10 is a comparison of the throughput of the MLGP, SBGR, NAR three algorithms under different scenarios.
Fig. 11 is a comparison of the average delay of the MLGP, SBGR, NAR algorithm under different scenarios.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without creative efforts, are within the protection scope of the invention.
Example 1 the present invention uses MAPC algorithm to form a virtual base station process.
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., available UEs selected in the initial phase), sets the maxThreshold value to 12, minthreshold value to 6 in this instance Shi Li, determines which available communication devices UEs are to be activated as virtual base stations with the proposed MAPC algorithm, and each virtual base station will have associated UEs.
It can be found that: during the virtual base station formation phase of these clusters, groups 7 and 2 are found to violate the threshold limit described above.
1. The size of group 7 clusters (15 UEs) is greater than the maximum allowed threshold (i.e., 12 UEs). In this case, the UEs associated with group 7 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 have no other available communication devices in their vicinity, they will associate directly with the BS.
2. The size of group 2 clusters (5 UEs) is below the lowest allowable threshold (i.e., 6 UEs). In this case, the cluster head of group 2 set will be deleted from the available AUE list and the user equipments UEs associated with it (highlighted as green circles) will be added in the "non-associated set". These general 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 heads 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.
Example 2 the present invention uses the multi-hop path selection procedure of the MLGP algorithm.
Referring to fig. 6, a set of virtual micro base stations not in "effective" communication range with the BS is denoted as S ue WhereinThe set of eligible UEs that can be selected as virtual relay nodes is denoted as R ue Wherein->Circles in the figure represent S ue The red line indicates the best path between the UE-VBS to the BS. Using the proposed MLGP algorithm to find source node +.>And the best path between BSs.
1. MLGP algorithm is inLocal search is performed within transmission range and qualified UEs in "on state" are selected. Wherein the "on mode" and "off mode" are according to R ue Residual energy of (2) and S ue The energy required to unload the data. In this embodiment, <' > a->And->The modes are all the "open mode", -the mode is the "open mode">At->Within the covered range, and->And->Is closer to +.>Euclidean distance to BS, therefore, select +.>As the next relay node and adds it to the path list. From->Begin following the same procedure and select +.>As the next relay node in the path. Finally, let(s)>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 followingSelect->As->The next relay node of the communication path to the BS performs the same procedure as described above. Then from->Initially, the algorithm performs a local search over its transmission range. In this case the number of the elements to be formed is,is found. However, due to +.>Is already used in the path of +.>Thus->Is insufficient to unload +.>Will->Is set to "off mode". Thus, select +.>As the next relay node and adds it to the path list. Finally, let(s)>A local search is performed within its transmission range, a BS (destination) is found within its transmission range, and a communication path is finally determined and established.
The correlation values for example 2 are given in table 3.
Table 3 symbols and values
Fig. 7, fig. 8, fig. 9, fig. 10, and fig. 11 show simulation results of the method according to the present invention on a Matlab platform, and it can be seen from the simulation results that the overall network performance of the cell is improved by using the method according to the present invention.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
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 (5)

1. The dynamic base station deployment and backhaul method in the ultra-dense network based on the virtual base station 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 method specifically comprises an initial stage and a virtual base station forming stage;
the initial stage comprises the following steps: the BS of the mobile communication base station calculates a similarity matrix S based on the messages exchanged between the total number N of communication devices in the cell and the total number M of communication devices available as base stations in the cell N×M Responsibility matrix R N×M And availability matrix A N×M ；
The responsibility matrix R N×M And the availability matrix A N×M Adding to build a new matrix E N×M Judging a new matrix E N×M If the element E (i, j) in the list is larger than 0, i represents user communication equipment, j represents communication equipment capable of serving as a base station, i epsilon N, j epsilon M, and if the element E (i, j) is larger than 0, the j-th communication equipment capable of serving as the base station is used as available communication equipment UE, the available communication equipment UE is recorded in a set L, and the record is carried out on each communication equipmentAn AUE list associated with each available communication device UE, and calculating the association between the communication device and the available communication device in the cell through the signal-to-noise ratio preference;
the forming a virtual base station stage comprises: determining available communication devices UE l Cluster size of (c):
if the number of the available communication equipment UE is smaller than the preset minimum number of the UE associated with the available communication equipment UE, the available communication equipment UE is used for the communication l Deleting from the set L, and including the set L 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 devices is larger than the preset maximum number maxThreshold associated with the available communication devices, the user communication devices in the cluster are ordered in descending order according to the signal-to-noise ratio preference value, the user communication devices with the sequence numbers larger than the maxThreshold are added into the unassociated set, and the available communication devices in the cluster are used as cluster heads, namely virtual base stations;
establishing a backhaul communication path from the virtual base station to the BS of the mobile communication base station according to a multi-hop load balancing geographic path selection algorithm MLGP;
the similarity matrix S N×M The specific calculation process is as follows:
calculating the distance between the user communication equipment i and the communication equipment j capable of serving as a base station:X i ，Y i representing the coordinates, X, of the communication device i j ，Y j Representing the coordinates of the communication equipment j capable of serving as a base station, i epsilon N and j epsilon M;
storing the inverse of the distance into S (i, j), i.e. S (i, j) = -d ij Representing the likelihood that a communication device operable as a base station is activated as a virtual base station, thereby yielding a similarity matrix S N×M N represents the total number of communication devices in the cell, M represents the number of communication devices in the cell which can be used as a base station;
responsibility matrix R N×M And availability matrix A N×M The calculation formula is as follows:
R(i,j)＝S(i,j)-max j's.t,j'≠j {A(i,j')+S(i,j')}
wherein S (i, j) represents the opposite number of the distance between the user communication device i and the communication device j which can be a base station, and S (i, j ') represents the opposite number of the distance between the user communication device i and the communication device j' which can be a base station; r (i, j) is information that the user communication device i transmits to the communication device j capable of serving as a base station, R (i ', j) is information that the user communication device i' transmits to the communication device j capable of serving as a base station, and R matrix reflects the user devices more suitable to become virtual base stations; a (i, j) is the information that communication device j, which may act as a base station, transmits to user communication device i, a (i, j ') is the information that communication device j', which may act as a base station, transmits to user communication device i, and the a matrix reflects the possible cell clusters, i.e. indicates the user communication devices connected to the virtual base station.
2. The method for dynamic base station deployment and backhaul in a virtual base station-based ultra-dense network according to claim 1, wherein the signal-to-noise ratio preference calculation formula is:
SNR ij ＝TP ij *G ij /σ
wherein SNR is ij Representing the signal-to-noise ratio, TP, of a user communication device i to a communication device j operable as a base station ij Representing the transmission power of a user communication device i to a communication device j operable as a base station, G ij Representing channel gain from communication device j, which can act as a base station, to user communication device i, σ represents noise power, α represents attenuation factor, d ij Indicating the distance of the user communication device i from the communication device j which can act as a base station.
3. The method for dynamic base station deployment and backhaul in a virtual base station-based ultra-dense network according to claim 1, wherein establishing a backhaul communication path from a virtual base station to a mobile communication base station BS according to a 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 mobile communication base station BS and a virtual relay node set R which can be used as a virtual relay node set;
calculating the residual energy of the virtual relay node jWhether the energy of the virtual base station k is larger than or equal to that of the virtual base station k, wherein k epsilon S is satisfied, the j state of the virtual relay node is an on mode, and otherwise, the j state of the virtual relay node is an off mode;
drawing Euclidean lines between the kth virtual base station and the BS of the mobile communication base station, and calculating Euclidean distances between the kth virtual base station and communication equipment capable of serving as the base station;
calculating Euclidean line DE between a virtual relay node j and the BS of the mobile communication base station line ；
Selecting the Euclidean line DE line A virtual relay node of an on mode having a shortest and maximum euclidean distance from the virtual base station;
and regarding the virtual relay node as the next hop from the virtual base station to the mobile communication base station BS, wherein the virtual relay node establishes a communication path with the mobile communication base station BS.
4. The method for dynamic base station deployment and backhaul in a virtual base station based ultra-dense network of claim 3 wherein,
wherein P is l R Representing the total energy consumption of the virtual relay node l,representing the minimum output power of the virtual relay node, Δp representing the load of the virtual relay node, Δp k Representing the load of the kth virtual base station, R e Indicating the remaining power +.>Representing maximum power of virtual relay node, +.>Representing the total energy consumption of virtual base station k +.>Representing the minimum output power of the virtual base station, +.>Representing maximum power, BW, of a virtual base station PRB log 2 (1+SNR) represents the spectral efficiency of the signal at the virtual base station, < >>Representing N resource blocks allocated to signals by virtual micro base station k, f n Representing the transmission rate of the signal on resource block N, N e N.
5. The method for dynamic base station deployment and backhaul in a virtual base station based ultra-dense network of claim 3, wherein euclidean line DE line The calculation formula is as follows:
DE line ＝((Y l -Y k )X l +(X k -X 1 )Y l +X 1 Y k -Y 1 X k )/d kl
wherein,
wherein, (X 1 ，Y 1 ) Representing the coordinates of the actual base station BS, (X k ,Y k ) Representing the coordinates of the user communication device k, (X) l ,Y l ) Representing the coordinates, d, of the virtual base station l kl Indicating the distance of the user communication device k from the virtual base station l.
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