CN110012509A - Resource allocation methods based on user mobility in a kind of 5G small cell network - Google Patents
Resource allocation methods based on user mobility in a kind of 5G small cell network Download PDFInfo
- Publication number
- CN110012509A CN110012509A CN201910290485.5A CN201910290485A CN110012509A CN 110012509 A CN110012509 A CN 110012509A CN 201910290485 A CN201910290485 A CN 201910290485A CN 110012509 A CN110012509 A CN 110012509A
- Authority
- CN
- China
- Prior art keywords
- user
- gnb
- network
- resource allocation
- virtual subdistrict
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 43
- 238000013468 resource allocation Methods 0.000 title claims abstract description 39
- 230000005540 biological transmission Effects 0.000 claims abstract description 44
- 238000005457 optimization Methods 0.000 claims abstract description 32
- 238000004891 communication Methods 0.000 claims abstract description 12
- 238000000354 decomposition reaction Methods 0.000 claims abstract description 4
- 230000008569 process Effects 0.000 claims description 7
- 238000005259 measurement Methods 0.000 claims description 6
- 230000008859 change Effects 0.000 claims description 5
- 230000011664 signaling Effects 0.000 claims description 5
- 238000012935 Averaging Methods 0.000 claims description 2
- 238000005516 engineering process Methods 0.000 abstract description 6
- 238000010295 mobile communication Methods 0.000 abstract description 2
- 230000000875 corresponding effect Effects 0.000 description 11
- 239000011159 matrix material Substances 0.000 description 11
- 238000012546 transfer Methods 0.000 description 6
- 230000008901 benefit Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 241000854291 Dianthus carthusianorum Species 0.000 description 1
- 206010062519 Poor quality sleep Diseases 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000002079 cooperative effect Effects 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
- 239000011800 void material Substances 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
- H04W28/0231—Traffic management, e.g. flow control or congestion control based on communication conditions
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Quality & Reliability (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The present invention relates to the resource allocation methods based on user mobility in a kind of 5G small cell network, belong to mobile communication technology field.Firstly, for serious interference problem in small cell network, after non-excited users are successfully accessed network by paging, the present invention effectively reduces user's communication interference issues by establishing the virtual subdistrict of customer-centric.There is no switching during user is mobile in virtual subdistrict, guarantee the continuity of business.Secondly, being based on Lyapunov optimization method to improve resource utilization, realize that network average energy efficiency maximizes.The present invention fully considers user data package queue length and channel quality, is that user's optimal transmission resource allocation and optimal power allocation two sub-problems solve by the average energy efficiency PROBLEM DECOMPOSITION of maximization network.By the optimization distribution to Internet resources, transmission quality is promoted, and realizes the stability for guaranteeing system queue while maximizing system average energy efficiency.
Description
Technical field
The invention belongs to mobile communication technology field, it is related to the resource based on user mobility in a kind of 5G small cell network
Distribution method.
Background technique
With the development of Internet of Things and large-scale machines class, intelligent terminal and various user equipmenies increase sharply in network, so that
5G communication system faces unprecedented huge data traffic demand challenge.In order to cope with increasingly huge increasing data service and effectively
Lifting system capacity requirement, super-intensive small cell network are come into being.5G small cell network has low cost, low-power consumption, can oneself
The characteristics of tissue and self-optimizing, while its intensive covering can solve users' close quarters Exponential growth such as colleges and universities and shopping centre
Data traffic demand improves network capacity, expands the coverage area of wireless network.Further, since number of users increases sharply, to save function
User, when not having data transmit-receive, is converted to inactive (Inactive) state of light sleep by rate consumption.It is sought to improve
Efficiency is exhaled, the user of Inactive state will configure a position tracking region and be known as wireless access network notification area (RAN
Notification Area, RNA), when there are data transfer demands in network, RNA calling user can be passed through.However, intensive
When disposing cellulor, many problems are also faced:
(1) cellulor communication coverage is small, is easily away from the coverage area of serving cell and frequency when the user is mobile
Numerous base station for being switched to its service, to generate a large amount of hand off signaling expenses.
(2) super-intensive of small cell base station is disposed so that small area overlapping covers, and a large number of users will all be in multiple cell weights
Folded edge by serious inter-cell interference, and is extremely easy to happen ping-pong.
For problem (1), by by small cell base station sub-clustering in existing research, the data plane layer of user and control in cluster
Plane layer separation, control plane are connected by cluster head, and user's movement in cluster will not switch, to reduce user because frequently cutting
Change the signaling overheads of generation.
For problem (2), the representative art for solving cellulor problem of co-channel interference in existing research mainly has minizone
Interference coordination technique (Inter-Cell Interference Coordination, ICIC) and coordinated multipoint transmission technology
(Coordinated Multiple Point, CoMP).By dividing to frequency resource, neighboring community uses ICIC technology
Different frequencies realizes the control to interference, and cellulor is then divided into different CoMP groups by CoMP technology, in a CoMP
Inter-cell interference is eliminated by multiple cell cooperatives in group.
For facing challenges in 5G small cell network, traditional network architecture centered on base station is no longer satisfied
5G user's communication requirement.In order to respond actively these challenges, reduce inter-cell interference and simultaneously promote user experience, 5G propose with
Cell virtual technology centered on family, i.e. multiple entity cells around user form a virtual subdistrict, virtual small
Communication service is provided for user by way of cooperation between transmission node in area.The virtual subdistrict of customer-centric can eliminate side
Edge user alleviates the interference in super-intensive deployment small cell network, while reducing user's mobile handoff signaling overheads, improves communication
Quality promotes network user's experience.
In conclusion the present invention is the business continuance and interference problem for solving mobile subscriber in 5G small cell network, mention
The Resource Allocation Formula based on user mobility in a kind of 5G small cell network is gone out.It is dry in intensive small cell network to alleviate
Problem is disturbed, guarantees mobile subscriber business continuity, the virtual subdistrict of customer-centric is established, in virtual subdistrict between transmission node
Cooperation provides communication service for user.In addition, resource utilization is improved in order to optimize Internet resources, the present invention is based on
Lyapunov optimum theory considers that user data string stability is converted to overall network average energy efficiency optimization problem
User's optimal transmission resource allocation and optimal power allocation two sub-problems are protected while maximizing system average energy efficiency
Demonstrate,prove the stabilization of system queue.
Summary of the invention
In view of this, the purpose of the present invention is to provide the resources based on user mobility in a kind of 5G small cell network point
Method of completing the square.1) to alleviate the interference problem in intensive small cell network, guarantee mobile subscriber business continuity, foundation is with user
The virtual subdistrict at center, cooperation for user provides communication service between transmission node in virtual subdistrict.2) secondly, in order to improve resource
Utilization rate optimizes Internet resources using Lyapunov optimization method and fully considers user data package queue length and channel matter
Amount realizes that network average energy efficiency maximizes.
In order to achieve the above objectives, the present invention provides following technical method:
Resource allocation methods based on user mobility in a kind of 5G small cell network, this method is according to mentioned network scenarios
Characteristic reduce inter-cell interference and simultaneously guarantee to move firstly, establish the virtual subdistrict of customer-centric after user access network
Employ the business continuance at family；Secondly, optimizing distribution to Internet resources when user transmits data；
Method includes the following steps:
S1: when inactive Inactive user has data service arrival, network is accessed by network paging；
S2: the virtual subdistrict of customer-centric is established after user access network；
S3: user optimizes distribution to Internet resources when transmitting data.
Further, in the step S1, when there is the arrival of inactive Inactive user data package in network, for positioning
User, anchor point gNB will initiate paging；User receives and is converted to connection status by currently resident gNB after paging message,
Access network.
Further, in the step S2, the virtual subdistrict for establishing customer-centric be divided into the following three steps:
S21: after user access network, user is in wireless access network notification area RNA when unactivated state before
As candidate virtual cell, user detects the reference signal RS intensity of all gNB in RNA and measurement result is reported to user works as
Preceding resident gNB；
S22: user is currently resident gNB and the RS gNB for being greater than threshold value is reported to anchor point gNB, anchor point gNB according to measurement result
According to load information library, determines the gNB of Virtual cell and that result and virtual subdistrict configuration information are handed down to user is current
Resident gNB；
Virtual subdistrict configuration information is sent respectively to user and corresponding gNB building by S23: the gNB that user is currently resident
The virtual subdistrict of customer-centric provides communication service by way of cooperation between transmission node for user in virtual subdistrict.
Further, in the step S3, according to user data package queue length and channel quality, using being based on
The optimization method of Lyapunov is established using the time average energy efficiency of maximization network as the resource allocation optimization mesh of target
Mark.
Further, in the step S1, when user is in Inactive state, the connection of user and network is disconnected, and
There is the notification area RNA that user location is positioned when being used for paging.
Further, in the step S2, due to the mobility of user, the virtual subdistrict of customer-centric is included
Dynamic change will occur for gNB；With the movement of user, addition is met to the new gNB of condition, and removes and is unsatisfactory for the original of condition
gNB；Since user is in the process of moving there is no switching, virtual subdistrict identifier is constant；Anchor point gNB control is used in network
Family virtual subdistrict dynamic adjusts, to reduce frequent Signalling exchange in intensive small cell base station network.
Further, in the step S3, the property of virtual subdistrict system is measured by system time average energy efficiency
Can, system time average energy efficiency is defined as time average total number according to the ratio of digit rate and the consumption of time average total power.
Further, in the step S3, it to maximize the time average energy efficiency of system as optimization aim, and constrains
Have in condition and be averaged related constraint condition with the time, is converted into the excellent of each time slot using Lyapunov optimum theory
Change problem；Optimal resource allocation is carried out by minimizing the upper bound of the sum of Lyapunov offset function and penalty term, thus
Balance is realized between system queue stability and time averaging energy efficiency.
Further, in the step S3, it is the solving complexity for reducing problem, the energy in each time slot will be maximized
Efficiency optimization PROBLEM DECOMPOSITION is at two sub- optimization problems of equal value: 1) optimal transmission resource allocation optimization problem, and 2) optimal power
Allocation optimization problems；
When the virtual subdistrict of customer-centric carries out optimal transmission resource allocation, network is dynamic according to the channel conditions of user
Optimal gNB carries out data transmission in state selection virtual subdistrict, and the best resource block RB of transmission quality is distributed to corresponding
GNB, so that each user can obtain transmission quality best gNB and RB and service for it；
It is realized by three steps, firstly, first distributing the best RB of current transmission quality for each user；Secondly, guaranteeing
Each gNB is assigned RB；Finally, distributing remaining RB to most suitable user；
Gathered by the gNB and RB that obtain actually transmitting data in virtual subdistrict for user after optimal transmission resource allocation,
Optimization problem is converted into optimal power allocation problem；Then, it is carried out using Lagrange duality principle and subgradient update method
Solve optimal power value.
The beneficial effects of the present invention are:
1) optimal transmission resource allocation optimization problem.The virtual subdistrict of customer-centric carries out optimal transmission resource allocation
When, network can carry out data transmission according to gNB optimal in the channel conditions dynamic select virtual subdistrict of user, and will transmit matter
It measures best RB and distributes to corresponding gNB, so that each user can obtain transmission quality best gNB and RB and service for it.
2) optimal power allocation optimization problem.It is actually to use in virtual subdistrict by can be obtained after optimal transmission resource allocation
GNB and the RB set of data are transmitted in family, and optimization problem is converted into optimal power allocation problem.Then, Lagrange duality is utilized
Principle and subgradient update method carry out solving optimal power value.
The present invention fully considers user data package queue length and channel quality, by the average energy efficiency of maximization network
PROBLEM DECOMPOSITION is that user's optimal transmission resource allocation and optimal power allocation two sub-problems solve.By to the excellent of Internet resources
Change distribution, promote transmission quality, and realizes and guarantee the steady of system queue while maximizing system average energy efficiency
It is qualitative.
Other advantages, target and feature of the invention will be illustrated in the following description to a certain extent, and
And to a certain extent, based on will be apparent to those skilled in the art to investigating hereafter, Huo Zheke
To be instructed from the practice of the present invention.Target of the invention and other advantages can be realized by following specification and
It obtains.
Detailed description of the invention
In order to keep the purpose of the present invention, technical method and advantage clearer, the present invention is made below in conjunction with attached drawing excellent
The detailed description of choosing, in which:
Fig. 1 is the virtual cell network scene figure of customer-centric；
Fig. 2 is virtual subdistrict Establishing process figure；
Fig. 3 is optimal transmission resource allocation algorithm figure；
Fig. 4 is optimal power allocation algorithm pattern.
Specific embodiment
Illustrate embodiments of the present invention below by way of specific specific example, those skilled in the art can be by this specification
Other advantages and efficacy of the present invention can be easily understood for disclosed content.The present invention can also pass through in addition different specific realities
The mode of applying is embodied or practiced, the various details in this specification can also based on different viewpoints and application, without departing from
Various modifications or alterations are carried out under spirit of the invention.It should be noted that diagram provided in following embodiment is only to show
Meaning mode illustrates basic conception of the invention, and in the absence of conflict, the feature in following embodiment and embodiment can phase
Mutually combination.
Wherein, the drawings are for illustrative purposes only and are merely schematic diagrams, rather than pictorial diagram, should not be understood as to this
The limitation of invention；Embodiment in order to better illustrate the present invention, the certain components of attached drawing have omission, zoom in or out, not
Represent the size of actual product；It will be understood by those skilled in the art that certain known features and its explanation may be omitted and be in attached drawing
It is understood that.
The same or similar label correspond to the same or similar components in the attached drawing of the embodiment of the present invention；It is retouched in of the invention
In stating, it is to be understood that if there is the orientation or positional relationship of the instructions such as term " on ", "lower", "left", "right", "front", "rear"
To be based on the orientation or positional relationship shown in the drawings, be merely for convenience of description of the present invention and simplification of the description, rather than indicate or
It implies that signified device or element must have a particular orientation, be constructed and operated in a specific orientation, therefore is described in attached drawing
The term of positional relationship only for illustration, is not considered as limiting the invention, for the ordinary skill of this field
For personnel, the concrete meaning of above-mentioned term can be understood as the case may be.
It is the virtual cell network scene figure of customer-centric referring to Fig. 1, Fig. 1.Wherein by gNB and user's structure in network
At, and user be random distribution in a network.Assuming that a resource block (Resource Block, RB) is only assigned to one
GNB, and a user being assigned to only in the gNB uses.The total bandwidth of system is divided into the RB of N number of equal bandwidth, each
The bandwidth of RB is B=W/N.In the downlink, user is subjected to the transmission signal of gNB multiple in virtual subdistrict, i.e., empty
GNB uses the mode of CoMP to cooperate and provides service for user in quasi- cell, and is transmitted and used using different RB between the gNB to cooperate
User data.The interference and business of user in intensive small cell network is reduced in the virtual subdistrict for establishing customer-centric by this chapter
Continuity problem.
When Inactive user has data packet arrival in network, which accesses network by currently resident gNB and turns
Connection status is turned to, all gNB signal strengths and gNB loading condition detected according to user, after anchor point gNB screening
Establish the virtual subdistrict of customer-centric.In order to improve resource utilization, energy consumption is reduced, virtual subdistrict will carry out optimal transmission
Resource allocation, the gNB for only meeting transmission conditions are just cooperated in the form of CoMP as user service.
Referring to fig. 2, Fig. 2 is virtual subdistrict Establishing process figure.The virtual subdistrict of customer-centric can not only reduce it
His gNB to the interference of user, avoid user's frequent switching, moreover it is possible to eliminating edge customer improves communication quality.When user is in
When Inactive state, there is a position informing region RNA.Inactive user is when there is data transfer demands, by current
Resident gNB is converted to connection status, and using RNA as candidate virtual cell, and user detects all gNB signal strengths in RNA, warp
Cross the virtual subdistrict that customer-centric is established after anchor point gNB is screened.
Virtual subdistrict establishment process is as follows:
201, when there is the arrival of Inactive user data package in network, to position user, anchor point gNB paged initiation
Journey.User receives and is converted to connection status by currently resident gNB after paging message, accesses network；
202, after user access network, wireless access network notification area RNA when being in Inactive before user is made
For candidate virtual cell, user detects the RS intensity of all gNB in RNA and measurement result is reported to what user was currently resident
gNB；
203, user is currently resident gNB and the RS gNB for being greater than threshold value is reported to anchor point gNB, anchor point gNB according to measurement result
According to load information library, determines the gNB of Virtual cell and that result and virtual subdistrict configuration information are handed down to user is current
Resident gNB；
204, virtual subdistrict configuration information is sent respectively to user by the gNB that user is currently resident and corresponding gNB is constructed
The virtual subdistrict of customer-centric provides communication service by way of cooperation between transmission node for user in virtual subdistrict.
The present invention measures the performance of virtual subdistrict system by system time average energy efficiency, and system time is averaged energy
Amount efficiency is defined as time average total number according to the ratio of digit rate and the consumption of time average total power.
System may be expressed as: in the total user rate of t moment
Wherein, ak,m∈ { 0,1 } indicates the connection indicator variable in user k and virtual subdistrict between gNB m, ak,m=1 table
Show that user k is connect with gNB m, on the contrary ak,m=0.bn,m∈ { 0,1 } then indicates the distribution indicator variable between RB n and gNB m,
bn,mIndicate that RB n distributes to gNB m, otherwise bn,m=0.rk,n,m(t) the transmission digit rate for being gNB m user k on RB n.
Further, it is possible to obtain system time average total rate are as follows:
The sum of the power consumption of all gNB consumes in system for transmission data power and circuit power consumes, therefore this hair
Bright system power dissipation model is shown below:
Wherein τ is gNB power amplifier efficiency, and M is gNB quantity, pcirGNB generation circuit power when to be in idle condition
Consumption.The consumption of system time average total power may be expressed as:
If user's k downlink queue length is Qk(t), gNB side data packet queue length can indicate are as follows:
The queue length at t+1 moment=t moment queue length-t moment link is given out a contract for a project the arrival of number+t moment data packet
Number, then the downlink queue renewal process of user k indicates are as follows:
Qk(t+1)=max { Qk(t)-Dk(t),0}+Ak(t) (5)
Wherein, Qk(0)=0, Ak(t) it is the arrival number of user k data packet in time t, obeys Poisson distribution.Dk(t)
It is user k in the number of giving out a contract for a project of time t data packet, the size of each data packet is L, unit bit.
It can then be indicated using maximizing time average energy efficiency as the resource allocation optimization problem of target are as follows:
Wherein, RminFor the minimum transfer digit rate of each user, PmaxFor the maximum transmission power of single gNB.Constraint condition
C1Guarantee the stable demand of each Subscriber Queue, constraint condition C while maximizing system time average energy efficiency2For list
The minimum-rate constraint of demand of a user, constraint condition C3For the constraint of single gNB maximum transmission power, constraint condition C4It is single
The transimission power of user constrains, constraint condition C5It indicates each multiple gNB and can cooperate with as a user service, while one
GNB can distribute to multiple users, constraint condition C6Indicate that a RB can only distribute to a gNB, but each gNB can be divided
With multiple and different RB.
Further, it is based on Lyapunov Optimization Modeling, steps are as follows:
1) the Lyapunov function of system is defined:
2) Lyapunov transfer function is defined:
Δ Q (t)=E L (Q (t+1))-L (Q (t)) | Q (t) } (9)
3) Lyapunov penalty term is defined:
VU (t)=V (Rtot(t)-qPtot(t)) (10)
4) system optimization problem converts:
For the solving complexity for reducing problem, which is resolved into two sub- optimization problems of equal value: 1) optimal
Transfer resource allocation optimization problems 2) optimal power allocation optimization problem, and updated using Lagrange duality principle and subgradient
Method is solved.
It is optimal transmission resource allocation algorithm figure referring to Fig. 3, Fig. 3.Initialize installation first, it is assumed that have K use in system
Family, N number of RB, M gNB may make up the three dimensional channel gain matrix H (K, N, M) of K N × M in a network, i.e. K N row M is arranged
Channel gain matrix.Assuming that RB quantity is greater than gNB quantity and number of users, and gNB quantity is less than number of users, i.e. M≤K
≤N.Firstly, first distributing the best RB of current transmission quality for each user, secondly guarantee that each gNB is assigned RB,
Finally distribute the remaining RB user best to performance.Optimal transmission Resource Allocation Formula can be divided into the following three steps:
301, the best RB of current transmission quality is first distributed for each user.Ergodic channels gain matrix H (K, N,
M), by the maximum h of channel gaink,n,mCorresponding gNB distributes to corresponding user, and RB is distributed to gNB.It is right to delete RB institute
The row for the channel gain matrix answered, and delete the corresponding entire channel gain matrix of user.If gNB associated by this RB is not
In the virtual subdistrict of user, then this resource allocation is abandoned, selects suitable transfer resource again for user.It is surplus to continue traversal
Remaining channel yield value repeats above-mentioned allocation step until all users have gNB and RB to service for it.
302, guarantee that each gNB is assigned RB.It can since a gNB can be multiple user services by step 1)
It is repeated by the user selection, therefore there are the unallocated RB resources of M-x (1≤x≤M) a gNB, and N-K RB of residue is to be allocated.It is based on
This, generates new three dimensional channel gain matrix H'(K, N-K, M-x), i.e. the matrix of K N-K row M-x column.Continue ergodic channels to increase
Beneficial matrix H ', by the maximum h' of channel gaink',n',m'And corresponding gNB, corresponding user is distributed to, and RB is distributed to
gNB.The row and column for deleting the corresponding channel gain matrix of RB and gNB, judges whether the gNB distributed to user belongs to the void of user
Quasi- cell abandons this resource allocation if the gNB is not belonging to the virtual subdistrict of user.It repeats the above steps, until each
GNB is at least assigned RB, it can thus be concluded that gNB set G belonging to each userk, k ∈ 1,2 ... K }.
303, remaining RB is distributed to user.By step 1), 2), it is known that it is unallocated to there remains N-K-M+x RB, due to
GNB can distribute to multiple users, so still there is M gNB that can distribute.Based on this, generate three-dimensional matrice H " (K, N-K-M+x,
M), the matrix that both K N-K-M+x row M is arranged.Equally it is based on matrix H ", by maxgain value h "k",n",m"And its corresponding gNB points
The corresponding user of dispensing, and RB is distributed into gNB, allocated RB is deleted, until all RB are assigned, it can thus be concluded that each
The RB collection of gNB is combined into
GNB the and RB collection for actually transmitting data in virtual subdistrict for user can be obtained by optimal transmission resource allocation algorithm
Close, then the constraint condition C5 in optimization problem (11), C6, C7 have met, therefore former optimization problem can equivalence switch to it is following new
Optimization problem:
In the case where primary power efficiency value q is given, in order to acquire optimal power allocation, using Lagrange duality
It is as follows to obtain Lagrangian for method:
Wherein, αkAnd βmIt is constraint condition C respectively2And C3Corresponding Lagrange multiplier, and it is rightIt is all satisfied αk≥
0 and βm≥0。
Assuming that there are optimal solutionsSo that formula (12) objective function is optimal, and meet institute's Prescribed Properties.According to
KKT condition can pass through LagrangianL (p, αk,βm) to pk,n,m(t) derivation equation solution optimal power allocation solves
Optimal powerIt can obtain:
Wherein, [X]+=max { 0, X }.It, will be Lagrangian first with KKT condition during Lagrange solves
Multiplier is fixed, so that then Lagrange multiplier is updated by subgradient method after acquiring the power distribution of local optimum, when repeatedly
The approximate optimal solution of formula (15) can be acquired when meeting the condition of convergence for process.
Referring to fig. 4, Fig. 4 is optimal power allocation algorithm pattern.Lagrange multiplier α, β, control parameter value are initialized first
V, the queue length Q of t momentk(t),Primary power efficiency value q, error tolerate threshold value ε.Optimal power allocation scheme
It can divide that specific step is as follows:
401, according to (14) formula, the optimal power of t moment user k is calculated
402, the energy efficiency of t moment system is calculated
403, judge | Rtot(p*)-qPtot(p*) | whether≤ε is true；
404、|Rtot(p*)-qPtot(p*) | >=ε-algorithm, epsilon-algorithm is not converged, updates initial efficiency and isIt updates and draws
Ge Lang factor-alphak(t+1) and βm(t+1), iterative parameter t=t+1, return step 401 are updated；
405、|Rtot(p*)-qPtot(p*) | the convergence of≤ε-algorithm, epsilon-algorithm exports optimal power allocation p*WithAlgorithm
Terminate.
Finally, it is stated that above embodiments are only to illustrate technical method of the invention rather than limit, although referring to compared with
Good embodiment describes the invention in detail, those skilled in the art should understand that, it can be to skill of the invention
Art method is modified or replaced equivalently, and without departing from the objective and range of this technology method, should all be covered in the present invention
Scope of the claims in.
Claims (9)
1. the resource allocation methods based on user mobility in a kind of 5G small cell network, it is characterised in that:
This method is according to the characteristic of mentioned network scenarios, firstly, establishing the virtual of customer-centric after user access network
Cell reduces inter-cell interference and guarantees the business continuance of mobile subscriber；Secondly, when user transmits data to Internet resources
Optimize distribution；
Method includes the following steps:
S1: when inactive Inactive user has data service arrival, network is accessed by network paging；
S2: the virtual subdistrict of customer-centric is established after user access network；
S3: user optimizes distribution to Internet resources when transmitting data.
2. the resource allocation methods based on user mobility in a kind of 5G small cell network according to claim 1, special
Sign is: in the step S1, when there is the arrival of inactive Inactive user data package in network, to position user, anchor
Point gNB will initiate paging；User receives and is converted to connection status by currently resident gNB after paging message, accesses net
Network.
3. the resource allocation methods based on user mobility in a kind of 5G small cell network according to claim 1, special
Sign is: in the step S2, the virtual subdistrict for establishing customer-centric be divided into the following three steps:
S21: after user access network, wireless access network notification area RNA when will be in unactivated state before user as
Candidate virtual cell, user detect the reference signal RS intensity of all gNB in RNA and measurement result is reported to user currently stay
The gNB stayed；
S22: user is currently resident gNB and the RS gNB for being greater than threshold value is reported to anchor point gNB according to measurement result, anchor point gNB according to
Load information library determines the gNB of Virtual cell and result and virtual subdistrict configuration information is handed down to user and is currently resident
GNB；
S23: the gNB that user is currently resident by virtual subdistrict configuration information be sent respectively to user and corresponding gNB building with
Virtual subdistrict centered on family provides communication service by way of cooperation between transmission node for user in virtual subdistrict.
4. the resource allocation methods based on user mobility in a kind of 5G small cell network according to claim 1, special
Sign is: in the step S3, according to user data package queue length and channel quality, using the optimization based on Lyapunov
Method is established using the time average energy efficiency of maximization network as the resource allocation optimization target of target.
5. the resource allocation methods based on user mobility in a kind of 5G small cell network according to claim 2, special
Sign is: in the step S1, when user is in Inactive state, the connection of user and network is disconnected, and has a use
The notification area RNA of user location is positioned when paging.
6. the resource allocation methods based on user mobility in a kind of 5G small cell network according to claim 3, special
Sign is: in the step S2, due to the mobility of user, the gNB that the virtual subdistrict of customer-centric is included will be sent out
Raw dynamic change；With the movement of user, addition is met to the new gNB of condition, and removes the original gNB for the condition that is unsatisfactory for；By
In user in the process of moving there is no switching, virtual subdistrict identifier is constant；It is virtual to control user by anchor point gNB in network
District dynamic adjustment, to reduce frequent Signalling exchange in intensive small cell base station network.
7. the resource allocation methods based on user mobility in a kind of 5G small cell network according to claim 4, special
Sign is: in the step S3, the performance of virtual subdistrict system is measured by system time average energy efficiency, when system
Between average energy efficiency be defined as time average total number according to digit rate and time average total power consumption ratio.
8. the resource allocation methods based on user mobility in a kind of 5G small cell network according to claim 4, special
Sign is: in the step S3, the time average energy efficiency to maximize system has as optimization aim, and in constraint condition
Have and be averaged related constraint condition with the time, the optimization problem of each time slot is converted into using Lyapunov optimum theory；
Optimal resource allocation is carried out by minimizing the upper bound of the sum of Lyapunov offset function and penalty term, thus in system queue
Balance is realized between stability and time averaging energy efficiency.
9. the resource allocation methods based on user mobility in a kind of 5G small cell network according to claim 8, special
Sign is: in the step S3, for the solving complexity for reducing problem, will maximize the optimized for energy efficiency in each time slot
PROBLEM DECOMPOSITION is at two sub- optimization problems of equal value: 1) optimal transmission resource allocation optimization problem, and 2) optimal power allocation optimization
Problem；
When the virtual subdistrict of customer-centric carries out optimal transmission resource allocation, network is selected according to the channel conditions dynamic of user
It selects gNB optimal in virtual subdistrict to carry out data transmission, and the best resource block RB of transmission quality is distributed into corresponding gNB,
So that each user can obtain transmission quality best gNB and RB and service for it；
It is realized by three steps, firstly, first distributing the best RB of current transmission quality for each user；Secondly, guaranteeing each
GNB is assigned RB；Finally, distributing remaining RB to most suitable user；
Pass through gNB and the RB set for obtaining actually transmitting data in virtual subdistrict for user after optimal transmission resource allocation, optimization
Problem is converted into optimal power allocation problem；Then, it is solved using Lagrange duality principle and subgradient update method
Optimal power value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910290485.5A CN110012509B (en) | 2019-04-11 | 2019-04-11 | Resource allocation method based on user mobility in 5G small cellular network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910290485.5A CN110012509B (en) | 2019-04-11 | 2019-04-11 | Resource allocation method based on user mobility in 5G small cellular network |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110012509A true CN110012509A (en) | 2019-07-12 |
| CN110012509B CN110012509B (en) | 2022-04-19 |
Family
ID=67171133
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910290485.5A Active CN110012509B (en) | 2019-04-11 | 2019-04-11 | Resource allocation method based on user mobility in 5G small cellular network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110012509B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111314938A (en) * | 2020-02-24 | 2020-06-19 | 厦门大学 | Optimization method for time-frequency domain resource allocation of cellular network of single cell |
| CN113115401A (en) * | 2021-05-11 | 2021-07-13 | 中国电子科技集团公司第三十八研究所 | Access control method for maximizing satisfied user number in cellular network |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101772028A (en) * | 2009-01-05 | 2010-07-07 | 华为技术有限公司 | Resource management method, network equipment, user equipment and system |
| US20120281641A1 (en) * | 2011-05-06 | 2012-11-08 | The Hong Kong University Of Science And Technology | Orthogonal frequency division multiple access (ofdma) subband and power allocation |
| CN105376748A (en) * | 2014-08-27 | 2016-03-02 | 中兴通讯股份有限公司 | Construction method of virtual cell, selection method of cooperating node and device |
| WO2016036111A1 (en) * | 2014-09-04 | 2016-03-10 | Samsung Electronics Co., Ltd. | Resource management method and apparatus |
| CN105764100A (en) * | 2016-01-29 | 2016-07-13 | 北京邮电大学 | Mobility enhancement scheme based on the design of virtual cell facing dense cell disposition |
| CN107040917A (en) * | 2016-02-03 | 2017-08-11 | 上海贝尔股份有限公司 | Method and apparatus for generating virtual subdistrict mark |
| CN107426809A (en) * | 2017-06-20 | 2017-12-01 | 西安电子科技大学 | WVN power and cache allocation method based on Virtual User queuing model |
| CN107708157A (en) * | 2017-11-22 | 2018-02-16 | 重庆邮电大学 | Intensive small cell network resource allocation methods based on efficiency |
| WO2018065527A1 (en) * | 2016-10-06 | 2018-04-12 | Sony Corporation | Entity and user equipment for a mobile telecommunications system |
| CN108430104A (en) * | 2018-03-07 | 2018-08-21 | 北京科技大学 | A kind of method and its system of optimized for energy efficiency and resource allocation |
| CN108462996A (en) * | 2018-03-07 | 2018-08-28 | 北京科技大学 | A kind of non-orthogonal multiple network resource allocation method |
| CN109479238A (en) * | 2016-07-22 | 2019-03-15 | 索尼公司 | Mobile communication system method, user equipment and base station for on-demand Transmission system information |
-
2019
- 2019-04-11 CN CN201910290485.5A patent/CN110012509B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101772028A (en) * | 2009-01-05 | 2010-07-07 | 华为技术有限公司 | Resource management method, network equipment, user equipment and system |
| US20120281641A1 (en) * | 2011-05-06 | 2012-11-08 | The Hong Kong University Of Science And Technology | Orthogonal frequency division multiple access (ofdma) subband and power allocation |
| CN105376748A (en) * | 2014-08-27 | 2016-03-02 | 中兴通讯股份有限公司 | Construction method of virtual cell, selection method of cooperating node and device |
| WO2016036111A1 (en) * | 2014-09-04 | 2016-03-10 | Samsung Electronics Co., Ltd. | Resource management method and apparatus |
| CN105764100A (en) * | 2016-01-29 | 2016-07-13 | 北京邮电大学 | Mobility enhancement scheme based on the design of virtual cell facing dense cell disposition |
| CN107040917A (en) * | 2016-02-03 | 2017-08-11 | 上海贝尔股份有限公司 | Method and apparatus for generating virtual subdistrict mark |
| CN109479238A (en) * | 2016-07-22 | 2019-03-15 | 索尼公司 | Mobile communication system method, user equipment and base station for on-demand Transmission system information |
| WO2018065527A1 (en) * | 2016-10-06 | 2018-04-12 | Sony Corporation | Entity and user equipment for a mobile telecommunications system |
| CN107426809A (en) * | 2017-06-20 | 2017-12-01 | 西安电子科技大学 | WVN power and cache allocation method based on Virtual User queuing model |
| CN107708157A (en) * | 2017-11-22 | 2018-02-16 | 重庆邮电大学 | Intensive small cell network resource allocation methods based on efficiency |
| CN108430104A (en) * | 2018-03-07 | 2018-08-21 | 北京科技大学 | A kind of method and its system of optimized for energy efficiency and resource allocation |
| CN108462996A (en) * | 2018-03-07 | 2018-08-28 | 北京科技大学 | A kind of non-orthogonal multiple network resource allocation method |
Non-Patent Citations (6)
| Title |
|---|
| HONGXIN WEI: "Energy-efficient resource allocation for small-cell networks: A stable queue perspective", 《IEEE》 * |
| KEYVAN ZARIFI: "Radio access virtualization: Cell follows user", 《IEEE》 * |
| WEIHUA WU: "Adaptive Resource Allocation Algorithm of Lyapunov Optimization for Time-Varying Wireless Networks", 《IEEE COMMUNICATIONS LETTERS》 * |
| 曹春燕: "MEC 辅助的 Inactive 状态用户动态位置管理方案", 《重庆邮电大学学报(自然科学版)》 * |
| 赵晓宁: "超密集网基于干扰公平及多维协作的虚拟小区生成算法", 《电信科学》 * |
| 陈露: "超密集网络中以用户为中心的虚拟小区技术研究", 《硕士电子期刊》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111314938A (en) * | 2020-02-24 | 2020-06-19 | 厦门大学 | Optimization method for time-frequency domain resource allocation of cellular network of single cell |
| CN113115401A (en) * | 2021-05-11 | 2021-07-13 | 中国电子科技集团公司第三十八研究所 | Access control method for maximizing satisfied user number in cellular network |
| CN113115401B (en) * | 2021-05-11 | 2022-04-01 | 中国电子科技集团公司第三十八研究所 | Access control method for maximizing satisfied user number in cellular network |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110012509B (en) | 2022-04-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Peng et al. | System architecture and key technologies for 5G heterogeneous cloud radio access networks | |
| CN106954267B (en) | A kind of method for managing resource based on wireless network slice | |
| CN110493826B (en) | Heterogeneous cloud wireless access network resource allocation method based on deep reinforcement learning | |
| Han et al. | 5G converged cell-less communications in smart cities | |
| Peng et al. | Heterogeneous cloud radio access networks: A new perspective for enhancing spectral and energy efficiencies | |
| CN104796918B (en) | The method of wireless communication network | |
| JP5697622B2 (en) | Mobile communication system and remote radio unit clustering method thereof | |
| Ran et al. | Balancing backhaul load in heterogeneous cloud radio access networks | |
| CN109792613A (en) | Provided for radio resources management configures device and method | |
| CN104641695B (en) | Energy saving method in cellular communication system | |
| WO2015131677A1 (en) | Method and device for constructing virtual cell and selecting cooperative node | |
| CN105325029A (en) | User equipment and evolved node-B supporting machine type communication and small data communication | |
| US9294960B2 (en) | Method, apparatus and system for cooperative resource scheduling and cooperative communication | |
| CN104053163A (en) | Heterogeneous wireless network networking method based on calculation and processing | |
| KR102051831B1 (en) | Method and apparatus for traffic load balancing in mobile communication system | |
| Georgakopoulos et al. | Coordination multipoint enabled small cells for coalition-game-based radio resource management | |
| CN103781120A (en) | Mobility load balancing method combined with hierarchical dynamic resource distribution | |
| CN107708157A (en) | Intensive small cell network resource allocation methods based on efficiency | |
| CN106454909A (en) | AP set information processing method and eNB | |
| CN105050124A (en) | Service-aware based interstation spectrum resource polymerization method of heterogeneous cellular network | |
| CN110012509A (en) | Resource allocation methods based on user mobility in a kind of 5G small cell network | |
| CN107454601B (en) | Wireless virtual mapping method considering inter-cell interference under ultra-dense environment | |
| Wang et al. | MiFo: A novel edge network integration framework for fog computing | |
| CN102651879A (en) | Method for selecting cooperative cells based on UE intelligent association and cooperative user equipment | |
| CN104363621A (en) | Tracking area management entity, switching method based on tracking area change and switching device based on tracking area change |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20231024 Address after: Room 596, No. 503, Lane 6825, Caolang Road, Langxia Town, Jinshan District, Shanghai 201500 Patentee after: Shanghai Miyang Communication Technology Co.,Ltd. Address before: 400065 Chongqing Nan'an District huangjuezhen pass Chongwen Road No. 2 Patentee before: CHONGQING University OF POSTS AND TELECOMMUNICATIONS |