CN104918262B - Network optimized approach and device - Google Patents
Network optimized approach and device Download PDFInfo
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- CN104918262B CN104918262B CN201410088189.4A CN201410088189A CN104918262B CN 104918262 B CN104918262 B CN 104918262B CN 201410088189 A CN201410088189 A CN 201410088189A CN 104918262 B CN104918262 B CN 104918262B
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- 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
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
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- 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
- H04W28/08—Load balancing or load distribution
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Abstract
A kind of network optimized approach of offer of the embodiment of the present invention and device, wherein the method includes：Each user is grouped according to the transmitting-receiving performance parameter of each user of acquisition, forms at least two user groups, and obtain the connectivity of each user group respectively；The power sharing learning of each user and the power sharing learning of each user group are obtained respectively；According to the power of each node, the power sharing learning of Downtilt, the power sharing learning of each user and each user group, internuncial optimal value of each user group and internuncial optimal value of each user are obtained；According to internuncial optimal value of each user group, the power of each node and the optimal value of Downtilt are obtained；It repeats the above steps, until iterations reach preset first threshold；Obtain power, Downtilt and the internuncial optimal value of each user of each node in network.The embodiment of the present invention improves power system capacity and covering performance and resource utilization ratio.
Description
Technical field
The present embodiments relate to the communication technology more particularly to a kind of network optimized approach and device.
Background technology
Self-organization of network technology（Self-Organized Network, abbreviation SON）Refer to network according to Network status from
It is dynamic to carry out self-configuring, self-optimizing, from operations such as healings, realize that real-time automated network is safeguarded, it is artificial dry so as to reduce
In advance, O＆M cost is reduced.Capacity and coverage optimization（Coverage and Capacity Optimization, abbreviation COO）, it is negative
It carries balanced（Load Balancing, abbreviation LB）It is two important use-cases of SON.
Existing capacity and coverage optimization technology are accomplished that the optimization of cell-level, with improve cell average spectral efficiency and
Edge spectrum efficiency is target, maximizes capacity and the covering of each cell as possible；But for whole net, the prior art can not
It most makes full use of system resource and maximizes capacity and the covering of system, be especially distributed highly non-uniform situation in network load
Under, heavy duty cell is difficult to meet the needs of community user due to inadequate resource, to cause business service quality
（Quality of Service, abbreviation QoS）Decline.Therefore, the prior art can not make the capacity and covering performance of system
Being optimal.
Existing load-balancing technique is used come triggering part according to the load difference counted in each cell operational process
The switching at family makes certain customers' reconnection of high load cell be connected to neighbouring low-load cell, by the load for realizing minizone
Transfer is so that the load of each cell is able to equilibrium, the reduction of guarantee inter-cell load difference, to have front to network capacity
Influence, still, the prior art can not be such that the capacity of system and covering performance reaches most only using the load of cell as measurement index
Optimization.
Invention content
A kind of network optimized approach of offer of the embodiment of the present invention and device, to solve power system capacity and covering performance and resource
The low problem of utilization rate.
In a first aspect, the embodiment of the present invention provides a kind of network optimized approach, wherein the method includes：
Each user is grouped according to the transmitting-receiving performance parameter of each user of acquisition, forms at least two users
Group, and the connectivity of each user group is obtained respectively；Wherein, the connectivity of the user group is used to indicate the pass of user group
Interlink point；
The power sharing learning of each user and the power sharing learning of each user group are obtained respectively；
According to the power of each node, Downtilt, the power sharing learning of each user and each user group
Power sharing learning obtains internuncial optimal value of each user group and internuncial optimal value of each user；Its
In, the connectivity of the user is used to indicate the associated nodes of user；
According to internuncial optimal value of each user group, obtain each node power and Downtilt it is excellent
Change value；
It repeats the above steps, until iterations reach preset first threshold；
Obtain the power of each node in the network, Downtilt and internuncial optimal value of each user.
It is described according to each node according in a first aspect, in the first possible realization method of first aspect
The power sharing learning of power, Downtilt, the power sharing learning of each user and each user group, described in acquisition
Internuncial optimal value of each user group and internuncial optimal value of each user, including：
According to the connection of the power of each node, the power sharing learning of each user group and each user group
Property, determine the power of each user group；
The candidate association node for traversing each user group respectively, according to the Downtilt of each node and described each
The power and power sharing learning of user group obtain the candidate association of each user group and corresponding candidate association node
Interference correlative；
Each user group is corresponding with the least interference correlative of candidate association in corresponding candidate association node respectively
Purpose associated nodes establish association；
According to the maximum value and Objective of the power of the least interference correlative of each user group, each user group
Can, update the power of each user group；
It repeats the above steps, until the power update amplitude of each user group is no more than preset second threshold；
Obtain internuncial optimal value of each user group and the optimal value of power；
According to the relevance of the internuncial optimal value and user and user group of each user group, each user is determined
Internuncial optimal value.
It is described according to each user group according in a first aspect, in second of possible realization method of first aspect
Internuncial optimal value, obtain the power of each node and the optimal value of Downtilt, including：
The candidate Downtilt for traversing each node respectively, according to internuncial optimal value of each user group,
Obtain interference correlative of each node to the candidate association of corresponding candidate Downtilt；
Each node is corresponding with the least interference correlative of candidate association in corresponding candidate Downtilt respectively
Purpose Downtilt establish association；
According to the least interference correlative of each node, the maximum value and performance limits of the power of each node, more
The power of new each node；
It repeats the above steps, until the power update amplitude of each node is no more than preset third threshold value；
Obtain the optimal value of the Downtilt of each node and the optimal value of power.
According in a first aspect, in the third possible realization method of first aspect, the transmitting-receiving performance parameter is：With
The Reference Signal Received Power RSRP that family measures, and/or, the signal-to-noise ratio SINR of user.
Second aspect, the embodiment of the present invention provide a kind of network optimization device, wherein described device includes：
Grouped element, the transmitting-receiving performance parameter for each user according to acquisition are grouped each user, are formed
At least two user groups, and the connectivity of each user group is obtained respectively；Wherein, the connectivity of the user group, for referring to
Show the associated nodes of user group；
First acquisition unit, the power of power sharing learning and each user group for obtaining each user respectively
Sharing learning；
Second acquisition unit, for according to the power of each node, Downtilt, each user power sharing learning
And the power sharing learning of each user group, obtain internuncial optimal value of each user group and the company of each user
The optimal value of connecing property；Wherein, the connectivity of the user is used to indicate the associated nodes of user；
Third acquiring unit obtains the work(of each node for internuncial optimal value according to each user group
The optimal value of rate and Downtilt；
Iteration unit, for grouped element, the first acquisition unit, the second acquisition unit described in iteration control and
The third acquiring unit, until iterations reach preset first threshold；
Acquiring unit, for obtaining the internuncial of the power of each node in the network, Downtilt and each user
Optimal value.
According to second aspect, in the first possible realization method of second aspect, the second acquisition unit, specifically
For：
According to the connectivity of the power of each node, the power sharing learning of each user and each user group,
Determine the power of each user group；
The candidate association node for traversing each user group respectively, according to the Downtilt of each node and described each
The power and power sharing learning of user group obtain the candidate association of each user group and corresponding candidate association node
Interference correlative；
Each user group is corresponding with the least interference correlative of candidate association in corresponding candidate association node respectively
Purpose associated nodes establish association；
According to the maximum value and Objective of the power of the least interference correlative of each user group, each user group
Can, update the power of each user group；
It repeats the above steps, until the power update amplitude of each user group is no more than preset second threshold；
Obtain internuncial optimal value of each user group and the optimal value of power；
According to the relevance of the internuncial optimal value and user and user group of each user group, each user is determined
Internuncial optimal value.
According to second aspect, in second of possible realization method of second aspect, the third acquiring unit, specifically
For：
The candidate Downtilt for traversing each node respectively, according to internuncial optimal value of each user group,
Obtain interference correlative of each node to the candidate association of corresponding candidate Downtilt；
Each node is corresponding with the least interference correlative of candidate association in corresponding candidate Downtilt respectively
Purpose Downtilt establish association；
According to the least interference correlative of each node, the maximum value and performance limits of the power of each node, more
The power of new each node；
It repeats the above steps, until the power update amplitude of each node is no more than preset third threshold value；
Obtain the optimal value of the Downtilt of each node and the optimal value of power.
According to second aspect, in the third possible realization method of second aspect, the transmitting-receiving performance parameter is：With
The Reference Signal Received Power RSRP that family measures, and/or, the signal-to-noise ratio SINR of user.
Network optimized approach and device provided in an embodiment of the present invention pass through capacity to network and covering and load balancing
Carry out combined optimization, solve capacity in the prior art and covering and load balancing respectively single optimization and lead to the capacity of system
The problem low with covering performance and resource utilization so that the capacity and covering performance of system are optimized, and ensure cell
Between load be relative equilibrium, improve resource utilization ratio.
Description of the drawings
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technology description to be briefly described, it should be apparent that, the accompanying drawings in the following description is this hair
Some bright embodiments for those of ordinary skill in the art without having to pay creative labor, can be with
Obtain other attached drawings according to these attached drawings.
Fig. 1 is the flow chart of network optimized approach provided in an embodiment of the present invention；
Fig. 2 is the flow chart of load balancing provided in an embodiment of the present invention；
Fig. 3 is the flow chart of capacity provided in an embodiment of the present invention and coverage optimization；
Fig. 4 is the structural schematic diagram of network optimization device provided in an embodiment of the present invention.
Specific implementation mode
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art
The every other embodiment obtained without creative efforts, shall fall within the protection scope of the present invention.
Technical solution provided in an embodiment of the present invention can be applied to various cordless communication networks, such as：The whole world is mobile logical
Letter（Global system for mobile communication, referred to as GSM）System, CDMA（code
Division multiple access, referred to as CDMA）System, wideband code division multiple access（wideband code division
Multiple access, referred to as WCDMA）System, universal mobile communications（universal mobile
Telecommunication system, referred to as UMTS）System, General Packet Radio Service（general packet
Radio service, referred to as GPRS）System, long term evolution（Long term evolution, referred to as LTE）System, elder generation
Into long term evolution（Long term evolution advanced, referred to as LTE-A）System, global interconnection inserting of microwave
（Worldwide interoperability for microwave access, referred to as WiMAX）System etc..Term " net
Network " and " system " can be replaced mutually.
In embodiments of the present invention, node can be and user equipment（User equipment, referred to as UE）Or it is other
The equipment that communication site's such as relay is communicated, the node for example can be base stations（Basestation, referred to as
BS）, the communication overlay of specific physical region can be provided.For example, base station can be specifically the base transceiver station in GSM or CDMA
（Base Transceiver Station, referred to as BTS）Or base station controller（Base Station Controller, referred to as
For BSC）；Can also be the node B in UMTS（Node B, referred to as NB）Or the radio network controller in UMTS（Radio
Network Controller, referred to as RNC）；It can also be Home eNodeB；It can also be the evolved base station in LTE
（Evolutional Node B, referred to as eNB or eNodeB）；Alternatively, can also be the offer access in cordless communication network
Other access network equipments of service, the present invention do not limit.In embodiments of the present invention, user can be distributed in entire wireless network
In network, each user can be static or mobile.
Fig. 1 is the flow chart of network optimized approach provided in an embodiment of the present invention.As shown in Figure 1, the embodiment of the present invention carries
The network optimized approach of confession, including：
101, according to current network configuration, the current connectivity of each user is obtained, and calculate the receipts of each user
Volatility parameter simultaneously carries out user grouping, forms at least two user groups, determines the relevance of user and user group, determine described in
The connectivity of each user group；Wherein, the connectivity of the user is used to indicate the associated nodes of user；The company of the user group
Connecing property is used to indicate the associated nodes of user group.
Specifically, the current network configuration refers to the wireless parameter configuration of each node in current time, network, such as
Power distribution, Downtilt setting and other wireless resource management parameters；The transmitting-receiving performance parameter for example, it may be
The Reference Signal Received Power that user measures（Reference Signal Receiving Power, RSRP）, can also be use
The signal-to-noise ratio at family（SINR）.
102, according to the power that the current associated nodes of each user are each user distribution, each user is obtained respectively
Power sharing learning and each user group power sharing learning.
Specifically, the power sharing learning of user refers to the associated nodes that the power assigned by the user accounts for the user
The proportion of total allocation power；The power sharing learning of user group refers to the pass that the power assigned by the user group accounts for the user group
The proportion of the total allocation power of interlink point.In the case where current network configuration is connected with user, node is that each user is assigned with accordingly
Power, it is power sharing ratio that the user obtains that the power sharing learning of user is corresponding；The power sharing learning of user group
Corresponding is the power sharing ratio that the user group is obtained.
103, according to the power of each node, Downtilt, the power sharing learning of each user and described each
The power sharing learning of user group, obtain each user group internuncial optimal value and each user it is internuncial excellent
Change value.
104, according to internuncial optimal value of each user group, the power and Downtilt of each node are obtained
Optimal value.
105, judge that iterations reach preset first threshold：If iterations reach the first threshold, go to
Step 106；If iterations are not up to the first threshold, iterations are added 1, and go to step 101.
106, network optimization result is obtained；Wherein, the network optimization result includes：Each user's is internuncial excellent
The optimal value of the power and Downtilt of change value and each node.
Specifically, the executive agent of the embodiment of the present invention can be network optimization device, and the network optimization device can be with
It is arranged on node in a network or convergence device, can also be arranged on webmaster or be separately provided.
Network optimized approach provided in an embodiment of the present invention, the first step are grouped each user to form different users
Group optimizes institute according to the power of each node and Downtilt, user power sharing learning and user group power sharing learning
The connectivity for having user group reaches the load balancing of whole net；Second step, it is optimal according to internuncial optimal value of each user group
The power and Downtilt for changing all nodes, the capacity and covering performance for reaching whole net maximize；By to above two step
Iteration realizes the capacity and the combined optimization of covering and load balancing of network, solves capacity in the prior art and covering and bears
It carries balanced respectively single optimization and leads to the capacity and covering performance and the low problem of resource utilization of system so that the appearance of system
Amount and covering performance are optimized, and ensure that the load of minizone is relative equilibrium, improve resource utilization ratio.
Network optimized approach provided in an embodiment of the present invention is joined by capacity to network and covering with load balancing
Close optimization, solve capacity in the prior art and covering and load balancing respectively single optimization and lead to capacity and the covering of system
Performance and the low problem of resource utilization so that the capacity and covering performance of system are optimized, and ensure the negative of minizone
Load is relative equilibrium, improves resource utilization ratio.
Fig. 2 is the flow chart of load balancing provided in an embodiment of the present invention.Load balancing provided in an embodiment of the present invention is
The method that whole net load balancing is realized in above-described embodiment is further limited.As shown in Fig. 2, the embodiment of the present invention provides
Load-balancing method, including：
201, according to the power of each node and Downtilt, the power sharing learning of each user and each described
The connectivity of user group determines the power of each user group.
202, for each user group, the candidate association node of the user group is traversed, according to the power of the user group, institute
The power sharing learning of each user and the Downtilt of each node are stated, the candidate association for obtaining the user group and traversing
The interference correlative of the candidate association of node, and the minimum corresponding candidate association node of interference correlative is determined as the use
The purpose associated nodes of family group.
203, each user group is associated with the foundation of its purpose associated nodes respectively.
204, according to the maximum value and target of the power of the least interference correlative of each user group, each user group
Performance updates the power of each user group.
205, judge whether the update amplitude of the power of each user group is no more than preset second threshold：If updating width
Degree is no more than the second threshold, then goes to step 206；If the amplitude of update is more than the second threshold, step 201 is gone to.
206, internuncial optimal value of each user group and the optimal value of power are obtained.
207, it according to the relevance of the internuncial optimal value and user and user group of each user group, determines described each
Internuncial optimal value of user.
Specifically, method provided in an embodiment of the present invention, according to the power and Downtilt of each node in network, optimization
The connectivity and power of all user groups in network realize the negative of whole net while ensureing the capacity and covering performance of system
Equilibrium is carried, to improve network performance.Wherein, the performance of user group can at least be indicated by following three kinds of modes：
The average behavior of all users in mode 1, user group, can reflect the volumetric properties of user group.
Worst user performance in mode 2, user group, can reflect the covering performance of user group.
The weighting of the average behavior of all users and worst user performance in mode 3, user group, can reflect user group
The trade off performance of capacity and covering.
For mode 1：If considering the average behavior of all users in user group, all users in user group may be used
Downlink be averaged performance indicators of the SINR as network, by taking user group c as an example, the downlink evenness of all users in user group c
Energy, pass through following formula（1）It obtains：
Wherein：KcIndicate the number of users in user group c；Κ(c)Indicate the user index in user group c, c ∈ [1, C], C
Indicate user group number；K indicates k-th of user in user group c（User k）, k ∈ [1, K], K indicate the number of users in network
Mesh；SINRkIndicate the SINR of user k；It is averaged the lower limit of SINR for the downlink of all users in user group c；qkIt indicates to use
The associated nodes of family k are the power of user's k distribution, vkkThe associated nodes of user k are indicated to the channel gain of the user k,
Indicate interfering for other node signals being subject to when user k is associated with node communication,Indicate average noise power, gk=αkvkk；
Wherein,Indicate coupling matrix,It indicates to send when Downtilt is θ
To user k1 signal to the reception gain of user k2, VθForIn self-interference and cell in/user group in distracter zero setting
The interference and coupling matrix obtained afterwards, VθIndicate that the Downtilt in the affiliated nodes of user group c is θ, and doing certainly by each user
Disturb in cell/user group in user's interference volume after distracter zero setting；
J indicates node-user-association matrix, Jbk=1 indicates that the connectivity of user k, i.e. user k are assigned
The interstitial content in network is indicated to node b, b ∈ [1, B], B；U indicates reception gain matrix, UbkIndicate node b to user k's
Reception gain；
J=BAT, B expression node-user group incidence matrix, Bbc=1 indicates that the connectivity of user group c, i.e. user group c are referred to
It is fitted on node b；A indicates user-user group incidence matrix, Akc=1 indicates that the relevance of user k and user group c, i.e. user k are referred to
It is fitted on user group c；ATα=1, α indicate user power allocation vector α=[α1,...,αK]T, αkIndicate the power of user k it is shared because
Son；AαIndicate user-user group associated power matrix, Aα=diag{α}A；
P indicates user group vector power, p=[p1,...,pC]T, pcIndicate the power in user group c；p=diag{β}BTr；β
Indicate user group power allocation vector, β=[β1,...,βC]T, βcIndicate the power sharing learning of user group c, β=1 B；R indicates section
Point vector power, r=[r1,...,rB]T, rbIndicate the power of node b.
Definition：Interference matrix between user groupThe element of interference matrix G interferes between user group between user group
Measure g；WithThen formula（1）It can be written as formula（2）：
According to the uplink and downlink principle of duality, the be averaged lower limit of SINR of the uplink of all users is in user group c：
Definition：n=[n1,...,nC], and define one and channel gain and dry
The related interference correlative D of the amount of disturbing-1Gp+D-1N, the then performance of user group cCorresponding minimum interferes phase when maximization
Pass amount is Ιc(p)：
Wherein, bcIndicate a candidate association node of user group c, BcIndicate the collection of the candidate association node of user group c
It closes.
For each user group, and node association can by single optimization, and with the association of other users group
Property is uncorrelated.
For mode 2：If considering the performance of worst user in user group, may be used in user group under worst user
Performance indicators of the row SINR as network, by taking user group c as an example, the downlink performance of worst user in user group cBy such as
Lower formula（5）It obtains：
Wherein：S indicates the worst user's oriental matrixs of SINR in all user groups, S=[s1|...|sC]T, scIt is a K dimension
Vector, scIndicate that the worst users of SINR indicate vector, s in user group ckc=1 indicates the SINR of the user k in user group c in user
User worst SINR, s in group ccIn in addition to the corresponding element of user worst in user group c be 1 other than, other elements are 0；
The performance of user group cCorresponding minimum antithesis uplink interference correlative is when maximization：
For mode 3：If considering the weighting of the average behavior and worst user performance of all users in user group, use
Following formula characterization can be used in the performance of family group c minimum interference correlative corresponding when maximizing：
Wherein, μ ∈ [0,1] are weighted value, can indicate the average behavior of all users in control user group and worst
User performance compromise degree；The purpose for interfering the corresponding candidate association node of correlative minimum value to be determined as user group c is associated with section
Point.
As it can be seen that in conjunction with the power and Downtilt of node, by optimizing the connectivity of user group c, use can be calculated
The optimal performance u of family group cc, wherein ucCan be that the uplink of all users in user group c is averaged the lower limit of SINR（Corresponding to use
The volumetric properties of family group）, worst user SINR（Corresponding to the covering performance of user group）And the synthesis of the two（Correspond to
The capacity of user group and the trade off performance of covering）；Solve above-mentioned formula（7）Corresponding solution, which corresponds to, obtains the optimal of user group c
Performance uc。
The above method uses fixed point optimization algorithm, in conjunction with the power of each node, formula（7）Solution can pass throughIteration optimization realize；Wherein,Indicate the maximum value of the power of user group c；For
The target capabilities of user group c,Depending on the rate requirement of user, n indicates iterations.
For SON, the performance of all users of the whole network optimized is needed, for this purpose, based on ensureing all users' of the whole network
Fairness, SON optimization aims are to maximize the performance of the worst user group of performance in all user groups, i.e.,：
Wherein, PmaxIndicate the maximum value of the user group power in all user groups.
Above-mentioned formula（8）The network optimum target capabilities of reflection are equal to：
Load-balancing method provided in an embodiment of the present invention, using fixed point optimization algorithm, according to each node in network
Power and Downtilt optimize the connectivity and power of all user groups in network, in the capacity and spreadability for ensureing system
While energy, the load balancing of whole net is realized, to improve network performance.
Fig. 3 is the flow chart of capacity provided in an embodiment of the present invention and coverage optimization.Capacity provided in an embodiment of the present invention
It is further limiting for the method for the capacity and coverage optimization for realizing network in above-described embodiment with coverage optimization.Such as Fig. 3
It is shown, capacity and coverage optimization method provided in an embodiment of the present invention, including：
301, the power of each node is initialized.
302, for each node, the candidate Downtilt of the node is traversed, according to the connection of each user group
Property optimal value, obtain interference correlative of the node based on the candidate Downtilt traversed, and by minimum interference phase
Measure the purpose Downtilt that corresponding candidate Downtilt is determined as the node in pass.
303, according under the least interference correlative of each node, the maximum value and performance of the power of each node
Limit updates the power of each node.
304, judge whether the update amplitude of the power of each node is no more than preset third threshold value：If the amplitude of update
No more than the third threshold value, then step 305 is gone to；If the amplitude of update is more than the third threshold value, step 301 is gone to.
305, the optimal value of the Downtilt of each node and the optimal value of power are obtained.
Specifically, method provided in an embodiment of the present invention optimizes according to internuncial optimal value of each user group in network
The Downtilt and power of all nodes realize that the load of whole net is equal while ensureing the capacity and covering performance of system
Weighing apparatus, to improve network performance.Wherein, the performance of node can at least be indicated by following three kinds of modes：
The average behavior of all users, can reflect the volumetric properties of node in mode 1` nodes.
Worst user performance in mode 2` nodes, can reflect the covering performance of node.
The weighting of the average behavior and worst user performance of all users, can reflect the capacity of node in mode 3` nodes
With the trade off performance of covering.
For mode 1`：If considering the average behavior of all users in node, all users in node may be used
Downlink is averaged performance indicators of the SINR as network, by taking node b as an example, the downlink average behavior of all users in node bPass through following formula（10）It obtains：
Wherein：Κ(b)Indicate the number of users in node b, C(b)Indicate user's group index in node b,
It is averaged the lower limit of SINR for the downlink of all users in node b.
According to the uplink and downlink principle of duality, the be averaged lower limit of SINR of the uplink of all users is in node b：
Definition：The then property of node b
Corresponding minimum interference correlative is when can maximize：
Wherein, θbIndicate a candidate Downtilt of node b, ΘbIndicate the collection of the candidate Downtilt of node b
It closes, θ indicates the Downtilt vector of nodes, θ=[θ1,...,θB],
For mode 2：If considering the performance of worst user in node, the downlink of worst user in node may be used
Performance indicators of the SINR as network, by taking node b as an example, the downlink performance of worst user in node bPass through following formula
（14）It obtains：
Wherein：T=diag{α}Adiag{β}BT, q=Tr.
According to the uplink and downlink principle of duality, the ascending performance of worst user in node bFor：
The performance of node bCorresponding minimum interference correlative is when maximization：
For mode 3：If considering the weighting of the average behavior and worst user performance of all users in node, that is, combine
When optimizing the capacity and covering performance of each cell, then corresponding minimum interferes correlative when the performance of node b maximizes
Following formula characterization can be used：
The purpose Downtilt that the corresponding candidate Downtilt of correlative minimum value will be interfered to be determined as node b.
As it can be seen that in conjunction with internuncial optimal value of each user group, by optimizing the Downtilt and power of node b,
The optimal performance u of egress b can be calculatedb, wherein ubCan be that the uplink of all users in node b is averaged the lower limit of SINR（It is right
It should be in the volumetric properties of node）, worst user SINR（Corresponding to the covering performance of node）And the synthesis of the two（It is corresponding
In the capacity of node and the trade off performance of covering）；Solve above-mentioned formula（17）Corresponding solution corresponds to the optimality for obtaining node b
It can ub。
The above method uses fixed point optimization method, in conjunction with the power of node b, formula（17）Solution can pass throughIteration optimization realize；Wherein,Indicate the maximum value of the power of node b, γbFor
Minimum SINR thresholdings usually take -6.5dB, n to indicate iterations.
For SON, the performance of all users of the whole network optimized is needed, for this purpose, based on ensureing all users' of the whole network
Fairness, SON optimization aims are to maximize the performance of the worst node of performance in all nodes, i.e.,：
Wherein, rmaxIndicate the maximum value in all node interior joint power.
Capacity and coverage optimization method provided in an embodiment of the present invention, using fixed point optimization algorithm, according to each use
Internuncial optimal value of family group, optimize network in all nodes Downtilt and power, ensure system capacity and
While covering performance, the load balancing of whole net is realized, to improve network performance.
In network optimized approach provided in an embodiment of the present invention, the input dependence of load balance optimization process in capacity with cover
The power and Downtilt of the node of the output of lid optimization process, meanwhile, the input dependence of capacity and coverage optimization process in
The connectivity of the user group of the output of load balance optimization process；It is executed by loop iteration successively provided in an embodiment of the present invention
Load balance optimization process and capacity and coverage optimization process, terminate stream after iterations reach preset first threshold
Journey；Export network optimization result：The power and Downtilt of internuncial optimal value of each user and each node
Optimal value.
Network optimized approach provided in an embodiment of the present invention, it is excellent by combining for capacity and coverage optimization and load balancing
Change so that while cell load is distributed relative equilibrium, capacity and covering are optimized, and effectively promote Internet usage effect
Rate；The uplink and downlink principle of duality is utilized during realizing capacity and coverage optimization and load balance optimization and using fixed point
Optimization algorithm realizes the optimization based on model, and Fast Convergent.
Fig. 4 is the structural schematic diagram of network optimization device provided in an embodiment of the present invention.As shown in figure 4, the present invention is implemented
The network optimization device 400 that example provides, including：
Grouped element 401, the transmitting-receiving performance parameter for each user according to acquisition are grouped each user, shape
At at least two user groups, and the connectivity of each user group is obtained respectively；Wherein, the connectivity of the user group, is used for
Indicate the associated nodes of user group；
First acquisition unit 402, power sharing learning and each user group for obtaining each user respectively
Power sharing learning；
Second acquisition unit 403, for shared according to the power of the power of each node, Downtilt, each user
The power sharing learning of the factor and each user group obtains internuncial optimal value of each user group and each user
Internuncial optimal value；Wherein, the connectivity of the user is used to indicate the associated nodes of user；
Third acquiring unit 404 obtains each node for internuncial optimal value according to each user group
The optimal value of power and Downtilt；
Iteration unit 405, for grouped element 401, the first acquisition unit 402, described second described in iteration control
Acquiring unit 403 and the third acquiring unit 404, until iterations reach preset first threshold；
Acquiring unit 406, the connectivity for obtaining the power of each node, Downtilt and each user in the network
Optimal value.
Network optimization device 400 provided in an embodiment of the present invention can be used for executing network optimized approach shown in Fig. 1 and implement
The technical solution of example, implementing principle and technical effect are similar, and details are not described herein again.
Further, the second acquisition unit 403, is specifically used for：
According to the connectivity of the power of each node, the power sharing learning of each user and each user group,
Determine the power of each user group；
The candidate association node for traversing each user group respectively, according to the Downtilt of each node and described each
The power and power sharing learning of user group obtain the candidate association of each user group and corresponding candidate association node
Interference correlative；
Each user group is corresponding with the least interference correlative of candidate association in corresponding candidate association node respectively
Purpose associated nodes establish association；
According to the maximum value and Objective of the power of the least interference correlative of each user group, each user group
Can, update the power of each user group；
It repeats the above steps, until the power update amplitude of each user group is no more than preset second threshold；
Obtain internuncial optimal value of each user group and the optimal value of power；
According to the relevance of the internuncial optimal value and user and user group of each user group, each user is determined
Internuncial optimal value.
Or third acquiring unit 404 described further, it is specifically used for：
The candidate Downtilt for traversing each node respectively, according to internuncial optimal value of each user group,
Obtain interference correlative of each node to the candidate association of corresponding candidate Downtilt；
Each node is corresponding with the least interference correlative of candidate association in corresponding candidate Downtilt respectively
Purpose Downtilt establish association；
According to the least interference correlative of each node, the maximum value and performance limits of the power of each node, more
The power of new each node；
It repeats the above steps, until the power update amplitude of each node is no more than preset third threshold value；
Obtain the optimal value of the Downtilt of each node and the optimal value of power.
Or further, the transmitting-receiving performance parameter is：The Reference Signal Received Power RSRP that user measures, and/or, it uses
The signal-to-noise ratio SINR at family.
In several embodiments provided by the present invention, it should be understood that disclosed device and method can pass through it
Its mode is realized.For example, the apparatus embodiments described above are merely exemplary, for example, the division of the unit, only
Only a kind of division of logic function, formula that in actual implementation, there may be another division manner, such as multiple units or component can be tied
Another system is closed or is desirably integrated into, or some features can be ignored or not executed.Another point, it is shown or discussed
Mutual coupling, direct-coupling or communication connection can be the INDIRECT COUPLING or logical by some interfaces, device or unit
Letter connection can be electrical, machinery or other forms.
The unit illustrated as separating component may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, you can be located at a place, or may be distributed over multiple
In network element.Some or all of unit therein can be selected according to the actual needs to realize the mesh of this embodiment scheme
's.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, it can also
It is that each unit physically exists alone, it can also be during two or more units be integrated in one unit.Above-mentioned integrated list
The form that hardware had both may be used in member is realized, can also be realized in the form of hardware adds SFU software functional unit.
The above-mentioned integrated unit being realized in the form of SFU software functional unit can be stored in one and computer-readable deposit
In storage media.Above-mentioned SFU software functional unit is stored in a storage medium, including some instructions are used so that a computer
Equipment（Can be personal computer, server or the network equipment etc.）Or processor（processor）It is each to execute the present invention
The part steps of embodiment the method.And storage medium above-mentioned includes：USB flash disk, mobile hard disk, read-only memory（Read-
Only Memory, ROM）, random access memory（Random Access Memory, RAM）, magnetic disc or CD etc. it is various
The medium of program code can be stored.
Those skilled in the art can be understood that, for convenience and simplicity of description, only with above-mentioned each function module
Division progress for example, in practical application, can be complete by different function modules by above-mentioned function distribution as needed
At the internal structure of device being divided into different function modules, to complete all or part of the functions described above.On
The specific work process for stating the device of description, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
Finally it should be noted that：The above embodiments are only used to illustrate the technical solution of the present invention., rather than its limitations；To the greatest extent
Present invention has been described in detail with reference to the aforementioned embodiments for pipe, it will be understood by those of ordinary skill in the art that：Its according to
So can with technical scheme described in the above embodiments is modified, either to which part or all technical features into
Row equivalent replacement；And these modifications or replacements, various embodiments of the present invention technology that it does not separate the essence of the corresponding technical solution
The range of scheme.
Claims (8)
1. a kind of network optimized approach, which is characterized in that including：
Each user is grouped according to the transmitting-receiving performance parameter of each user of acquisition, forms at least two user groups, and
The connectivity of each user group is obtained respectively；Wherein, the connectivity of the user group is used to indicate the association section of user group
Point；
The power sharing learning of each user and the power sharing learning of each user group are obtained respectively；
According to the power of each node, the power of Downtilt, the power sharing learning of each user and each user group
Sharing learning obtains internuncial optimal value of each user group and internuncial optimal value of each user；Wherein, the use
The connectivity at family is used to indicate the associated nodes of user；
According to internuncial optimal value of each user group, the optimization of the power and Downtilt of each node is obtained
Value；
It repeats the above steps, until iterations reach preset first threshold；
Obtain the power of each node in the network, Downtilt and internuncial optimal value of each user.
2. according to the method described in claim 1, it is characterized in that, it is described according to the power of each node, Downtilt,
The power sharing learning of the power sharing learning of each user and each user group obtains the connectivity of each user group
Optimal value and each user internuncial optimal value, including：
According to the connectivity of the power of each node, the power sharing learning of each user and each user group, determine
The power of each user group；
The candidate association node for traversing each user group respectively, according to the Downtilt of each node and each user
The power and power sharing learning of group, acquisition each user group are dry with the candidate association of corresponding candidate association node
Disturb correlative；
Each user group respectively with the corresponding mesh of least interference correlative of candidate association in corresponding candidate association node
Associated nodes establish association；
According to the maximum value and target capabilities of the power of the least interference correlative of each user group, each user group, more
The power of new each user group；
It repeats the above steps, until the power update amplitude of each user group is no more than preset second threshold；
Obtain internuncial optimal value of each user group and the optimal value of power；
According to the relevance of the internuncial optimal value and user and user group of each user group, the company of each user is determined
The optimal value of connecing property.
3. according to the method described in claim 1, it is characterized in that, internuncial optimization according to each user group
Value obtains the power of each node and the optimal value of Downtilt, including：
The candidate Downtilt for traversing each node respectively is obtained according to internuncial optimal value of each user group
Interference correlative of each node to the candidate association of corresponding candidate Downtilt；
Each node respectively with the corresponding mesh of least interference correlative of candidate association in corresponding candidate Downtilt
Downtilt establish association；
According to the least interference correlative of each node, the maximum value and performance limits of the power of each node, institute is updated
State the power of each node；
It repeats the above steps, until the power update amplitude of each node is no more than preset third threshold value；
Obtain the optimal value of the Downtilt of each node and the optimal value of power.
4. according to the method described in claim 1, it is characterized in that, the transmitting-receiving performance parameter is：The reference letter that user measures
Number receive power RSRP, and/or, the signal-to-noise ratio SINR of user.
5. a kind of network optimization device, which is characterized in that including：
Grouped element, the transmitting-receiving performance parameter for each user according to acquisition are grouped each user, are formed at least
Two user groups, and the connectivity of each user group is obtained respectively；Wherein, the connectivity of the user group, is used to indicate use
The associated nodes of family group；
The power of first acquisition unit, power sharing learning and each user group for obtaining each user respectively is shared
The factor；
Second acquisition unit, for according to the power of each node, Downtilt, the power sharing learning of each user and institute
State the power sharing learning of each user group, obtain each user group internuncial optimal value and each user it is internuncial excellent
Change value；Wherein, the connectivity of the user is used to indicate the associated nodes of user；
Third acquiring unit, power for according to internuncial optimal value of each user group, obtaining each node and
The optimal value of Downtilt；
Iteration unit, for grouped element, the first acquisition unit, the second acquisition unit described in iteration control and described
Third acquiring unit, until iterations reach preset first threshold；
Acquiring unit, for obtaining the power of each node in the network, Downtilt and internuncial optimization of each user
Value.
6. device according to claim 5, which is characterized in that the second acquisition unit is specifically used for：
According to the connectivity of the power of each node, the power sharing learning of each user and each user group, determine
The power of each user group；
The candidate association node for traversing each user group respectively, according to the Downtilt of each node and each user
The power and power sharing learning of group, acquisition each user group are dry with the candidate association of corresponding candidate association node
Disturb correlative；
Each user group respectively with the corresponding mesh of least interference correlative of candidate association in corresponding candidate association node
Associated nodes establish association；
According to the maximum value and target capabilities of the power of the least interference correlative of each user group, each user group, more
The power of new each user group；
It repeats the above steps, until the power update amplitude of each user group is no more than preset second threshold；
Obtain internuncial optimal value of each user group and the optimal value of power；
According to the relevance of the internuncial optimal value and user and user group of each user group, the company of each user is determined
The optimal value of connecing property.
7. device according to claim 5, which is characterized in that the third acquiring unit is specifically used for：
The candidate Downtilt for traversing each node respectively is obtained according to internuncial optimal value of each user group
Interference correlative of each node to the candidate association of corresponding candidate Downtilt；
Each node respectively with the corresponding mesh of least interference correlative of candidate association in corresponding candidate Downtilt
Downtilt establish association；
According to the least interference correlative of each node, the maximum value and performance limits of the power of each node, institute is updated
State the power of each node；
It repeats the above steps, until the power update amplitude of each node is no more than preset third threshold value；
Obtain the optimal value of the Downtilt of each node and the optimal value of power.
8. device according to claim 5, which is characterized in that the transmitting-receiving performance parameter is：The reference letter that user measures
Number receive power RSRP, and/or, the signal-to-noise ratio SINR of user.
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