CN109004968A - The determination method and device of parameter value when efficiency is optimal in heterogeneous network - Google Patents
The determination method and device of parameter value when efficiency is optimal in heterogeneous network Download PDFInfo
- Publication number
- CN109004968A CN109004968A CN201810861172.6A CN201810861172A CN109004968A CN 109004968 A CN109004968 A CN 109004968A CN 201810861172 A CN201810861172 A CN 201810861172A CN 109004968 A CN109004968 A CN 109004968A
- Authority
- CN
- China
- Prior art keywords
- optimal
- base station
- efficiency
- parameter value
- value
- 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.)
- Pending
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/06—Testing, supervising or monitoring using simulated traffic
-
- 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)
- Mobile Radio Communication Systems (AREA)
Abstract
This application discloses a kind of determination method and devices of parameter value when optimal of efficiency in heterogeneous network, it include: to establish the system energy efficiency optimal models for meeting preset condition, convex optimization processing is carried out to the system energy efficiency optimal models, obtain Optimized model, optimal beam figuration matrix is determined according to the seismic responses calculated, it in conjunction with the optimal beam figuration matrix, determines under different base station quantity, the optimum parameter value of other influences factor when system energy efficiency is optimal.This method and device not only allow for influence of the base station number to system energy efficiency in implementation process, and influence of the other parameters to system energy efficiency is considered simultaneously, parameter value when can determine that system energy efficiency is optimal using this method and device, it is subsequent that determining parameter value is applied to actual scene, be conducive to promote communication system efficiency.
Description
Technical field
The present invention relates to field of communication technology, parameter value when optimal more specifically, it relates to efficiency in a kind of heterogeneous network
Determination method and device.
Background technique
In recent years, the energy consumption of information and communication technology (ICT) is always in rapid growth, and mobile multimedia data flow
It is exponentially increased trend, therefore, communication system efficiency has become the research hotspot of mobile communication field at present.By to existing logical
The energy distribution research of letter system show that the energy consumption of internet transmission of virtual laboratory has actually accounted for nearly the 90% of total energy consumption, and
The energy consumption of terminal part only accounts for total energy consumption 10% or so.As it can be seen that the energy consumption of internet transmission of virtual laboratory, which how will be greatly lowered, to be
Future realizes the key point of green communications system.
In the prior art, there are a kind of research approach for improving system energy efficiency, program analysis passes through Massive MIMO
(large-scale antenna array) technology and the small base station of deployment are come a possibility that improving system energy efficiency.However in its research process not
Have and considers that the dynamic change of different system parameter may influence system energy efficiency bring, thus finally determining system energy efficiency
Optimality cannot be guaranteed.
Summary of the invention
In view of this, the present invention provides the efficiency optimization method and device in a kind of heterogeneous network, it is more accurate to realize
System optimal efficiency determination.
To achieve the above object, the invention provides the following technical scheme:
A kind of determination method of parameter value when efficiency is optimal in heterogeneous network, comprising:
The system energy efficiency optimal models for meeting preset condition are established, the preset condition includes that total power consumption is minimum, any one
The Signal to Interference plus Noise Ratio of a user is most no more than preset antenna not less than the transimission power of minimum quality of service and any one antenna
Big transmission power；
Convex optimization processing is carried out to the system energy efficiency optimal models, obtains Optimized model；
Optimal beam figuration matrix is determined according to the seismic responses calculated；
In conjunction with the optimal beam figuration matrix, determine under different base station quantity, when system energy efficiency is optimal other influences because
The optimum parameter value of element.
Optionally, described that convex optimization processing is carried out to the system energy efficiency optimal models, obtain Optimized model, comprising:
Convex optimization processing is carried out to the system energy efficiency optimal models using semi definite programming and positive semidefinite relaxation method, is obtained
To Optimized model.
Optionally, the other influences factor includes at least one in antenna for base station quantity, service quality and number of users
Kind.
Optionally, optimal beam figuration matrix described in the combination, determines under different base station quantity, when system energy efficiency is optimal
The optimum parameter value of other influences factor, comprising:
Initialize system environments；
Under the premise of traversing different base station quantity, the different choosing values of other influences factor are traversed, in conjunction with the optimal wave
Beam figuration matrix, determines under different base station quantity, other influences factor system energy efficiency other influences factor when optimal
Optimum parameter value.
Optionally, described under the premise of traversing different base station quantity, the different choosing values of other influences factor are traversed, in conjunction with
The optimal beam figuration matrix, determines under different base station quantity, when the other influences factor system energy efficiency is optimal described in its
The optimum parameter value of his influence factor, comprising:
Under the premise of traversing different base station quantity, for the choosing value of other influences factor described in each, in conjunction with described
Optimal beam figuration matrix carries out multiple efficiency calculating；
The average value for determining the multiple efficiency calculated result, the current choosing value as the other influences factor are corresponding
System energy efficiency value；
Determine that the different choosings of the other influences factor are worth the maximum energy valid value in corresponding system energy efficiency value, and will be described
The choosing value of the corresponding other influences factor of maximum energy valid value is determined as optimum parameter value.
Optionally, the initialization system environments, comprising:
Generate the coordinate position set of all base stations under different cooperative base station quantity；
According to the coordinate position set, at least there is the premise of a user in each cooperative base station overlay area
Under, the position of all users is generated at random；
According to the minimum range set of each user and the coordinate position set, all users are judged using backtracking method
Whether the distance apart from each base station is not less than default minimum range；
If it is not, the step of then returning to the position for generating all users at random, until each base of all user distances
The distance stood all is not less than the default minimum range.
Optionally, comprising:
Model building module, for establishing the system energy efficiency optimal models for meeting preset condition, the preset condition includes
Total power consumption is minimum, any one user Signal to Interference plus Noise Ratio not less than the transimission power of minimum quality of service and any one antenna
Greater than preset antenna maximum transmission power；
Model optimization module obtains Optimized model for carrying out convex optimization processing to the system energy efficiency optimal models；
Matrix deciding module, for determining optimal beam figuration matrix according to the seismic responses calculated；
Parameter value determining module, for determining under different base station quantity, system energy in conjunction with the optimal beam figuration matrix
The optimum parameter value of other influences factor when imitating optimal.
Optionally, the other influences factor includes at least one in antenna for base station quantity, service quality and number of users
Kind.
Optionally, the parameter value determining module includes:
Initialization module, for initializing system environments；
Parameter value determines submodule, under the premise of traversing different base station quantity, traversal other influences factor to be not
It is determined under different base station quantity with choosing value in conjunction with the optimal beam figuration matrix, the other influences factor system energy efficiency is most
The optimum parameter value of other influences factor when excellent.
Optionally, the parameter value determines that submodule includes:
Traverse computing module, under the premise of traversing different base station quantity, for other influences described in each because
The choosing value of element carries out multiple efficiency calculating in conjunction with the optimal beam figuration matrix；
Mean value determining module, for determining the average value of the multiple efficiency calculated result, as the other influences because
The current choosing of element is worth corresponding system energy efficiency value；
Optimum value determining module, for determining that the different choosings of the other influences factor are worth in corresponding system energy efficiency value
Maximum energy valid value, and the choosing value of the corresponding other influences factor of the maximum energy valid value is determined as optimum parameter value.
It can be seen via above technical scheme that compared with prior art, the embodiment of the invention discloses in a kind of heterogeneous network
The determination method and device of parameter value when efficiency is optimal, comprising: the system energy efficiency optimal models for meeting preset condition are established, to institute
It states system energy efficiency optimal models and carries out convex optimization processing, obtain Optimized model, optimal wave is determined according to the seismic responses calculated
Beam figuration matrix determines under different base station quantity in conjunction with the optimal beam figuration matrix, other influences when system energy efficiency is optimal
The optimum parameter value of factor.This method and device not only allow for influence of the base station number to system energy efficiency in implementation process,
And influence of the other parameters to system energy efficiency is considered simultaneously, when can determine that system energy efficiency is optimal using this method and device
Parameter value, it is subsequent that determining parameter value is applied to actual scene, be conducive to promote communication system efficiency.
Detailed description of the invention
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 technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
The embodiment of invention for those of ordinary skill in the art without creative efforts, can also basis
The attached drawing of offer obtains other attached drawings.
Fig. 1 is the determination method flow diagram of parameter value when efficiency is optimal in heterogeneous network disclosed by the embodiments of the present invention；
Fig. 2 is downlink bilayer heterogeneous network list cell schematic diagram disclosed by the embodiments of the present invention；
Fig. 3 is the flow chart of determining optimum parameter value disclosed by the embodiments of the present invention；
Fig. 4 is the base station deployment figure of different cooperative base station numbers disclosed by the embodiments of the present invention；
Fig. 5 is system energy efficiency schematic diagram under different base station antenna number disclosed by the embodiments of the present invention；
Fig. 6 is system energy efficiency schematic diagram under different service quality disclosed by the embodiments of the present invention；
Fig. 7 is system energy efficiency schematic diagram under different user quantity disclosed by the embodiments of the present invention；
Fig. 8 is system energy efficiency schematic diagram under many kinds of parameters disclosed by the embodiments of the present invention；
Fig. 9 is the structural representation of the determining device of parameter value when efficiency is optimal in heterogeneous network disclosed by the embodiments of the present invention
Figure；
Figure 10 is the structural schematic diagram of parameter value determining module disclosed by the embodiments of the present invention；
Figure 11 is the structural schematic diagram that parameter value disclosed by the embodiments of the present invention determines submodule.
Specific embodiment
For the sake of quoting and understanding, hereafter used in technical term explanation, write a Chinese character in simplified form or abridge and be summarized as follows:
Heterogeneous network: refer to and collectively formed by macro base station and different type low transmitting power base station.Common low transmitting power base
It stands including micro-base station, millimicro base station, Home eNodeB and remote radio frequency node.Low transmitting power base station is referred to as in the description of this article
Small base station.The coverage area of macro base station is known as macrocell, and the coverage area of small base station is known as cell.
Wave beam forming: traditional communication mode is the electromagnetic transmission of single antenna between base station and mobile phone, and in wave beam forming
In technology, base station end possesses more antennas, can automatically adjust the phase of each antenna transmitting signal, make it in mobile phone receiving point
The superposition of electromagnetic wave is formed, to achieve the purpose that improve received signal strength.It is this to utilize digital signal from the aspect of base station
The Overlay generated is handled just as the construction for completing base station end virtual-antenna directional diagram, because being referred to herein as " wave beam forming " skill
Art.By this technology, emitted energy can be pooled to the position where user, without being spread to other directions, and base station
The electromagnetic wave signal of mobile phone receiving point at any time can be guaranteed all in overlaying state by the signal of detection user.Wave
Beam figuration technology has very big advantage in terms of expanding the coverage area, improving edge throughput and interference.
Massive MIMO: large-scale antenna array is based on forming multiuser wave beam principle, arranges in base station end several
Hundred antennas are modulated respective wave beam to tens intended receivers, are isolated by spacing wave, in same frequency resource simultaneously
Transmit tens bars.This abundant excavation to space resources can efficiently use valuable and rare band resource, and
Tens times of ground promote network capacity.
LTE-Advanced:4G communication technology standard, specification.It can also be abbreviated as LTE-A.
CoMP:Coordinated Multipoint, cooperative multi-point.It is most important enhanced biography in LTE-Advanced
Transferring technology is the effective ways for solving Cell Edge User and average user rate.Cooperative multipoint transmission refers to divides on geographical location
From multiple transmission point, the data transmission that collaboration participates in as terminal.Whether user data, downlink are shared according between base station
COMP can be divided into cooperative beam figuration (CB) and Combined Treatment (JP).Based on CoMP-CB only need between base station share letter
Corresponding resource block is distributed according to the position user Dian and channel condition for it in road information, base station.It is not only needed based on CoMP-JP small
Share channel information in section, it is also necessary to the data of shared user.In JP system, the multiple base stations united transmission user of cooperation is participated in
Data can effectively improve the reception Signal to Interference plus Noise Ratio of user and inhibit interference.
SINR:Signal to Interference plus Noise Ratio, Signal to Interference plus Noise Ratio.Signal adds with interference makes an uproar
Acoustic ratio refer to the useful signal received intensity and the interference signal plus noise received and ratio.It is commonly used for measuring communication system
One the key technical indexes of communication quality reliability of uniting.
CMBF:Coordinated multi-point transmission beamforming, multipoint cooperative wave beam are assigned
Shape can use single or more antenna of multiple nodes, a facilitating communications network be formed, to realize multiplexing and diversity.
This characteristic more adapts to most wireless application scene, i.e., each base station or user terminal are and every with the fractions distribution that is scattered
A base station and user terminal all only configure limited transmitting antenna.Cooperative multi-point itself is to assume that each participates in the independent section of cooperation
Point, by beam forming technique and precoder, the data that the every antenna that each cooperative node is configured is issued are adjusted
The data flow that similar wave beam is made issues user.Herein, CMBF is presented as that multiple base stations (macro base station and small base station) are assisted
Make wave beam forming service user.
SDP:SemiDefinite programming, half positive planning.
SDR:SemiDefinite Relaxation, positive semidefinite relaxation.
EE:Energy Efficiency, system energy efficiency.
BS:base station, base station.
MBS:macro base station, macro base station.The coverage area of macro base station is known as macrocell.
SBS:small base station, small base station.The coverage area of small base station is known as cell.
QCQP:quadratically constrained quadratic program, quadratically constrained quadratic programming.
QoS:Quality of Service, service quality.The different business of user needs its QoS demand also different.?
There can be a variety of services in following 5G network, the QoS demand of these services is all different, such as video conference, it is one
A real-time multimedia traffic, its requirement to time delay is very high, but can tolerate a degree of mistake；And file transmits, it
It is sensitive to mistake, and to time delay without very high requirement, so system allows for providing a variety of QoS guarantees and meets user not
Same business demand.
Wireless backhaul: CoMP needs to share user data and channel state information between base station and data sharing passes through wirelessly
Backhaul link is completed.
Dynamic emission power, static transmission power: the total power consumption in heterogeneous network is divided into dynamic part and quiet herein
Polymorphic segment.Dynamic part refers to base station antenna transmission power consumption, and static part refers to the intrinsic circuit power consumption in base station, with antenna number at
Direct ratio.It is an optimized variable that " dynamic ", which can be understood as antenna transmission power consumption, can be optimised, and " static state " is understood that
It is constant for the intrinsic circuit power consumption in base station.
TDD: time division duplex is one kind of full-duplex communication technology used in mobile communication system.TDD only needs one
Channel, no matter uplink or conveying information downstream all use same channel.Transmitter and receiver is operated in different time-gap.In this way
Communication system be by the time come differentiating uplink and downlink data, the identical frequency resource of all data sharings.In TDD system
In, it is only necessary to channel estimation is carried out to the reference signal in upstream data, so that it may obtain the channel information of downlink.It uses herein
TDD downlink system, that is to say, that system default base station end has obtained the channel state information of downlink.
Channel: be in wireless communication between transmitting terminal and receiving end communication link a kind of Vivid analogy, for wireless
For electric wave, it is from transmitting terminal to receiving end, and therebetween there is no a tangible connection, its propagation path is also possible to incessantly
One, we are in order to vividly describe the work between transmitting terminal and receiving end, it is envisaged that have between the two one it is invisible
Road linking, this linking access is called channel.
Downlink: refer to signal from base station to mobile station (such as mobile phone terminal) communication link, uplink correspondingly refers to letter
Communication link number from mobile station to base station.
CSI:channel state information, channel state information.In wireless communication field, so-called CSI,
It is exactly the attribute of communication link.It describe signal the weak factor of every transmission paths, i.e. channel gain matrix H (sometimes
Referred to as channel matrix, channel fading matrix) in each element value, such as signal dispersion, environment are weak, range attenuation information.
H is referred to as channel matrix herein.
Channel model: channel model, which refers to, can describe the characteristic of channel with mathematic(al) representation.
Block fading model: in some cases, if almost without relative movement between base station and mobile station, it is believed that certain
Channel is held essentially constant in time, the decline that signal during this period of time is subjected to be it is identical, here it is block decline mould
Type.
White Gaussian noise: if a noise, its instant value Gaussian distributed, and its power spectral density is sometimes equal
Even distribution, then he is referred to as white Gaussian noise.Main Noise Sources in communication --- thermal noise just belongs to this noise like.
Multistream signal: refer to that user terminal can receive multiple signals come from the transmitting of different transmitting terminals.Herein refer to multiple bases
It stands and emits identical signal to some user.
Information rate: refer to the information content of transmitted per unit time.Unit: bit/s.
Bandwidth: referring to the difference of the highest frequency that signals in wireless communications can be used and low-limit frequency, in other words " frequency band
Width ".
Handling capacity: refer to the information bit that some system is correctly transmitted within the unit time.
Carrier wave: carrier wave is exactly the carrier electric wave for transmitting signal, and carrier frequency generally will significantly larger than transmit the power of signal.
Low frequency signal is unfavorable for transmitting, and needs to be modulated on high frequency, such as carrier wave (frequency is high).
Subcarrier: a carrier wave is divided into many a bandwidth relative narrower subcarriers, i.e. subcarrier.These carrier waves are mutually just
It hands over.
A kind of Rayleigh multipath fading model: channel fading model.It is intensive that Rayleigh fading model is suitable for description building
Town Center area wireless channel.Intensive building and other objects make between the transmitter and receiver of wireless device
There is no direct path, and is attenuated wireless signal, reflects, reflecting, diffraction.
Path loss: it is also known as propagation loss, refers to electric wave loss caused by spatial, be the radiation by transmitter
Caused by the propagation characteristic of diffusion and channel, the variation of received signal power mean value in macro-scope is reflected.
Non line of sight: the propagation conditions of wireless communication system is usually divided into sighting distance (LOS) and non line of sight (NLOS) two by us
Kind environment.Under line of sight conditions, wireless signal " straightline propagation " unobstructedly between transmitting terminal and receiving end.And there is barrier
In the case where, wireless signal can only reach receiving end, referred to as non line-of-sight communication by reflection, scattering and diffraction mode, at this time
Wireless signal is received through a variety of ways.
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Fig. 1 is the determination method flow diagram of parameter value when efficiency is optimal in heterogeneous network disclosed by the embodiments of the present invention, referring to
Shown in Fig. 1, the determination method of parameter value may include: when efficiency is optimal in heterogeneous network
Step 101: establishing the system energy efficiency optimal models for meeting preset condition.
Wherein, the preset condition can with but be not limited to include that total power consumption is minimum, Signal to Interference plus Noise Ratio of any one user
It is not more than preset antenna maximum transmission power not less than the transimission power of minimum quality of service and any one antenna.
In the present embodiment, the system energy efficiency optimal models for meeting preset condition are initially set up, specifically can satisfy: being met
While user QoS constraint and antenna power constrain, total power consumption is minimized, it is maximum to enable the system to effect.
Fig. 2 is downlink bilayer heterogeneous network list cell schematic diagram disclosed by the embodiments of the present invention.As shown in connection with fig. 2, exist
First layer disposes a macro base station, is equipped with NBSRoot antenna, the second layer dispose the small base stations S, small base station in heterogeneous network cell with
Machine is uniformly disposed, each small base station is equipped with NSRoot antenna.There is different maximum antennas to emit function for macro base station and small base station
Rate, respectively P0And Ps, wherein P0> Ps.K user is uniformly deployed in heterogeneous network cell at random, and number of users is greater than macrocell
Interior base station number, at least one interior user of each cell.User is opposing stationary in cell, has non mobility, user
Channel model be block fading model.Consider that a TDD downlink system, channel fading model are Rayleigh multipath fading model,
Path loss model is obstructed path loss model, and base station end can obtain complete channel state information.Macro base station and small
Base station connects exchange information by backhaul link, and the backhaul link between base station has enough capacity and no time delay.Macro base
It stands and small base station can be with some user of collaboration services, it can ideal Timing Synchronization (base station collaboration between cooperative base station and user
Need time synchronization).
Consider in a TDD downlink system, disposes a macro base station and C participates in the small base station to cooperate.Macro base station day
Line number is NBSA, each small antenna for base station number is NSA, the total antenna number of system is N=NBS+CNS.Here symbol j is used
Indicate base station, j=0,1 ..., C, wherein j=0 indicate macro base station, j=1,2 ..., C respectively indicate the 1st, second ...
C small base stations.
The down channel matrix of N root antenna, the system of K user can be expressed as H,
hkIndicate the channel of k-th of user,Wherein hj,kIndicate that j-th of base station is used to k-th
The channel at family,Macro base station and j-th small base station are sent to k-th of user
Signal code be expressed as s0, kAnd sJ, k, meet zero-mean and unit variance.It enablesAndPoint
Not Biao Shi the wave beam forming vector from macro base station and small base station signal, then j-th of base station send the signal (letter after weighting
Number) can be expressed as
The signal that then k-th of user receives is
N in formulakFor white Gaussian noise,Wherein nkFinger belongs to k-th of user's white noise, obeys mean value
It is 0, variance isGaussian Profile, nkReferred to as white Gaussian noise.
Assuming that the data information of different user and reception noise are mutually indepedent, the information rate of k-th of user is expressed as
Rk=B log2(1+SIN Rk) (3)
B indicates bandwidth, SIN R in formula (3)kIndicate the Signal to Interference plus Noise Ratio of k-th of user, it is as follows
In formula | h0,kw0,k|2Indicate that macro base station sends signal power to k-th of user,Indicate macro base station and C
A small base station to k-th user send signal power and.
System power consumption can be modeled as the sum of transimission power and circuit power consumption, i.e. Ptotal=Pt+Pc, wherein Pt
For transimission power, it is dynamic part, can be expressed as
Wherein η0,ηjIt is expressed as the efficiency power amplifier of macro base station and j-th small base station.Assuming that owning in system
The efficiency power amplifier of small base station is equal, i.e. setting ηj=ηC, j=1,2 ... C. Point
Not Biao Shi macro base station transimission power consumption and all small base stations transmission power consumption.
PcFor circuit power consumption, it is proportional to number of antennas, can be expressed as
ρ in formula0,ρjRespectively indicate macro base station, small base station circuitry power consumption.Base station circuitry power consumption includes cooling loss, feeder line damage
Consumption, filter loss, mixer loss etc., circuit power consumption is base station natural disipate.First item ρ in formula0NBSIndicate macro base station electricity
Road power consumption, Section 2Indicate all small base station circuitry power consumptions, wherein MBS and SBS the two be referred to as expressed as it is macro
Base station and small base station.Base station power consumption model can be further represented as at this time
System energy efficiency is defined as ratio (the efficiency unit bit/ of user throughput and system total power consumption in the unit time
J)。
Statistical average is asked in E { } expression in formula, wherein total number of users is K (capitalization), k (small letter) indicates k-th of user.
It is dry not less than ownership goal letter that the double-deck heterogeneous network system energy efficiency optimization problem can be modeled as user's Signal to Interference plus Noise Ratio
The QoS constraint condition of ratio of making an uproar and the antenna transmission power of base station every are constrained no more than the antenna power of antenna maximum transmission power
Condition, meanwhile, keep total system power consumption minimum.
Use γkIndicate target user's Signal to Interference plus Noise Ratio, γkFor a given value, can be indicated to be γ by QoSk=2QoS- 1, QoS
Unit: bit/s/Hz.When designing system efficiency is optimal, to meet the minimum quality of service of each user in system, it can be with
It is expressed as follows
WhereinIndicate any one user.SINRkIndicate the Signal to Interference plus Noise Ratio of k-th of user, γkIndicate k-th of user
Target Signal to Interference plus Noise Ratio.SINRkIt can regard the current Signal to Interference plus Noise Ratio of k-th of user as, that is, the Signal to Interference plus Noise Ratio surveyed, and γkIt indicates
The Signal to Interference plus Noise Ratio of system requirements either user wishes the Signal to Interference plus Noise Ratio reached.Signal to Interference plus Noise Ratio can measure communication system performance.Expression requires the Signal to Interference plus Noise Ratio of each user in system to be not less than its minimum requirements, and (target letter is dry
It makes an uproar and compares, γk)。
According to LTE-A standard, there are the limitation of its maximum transmission power, i.e., the transmission of every antenna in base station in base station in system
Power however be more than its maximum transmission power.Use Qj,lIndicate l root antenna in j-th of base station matrix weight (l=1 ...,
Lj)。LjIndicate antenna for base station number, wherein L0Indicate macro base station antenna number L0=NBS, Lj, j=1 ..., C indicates small antenna for base station number
Lj=NS.Then base station l root antenna transmission power constraint is represented by
In formula, pj,lIndicate the maximum transmission power of j-th of base station l root antenna.
Thus heterogeneous network efficiency optimal problem can be modeled as follows
Under this Optimized model, each user's's (including Cell Center User and Cell Edge User) is minimum in system
Information rate is Blo g2(1+γk), total system power consumption is minimum, and system energy efficiency is optimal.
Step 102: convex optimization processing being carried out to the system energy efficiency optimal models, obtains Optimized model.
It is described that convex optimization processing is carried out to the system energy efficiency optimal models, Optimized model is obtained, may include: using half
Positive definite planning and positive semidefinite relaxation method carry out convex optimization processing to the system energy efficiency optimal models, obtain Optimized model.
Specifically, QoS constraint condition makes solving optimization problem hard and non-convex in formula (11), can establish rules by using half
Formula (11) is converted to the convex optimization problem of quadratically constrained quadratic programming (QCQP) form by the method for drawing (SDP).Introduce new square
Battle array Wj,kAnd Hj,k, definitionTr (W can be obtainedj,k)=| | wj,k||2With Tr (Hj,kWj,k)
=| hj,kwj,k|2。Wj,kIt will replace wj,kAs new optimization variable.Due toSo Wj,kIt must be partly just
Set matrix has Wj,k>=0, and have Wj,kOrder be less than or equal to 1 constraint condition, i.e.,Due to
Wj,kOrder optimization problem will be made non-convex equal to 1 constraint condition, the method that positive semidefinite relaxation (SDR) can be used ignores Rank
(wJ, k)≤1Constraint condition.In addition, circuit power consumes P in the total power consumption of systemcIt is only related and only with number of antennas
Stand on optimized variable Wj,k。PcIt is directly proportional to antenna number, the i.e. P of fixed value can be regarded ascIt is static, so optimization aim is converted
P is consumed to minimize transimission powert.Optimization problem (11) can be exchanged into convex optimization problem as a result, as follows
Step 103: optimal beam figuration matrix is determined according to the seismic responses calculated.
In the present embodiment, under given user QoS constraint condition and antenna maximum transmission power constraint condition, optimization is asked
Topic (formula 12) can be solved by algorithm 1.Algorithm 1 has used CVX optimization tool packet to solve optimal beam figuration matrix W.It is excellent herein
Change algorithm under, each of system with per family can get a minimum quality of service requirement while total system power consumption most
It is low.Algorithm 1 is as follows:
Step 104: in conjunction with the optimal beam figuration matrix, determine under different base station quantity, when system energy efficiency is optimal its
The optimum parameter value of his influence factor.
Wherein, the other influences factor includes at least one of antenna for base station quantity, service quality and number of users.
In a schematical example, optimal beam figuration matrix described in the combination is determined under different base station quantity,
The optimum parameter value of other influences factor when system energy efficiency is optimal may include: initialization system environments, in traversal different base station
Under the premise of quantity, the different choosing values of traversal other influences factor determine different base station in conjunction with the optimal beam figuration matrix
Under quantity, the optimum parameter value of other influences factor system energy efficiency other influences factor when optimal.
Wherein, the initialization system environments may include: the coordinate for generating all base stations under different cooperative base station quantity
Location sets, according to the coordinate position set, before at least there is a user in each cooperative base station overlay area
It puts, generates the position of all users at random, according to the minimum range set of each user and the coordinate position set, adopt
Judge whether the distance of all each base stations of user distance is not less than default minimum range with backtracking method, if it is not, then returning to institute
The step of stating the position for generating all users at random, until all each base stations of user distance distance be not less than it is described pre-
If minimum range.
Fig. 3 is the flow chart of determining optimum parameter value disclosed by the embodiments of the present invention, shown in Figure 3, described to traverse
Under the premise of different base station quantity, the different choosing values of other influences factor are traversed, in conjunction with the optimal beam figuration matrix, are determined
Under different base station quantity, the optimum parameter value of other influences factor system energy efficiency other influences factor when optimal can
To include:
Step 301: under the premise of traversing different base station quantity, for the choosing value of other influences factor described in each,
In conjunction with the optimal beam figuration matrix, multiple efficiency calculating is carried out.
Step 302: determining the average value of the multiple efficiency calculated result, the current choosing as the other influences factor
It is worth corresponding system energy efficiency value.
Step 303: determine that the different choosings of the other influences factor are worth the maximum energy valid value in corresponding system energy efficiency value,
And the choosing value of the corresponding other influences factor of the maximum energy valid value is determined as optimum parameter value.
Specifically, the final goal of the technical program is to pass through base station collaboration under the premise of considering that other factors influence
System energy efficiency is improved, specific cooperation scheme can be the different cooperative base station numbers of traversal, and cooperative beam tax is done in the base station for participating in cooperation
Shape.On the basis of traversing different cooperative base station numbers, different parameters are considered respectively, and parameter may include that antenna for base station quantity is (macro
Antenna for base station quantity and small antenna for base station quantity), QoS and number of users.Under the influence of considering these parameters respectively, analysis is not
Influence with cooperative base station number to system energy efficiency is improved.The influence to above three parameter to system energy efficiency is done in detail separately below
It introduces.
Massive MIMO technology and Small Cell technology are combined and system energy efficiency can be improved in heterogeneous network.
Base station collaboration scheme in the case where considering Massive MIMO factor, under conceptual design different antennae quantity.Fig. 4 is that the present invention is real
The base station deployment figure of difference cooperative base station number disclosed in example is applied, as shown in connection with fig. 4, in the double-deck heterogeneous network list cell, macro base station
Positioned at center of housing estate position, centered on macro base station, small base station is symmetrically deployed in cell.Given intra-cell users quantity
K, K user's random placements are in cell, wherein at least one service user in each small base station range.
1, parameter: antenna for base station number
Consider that the cooperation scheme method under antenna for base station number can be realized by algorithm 2, algorithm 2 is as follows
2, parameter: QoS
In actual scene, the different business of different users can be had different needs.However, existing method is mostly only
Consider the raising of cell transmission rate and the availability of frequency spectrum, and ignores the difference of resource requirement between different user different business
Property.In order to maximally utilise resource, improve system energy efficiency, a kind of considerations user's different QoS requirements of conceptual design are expiring
Base station collaboration scheme under the minimum QoS demand of sufficient user.Scheme can have the realization of algorithm 3, as follows
3, parameter: number of users
After considering antenna number and qos parameter, scheme then considers the shadow that number of users improves efficiency to base station collaboration
It rings.Base station can service how many user, need to consider the configuration of base station and the business demand of user.Base station configuration reflects base station
Processing capacity and network capacity.The business demand of user mainly see the use habit of user, frequency and with cell distribution
It is related in number of carrier wave.It is devised in the case where given cell number of subcarriers and antenna for base station number a kind of based on number of users
The base station collaboration scheme of amount.The program can realize by algorithm 4, and algorithm 4 is a given antenna for base station several user QoS demands the case where
The lower efficiency for calculating different cooperative base station numbers under different user number.Algorithm 4 is as follows
In specific implementation, heterogeneous network cell scenario can be created under MATLAB simulation software, referring to LTE-A standard,
Influence to antenna number, QoS and number of users these parameters to system energy efficiency emulates.
Simulating scenes are the double-deck heterogeneous network regular hexagon list cell, NCBSA Home eNodeB is apart from center of housing estate
It at 0.35km, angularly divides, is uniformly deployed in cell, the minimum range between small base station is 0.04km, cooperative base station number
NCBS∈ { 0,1,2,3 ... C }, K user of random placement in cell, at least one user in each small base station range.
As shown in the base station deployment figure of Fig. 4 difference cooperative base station number.Channel fading model Rayleigh multipath fading model, path loss mould
Type is non line of sight (NLOS) path loss model, other simulation parameters are as shown in Table 1 below.
1 simulation parameter of table
The influence of most of early stages researched and analysed efficiency and concentrate on dynamic transmission power, and dependent on transceiver hardware
Static circuit power consumption part is typically ignored, however in the heterogeneous network scene of cooperation Massive MIMO, base station end is matched
Tens to several hundred antennas are set, static system circuit power consumption can also increase with the increase of antenna number, to the efficiency of system
It produces a very large impact, so static system circuit power consumption cannot be ignored.In this emulation, total power consumption be divided into dynamic part and
Static part, dynamic part are the consumption of system transimission power, and static part is circuit system power consumption.Considering Massive
Under MIMO factor, the base station collaboration efficiency under different antennae quantity is emulated, as shown in Figure 5.User QoS is 2bits/s/Hz, macro
Antenna for base station number NMBS∈ { 20,30 ..., 100 }, cooperating station number NCBS∈ { 0,1,2,3 ... 10 } cooperates in 11 scheme totally.Emulate table
Bright static system circuit power consumption can reduce system EE.In QoS constraint and different cooperative base station number NCBSUnder, it is available best
Antenna amount enables the system to imitate optimal.Also observable goes out from Fig. 5, and system EE can be improved in Massive MIMO, passes through deployment
Small base station and base station collaboration wave beam forming also can be further improved system energy efficiency.In Fig. 5, NCBS∈ { 0,1 ..., 10 }, QoS
=2bit/s/Hz, NS=2.
Fig. 6 gives the N under different QoS constraintS=2, NCBS∈ 0,1 ..., 5 } and NBSSystem when { 64,128 } ∈
Efficiency.Simulation result shows that the increase with QoS, system energy efficiency presentation first increase the trend reduced afterwards, show in given antenna
In the case where number, system can provide an optimal service quality for user and enable the system to effect highest.At the same time, pass through increasing
Cooperative base station number is added also to can be further improved system energy efficiency.Compared with Fig. 6 (a), from Fig. 6 (b) it can be seen that in system
Under efficiency same case, more antenna numbers can provide higher service quality for user.In Fig. 6, NS=2, NCBS∈{0,
1 ..., 5 }, NBS=64 (a), NBS=128 (b).
Fig. 7 gives the influence in the case where considering number of users and cooperative base station number both factors to system energy efficiency.It can be with
Find out in the case where antenna for base station number is certain, there are a critical values for the number of users that system can service, that is, have one
Optimal service number of users, under the number of users, system can guarantee the minimum quality of service requirement of each user.It also sends out simultaneously
In the case where present same subscriber number and macro base station antenna number, by way of increasing and disposing small base station number, base station collaboration
It can also be improved system energy efficiency.(number of users, antenna number, QoS, transmission power, base station deployment in the case where other parameters are certain
Mode etc.), there are a critical values for cooperative base station number, effect highest are enabled the system to, as cooperative base station number critical value is 4 in Fig. 7
When system energy efficiency highest.In Fig. 7, NCBS∈ { 0,1,2,3,4, } 5, NUE∈ { 5,10 ..., 30 } (a), NUE∈{20,30,…,
60 } (b), QoS=2bit/s/Hz, NBS=64 (a), NBS=128 (b).
Fig. 8 gives the system energy efficiency in the case where comprehensively considering different user service quality and cooperative base station number.
Wherein parameter includes NS∈ { 2,4 }, QoS ∈ { 1,2,3 } and NCBS∈{0,1,2}.Wherein, user's number is 10.Pass through analysis
Different antenna amounts, QoS constraint and the base station collaboration of base station, Fig. 7 shows in system design, can be joined by these
Several optimal setting improves efficiency.Simultaneously, it was found that in the case where identical efficiency, can by increase cooperative base station number,
Less macro base station antenna number also can satisfy qos requirement.Compared with Fig. 8 (a), in Fig. 8 (b), by increasing the base that cooperates
The antenna amount stood, also can be further improved system energy efficiency.In Fig. 8, NCBS∈ { 0,1,2 }, QoS ∈ { 1,2,3 }, NS=2
(a), NS=4 (b).
In the present embodiment, the determination method of parameter value not only considers in implementation process when efficiency is optimal in the heterogeneous network
Influence of the base station number to system energy efficiency, and consider influence of the other parameters to system energy efficiency simultaneously, using this method and
Device can determine parameter value when system energy efficiency is optimal, subsequent that determining parameter value is applied to actual scene, be conducive to mention
Rise communication system efficiency.
For the various method embodiments described above, for simple description, therefore, it is stated as a series of action combinations, but
Be those skilled in the art should understand that, the present invention is not limited by the sequence of acts described because according to the present invention, certain
A little steps can be performed in other orders or simultaneously.Secondly, those skilled in the art should also know that, it is retouched in specification
The embodiment stated belongs to preferred embodiment, and related actions and modules are not necessarily necessary for the present invention.
Method is described in detail in aforementioned present invention disclosed embodiment, diversified forms can be used for method of the invention
Device realize that therefore the invention also discloses a kind of devices, and specific embodiment is given below and is described in detail.
Fig. 9 is the structural representation of the determining device of parameter value when efficiency is optimal in heterogeneous network disclosed by the embodiments of the present invention
Figure, shown in Figure 9, the determining device 90 of parameter value may include: when efficiency is optimal in heterogeneous network
Model building module 901, for establishing the system energy efficiency optimal models for meeting preset condition.
Wherein, the preset condition includes that total power consumption is minimum, Signal to Interference plus Noise Ratio of any one user is not less than lowest service
Quality and the transimission power of any one antenna are not more than preset antenna maximum transmission power.
In the present embodiment, the system energy efficiency optimal models for meeting preset condition are initially set up, specifically can satisfy: being met
While user QoS constraint and antenna power constrain, total power consumption is minimized, it is maximum to enable the system to effect.
Model optimization module 902 obtains optimization mould for carrying out convex optimization processing to the system energy efficiency optimal models
Type.
The model optimization module 902 specifically can be used for: using semi definite programming and positive semidefinite relaxation method to described
System energy efficiency optimal models carry out convex optimization processing, obtain Optimized model.
Matrix deciding module 903, for determining optimal beam figuration matrix according to the seismic responses calculated.
In the present embodiment, under given user QoS constraint condition and antenna maximum transmission power constraint condition, optimization is asked
Topic (formula 12) can be solved by algorithm 1.Optimal beam figuration matrix can be determined in the process.
Parameter value determining module 904, for determining under different base station quantity, being in conjunction with the optimal beam figuration matrix
The optimum parameter value of other influences factor when efficiency of uniting is optimal.
Wherein, the other influences factor includes at least one of antenna for base station quantity, service quality and number of users.
In a schematical example, the structure of the parameter value determining module 904 can participate in Figure 10, comprising:
Initialization module 1001, for initializing system environments.
Parameter value determines submodule 1002, for traversing other influences factor under the premise of traversing different base station quantity
Different choosing values determined under different base station quantity in conjunction with the optimal beam figuration matrix, the other influences factor system energy
The optimum parameter value of other influences factor when imitating optimal.
Wherein, the initialization module 1001 specifically can be used for: generate all base stations under different cooperative base station quantity
At least there is a user in each cooperative base station overlay area according to the coordinate position set in coordinate position set
Under the premise of, the position of all users is generated at random, according to the minimum range collection of each user and the coordinate position set
It closes, judges whether the distance of all each base stations of user distance is not less than default minimum range using backtracking method, if it is not, then returning
The step of going back to the position for generating all users at random, until the distance of all each base stations of user distance is not less than institute
State default minimum range.
Figure 11 is the structural schematic diagram that parameter value disclosed by the embodiments of the present invention determines submodule, shown in Figure 11, institute
It states parameter value and determines that submodule 1002 may include:
Computing module 1101 is traversed, is used under the premise of traversing different base station quantity, for other shadows described in each
The choosing value of the factor of sound carries out multiple efficiency calculating in conjunction with the optimal beam figuration matrix.
Mean value determining module 1102, for determining the average value of the multiple efficiency calculated result, as other described shadows
The current choosing of the factor of sound is worth corresponding system energy efficiency value.
Optimum value determining module 1103, for determining the corresponding system energy efficiency value of different choosing values of the other influences factor
In it is maximum can valid value, and by it is described it is maximum can the choosing value of the corresponding other influences factor of valid value be determined as optimal parameter
Value.
In the present embodiment, the determining device of parameter value not only considers in implementation process when efficiency is optimal in the heterogeneous network
Influence of the base station number to system energy efficiency, and consider influence of the other parameters to system energy efficiency simultaneously, using this method and
Device can determine parameter value when system energy efficiency is optimal, subsequent that determining parameter value is applied to actual scene, be conducive to mention
Rise communication system efficiency.
Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with other
The difference of embodiment, the same or similar parts in each embodiment may refer to each other.For device disclosed in embodiment
For, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is said referring to method part
It is bright.
It should also be noted that, herein, relational terms such as first and second and the like are used merely to one
Entity or operation are distinguished with another entity or operation, without necessarily requiring or implying between these entities or operation
There are any actual relationship or orders.Moreover, the terms "include", "comprise" or its any other variant are intended to contain
Lid non-exclusive inclusion, so that the process, method, article or equipment including a series of elements is not only wanted including those
Element, but also including other elements that are not explicitly listed, or further include for this process, method, article or equipment
Intrinsic element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that
There is also other identical elements in process, method, article or equipment including the element.
The step of method described in conjunction with the examples disclosed in this document or algorithm, can directly be held with hardware, processor
The combination of capable software module or the two is implemented.Software module can be placed in random access memory (RAM), memory, read-only deposit
Reservoir (ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or technology
In any other form of storage medium well known in field.
The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present invention.
Various modifications to these embodiments will be readily apparent to those skilled in the art, as defined herein
General Principle can be realized in other embodiments without departing from the spirit or scope of the present invention.Therefore, of the invention
It is not intended to be limited to the embodiments shown herein, and is to fit to and the principles and novel features disclosed herein phase one
The widest scope of cause.
Claims (10)
1. a kind of determination method of parameter value when efficiency is optimal in heterogeneous network characterized by comprising
The system energy efficiency optimal models for meeting preset condition are established, the preset condition includes total power consumption minimum, any one use
The Signal to Interference plus Noise Ratio at family is sent out not less than the transimission power of minimum quality of service and any one antenna no more than preset antenna maximum
Penetrate power；
Convex optimization processing is carried out to the system energy efficiency optimal models, obtains Optimized model；
Optimal beam figuration matrix is determined according to the seismic responses calculated；
It in conjunction with the optimal beam figuration matrix, determines under different base station quantity, other influences factor when system energy efficiency is optimal
Optimum parameter value.
The determination method of parameter value when 2. efficiency is optimal in heterogeneous network according to claim 1, which is characterized in that described right
The system energy efficiency optimal models carry out convex optimization processing, obtain Optimized model, comprising:
Convex optimization processing is carried out to the system energy efficiency optimal models using semi definite programming and positive semidefinite relaxation method, is obtained excellent
Change model.
The determination method of parameter value when 3. efficiency is optimal in heterogeneous network according to claim 1, which is characterized in that it is described its
His influence factor includes at least one of antenna for base station quantity, service quality and number of users.
The determination method of parameter value when 4. efficiency is optimal in heterogeneous network according to claim 1, which is characterized in that the knot
The optimal beam figuration matrix is closed, is determined under different base station quantity, the best ginseng of other influences factor when system energy efficiency is optimal
Numerical value, comprising:
Initialize system environments；
Under the premise of traversing different base station quantity, the different choosing values of other influences factor are traversed, are assigned in conjunction with the optimal beam
Shape matrix determines under different base station quantity, and the other influences factor is most when optimal for the other influences factor system energy efficiency
Good parameter value.
The determination method of parameter value when 5. efficiency is optimal in heterogeneous network according to claim 4, which is characterized in that it is described
Under the premise of traversing different base station quantity, the different choosing values of other influences factor are traversed, in conjunction with the optimal beam figuration matrix,
It determines under different base station quantity, the optimal parameter of other influences factor system energy efficiency other influences factor when optimal
Value, comprising:
Under the premise of traversing different base station quantity, for the choosing value of other influences factor described in each, in conjunction with described optimal
Wave beam formed matrix carries out multiple efficiency calculating；
The average value for determining the multiple efficiency calculated result, the current choosing as the other influences factor are worth corresponding system
It can valid value；
Determine the different choosings of the other influences factor be worth in corresponding system energy efficiency value it is maximum can valid value, and by the maximum
The choosing value of the corresponding other influences factor of energy valid value is determined as optimum parameter value.
The determination method of parameter value when 6. efficiency is optimal in heterogeneous network according to claim 4, which is characterized in that described first
Beginningization system environments, comprising:
Generate the coordinate position set of all base stations under different cooperative base station quantity；
According to the coordinate position set, under the premise of at least there is a user in each cooperative base station overlay area,
The position of all users is generated at random；
According to the minimum range set of each user and the coordinate position set, all user distances are judged using backtracking method
Whether the distance of each base station is not less than default minimum range；
If it is not, the step of then returning to the position for generating all users at random, until all each base stations of user distance
Distance is all not less than the default minimum range.
The determining device of parameter value when 7. efficiency is optimal in a kind of heterogeneous network characterized by comprising
Model building module, for establishing the system energy efficiency optimal models for meeting preset condition, the preset condition includes total work
Minimum, any one user Signal to Interference plus Noise Ratio is consumed to be not more than not less than the transimission power of minimum quality of service and any one antenna
Preset antenna maximum transmission power；
Model optimization module obtains Optimized model for carrying out convex optimization processing to the system energy efficiency optimal models；
Matrix deciding module, for determining optimal beam figuration matrix according to the seismic responses calculated；
Parameter value determining module, for determining under different base station quantity, system energy efficiency is most in conjunction with the optimal beam figuration matrix
The optimum parameter value of other influences factor when excellent.
The determining device of parameter value when 8. efficiency is optimal in heterogeneous network according to claim 7, which is characterized in that it is described its
His influence factor includes at least one of antenna for base station quantity, service quality and number of users.
The determining device of parameter value when 9. efficiency is optimal in heterogeneous network according to claim 7, which is characterized in that the ginseng
Numerical value determining module includes:
Initialization module, for initializing system environments；
Parameter value determines submodule, under the premise of traversing different base station quantity, the different of traversal other influences factor to be selected
Value, in conjunction with the optimal beam figuration matrix, determines under different base station quantity, when the other influences factor system energy efficiency is optimal
The optimum parameter value of the other influences factor.
The determining device of parameter value when 10. efficiency is optimal in heterogeneous network according to claim 9, which is characterized in that described
Parameter value determines that submodule includes:
Computing module is traversed, is used under the premise of traversing different base station quantity, for other influences factor described in each
Choosing value carries out multiple efficiency calculating in conjunction with the optimal beam figuration matrix；
Mean value determining module, for determining the average value of the multiple efficiency calculated result, as the other influences factor
Current choosing is worth corresponding system energy efficiency value；
Optimum value determining module, the maximum being worth in corresponding system energy efficiency value for determining the different choosings of the other influences factor
Energy valid value, and the choosing value of the corresponding other influences factor of the maximum energy valid value is determined as optimum parameter value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810861172.6A CN109004968A (en) | 2018-08-01 | 2018-08-01 | The determination method and device of parameter value when efficiency is optimal in heterogeneous network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810861172.6A CN109004968A (en) | 2018-08-01 | 2018-08-01 | The determination method and device of parameter value when efficiency is optimal in heterogeneous network |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109004968A true CN109004968A (en) | 2018-12-14 |
Family
ID=64596381
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810861172.6A Pending CN109004968A (en) | 2018-08-01 | 2018-08-01 | The determination method and device of parameter value when efficiency is optimal in heterogeneous network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109004968A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110350961A (en) * | 2019-07-15 | 2019-10-18 | 福州数据技术研究院有限公司 | Suitable for the extensive MIMO mixed-beam forming algorithm of 5G multi-user and system |
| CN112383936A (en) * | 2020-11-27 | 2021-02-19 | 中国联合网络通信集团有限公司 | Method and device for evaluating number of accessible users |
| CN116367196A (en) * | 2023-04-06 | 2023-06-30 | 广州爱浦路网络技术有限公司 | Network energy efficiency evaluation method and system based on new generation communication system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103581913A (en) * | 2012-07-27 | 2014-02-12 | 华为技术有限公司 | Cooperative transmission method and device in heterogeneous network |
| CN104202716A (en) * | 2014-09-12 | 2014-12-10 | 东南大学 | D2D efficient power optimization method based on heterogeneous network |
| CN104301975A (en) * | 2014-11-06 | 2015-01-21 | 东南大学 | Multipoint coordinated transmission mode selection-based network energy saving method |
| CN105246139A (en) * | 2015-09-30 | 2016-01-13 | 吴豪 | Method and device for energy-efficient transmission of treatment data in heterogeneous network |
| CN105392161A (en) * | 2015-10-15 | 2016-03-09 | 北京航空航天大学 | User accessing and power control combined optimization method in cooperative heterogeneous network |
| CN106452546A (en) * | 2016-10-18 | 2017-02-22 | 华北电力大学（保定） | Wave beam forming method in power line MIMO communication based on energy efficiency |
| CN108063632A (en) * | 2018-02-27 | 2018-05-22 | 哈尔滨工业大学 | Cooperation resource allocation methods based on efficiency in isomery cloud access network |
-
2018
- 2018-08-01 CN CN201810861172.6A patent/CN109004968A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103581913A (en) * | 2012-07-27 | 2014-02-12 | 华为技术有限公司 | Cooperative transmission method and device in heterogeneous network |
| CN104202716A (en) * | 2014-09-12 | 2014-12-10 | 东南大学 | D2D efficient power optimization method based on heterogeneous network |
| CN104301975A (en) * | 2014-11-06 | 2015-01-21 | 东南大学 | Multipoint coordinated transmission mode selection-based network energy saving method |
| CN105246139A (en) * | 2015-09-30 | 2016-01-13 | 吴豪 | Method and device for energy-efficient transmission of treatment data in heterogeneous network |
| CN105392161A (en) * | 2015-10-15 | 2016-03-09 | 北京航空航天大学 | User accessing and power control combined optimization method in cooperative heterogeneous network |
| CN106452546A (en) * | 2016-10-18 | 2017-02-22 | 华北电力大学（保定） | Wave beam forming method in power line MIMO communication based on energy efficiency |
| CN108063632A (en) * | 2018-02-27 | 2018-05-22 | 哈尔滨工业大学 | Cooperation resource allocation methods based on efficiency in isomery cloud access network |
Non-Patent Citations (3)
| Title |
|---|
| ALESSIO ZAPPONE等: "Energy-Efficient Power Control: A Look at 5G Wireless Technologies", 《IEEE TRANSACTIONS ON SIGNAL PROCESSING》 * |
| EMIL BJORNSON等: "Massive MIMO and small cells: Improving energy efficiency by optimal soft-cell coordination", 《ICT 2013》 * |
| YINGHUI ZHANG等: "A Novel Diversity Receiver Design for Cooperative Transmission System", 《IEEE ACCESS》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110350961A (en) * | 2019-07-15 | 2019-10-18 | 福州数据技术研究院有限公司 | Suitable for the extensive MIMO mixed-beam forming algorithm of 5G multi-user and system |
| CN112383936A (en) * | 2020-11-27 | 2021-02-19 | 中国联合网络通信集团有限公司 | Method and device for evaluating number of accessible users |
| CN112383936B (en) * | 2020-11-27 | 2023-05-26 | 中国联合网络通信集团有限公司 | Method and device for evaluating number of accessible users |
| CN116367196A (en) * | 2023-04-06 | 2023-06-30 | 广州爱浦路网络技术有限公司 | Network energy efficiency evaluation method and system based on new generation communication system |
| CN116367196B (en) * | 2023-04-06 | 2024-01-30 | 广州爱浦路网络技术有限公司 | Network energy efficiency evaluation method and system based on new generation communication system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zheng et al. | Survey of large-scale MIMO systems | |
| US10972158B2 (en) | Distributed FD-MIMO: cellular evolution for 5G and beyond | |
| RU2678562C1 (en) | Wireless communication system and device and method in the wireless communication system | |
| Goyal et al. | Full duplex cellular systems: will doubling interference prevent doubling capacity? | |
| Sanguinetti et al. | Interference management in 5G reverse TDD HetNets with wireless backhaul: A large system analysis | |
| CN106169948B (en) | The method and apparatus of reference signal transmission are executed in a wireless communication system | |
| JP6786479B2 (en) | Equipment and methods for full-dimensional MIMO with one-dimensional CSI feedback | |
| CN110313199A (en) | The detection reference signal power control of multi-input and-output radio system | |
| CN102026259B (en) | System level simulation method for CoMP (coordinated multi-point) technique in LTE-A (long term evolution-advanced) system | |
| US8989295B2 (en) | Multi-layer beamforming with partial channel state information | |
| CN110035441A (en) | Determine wave beam, signal quality measured method and communication device | |
| Kim et al. | Hierarchical maritime radio networks for internet of maritime things | |
| Osman et al. | Achievable rate evaluation of in-building distributed antenna systems | |
| WO2020140353A1 (en) | System and Method for Beam Management with Emissions Limitations | |
| CN109004968A (en) | The determination method and device of parameter value when efficiency is optimal in heterogeneous network | |
| WO2018068668A1 (en) | Antenna rollback method, and base station | |
| CN104168574B (en) | Uplink transmission method based on adaptable interference selection in mixed cellular system | |
| CN107332597A (en) | A kind of method and device being wirelessly transferred based on 3D MIMO | |
| CN106332291B (en) | The downlink radio resource distribution method of the service-oriented quality of customer-centric network | |
| US8976888B2 (en) | Method for uplink multi-user cooperation communication | |
| Saxena | Pilot contamination and mitigation techniques in massive MIMO systems | |
| Ngo et al. | Ultradense Cell-Free Massive MIMO for 6G: Technical Overview and Open Questions | |
| CN112788612B (en) | Beam processing method, device and storage medium | |
| Hsiao et al. | Multipath division multiple access for 5G cellular system based on massive antennas in millimeter wave band | |
| Xia et al. | Bandwidth allocation in heterogeneous networks with wireless backhaul |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181214 |