CN110430582A - A kind of resource allocation method based on quantum flora optimization algorithm under single cell multi-user communication network scenarios - Google Patents
A kind of resource allocation method based on quantum flora optimization algorithm under single cell multi-user communication network scenarios Download PDFInfo
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- 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
- H04B7/0413—MIMO systems
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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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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention discloses a kind of resource allocation methods based on quantum flora optimization algorithm under single cell multi-user communication network scenarios, in the case where the modern communication system background for the low energy consumption high-speed that green communications and 5G are communicated requires, from the energy efficiency of base station, loss model based on transmission power and line power and and Rate Models, establish energy efficiency model, by the antenna amount for optimizing antenna elevation angle and base station system, optimal pitch angle and antenna amount is obtained, to obtain the optimal value of energy efficiency.Incorporating quantum flora Intelligent Optimal algorithm in the present invention, can be greatly improved optimization efficiency and can be to avoid falling into local circulation.The present invention improves the energy efficiency of base station under single cell scenario, has certain researching value and application value.
Description
Technical field:
The present invention relates to the optimization methods in a kind of grid system, more particularly to one kind to be based on MIMO mobile communication system
The optimal resource allocation methods with quantum intelligence computation of energy efficiency, belong to the network technology in mobile communication system under scene of uniting
Field.
Background technique:
5th third-generation mobile communication (5th Generation 5G) system, it is intended to solve and be applied to present communications field institute
The new demand and new challenge of proposition are the third generation mobile communication systems developed towards mobile communication demand after the year two thousand twenty.
It is expected that 5G will the horizontal capacity for improving 1000 times or so more current than 4G mobile communication (4th Generation, 4G).Meanwhile it is right
The requirement of the telecommunication service quality of 5G network is obviously improved.With the technologies such as internet-of-things terminal and cloud computing make rapid progress it is fluffy
It breaks out and opens up and be linked into wireless network, the transmission rate and energy consumption of wireless communication are faced with bigger challenge, mobile fortune
The contradiction sought between the limited resource of quotient and growing user demand becomes current urgent problem to be solved.
In recent years, with the rapid development of wireless communication technique in telecom operators' business, China is had been developed as entirely
The growth of explosion type is presented so that Information and Telecommunication Industry in the maximum Communications Market of ball, high-speed data service value volume and range of product
(information and communication technology, ICT) becomes the fifth-largest energy consumption industry in the whole world at present.According to
Solution, energy-related cost account for cellular carrier cost and point out that greatly mobile operator electric cost expenditure is at outlay cost
Main project.According to statistics, electric cost expenditure accounts for the 25% of entire outlay cost, wherein being due to radio honeycomb more than 70%
The radio part of network.In addition, telecommunication department increases the contribution that global carbon dioxide discharges rapidly in the past ten years,
Thus mobile operator is the largest one of energy consumers.
Therefore, other than improving radio transmission efficiency, " green communications " for the purpose of energy conservation become 5G core technology
One of an important factor for be considered as and critical design target are designed, according to the rule of Mobile Communication Development, 5G will have super
The high availability of frequency spectrum and efficiency also will improve a magnitude than 4G mobile communication in terms of energy utilization.
It can be seen that the first third-generation mobile communication using frequency division multiple access (Frequency- from the development history of mobile communication
Division-Multiple-Address, FDMA), communication is realized by the transformation of analog signal to digital signal, and the second generation is moved
Dynamic communication network uses time-division more (time-Division-Multiple-Address, TDMA) and CDMA (Code-
Division-Multiple-Address, ADMA) technology, the data services such as linking Internet, third are expanded to by voice service
In third generation mobile communication network, the multimedia communication using video as representative is realized by CDMA technology, with higher rate and more
The requirement of wide bandwidth.
The 1970s is it has been proposed that be applied to communication system for MIMO technology, thereafter in the 1990s, Bell
Laboratory scholar Teladar, Foshini et al. give the MIMO capacity under fading profiles, propose diagonal-AT&T Labs
It is layered space-time techniques (D-BLAST, Diagonal Bell Laboratories Layered Space-Time), it is resonable for the first time
Communication link energy can be made to be doubled and redoubled by above demonstrating starting end and being all made of multiple antennas.This theory is in past 30 years
Extensive research and use are obtained, such as research of diversity spatial multiplexing gain, wave beam forming, interference management etc. all obtain fast
Hail exhibition.
Nowadays in forth generation mobile communications network, orthogonal frequency division multiplexi (Orthogonal is used
Frequency Division Multiplexing, OFDM) and MIMO technique (Multiple-Input
Multiple-Output, MIMO), not only transmission rate and communication quality have large increase, the new technology used regardless of
Industry or academia all attract extensive attention, and wherein mimo system is independently transmitted by more antennas and receives, by multipath
Disadvantage be converted to advantage, in the case where not increasing frequency spectrum resource and antenna transmission power, can increase exponentially and be
System channel capacity, the core technology for showing apparent advantage, being considered as next generation mobile communication.
Based on the requirement in the 5th third generation mobile communication network for higher message transmission rate and higher network reliability,
Extensive antenna MIMO technique (Massive MIMO) becomes one of the core technology in 5G system, works as communication environments
In there are when a large amount of scatterers, can be approximately considered different user (User Equipment) and base station (Base Station, BS)
Between it is mutually indepedent, at this moment, tend to be infinitely great as base station day keeps count of, the channel between user will gradually tend to be orthogonal, pole
The big interference reduced between system multi-user configures provided spatial degrees of freedom using extensive antenna base station, can
Multiplexing capacity of the frequency spectrum between multi-user, each user link spectrum efficiency and the interference performance for resisting minizone are promoted,
To which the overall utilization rate of frequency spectrum resource be substantially improved, provided diversity and array gain, each user are configured using base station
It is also greatly improved with power of communications in base station.
The research for the optimized for energy efficiency resource allocation that combining with green communicates under 5G network at present is less, simultaneously for the party
Face research also lacks more effective optimization method.
The information disclosed in the background technology section is intended only to increase the understanding to general background of the invention, without answering
When being considered as recognizing or imply that the information constitutes the prior art already known to those of ordinary skill in the art in any form.
Summary of the invention:
To achieve the above object, the present invention provides one kind in view of this, the purpose of the present invention is to provide one kind to be based on
The optimization method of single cell multi-user system energy efficiency of quantum flora optimization algorithm, this method is to base station transmitting power and day
Line angle of declination optimizes, with the system energy efficiency being optimal.
In order to achieve the above objectives, the invention provides the following technical scheme:
A kind of single cell multi-user system energy efficiency optimization method based on quantum flora optimization algorithm, including following step
It is rapid:
The influence of S1, analysis base station transmitting power and Downtilt to system energy efficiency.
S2, the Optimized model containing single cell multi-user system energy efficiency is established
S3, usage amount daughter bacteria colony optimization algorithm solve single cell multi-user system energy efficiency mathematical model.
Further, the S1 includes:
S11, assume the isolated user for having K random distribution in single cell.In the present system, base station end antenna amount is
Nt is highly z, and each user has a receiving antenna, and height is Z from the groundk.Aerial array uses uniform linear array
(Uniform LinerArray, ULA), is placed perpendicular to the ground.
S12, single cell system and rate expression formula are solved.
Path loss: LkIt indicates the path loss in cell between k-th of user and base station, can obtain:
Lk=L0*(dk)-α,
Wherein L0It is the path loss that unit propagates citing, dkIt is the distance between k-th of user of cell and base station, α is to decline
Fall the factor.As shown in figure, in which:
It therefrom can be obtained by the path loss between k-th of user of cell and base station.
Further, the slow fading channel gain g of 3D antenna gainkIt can indicate are as follows:
Wherein AkAntenna gain of the expression base station to k-th of user of cell.AkUnit be dB.This slow fading can make 3D
Influence of the wave beam forming to system performance.
The expression formula of S13,3D antenna gain；
3D propagation model: as shown, (xk, yk, zk) indicate in cell the coordinate for seeing a user, (x0, y0, z0) table
Show that the coordinate of base station, θ indicate the angle of declination of base station, indicates vertical angle of the base station to k-th of user of cell, rkIndicate that base station is arrived
The horizontal distance of k-th of user of cell.
Further, in the calculating of 3D antenna gain, it is assumed that the antenna that user terminal uses is isotropic, and base station makes
It is the aerial array of 3D orientation.3D antenna gain between k-th of user of cell and base station includes two parts: level increases
Benefit and vertical gain.It is indicated respectively with following formula:
Indicate horizontal beam angle, θ3dBIndicate vertical beam width.The level orientation of φ expression antenna spindle
Angle, θ indicate the vertical angle of antenna spindle.SLLH and SLLV respectively indicates maximum horizontal and vertical side lobe attenuation.AmaxIt indicates most
Big pad value.θkIt indicates the vertical angle between k-th of user of cell and base station, can indicate are as follows:
Further, 3D antenna gain can indicate are as follows:
Ak=AHk+AVk,
Further, discovery antenna gain needs to maximize and minimum is handled, and this adds increased the complexity of analysis.This
Outside, the beam gain of horizontal dimensions is very mature in previous research, so herein mainly for the wave of vertical dimensions
Shu Zengyi.Therefore, we do not consider the line gain of horizontal dimensions, and SLLV is infinity.So 3D antenna gain can be used as follows
Formula expression:
Further, the principal element for influencing slow fading includes: antenna height, the covering radius of base station, user location, antenna
Angle of declination etc..Herein mainly for Downtilt, number of users, the optimization problem of antenna amount and system emission power, because
This it is assumed herein that other parameters all given then above formula can be rewritten are as follows:
Therefore the independent variable of slow fading channel gain formula is the angle of declination of antenna.
S14 and rate Approximate Formula:
By formula it is found that when other parameters give, system slow fading coefficient is only related with Downtilt.Below
It herein will relationship between analysis system and rate and Downtilt.ULA aerial array is used herein, and transmitting terminal uses
MRT precoding.Herein, it is assumed that the power of each downlink chain circuit data stream is equal.Signal power gamma distribution shape and
Scale parameter are as follows:
The shape and scale parameter of the gamma distribution of inter-user interference power are as follows:
Further, we obtain demand power and the power expectation of distracter is respectively as follows:
Further, in cell k-th user's and rate are as follows:
Further, total system and rate can indicate are as follows:
R (θ)=∑k∈{1,....K}Rk(θ),
S15, system power dissipation mainly include two parts: first is that the line loss of sending and receiving end hardware, second is that transmitting signal
Consumed power.Line loss simplified partial is a fixed value by traditional power consumption models, and this simple mould
Type cannot use in the very big Massive mimo system of number of antennas.This is because being used for the digital signal of radio frequency (RF)
Circuit power consumed by processing and analog filter and Base-Band Processing changes with number of antennas and number of users, In
Number of antennas and number of users are smaller in small mimo system, can be regarded as constant, but its variation is in Massive
Key effect is played when mimo system, has large effect to its performance.Therefore, we give an accurate power first
Consumption models, and brief analysis has been carried out for the physical significance of each section power consumption.Power consumption are as follows:
P=PAP+PCP,
Further, PAPFor the power of power amplifier consumption, P is lost in line powerCPAre as follows:
PCP=PTC+PC/D+PCE+PLP+PFIX,
Further, the power consumption that a set of typical MIMO transmitter and receiver use is
PTC=PBS+PSYN+KPUE,
Wherein,
PBS: it is connected to the power of the BS component of each antenna, including converter, frequency mixer and filter；
PSYN: the power of oscillator consumption；
PUE: the power of nest refers to the power of all single-antenna subscriber receiver modules, including amplifier, frequency mixer
And filter.
Further, in the downlink, base station carries out Channel Coding and Modulation to K information symbol sequence, retransmits out
It goes.After each user receives signal, algorithm that recycle some suboptimums, fixation complexity solves the sequence received
Code.The process of uplink is in contrast.In these processes, the power P of consumptionC/DIt can indicate are as follows:
PC/D=BK (PCOD+PDEC),
Wherein,
PCOD: the power of each subscriber-coded consumption；
PDEC: each user decodes the power of consumption.
For convenient for analysis, it is assumed that the P of uplink and downlinkCODAnd PDECIt is identical
Further, enable base station it is every consumption erg-ten heat can carry out L calculating operation (also referred to as trigger/watt
It is special), each relevant resource block only carries out channel estimation once based on pilot tone, and each second includes B/T relevant resource blocks.Upper
Line link, user receive Mx τ pilot signal matrix, and by estimating channel multiplied by the pilot frequency sequence that corresponding length is τ
Information.This is a linear operation process, and the power consumption needed is
Further, linear process includes two parts: sending precoding and receives merging.Linear process matrix depends on letter
Road estimation, therefore linear process is also the power for carrying out the consumption of linear process in each relevant period are as follows:
Wherein, first item indicates that each data symbol does matrix and is transmitted across with the power consumed when vector multiplication in data
Cheng Zhong, when linear process matrix is multiplied with information symbol, the power for needing to consume isSection 2 is indicated for precoding
Matrix receives the calculating for merging matrix, and the complexity of calculating and the linear process mode of use are related.According to force zero (Zero
Forcing, ZF) linear process, due to carry out the matrix inversion operation based on standard Cholesky factorization and back substitution,
The power then consumed is
Further, system architecture can generate a fixed power PFIX, it is unrelated with M, K.This includes control signaling
Fixed power consumption, the consumption unrelated with load of backhaul infrastructure and baseband processor.
In step 2, system it is total and rate be R (θ)=∑k∈{1,....K}Rk(θ), by formula (15) and formula (16) system
Total energy efficiency are as follows:
Further, quantum flora optimization algorithm (the Quantum Bacterial Foraging in the S3
Optimization, QBFO) include:
S31, parameter setting and initialization of population:
Parameter setting: consider a single cell multi-user system.Assuming that only having 1 cell in system, then needing to this
The two parameters of the transmission power and Downtilt of a cell optimize, therefore dimension is 2.In population Q (t), dye
Colour solid length is len, and initialization population number is n, and chemotactic number is Nc, breeds times N re, disperses times N ed, migrate probability
Ped。
The initialization of population: initialization population For j-th of Escherichia coli in t generation, dye
Colour solidIt is defined as follows:
2n*len probability amplitude of whole n chromosomes is initialized toSo in 1st generation, all dyeing
Body is with identical probabilityAmong linear combination state in all possible states, i.e.,
Wherein skIt is by binary string (x1x2...xlen) description k-th of state, xi=0,1, i=1,2 ..., len.
So, the population of initialization
S32, by observing and measuring Q (t0) state generate binary system disaggregation p (t0)=(x1,x2,...xn), each solutionIt is the binary string that the length being made of 0 and 1 is len, value is 0 or 1 will be by corresponding quantum bit
Observation probabilityOrIt determines.
S33, assessment P (t0) fitness function value, with function fitness (x, y) be fitness function assessed；
S34, record P (t0) in the mesh of optimal fitness function value and corresponding optimized individual as next step population recruitment
Mark；
S35, chemotactic operation is carried out to the population in the present age, is realized using Quantum rotating gate appropriate, the quantum rotation of use
Revolving door are as follows:
More new strategy (the α ' of quantum statei β′i)=U (θi)·(αi βi), i.e.,
Wherein,It is i-th bit quantum bit in chromosome, θiIt is quantum rotation door rotation angle, size, direction can lead to
Corresponding data is crossed to check in.
It after Escherichia coli population Q (t) update, assesses P (t), records the fitness optimal value in the generation, if better than upper
In generation, then saves the generation, otherwise still retains previous generation's optimal value.
S36, reach N when chemotactic numbercWhen, chemotactic operation complete, solve optimal adaptation angle value, optimal adaptation angle value compared with
One hemichromosome of difference eliminates, and carries out duplication operation to a preferable hemichromosome, chromosome number remains unchanged.
S37, when number of copy times be less than Nre, step 6 is continued to execute, otherwise chromosome each in population is once dispersed
Judgement generates the decision content between 0-1, if it is determined that value, which is less than, disperses probability Ped, then execute bacterium and disperse, regenerate one
Individual.
S38, when reaching convergence or reaching maximum setting algebra, stop chromosome and update, export current optimum individual, calculate
Method terminates, and otherwise continues.
Further, the S3 is specifically included:
S41, parameter setting and initialization of population:
Consider a single cell multi-user system.Assuming that only having 1 cell in system, then needing the hair to this cell
It penetrates power and Downtilt the two parameters optimizes, therefore dimension is 2.In population Q (t), chromosome length is
Len=32, initialization population number are n=40, and chemotactic number is Nc=50, breed times N re=5, disperse times N ed=2,
Migrate probability P ed=0.25.
The initialization of population: initialization population For t generation in j-th of Escherichia coli,
ChromosomeIt is defined as follows:
2n*len probability amplitude of whole n chromosomes is initialized toSo in 1st generation, all dyeing
Body is with identical probabilityAmong linear combination state in all possible states, i.e.,
Wherein skIt is by binary string (x1x2...xlen) description k-th of state, xi=0,1, i=1,2 ..., len.
So, the population of initialization
S42, by observing and measuring Q (t0) state generate binary system disaggregation p (t0)=(x1,x2,...xn), each solutionIt is the binary string that the length being made of 0 and 1 is len, value is 0 or 1 will be by corresponding quantum bit
Observation probabilityOrIt determines.
S43, assessment P (t0) fitness function value, fitness function be above-mentioned optimization base station transmitting power and pitching
The mathematical model at angle:
S44, record P (t0) in the mesh of optimal fitness function value and corresponding optimized individual as next step population recruitment
Mark；
S45, chemotactic operation is carried out to the population in the present age, is realized using Quantum rotating gate appropriate, the quantum rotation of use
Revolving door are as follows:
More new strategy (the α ' of quantum statei β′i)=U (θi)·(αi βi), i.e.,
Wherein,It is i-th bit quantum bit in chromosome, θiIt is quantum rotation door rotation angle, size, direction can lead to
Corresponding data is crossed to check in.It is 45 ° desirable.
It after Escherichia coli population Q (t) update, assesses P (t), records the fitness optimal value in the generation, if better than upper
In generation, then saves the generation, otherwise still retains previous generation's optimal value.
S46, reach N when chemotactic numbercWhen, chemotactic operation complete, solve optimal adaptation angle value, optimal adaptation angle value compared with
One hemichromosome of difference eliminates, and carries out duplication operation to a preferable hemichromosome, chromosome number remains unchanged.
S47, when number of copy times be less than Nre, step 6 is continued to execute, otherwise chromosome each in population is once dispersed
Judgement generates the decision content between 0-1, if it is determined that value, which is less than, disperses probability Ped, then execute bacterium and disperse, regenerate one
Individual.
S48, when reaching convergence or reaching maximum setting algebra, stop chromosome and update, export current optimum individual, calculate
Method terminates, and otherwise continues.
The beneficial effects of the present invention are: it is multi-purpose that the present invention provides a kind of single cells based on quantum flora optimization algorithm
The optimization method of the system energy efficiency at family can reach system energy efficiency in the case where limited base station transmitting power
Optimal value.Improve capacity usage ratio.
Detailed description of the invention:
Fig. 1: the flow diagram of the method for the present invention；
Fig. 2: Dan little Qu multi-user's Massive MIMO scene figure；
Fig. 3: system energy efficiency is with base station transmitting power variation diagram；
Fig. 4: system energy efficiency is with pitch angle variation diagram；
Fig. 5: base station transmitting power optimal value is with simulation times variation diagram；
Fig. 6: pitch angle optimal value is with simulation times variation diagram；
Fig. 7: system energy efficiency optimal value is with simulation times variation diagram.
Specific embodiment:
Specific embodiments of the present invention will be described in detail below, it is to be understood that protection scope of the present invention is not
It is restricted by specific implementation.
Unless otherwise explicitly stated, otherwise in entire disclosure and claims, term " includes " or its change
Changing such as "comprising" or " including " etc. will be understood to comprise stated element or component, and not exclude other members
Part or other component parts.
A kind of energy efficiency optimization method based on quantum flora optimization algorithm, as shown in Figure 1, the specific steps of which are as follows:
S1 analyzes the influence of base station transmitting power and Downtilt to system energy efficiency.
(1) cell pattern
Each cell has an isolated user of K random distribution, and in this system, it is highly z that base station end antenna amount, which is Nt,
Each user has a receiving antenna, and height is Z from the groundk.As shown in Figure 1.Aerial array uses uniform linear array
(Uniform LinerArray, ULA), is placed perpendicular to the ground.
(2) and Rate Models
1. path loss model
LkIt indicates the path loss in cell between k-th of user and base station, can obtain:
Lk=L0*(dk)-α (1)
Wherein L0It is the path loss that unit propagates citing, dkIt is the distance between k-th of user of cell and base station, α is to decline
Fall the factor.As shown in figure, in which:
It therefrom can be obtained by the path loss between k-th of user of cell and base station.
2. slow fading channel gain model
The slow fading channel gain g of 3D antenna gainkIt can indicate are as follows:
Wherein AkAntenna gain of the expression base station to k-th of user of cell.AkUnit be dB.This slow fading can make 3D
Influence of the wave beam forming to system performance.
3.3D antenna gain
3D propagation model: as shown, (xk, yk, zk) indicate in cell the coordinate for seeing a user, (x0, y0, z0) table
Show that the coordinate of base station, θ indicate the angle of declination of base station, indicates vertical angle of the base station to k-th of user of cell, rkIndicate that base station is arrived
The horizontal distance of k-th of user of cell.
3D antenna gain: assuming that the antenna that user terminal uses is isotropic, and base station uses the day of 3D orientation
Linear array.3D antenna gain between k-th of user of cell and base station includes two parts: horizontal gain and vertical gain.Point
It is not indicated with following formula:
Indicate horizontal beam angle, θ3dBIndicate vertical beam width.The level orientation of φ expression antenna spindle
Angle, θ indicate the vertical angle of antenna spindle.SLLH and SLLV respectively indicates maximum horizontal and vertical side lobe attenuation.AmaxIt indicates most
Big pad value.θkIt indicates the vertical angle between k-th of user of cell and base station, can indicate are as follows:
So 3D antenna gain can indicate are as follows:
Ak=AHk+AVk (7)
It is seen that antenna gain needs to maximize and minimum processing from formula, this adds increased the complexity of analysis
Property.In addition, the beam gain of horizontal dimensions is very mature in previous research, so herein mainly for vertical dimensions
Beam gain.Therefore, we do not consider the line gain of horizontal dimensions, and SLLV is infinity.So 3D antenna gain can be used
As following formula is expressed:
The principal element for influencing slow fading includes: antenna height, the covering radius of base station, user location, Downtilt
Deng.Herein mainly for Downtilt, number of users, the optimization problem of antenna amount and system emission power, therefore this paper
It is assumed that other parameters are all given then above formula can be rewritten are as follows:
Therefore the independent variable of slow fading channel gain formula is the angle of declination of antenna.
(3) and rate Approximate Formula:
By formula it is found that when other parameters give, system slow fading coefficient is only related with Downtilt.Below
It herein will relationship between analysis system and rate and Downtilt.ULA aerial array is used herein, and transmitting terminal uses
MRT precoding.Herein, it is assumed that the power of each downlink chain circuit data stream is equal.Signal power gamma distribution shape and
Scale parameter are as follows:
The shape and scale parameter of the gamma distribution of inter-user interference power are as follows:
We obtain demand power and the power expectation of distracter is respectively as follows:
Then in cell k-th user's and rate are as follows:
Total system and rate can indicate are as follows:
R (θ)=∑k∈{1,....K}Rk(θ) (15)
It can be seen that base station transmitting power is related with system and rate, Downtilt is also related with system and rate.
(4) power consumption models are as follows:
P=PAP+PCP (16)
Wherein, PAPFor the power of power amplifier consumption, P is lost in line powerCPAre as follows:
PCP=PTC+PC/D+PCE+PLP+PFIX (17)
1. receiving-transmitting chain
The power consumption that a set of typical MIMO transmitter and receiver use is
PTC=PBS+PSYN+KPUE, (18)
Wherein,
PBS: it is connected to the power of the BS component of each antenna, including converter, frequency mixer and filter；
PSYN: the power of oscillator consumption；
PUE: the power of nest refers to the power of all single-antenna subscriber receiver modules, including amplifier, frequency mixer
And filter.
2. decoding and coding
In the downlink, base station carries out Channel Coding and Modulation to K information symbol sequence, retransmits away.Each
After user receives signal, algorithm that recycle some suboptimums, fixation complexity is decoded to the sequence received.Uplink
The process of link is in contrast.In these processes, the power P of consumptionC/DIt can indicate are as follows:
PC/D=BK (PCOD+PDEC) (19)
Wherein,
PCOD: the power of each subscriber-coded consumption；
PDEC: each user decodes the power of consumption.
For convenient for analysis, it is assumed that the P of uplink and downlinkCODAnd PDECIt is identical
3. channel estimation
L calculating operation (also referred to as trigger/watt), Mei Gexiang can be carried out by enabling the heat of the every consumption erg-ten in base station
Dry resource block only carries out channel estimation once based on pilot tone, and each second includes B/T relevant resource blocks.In uplink, use
Family receives Mx τ pilot signal matrix, and by estimating channel information multiplied by the pilot frequency sequence that corresponding length is τ.This is
One linear operation process, the power consumption needed are
4. linear process
Linear process includes two parts: sending precoding and receives merging.Linear process matrix depends on channel estimation,
Therefore linear process is also the power for carrying out the consumption of linear process in each relevant period are as follows:
Wherein, first item indicates that each data symbol does matrix and is transmitted across with the power consumed when vector multiplication in data
Cheng Zhong, when linear process matrix is multiplied with information symbol, the power for needing to consume isSection 2 is indicated for prelisting
Code matrix receives the calculating for merging matrix, and the complexity of calculating and the linear process mode of use are related.According to force zero
(Zero Forcing, ZF) linear process, due to carry out the matrix inversion based on standard Cholesky factorization and back substitution
Operation, the then power consumed are
5. constant drain
System architecture can generate a fixed power PFIX, it is unrelated with M, K.This includes the fixation function of control signaling
Consumption, the consumption unrelated with load of backhaul infrastructure and baseband processor.
It can be seen that consumption power is related with base station transmitting power, it is unrelated with angle of declination.
S2 establishes the Optimized model containing single cell multi-user system energy efficiency.It is optimal for target letter with system energy efficiency
Number includes two variables of base station transmitting power and Downtilt.
(1) objective function
It is optimal for objective function with system energy efficiency:
Wherein, R is system and rate, and P is system consumption general power.
(2) inequality constraints
Control variables constraint are as follows:
Pt.min≤Pt≤Pt.max (24)
θmin≤θ≤θmax (25)
Wherein, PtFor base station transmitting power, Pt.max, Pt.minFor the bound of base station transmitting power；θ has a down dip for antenna for base station
Angle, θc.min, θc.maxFor the bound of antenna for base station angle of declination, control variables constraint problem is handled using weighting method.
S3 usage amount daughter bacteria colony optimization algorithm solves single cell multi-user system energy efficiency mathematical model.
The quantum flora optimization algorithm (Quantum Bacterial Foraging Optimization, QBFO) of use
Realization process are as follows:
1) parameter setting and initialization of population:
Consider a single cell multi-user system.Assuming that only having 1 cell in system, then needing the hair to this cell
It penetrates power and Downtilt the two parameters optimizes, therefore dimension is 2.In population Q (t), chromosome length is
Len=32, initialization population number are n=40, and chemotactic number is Nc=50, breed times N re=5, disperse times N ed=2,
Migrate probability P ed=0.25.
The initialization of population: initialization population For t generation in j-th of Escherichia coli,
ChromosomeIt is defined as follows:
2n*len probability amplitude of whole n chromosomes is initialized toSo in 1st generation, all dyeing
Body is with identical probabilityAmong linear combination state in all possible states, i.e.,
Wherein skIt is by binary string (x1x2...xlen) description k-th of state, xi=0,1, i=1,2 ..., len.
So, the population of initialization
2) by observing and measuring Q (t0) state generate binary system disaggregation p (t0)=(x1,x2,...xn), each solutionIt is the binary string that the length being made of 0 and 1 is len, value is 0 or 1 will be by corresponding quantum bit
Observation probabilityOrIt determines.It can be assumed that0 probability is represented,1 probability is represented,
IfIts value is 0, ifIts value is 1, has just obtained two that the length being made of 0 and 1 is len
System character string.Two decimal numbers are converted by string of binary characters, preceding len/2 string of binary characters represents Base Transmitter
Probability, rear len/2 character string represent pitch angle size.After being converted into the decimal system, the range of dominated variable is weighted.
Such as: as len=32, preceding 16 strings of binary characters represent base station transmitting power, rear 16 binary-coded characters
String represents pitch angle size.Base station transmitting power scope limitation is in 0W -50W, then complete zero just represents 0W, complete 1 represents 50W, will
Decimal number weighting is limited between 0W -50W.And pitch range is limited in 0-pi/2, complete zero represents 0rad, complete 1 represent π/
Decimal number weighting is limited in 0-pi/2 by 2rad.
3) P (t is assessed0) fitness function value, fitness function be above-mentioned optimization base station transmitting power and pitch angle
Mathematical model:
The two-dimentional decimal number of each chromosome is substituted into fitness function, finds out optimal fitness value and chromosome.
4) P (t is recorded0) in the target of optimal fitness function value and corresponding optimized individual as next step population recruitment；
5) chemotactic operation is carried out to the population in the present age, is realized using Quantum rotating gate appropriate, the quantum rotation of use
Door are as follows:
More new strategy (the α ' of quantum statei β′i)=U (θi)·(αi βi), i.e.,
Wherein,It is i-th bit quantum bit in chromosome, θiIt is quantum rotation door rotation angle, size, direction can lead to
Corresponding data is crossed to check in.θ=π/4 are taken in an experiment.
It after Escherichia coli population Q (t) update, assesses P (t), records the fitness optimal value in the generation, if better than upper
In generation, then saves the generation, otherwise still retains previous generation's optimal value.
6) when chemotactic number reaches NcWhen, chemotactic operation is completed, and optimal adaptation angle value is solved, and optimal adaptation angle value is poor
A hemichromosome eliminate, duplication operation is carried out to a preferable hemichromosome, chromosome number remains unchanged.
7) when number of copy times is less than Nre, step 6 is continued to execute, otherwise chromosome each in population once disperse and be sentenced
It is disconnected, the decision content between 0-1 is generated, if it is determined that value, which is less than, disperses probability Ped, then execute bacterium and disperse, regenerate one by one
Body.
8) when reaching convergence or reaching maximum setting algebra, stop chromosome and update, export current optimum individual, algorithm
Terminate, otherwise continues.
9) after emulation terminates, available optimal base station transmitting power is 30.4786W, and optimal pitch angle is
1.0784rad, energy efficiency maximum can reach 6.9472.
10) fixed pitch angle is 1.0784rad, and energy efficiency changes as shown in Figure 3 with base station transmitting power.Fixed base stations
Transmission power is 30.4786W, and energy efficiency changes as shown in Figure 4 with pitch angle.
11) 1000 simulated programs are executed, obtain base station transmitting power, pitch angle, system energy efficiency with simulation times
Variation diagram.Find out optimal value, worst-case value and average value.As shown in Fig. 5, Fig. 6, Fig. 7.
The aforementioned description to specific exemplary embodiment of the invention is in order to illustrate and illustration purpose.These descriptions
It is not wishing to limit the invention to disclosed precise forms, and it will be apparent that according to the above instruction, can much be changed
And variation.The purpose of selecting and describing the exemplary embodiment is that explaining specific principle of the invention and its actually answering
With so that those skilled in the art can be realized and utilize a variety of different exemplary implementation schemes of the invention and
Various chooses and changes.The scope of the present invention is intended to be limited by claims and its equivalents.
Claims (8)
1. a kind of resource allocation method based on quantum flora optimization algorithm under single cell multi-user communication network scenarios,
It is characterized in that: from the energy efficiency of base station, establishing energy efficiency model, pass through optimization antenna elevation angle and base station system
The antenna amount of system, so that the optimal value of energy efficiency is obtained, the specific steps of which are as follows:
The influence of S1, analysis base station transmitting power and Downtilt to system energy efficiency；
S2, the Optimized model containing single cell multi-user system energy efficiency is established；
S3, usage amount daughter bacteria colony optimization algorithm solve single cell multi-user system energy efficiency mathematical model.
2. a kind of being optimized under single cell multi-user communication network scenarios based on quantum flora according to claim 1 is calculated
The resource allocation method of method, it is characterised in that: the S1 specifically,
S11, assume the isolated user for having K random distribution in single cell, in the present system, base station end antenna amount is Nt, high
Degree is z, and each user has a receiving antenna, and height is Z from the groundk, aerial array is using uniform linear array Uniform
LinerArray, ULA are placed perpendicular to the ground；
S12, single cell system and rate expression formula are solved；
Path loss: LkIt indicates the path loss in cell between k-th of user and base station, can obtain:
Lk=L0*(dk)-α,
Wherein L0It is the path loss that unit propagates citing, dkThe distance between k-th of user of cell and base station, α be decline because
Son, in which:
It therefrom can be obtained by the path loss between k-th of user of cell and base station；
The slow fading channel gain g of S13,3D antenna gainkIt can indicate are as follows:
Wherein AkAntenna gain of the expression base station to k-th of user of cell.AkUnit be dB.This slow fading can make 3D wave beam
Influence of the figuration to system performance.
The expression formula of S14,3D antenna gain；
In the calculating of 3D antenna gain, it is assumed that the antenna that user terminal uses is isotropic, and base station uses 3D fixed
To aerial array；3D antenna gain between k-th of user of cell and base station includes two parts: horizontal gain and vertical increasing
Benefit；It is indicated respectively with following formula:
S15, community user and base station vertical angle θkExpression formula；
Indicate horizontal beam angle, θ3dBIndicate vertical beam width；φ indicates the horizontal azimuth of antenna spindle, θ table
Show the vertical angle of antenna spindle；SLLH and SLLV respectively indicates maximum horizontal and vertical side lobe attenuation；AmaxIndicate maximum attenuation
Value；θkIt indicates the vertical angle between k-th of user of cell and base station, can indicate are as follows:
S16, to the approximation of 3D antenna gain；
3D antenna gain can indicate are as follows:
Ak=AHk+AVk；
It was found that antenna gain needs to maximize and minimum processing, this adds increased the complexity of analysis.In addition, horizontal dimensions
Beam gain is very mature in previous research, so herein mainly for the beam gain of vertical dimensions.Therefore, I
Do not consider the line gains of horizontal dimensions, SLLV is infinity.So 3D antenna gain can be expressed with such as following formula:
The slow fading channel gain g of S17,3D antenna gainkFinal expression formula；
The principal element for influencing slow fading includes: antenna height, the covering radius of base station, user location, Downtilt etc..This
Text is mainly for Downtilt, number of users, the optimization problem of antenna amount and system emission power, it is therefore assumed that other are joined
Number is all given then above formula can be rewritten are as follows:
Therefore the independent variable of slow fading channel gain formula is the angle of declination of antenna；
S18 and rate Approximate Formula:
By formula it is found that when other parameters give, system slow fading coefficient is only related with Downtilt；Lower surface analysis
Relationship between system and rate and Downtilt；Using ULA aerial array, transmitting terminal uses MRT precoding；Assuming that each
The power of downlink chain circuit data stream is equal；The shape and scale parameter of the gamma distribution of signal power are as follows:
The shape and scale parameter of the gamma distribution of inter-user interference power are as follows:
S19, we obtain demand power and the power expectation of distracter is respectively as follows:
In cell k-th user's and rate are as follows:
Total system and rate can indicate are as follows:
R (θ)=∑K ∈ 1 ... .K }Rk(θ)。
3. a kind of being optimized under single cell multi-user communication network scenarios based on quantum flora according to claim 1 is calculated
The resource allocation method of method, it is characterised in that: the S1 specifically,
S21, system power dissipation mainly include two parts: first is that the line loss of sending and receiving end hardware, second is that transmitting signal is disappeared
The power of consumption, power consumption are as follows:
P=PAP+PCP；
S22、PAPFor the power of power amplifier consumption, P is lost in line powerCPAre as follows:
PCP=PTC+PC/D+PCE+PLP+PFIX,
The power consumption that S23, a set of typical MIMO transmitter and receiver use is
PTC=PBS+PSYN+KPUE,
Wherein,
PBS: it is connected to the power of the BS component of each antenna, including converter, frequency mixer and filter；
PSYN: the power of oscillator consumption；
PUE: the power of nest refers to the power of all single-antenna subscriber receiver modules, including amplifier, frequency mixer and filter
Wave device.
S24, in the downlink, base station carry out Channel Coding and Modulation to K information symbol sequence, retransmit away；Each
After user receives signal, algorithm that recycle some suboptimums, fixation complexity is decoded the sequence received；Uplink
The process on road is in contrast；In these processes, the power P of consumptionC/DIt can indicate are as follows:
PC/D=BK (PCOD+PDEC)；
Wherein,
PCOD: the power of each subscriber-coded consumption；
PDEC: each user decodes the power of consumption；
For convenient for analysis, it is assumed that the P of uplink and downlinkCODAnd PDECIt is identical；
S25, enable the heat of the every consumption erg-ten in base station that can carry out L calculating operation (also referred to as trigger/watt), Mei Gexiang
Dry resource block only carries out channel estimation once based on pilot tone, and each second includes B/T relevant resource blocks；In uplink, use
Family receives Mx τ pilot signal matrix, and by estimating channel information multiplied by the pilot frequency sequence that corresponding length is τ；This is
One linear operation process, the power consumption needed are
S26, further, linear process include two parts: send precoding and receive merge；Linear process matrix depends on letter
Road estimation, therefore linear process is also to carry out once in each relevant period；The power of linear process consumption are as follows:
Wherein, first item indicates the power consumed when each data symbol does matrix and vector multiplication；In data transmission procedure,
When linear process matrix is multiplied with information symbol, the power for needing to consume isSection 2 is indicated for pre-coding matrix
Or the calculating for merging matrix is received, the complexity of calculating and the linear process mode of use are related；According to force zero (Zero
Forcing, ZF) linear process, due to carry out the matrix inversion operation based on standard Cholesky factorization and back substitution, then
The power of consumption are as follows:
S27, system architecture can generate a fixed power PFIX, it is unrelated with M, K；This includes the fixation function of control signaling
Consumption, the consumption unrelated with load of backhaul infrastructure and baseband processor.
4. a kind of being optimized under single cell multi-user communication network scenarios based on quantum flora according to claim 1 is calculated
The resource allocation method of method, it is characterised in that: single cell multi-user system energy efficiency mathematical model in the S2 includes mesh
Scalar functions and inequality constraints.
5. a kind of being optimized under single cell multi-user communication network scenarios based on quantum flora according to claim 3 is calculated
The resource allocation method of method, it is characterised in that: the expression formula of the objective function are as follows:
Wherein R is system and rate, and P is system consumption general power, the power P including power amplifier consumptionAP, line power damage
Consume PCP。
6. a kind of being optimized under single cell multi-user communication network scenarios based on quantum flora according to claim 3 is calculated
The resource allocation method of method, it is characterised in that: the expression formula of the control variable inequality are as follows:
Pt.min≤Pt≤Pt.max,
θmin≤θ≤θmax,
Wherein, PtFor base station transmitting power, Pt.max, Pt.minFor the bound of base station transmitting power；θ is antenna for base station angle of declination,
θc.min, θc.maxFor the bound of antenna for base station angle of declination, control variables constraint problem is handled using weighting method.
7. a kind of being optimized under single cell multi-user communication network scenarios based on quantum flora according to claim 1 is calculated
The resource allocation method of method, it is characterised in that: the quantum flora optimization algorithm in the S3 includes:
S31, parameter setting and initialization of population:
Parameter setting: consider a single cell multi-user system.Assuming that only having 1 cell in system, then needing small to this
The two parameters of the transmission power and Downtilt in area optimize, therefore dimension is 2, in population Q (t), chromosome
Length is len, and initialization population number is n, and chemotactic number is Nc, breeds times N re, disperses times N ed, migrate probability P ed；
The initialization of population: initialization population For j-th of Escherichia coli in t generation, chromosomeIt is defined as follows:
2n*len probability amplitude of whole n chromosomes is initialized toSo in 1st generation, all chromosomes are equal
With identical probabilityAmong linear combination state in all possible states, i.e.,
Wherein skIt is by binary string (x1x2...xlen) description k-th of state, xi=0,1, i=1,2 ..., len.So,
The population of initialization
S32, by observing and measuring Q (t0) state generate binary system disaggregation p (t0)=(x1, x2... xn), each solutionIt is the binary string that the length being made of 0 and 1 is len, value is 0 or 1 will be by corresponding quantum bit
Observation probabilityOrIt determines；
S33, assessment P (t0) fitness function value, with function fitness (x, y) be fitness function assessed；
S34, record P (t0) in the target of optimal fitness function value and corresponding optimized individual as next step population recruitment；
S35, chemotactic operation is carried out to the population in the present age, is realized using Quantum rotating gate appropriate, the Quantum rotating gate of use
Are as follows:
More new strategy (the α ' of quantum statei β′i)=U (θi)·(αi βi), i.e.,
Wherein,It is i-th bit quantum bit in chromosome, θiIt is quantum rotation door rotation angle, size, direction can pass through phase
The data answered checks in；
After Escherichia coli population Q (t) update, assesses P (t), record the fitness optimal value in the generation, if being better than the previous generation,
The generation is saved, previous generation's optimal value is otherwise still retained；
S36, reach N when chemotactic numbercWhen, chemotactic operation is completed, and optimal adaptation angle value is solved, and optimal adaptation angle value is poor
One hemichromosome eliminates, and carries out duplication operation to a preferable hemichromosome, chromosome number remains unchanged；
S37, when number of copy times be less than Nre, step 6 is continued to execute, otherwise chromosome each in population once disperse and be sentenced
It is disconnected, the decision content between 0-1 is generated, if it is determined that value, which is less than, disperses probability Ped, then execute bacterium and disperse, regenerate one by one
Body；
S38, when reaching convergence or reaching maximum setting algebra, stop chromosome and update, export current optimum individual, algorithm knot
Otherwise beam continues.
8. a kind of being optimized under single cell multi-user communication network scenarios based on quantum flora according to claim 6 is calculated
The resource allocation method of method, it is characterised in that: in the S3:
S31, in population Q (t), chromosome length len=32, initialization population number be n=40, chemotactic number be Nc=
50, times N re=5 is bred, times N ed=2 is dispersed, migrates probability P ed=0.25；
S33, assessment P (t0) fitness function value, fitness function is the number of above-mentioned optimization base station transmitting power and pitch angle
Learn model:
S35、θiTake 45 °.
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| CN111309779A (en) * | 2020-01-19 | 2020-06-19 | 北京互联无界科技有限公司 | Method and system for realizing beam parameter sample collection based on clustering technology |
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