CN105898852B - Energy efficiency optimization method in Bi-directional amplifier forward relay system - Google Patents
Energy efficiency optimization method in Bi-directional amplifier forward relay system Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/18—TPC being performed according to specific parameters
- H04W52/26—TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service]
- H04W52/267—TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service] taking into account the information rate
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/38—TPC being performed in particular situations
- H04W52/46—TPC being performed in particular situations in multi hop networks, e.g. wireless relay networks
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Abstract
The invention discloses the energy efficiency optimization method in a kind of Bi-directional amplifier forward relay system, mainly solve the problems, such as that existing power distribution method energy efficiency is lower.Its technical solution includes: obtain two user equipmenies in Bi-directional amplifier forward relay system and rate；It is proposed the initial optimization model that target is turned to energy efficiency maximum；According to the amplification factor of relaying, initial optimization model is rewritten as double optimization model；Double optimization problem is split as two sub- Optimized models again, and obtains the optimal solution of the two sub- Optimized models；Finally, obtaining the optimum power value of two user equipmenies and relaying according to the optimal solution of sub- Optimized model and in conjunction with iterative algorithm.The perfect existing optimized for energy efficiency model of the present invention, and energy efficiency optimization method computation complexity is low, realizes simple, can be used for the data transmission of Bi-directional amplifier forward relay system.
Description
Technical field
The invention belongs to mobile communication system technical field more particularly to a kind of energy efficiency optimization method, can be used for double
To amplification forwarding relay system.
Background technique
With the development of mobile Internet, Internet of Things, the mobile data flow of rapid growth is connected with the equipment of magnanimity to be made
Energy consumption cost constantly rises, ecological environment worsening, green communications technology widely paid close attention to therefrom.As measurement
The index of green communications system energy consumption, energy efficiency become current research hotspot.In order to solve traditional relaying technique time slot
The low problem of waste, spectrum efficiency, bi-directional relaying technology are introduced into.In bidirectional relay system, during two terminal nodes pass through
After realizing information exchange, when relay node is handled the signal received using amplification forwarding agreement, two terminals are realized
The timeslot number of primary information interaction is reduced by 4 of traditional one-way junction technology to 2, has been obviously improved spectrum efficiency.
Most of research in terms of the optimized for energy efficiency of bidirectional relay system at present is not direct maximization energy
Amount efficiency, but from the energy efficiency of the indirect lifting system of other angles.The scholars such as M.Askari are in " IEEE
Asilomar Conference on Signals, Systems and Computers, the article that 2015:968-972 " is delivered
" Sum-rate maximization for asynchronous two-way relay networks " for it is asynchronous it is two-way in
After system, under the constraint condition of total consumed power, maximized by optimizing the transmission power of each node system and rate.
The scholars such as Ben Yahia E are in " IEEE Wireless Communications and Mobile Computing
Article " the Energy-efficient AF OSTBC-MIMO systems that Conference, 2015:1056-1061 " are delivered
For two-way relaying considering circuit energy consumption " is then for bi-directional relaying
System has carried out the research for minimizing power consumption by fixing the transmission rate of two source nodes.This two articles are not
Direct maximum energy efficiency is maximized using the ratio of overall system capacity and total power consumption as optimization aim.
In order to meet the needs of different user is different to transmission rate, different applications is realized, for transmission rate requirements
The considerations of be indispensable.Huang R etc. is in IEEE International Symposium on Wireless
Article " Energy efficient power on Personal Multimedia Communications, 2014:65-69
Allocation and beamforming in non-regenerative two-way MIMO relay networks " is mentioned
Gone out to make always to transmit under the conditions of meeting bidirectional relay system end-to-end minimum transmission rate efficiency it is optimal when power distribution side
Case, the program although it is contemplated that two-way link and transmission rate constraint transmitting scene, but not each section in consideration system
The maximum transmission power constraint of point, and in the transmission of actual signal, each user in system may be independent from each other, and
And the attainable maximum transmission power of institute is different, ignores this problem, it will seriously affect the efficiency of communication system.
Summary of the invention
It is an object of the invention in view of the above shortcomings of the prior art, propose in a kind of Bi-directional amplifier forward relay system
Energy efficiency optimization method guarantee the reliable link of communication link to improve the efficiency of communication system, realize green communications.
To achieve the above object, technical solution of the present invention includes the following:
(1) obtain two user equipmenies A, B in Bi-directional amplifier forward relay system and rate R (P):
(2) according to two user equipmenies A, B and rate R (P) and system general power Psum(P) energy of system is obtained
Efficiency etaEE(P)；According to the energy efficiency η of systemEE(P), building turns to the initial optimization model of target with energy efficiency maximum
P1:
(P1)
Wherein Psum(P)=(PA+PB+PR)/ε+PcFor the general power of system, PcPower, ε are consumed for circuit total in system
∈ (0,1] it is power amplifier efficiency, Rth,iIndicate minimum transmission rate of the user equipment i under unit bandwidth, PAT, PBT, PRTTable
Show two user equipmenies A, B and relays the respective transmission power threshold of R；
(3) according to the transmission power P of two user equipmenies A, B and relaying RA, PB, PRAnd the amplification factor G of relaying R, it will
Initial optimization model P1 is rewritten as double optimization model P2:
(P2)
Wherein β=G2, ηEE(PA,PB, β) expression independent variable be PA, PB, the system energy efficiency of β, RA(PA,PB, β) and it indicates
Independent variable is PA, PB, the rate of the first user equipment A of β, RB(PA,PB, β) expression independent variable be PA, PB, the second user of β sets
The rate of standby B, Psum(PA,PB, β) expression independent variable be PA, PB, the total system power consumption of β；
(4) double optimization model P2 is split as sub- Optimized model P3 and sub- Optimized model P4, i.e., first using β as definite value,
Optimize the first user equipment A and sends power PAWith the transmission power P of second user equipment BB, then by PA, PBAs definite value, optimization
Square β for relaying the amplification factor of R, obtains the first sub- sub- Optimized model of Optimized model P3 and second of the second Optimized model P2
P4:
(P3)
(P4)
Wherein, ηEE(PA,PB) expression independent variable be PA, PBSystem energy efficiency, RA(PA) expression independent variable be PA?
The rate of one user equipment A, RB(PB) expression independent variable be PBSecond user equipment B rate, Psum(PA,PB) indicate from change
Amount is PA, PBTotal system power consumption, ηEE(β) indicates that independent variable is the system energy efficiency of β, RA(β) indicates that independent variable is the of β
The rate of one user equipment A, RB(β) indicates that independent variable is the rate of the second user equipment B of β, Psum(β) indicates that independent variable is β
Total system power consumption, PR(β) indicates the transmission power for the relaying R that independent variable is β；
(5) the best transmission power of the first user equipment A in the first sub- Optimized model P3 is obtained respectivelyIt is used with second
The best transmission power of family equipment B
(5a) is according to RA(PA) and RB(PB) monotonic increase characteristic, by institute's Prescribed Properties of the first sub- Optimized model P3
It is equivalent to Pit≤Pi≤PiT, i ∈ { A, B }, wherein PitIt indicates according to Ri(Pi)=Rth,iThe P acquirediValue；
(5b) intends recessed characteristic according to the objective function of the first sub- Optimized model P3, introduces a parameter lambda, and the first son is excellent
Change model P3 and be equivalent to an optimization model, and the best of the first user equipment A is gone out by Dinkelbach algorithm search
Transmission powerWith the best transmission power of second user equipment B
(6) obtain the second sub- Optimized model P4 in relaying R amplification factor square optimum value β*:
(6a) is according to RA(β), RB(β) and PRThe characteristic of (β) monotonic increase, by the second sub- Optimized model P4 it is all about
Beam condition equivalence is βmin≤β≤βmax, wherein βmin=max { βAmin,βBmin, βAminIt indicates according to RA(β)=Rth,AThe β acquired
Value, βBminIt indicates according to RB(β)=Rth,BThe value of the β acquired, βmaxIt indicates according to PR(β)=PRTThe value of the β acquired:
(6b) is according to the objective function η of the second sub- Optimized model P4EE(β's) intends recessed characteristic, ηEE(β) is in value range βmin
≤β≤βmaxInterior property can be divided into monotonic increase, monotone decreasing, three kinds of situations of monotone decreasing after first monotonic increase, for every
A kind of situation can acquire the optimum value β of the amplification factor square of relaying R*；
(7) it by the method for iteration and the solving result of combination step (5) and (6), searches out the first user in system and sets
The best transmission power value of standby AThe best transmission power value of second user equipment BAnd the best transmission power of relaying R
Value
Compared with the prior art, the present invention has the following advantages:
First, definition mode of the present invention using the ratio of overall system capacity and total power consumption as energy efficiency, rather than
It regard one of overall system capacity and total power consumption as definite value, goes to optimize another, therefore optimization aim of the invention more meets
Actual communication environment；
Second, the present invention ensure that the minimum transmission rate of each user equipment while optimizing energy efficiency, and examine
Each user equipment is considered and the maximum of relaying sends power constraint.
Third, efficiency optimization method proposed by the invention, the optimal solution obtained with exhaust algorithm is very close, and
The complexity of this efficiency optimization method reduces much compared with exhaust algorithm, is very suitable to application in practice.
Detailed description of the invention
Fig. 1 is the Bi-directional amplifier forward relay system model figure that the present invention uses；
Fig. 2 is implementation flow chart of the invention；
Fig. 3 is the system energy efficiency η that the independent variable in the present invention is βEEThe curve shape of the first of (β)；
Fig. 4 is the system energy efficiency η that the independent variable in the present invention is βEESecond of the curve shape of (β)；
Fig. 5 is the system energy efficiency η that the independent variable in the present invention is βEEThe third the curve shape of (β)；
Fig. 6 is the system optimal energy efficiency comparison diagram obtained using the present invention and existing exhaust algorithm.
Fig. 7 is the time complexity comparison diagram using the present invention and existing exhaust algorithm.
Specific embodiment
A specific embodiment of the invention and effect are further described with reference to the accompanying drawing.
Referring to Fig.1, the Bi-directional amplifier forward relay system model that the present invention uses includes that R and two user of a relaying sets
It is standby, i.e. the first user equipment A and second user equipment B.First user equipment A and second user equipment B are respectively mounted more antennas,
Antenna number is NA, relaying R installs single antenna, and all works under half-duplex mode.Due to two user equipmenies A, B in system
Between there are serious shadow fadings so that straight chain channel between the two can not be communicated, therefore they can only utilize relaying R
Carry out information exchange, wherein relaying R uses amplification forwarding agreement.
In the system shown in figure 1, it is assumed that the first user equipment A and relaying R between channel and second user equipment B with
Channel between relaying R all obeys Nakagami-m decline, and path loss index is all α, between user equipment i and relaying R
Distance be di, channel fading parameters mi, channel vector hiR, and | | hiR||2~G (ΩiR/mi,NAmi), whereinI ∈ { A, B }, | | | |2Two norm operations are asked in expression, and the white Gaussian noise power in system at all nodes is equal
For σ2。
Transmission rate QoS guarantee is provided using the Bi-directional amplifier forward relay system and maximum transmission power guarantees, for A
Data flow and B → R → direction A data flow in the direction → R → B, the minimum transmission rate that system guarantees is respectively Rth,BWith
Rth,A, for the first user equipment A, second user equipment B and relaying R, the maximum transmission power that system guarantees is respectively PAT,
PBT, PRT。
Referring to the method that Fig. 2, the present invention carry out optimized for energy efficiency according to the Bi-directional amplifier forward relay system of Fig. 1, packet
Include following steps:
Step 1, obtain two user equipmenies A, B in Bi-directional amplifier forward relay system and rate R (P).
(1a) calculates separately the rate R of the first user equipment AA(P) and the rate R of second user equipment BB(P):
WhereinIndicate the signal-to-noise ratio of the first user equipment A,
Indicate the signal-to-noise ratio of second user equipment B,
P=[PA,PB,PR] it is to send vector power；
The rate of first user equipment A is added by (1b) with the rate of second user equipment B, both obtaining and fast
Rate:
R (P)=RA(P)+RB(P)。
Step 2, the energy efficiency η of Bi-directional amplifier forward relay system is calculatedEE(P), and with energy efficiency maximum mesh is turned to
Mark building initial optimization model P1.
(2a) according to the first user equipment A and second user equipment B and rate R (P), the energy efficiency η of computing systemEE
(P)=R (P)/Psum(P), wherein Psum(P)=(PA+PB+PR)/ε+PcThe general power of expression system, PcFor the way circuit function of system
Rate, and ε ∈ (0,1] it is power amplifier efficiency；
(2b) is according to the energy efficiency η of systemEE(P), building turns to the initial optimization model of target with energy efficiency maximum
P1:
(P1)
Step 3, according to the transmission power P of two user equipmenies A, B and relaying RA, PB, PRAnd the amplification factor of relaying R
Initial optimization model P1 is rewritten as double optimization model P2 by G.
(3a) is according to the amplification factor for relaying RObtain the transmission of relaying R
Power PR, the transmission power P of the first user equipment AAWith the transmission power P of second user equipment BBBetween relationship: PR=β (PA|
|hAR||2+PB||hBR||2+σ2), wherein β=G2。
(3b) uses the transmission power P of the first user equipment AA, the transmission power P of second user equipment BBWith putting for relaying R
Big factor G replaces the transmission power P of relaying RR, initial excellent model P1 is rewritten as double optimization model P2:
(P2)
Wherein, ηEE(PA,PB, β) expression independent variable be PA, PB, the system energy efficiency of β；
Expression independent variable is PA, PB, the first user equipment A's of β
Rate, wherein γA(PA,PB, β) and=PAβ||hAR||2||hBR||2/(σ2(1+β||hBR||2))；
Expression independent variable is PA, PB, the second user equipment B's of β
Rate, wherein γB(PA,PB, β) and=PBβ||hAR||2||hBR||2/(σ2(1+β||hAR||2))；
Psum(PA,PB, β) and=(PA+PB+β(PA||hAR||2+PB||hBR||2+σ2))/ε+PcExpression independent variable is PA, PB, β
Total system power consumption.
Step 4, double optimization model P2 is split as the first sub- sub- Optimized model P4 of Optimized model P3 and second.
The independent variable of double optimization model P2 is grouped, first group of transmission power P for the first user equipment AAWith
The transmission power P of second user equipment BB, second group is square β for relaying the amplification factor of R, and splitting step is as follows:
(4a) assumes that β is definite value, optimizes the transmission power P of the first user equipment AAWith the transmission function of second user equipment B
Rate PB, obtain the first sub- Optimized model P3 of double optimization model P2:
(P3)
Wherein, ηEE(PA,PB) expression independent variable be PA, PBSystem energy efficiency；
Expression independent variable is PAThe first user equipment A rate, wherein γA
(PA)=PAβ||hAR||2||hBR||2/(σ2(1+β||hBR||2))；
Expression independent variable is PBSecond user equipment B rate, wherein γB
(PB)=PBβ||hAR||2||hBR||2/(σ2(1+β||hAR||2))；
Psum(PA,PB)=(PA+PB+β(PA||hAR||2+PB||hBR||2+σ2))/ε+PcExpression independent variable is PA, PBBe
System total power consumption.
(4a) assumes PA, PBFor definite value, square β of the amplification factor of optimization relaying R obtains the of double optimization model P2
Two sub- Optimized model P4:
(P4)
Wherein, ηEE(β) indicates that independent variable is the system energy efficiency of β；
Indicate that independent variable is the rate of the first user equipment A of β, wherein γA(β)
=PAβ||hAR||2||hBR||2/(σ2(1+β||hBR||2))；
Indicate that independent variable is the rate of the second user equipment B of β, wherein γB(β)
=PBβ||hAR||2||hBR||2/(σ2(1+β||hAR||2))；
Psum(β)=(PA+PB+β(PA||hAR||2+PB||hBR||2+σ2))/ε+PcIndicate that independent variable is the system total work of β
Consumption；
PR(β)=β (PA||hAR||2+PB||hBR||2+σ2) indicate the transmission power for relaying R that independent variable is β.
Step 5, the best transmission power of the first user equipment A in the first sub- Optimized model P3 is obtainedIt is used with second
The best transmission power of family equipment B
(5a) is by being P to independent variableAThe first user equipment A rate RA(PA) and independent variable be PBSecond user
The rate R of equipment BB(PB) derivation is carried out respectively, judge RA(PA) and RB(PB) monotonicity:
Due to derivation the result is that:
Therefore RA(PA) and RB(PB) it is all monotonic increase；
(5b) is according to RA(PA) monotonic increase characteristic, by the constraint condition R of the first sub- Optimized model P3A(PA)≥Rth,ADeng
Valence is PA≥PAt, wherein PAtIt indicates according to RA(PA)=Rth,AThe P acquiredAValue；
(5c) is according to RB(PB) monotonic increase characteristic, by the constraint condition R of the first sub- Optimized model P3B(PB)≥Rth,BDeng
Valence is PB≥PBt, wherein PBtIt indicates according to RB(PB)=Rth,BThe P acquiredBValue；
Institute's Prescribed Properties of first sub- Optimized model P3 are equivalent to P by (5d)it≤Pi≤PiT,i∈{A,B}；
(5e) introduces a parameter lambda, and the first sub- Optimized model P3 is equivalent to an optimization model P5:
(P5)
The solution of optimization model P5 is the solution of the first sub- Optimized model P3, and the value of corresponding λ is the first son optimization
The optimal energy efficiency of model P3；
(5f) intends recessed characteristic according to the objective function of the first sub- Optimized model P3, is searched by using Dinkelbach algorithm
Rope goes out the best transmission power of the first user equipment AWith the best transmission power of second user equipment B
The value that (5f1) initializes λ is λ0, make R (PA,PB)-λ0Psum(PA,PBWherein R (the P of) >=0A,PB)=RA(PA)+RB
(PB), and it is Λ > 0, iteration count n=0 that precision, which is arranged,；
(5f2) enables λ=λn, it is updated in following two formula, obtainsWithValue:
(5f3) will be above-mentionedWithIt is brought into λn+1=R (PA,PB)/Psum(PA,PB) in, obtain λn+1Value；
(5f4) is by R (PA,PB)、λnPsum(PA,PB) difference be compared with precision Λ:
If | R (PA,PB)-λnPsum(PA,PB) | > Λ then enables n=n+1, return step (5f2)；
If | R (PA,PB)-λnPsum(PA,PB) | then the first user equipment A in the first sub- Optimized model P3 is most by≤Λ
Good transmission power valueThe best transmission power value of second user equipment B
Step 6, obtain the second sub- Optimized model P4 in relaying R amplification factor square optimum value β*。
(6a) passes through the rate R to the first user equipment A that independent variable is βA(β), independent variable are the second user equipment of β
The rate R of BBThe transmission power P for the relaying R that (β) and independent variable are βR(β) carries out derivation respectively, judges RA(β), RB(β) and PR
The monotonicity of (β):
It is all larger than 0 according to following derivation result, can determine whether out RA(β), RB(β) and PR(β) is all monotonic increase:
(6b) is according to RAThe characteristic of (β) monotonic increase, by the constraint condition R of the second sub- Optimized model P4A(β)≥Rth,ADeng
Valence is β >=βAmin, βAminIt indicates according to RA(β)=Rth,AThe value of the β acquired；
(6c) is according to RBThe characteristic of (β) monotonic increase, by the constraint condition R of the second sub- Optimized model P4B(β)≥Rth,BDeng
Valence is β >=βBmin, βBminIt indicates according to RB(β)=Rth,BThe value of the β acquired；
(6d) is according to RBThe characteristic of (β) monotonic increase, by 0≤P of constraint condition of the second sub- Optimized model P4R(β)≤PRT
It is equivalent to 0≤β≤βmax, βmaxIt indicates according to PR(β)=PRTThe value of the β acquired；
Institute's Prescribed Properties of second sub- Optimized model P4 are equivalent to β by (6e)min≤β≤βmax, wherein βmin=max
{βAmin,βBmin}；
(6c) is according to the objective function η of the second sub- Optimized model P4EE(β's) intends recessed characteristic, can be by ηEE(β) is in value
Range betamin≤β≤βmaxInterior curve shape is divided into following three kinds of situations:
IfThen ηEEThe curve shape of (β) is as shown in figure 3, as seen from Figure 3, ηEE(β) exists
βmin≤β≤βmaxOn be monotonic increase, relaying R amplification factor square optimum value β*=βmax；
IfThen ηEEThe curve shape of (β) is as shown in figure 4, from fig. 4, it can be seen that ηEE(β) exists
βmin≤β≤βmaxOn be monotone decreasing, relaying R amplification factor square optimum value β*=βmax；
IfAndThen ηEEThe curve shape of (β) such as Fig. 5 institute
Show, as seen from Figure 5, ηEE(β) is in βmin≤β≤βmaxOn be monotone decreasing after first monotonic increase, relay R amplification factor square
Optimum value β*It can be obtained by using dichotomizing search.
Step 7, by the solving result of the method for iteration and combination step 5 and step 6, the first user in system is searched out
The best transmission power value of equipment AThe best transmission power value of second user equipment BAnd the best transmission function of relaying R
Rate value
This step is implemented as follows:
Precision Δ > 0 is arranged in (7a), this example sets Δ=0.01, initializes the transmission power value of the first user equipment A
The transmission power value of second user equipment BAnd the transmission power value of relaying R
(7b) will be above-mentionedWithIt is brought into Optimized model P1, obtains the system energy efficiency of the l times iteration
(7c) is according to above-mentionedWithCalculate the square value of the relaying R amplification factor of the l times iteration:Wherein, hARIt indicates the first user equipment A and relays the channel vector between R,
hARIt indicates second user equipment B and relays the channel vector between R, | | | |2Two norm operations are asked in expression；
(7d) is by above-mentioned βlIt is updated in the first sub- Optimized model P3, and obtains the of the l+1 times iteration in conjunction with step (5)
The best transmission power value of one user equipment AWith the best transmission power value of second user equipment B
(7d) will be above-mentionedIt is updated in the second sub- Optimized model P4, and is obtained the l+1 times in conjunction with step (6)
The optimum value β of the relaying R amplification factor square of iterationl+1；
(7e) is according to above-mentionedAnd βl+1Calculate the transmission power of the relaying R of the l+1 times iteration:
(7f) willIt is brought into Optimized model P1, obtains the system energy efficiency of the l+1 times iteration
(7g) willDifference be compared with precision Δ: ifL=l+1 is then enabled, is returned
It returns step (7d)；IfThe then best transmission power value of the first user equipment A in Optimized model P1The best transmission power value of second user equipment BRelay the best transmission power value of R
The optimal energy efficiency of system is
So far, it completes to the optimized for energy efficiency in Bi-directional amplifier forward relay system.
Effect of the invention can be described further by following emulation:
1) simulated conditions:
First user equipment A, second user equipment B are located on the same line with relaying R, by the first user equipment A and
The distance between second user equipment B is normalized to 1, i.e. dA+dB=1, wherein dAIt indicates between the first user equipment A and relaying R
Distance, dBAt a distance from indicating second user equipment B between relaying R.
Assuming that the path loss index of channel is 3, then
If the channel fading parameters m between the first user equipment A and relaying R1=0.5, the first user equipment B and relaying R
Between channel fading parameters m2=0.5, system bandwidth W=1Hz, power amplifier efficiency ε=0.38, B → R → direction A are most
Low transmission rate Rth,AThe minimum transmission rate in=0.5bit/s, A → R → direction B is set as Rth,B=0.5bit/s.
Two user equipment A and B and the maximum transmission power for relaying R are PAT=PBT=PRT=33dBm, circuit power
Pc=1W, noise power σ2=1, the transmitting antenna number N of user equipment A and BA=8.
2) emulation content and result:
Emulation 1, under above-mentioned simulated conditions, using method of the invention and existing exhaust algorithm, puts to two-way respectively
The best efficiency of normalization of big forward relay system carries out emulation comparison, as a result as shown in Figure 6.Abscissa is the first use in Fig. 6
Family equipment A distance d between relaying RA, ordinate is the best efficiency of normalization of system.
Emulation 2, it is double to solving respectively using method of the invention and existing exhaust algorithm under above-mentioned simulated conditions
Emulation comparison is carried out to the time complexity of the best efficiency of normalization of amplification forwarding relay system, as a result as shown in Figure 7.Fig. 7
Middle abscissa is the ratio N of transmission power siding-to-siding block length and search precision, and ordinate is the function of time complexity.
It the best efficiency that is obtained it can be seen from Fig. 6 and Fig. 7 using the method for the present invention and is obtained most by exhaust algorithm
Canon's effect is very close, and the time complexity of the method for the present invention is far below the time complexity of exhaust algorithm, this illustrates this
Inventive method can obtain the optimal energy efficiency of Bi-directional amplifier forward relay system in the form of low complex degree, in practical communication
There is very strong practicability in scene.
Claims (10)
1. the energy efficiency optimization method in Bi-directional amplifier forward relay system, comprising:
(1) obtain two user equipmenies A, B in Bi-directional amplifier forward relay system and rate R (P)；
(2) according to two user equipmenies A, B and rate R (P) and system general power Psum(P) energy efficiency of system is obtained:
ηEE(P)=R (P)/Psum(P)；According to the energy efficiency η of systemEE(P), building turns to the initial of target with energy efficiency maximum
Optimized model P1:
(P1)
Wherein P=[PA,PB,PR] it is to send vector power, RA(P) rate for being the first user equipment A, RBIt (P) is second user
The rate of equipment B, Psum(P)=(PA+PB+PR)/ε+PcFor the general power of system, PcPower, ε are consumed for circuit total in system
∈ (0,1] it is power amplifier efficiency, Rth,iIndicate minimum transmission rate of the user equipment i under unit bandwidth, PAT, PBT, PRTTable
Show two user equipmenies A, B and relays the respective transmission power threshold of R；
(3) according to the transmission power P of two user equipmenies A, B and relaying RA, PB, PRAnd the amplification factor G of relaying R, it will be initial
Optimized model P1 is rewritten as double optimization model P2:
(P2)
Wherein β=G2, ηEE(PA,PB, β) expression independent variable be PA, PB, the system energy efficiency of β, RA(PA,PB, β) and indicate independent variable
For PA, PB, the rate of the first user equipment A of β, RB(PA,PB, β) expression independent variable be PA, PB, the second user equipment B's of β
Rate, Psum(PA,PB, β) expression independent variable be PA, PB, the total system power consumption of β；
(4) double optimization model P2 is split as sub- Optimized model P3 and sub- Optimized model P4, i.e., first using β as definite value, optimization
First user equipment A sends power PAWith the transmission power P of second user equipment BB, then by PA, PBAs definite value, optimization relaying R
Amplification factor square β, obtain the first sub- sub- Optimized model P4 of Optimized model P3 and second of the second Optimized model P2:
(P3)
(P4)
Wherein, ηEE(PA,PB) expression independent variable be PA, PBSystem energy efficiency, RA(PA) expression independent variable be PAFirst use
The rate of family equipment A, RB(PB) expression independent variable be PBSecond user equipment B rate, Psum(PA,PB) indicate that independent variable is
PA, PBTotal system power consumption, ηEE(β) indicates that independent variable is the system energy efficiency of β, RA(β) indicates that independent variable is β first uses
The rate of family equipment A, RB(β) indicates that independent variable is the rate of the second user equipment B of β, Psum(β) indicates that independent variable is for β
System total power consumption, PR(β) indicates the transmission power for the relaying R that independent variable is β；
(5) the best transmission power of the first user equipment A in the first sub- Optimized model P3 is obtained respectivelyIt is set with second user
The best transmission power of standby B
(5a) is according to RA(PA) and RB(PB) monotonic increase characteristic, institute's Prescribed Properties of the first sub- Optimized model P3 are equivalent to
Pit≤Pi≤PiT, i ∈ { A, B }, wherein PitIt indicates according to Ri(Pi)=Rth, P that i is acquirediValue；
(5b) intends recessed characteristic according to the objective function of the first sub- Optimized model P3, introduces a parameter lambda, and the first son is optimized mould
Type P3 is equivalent to an optimization model P5:
(P5)
Wherein R (PA,PB)=RA(PA)+RB(PB), the solution of optimization model P5 is the solution of the first sub- Optimized model P3, corresponding
λ value be the first sub- Optimized model P3 optimal energy efficiency；And the first user is gone out by Dinkelbach algorithm search
The best transmission power of equipment AWith the best transmission power of second user equipment B
(6) obtain the second sub- Optimized model P4 in relaying R amplification factor square optimum value β*:
(6a) is according to RA(β), RB(β) and PRThe characteristic of (β) monotonic increase, by all constraint items of the second sub- Optimized model P4
Part is equivalent to βmin≤β≤βmax, wherein βmin=max { βAmin,βBmin, βAminIt indicates according to RA(β)=Rth,AThe value of the β acquired,
βBminIt indicates according to RB(β)=Rth,BThe value of the β acquired, βmaxIt indicates according to PR(β)=PRTThe value of the β acquired:
(6b) is according to the objective function η of the second sub- Optimized model P4EE(β's) intends recessed characteristic, ηEE(β) is in value range βmin≤β≤
βmaxInterior property can be divided into monotonic increase, monotone decreasing, three kinds of situations of monotone decreasing after first monotonic increase, for each
Situation can acquire the optimum value β of the amplification factor square of relaying R*；
(7) by the method for iteration and the solving result of combination step (5) and (6), the first user equipment A in system is searched out
Best transmission power valueThe best transmission power value of second user equipment BAnd the best transmission power value of relaying R
2. according to the method described in claim 1, wherein two in acquisition Bi-directional amplifier forward relay system described in step (1)
User equipment A, B and rate R (P) is carried out as follows:
(1a) calculates separately the rate R of the first user equipment AA(P) and the rate R of second user equipment BB(P):
(1b) calculate first user equipment A and second user equipment B's and rate:
R (P)=RA(P)+RB(P),
Wherein, P=[PA,PB,PR] it is to send vector power, PA、PBAnd PRIt respectively indicates user equipment A, B and relays the transmission of R
Power.
3. according to the method described in claim 2, wherein in step (1a) the first user equipment A rate RA(P) and second user
The rate R of equipment BB(P), it is calculated according to following formula:
WhereinIndicate the first user equipment A received signal to noise ratio；
Indicate the received signal to noise ratio of second user equipment B；
Wherein, hARIndicate channel vector of the first user equipment A to relaying R, hBRIndicate the letter of second user equipment B to relaying R
Road vector, | | | |2Two norm operations, σ are asked in expression2For the additive white Gaussian noise function at user equipment A and B and relaying R
Rate.
4. according to the method described in claim 1, wherein the relaying R amplification factor G in step (3), expression are as follows:
Wherein hARIndicate channel vector of the first user equipment A to relaying R, hBRIndicate the channel of second user equipment B to relaying R
Vector, | | | |2Two norm operations, σ are asked in expression2For the additive white Gaussian noise power at user equipment A and B and relaying R.
5. according to the method described in claim 1, wherein the first user equipment involved in double optimization model P2 in step (3)
The rate R of AA(PA,PB, β), the rate R of second user equipment BB(PA,PB, β), total system power consumption Psum(PA,PB, β), difference table
Show as follows:
Psum(PA,PB, β) and=(PA+PB+β(PA||hAR||2+PB||hBR||2+σ2))/ε+Pc
Wherein, γA(PA,PB, β) and=PAβ||hAR||2||hBR||2/(σ2(1+β||hBR||2))
γB(PA,PB, β) and=PBβ||hAR||2||hBR||2/(σ2(1+β||hAR||2)),
Wherein hARIndicate channel vector of the first user equipment A to relaying R, hBRIndicate the channel of second user equipment B to relaying R
Vector, | | | |2Two norm operations, σ are asked in expression2For the additive white Gaussian noise power at user equipment A and B and relaying R.
6. according to the method described in claim 1, wherein the first user involved in the first sub- Optimized model P3 sets in step (4)
The rate R of standby AA(PA), the rate R of second user equipment BB(PB), total system power consumption Psum(PA,PB), it respectively indicates as follows:
Psum(PA,PB)=(PA+PB+β(PA||hAR||2+PB||hBR||2+σ2))/ε+Pc,
Wherein, γA(PA)=PAβ||hAR||2||hBR||2/(σ2(1+β||hBR||2)),
γB(PB)=PBβ||hAR||2||hBR||2/(σ2(1+β||hAR||2)),
Wherein hARIndicate channel vector of the first user equipment A to relaying R, hBRIndicate the channel of second user equipment B to relaying R
Vector, | | | |2Two norm operations, σ are asked in expression2For the additive white Gaussian noise power at user equipment A and B and relaying R.
7. according to the method described in claim 1, wherein the first user involved in the second sub- Optimized model P4 sets in step (4)
The rate R of standby AA(β), the rate R of second user equipment BB(β), total system power consumption Psum(β) relays the transmission power P of RR(β),
It respectively indicates as follows:
Psum(β)=(PA+PB+β(PA||hAR||2+PB||hBR||2+σ2))/ε+Pc,
PR(β)=β (PA||hAR||2+PB||hBR||2+σ2),
Wherein, γA(β)=PAβ||hAR||2||hBR||2/(σ2(1+β||hBR||2)),
γB(β)=PBβ||hAR||2||hBR||2/(σ2(1+β||hAR||2)),
Wherein hARIndicate channel vector of the first user equipment A to relaying R, hBRIndicate the channel of second user equipment B to relaying R
Vector, | | | |2Two norm operations, σ are asked in expression2For the additive white Gaussian noise power at user equipment A and B and relaying R.
8. according to the method described in claim 1, wherein going out the first user by Dinkelbach algorithm search in step (5b)
The best transmission power of equipment AWith the best transmission power of second user equipment BIt carries out as follows:
The value that (5b1) initializes λ is λ0, make R (PA,PB)-λ0Psum(PA,PB) >=0, wherein R (PA,PB)=RA(PA)+RB(PB),
And it is Λ > 0, iteration count n=0 that precision, which is arranged,；
(5b2) enables λ=λn, it is updated in following two formula, obtainsWithValue:
Wherein, Psum(PA,PB)=(PA+PB+β(PA||hAR||2+PB||hBR||2+σ2))/ε+Pc；hARIndicate the first user equipment A
To the channel vector of relaying R, hBRIndicate the channel vector of second user equipment B to relaying R, | | | |2Expression asks two norms to transport
It calculates, σ2For the additive white Gaussian noise power at user equipment A and B and relaying R；
(5b3) will be above-mentionedWithIt is brought into λn+1=R (PA,PB)/Psum(PA,PB) in, obtain λn+1Value；
(5b4) is by R (PA,PB)、λnPsum(PA,PB) difference be compared with precision Λ:
If | R (PA,PB)-λnPsum(PA,PB) | > Λ then enables n=n+1, return step (5b2)；
If | R (PA,PB)-λnPsum(PA,PB) |≤Λ, the then best hair of the first user equipment A in the first sub- Optimized model P3
Send performance numberThe best transmission power value of second user equipment B
9. according to the method described in claim 1, wherein in β in step (6b)min≤β≤βmaxInterior solution monotone decreasing, it is first single
Adjust the optimum value β for relaying the amplification factor square of R after being incremented by the case of three kinds of monotone decreasing*, it carries out according to the following rules:
IfThen ηEE(β) is in βmin≤β≤βmaxOn be monotonic increase, β*=βmax；
IfThen ηEE(β) is in βmin≤β≤βmaxOn be monotone decreasing, β*=βmin；
IfAndThen ηEE(β) is in βmin≤β≤βmaxOn be first dullness
Monotone decreasing, β after being incremented by*It is obtained by using dichotomizing search.
10. according to the method described in claim 1, wherein the step (7) carries out as follows:
Precision Δ > 0, iteration count l=0 is arranged in (7a), initializes the transmission power value of the first user equipment ASecond user
The transmission power value of equipment BAnd the transmission power value of relaying R
(7b) will be above-mentionedWithIt is brought into Optimized model P1, obtains the system energy efficiency of the l times iteration
(7c) obtains the square value of the relaying R amplification factor of the l times iteration:
(7d) is by above-mentioned βlIt is updated in the first sub- Optimized model P3, and obtains the first of the l+1 times iteration in conjunction with step (5) and use
The best transmission power value of family equipment AWith the best transmission power value of second user equipment B
(7d) will be above-mentionedIt is updated in the second sub- Optimized model P4, and obtains the l+1 times iteration in conjunction with step (6)
Relay the optimum value β of R amplification factor squarel+1；
(7e) obtains the transmission power of the relaying R of the l+1 times iteration:
Wherein hARIndicate channel vector of the first user equipment A to relaying R, hBRIndicate the channel of second user equipment B to relaying R
Vector, | | | |2Two norm operations, σ are asked in expression2For the additive white Gaussian noise power at user equipment A and B and relaying R；
(7f) willIt is brought into Optimized model P1, obtains the system energy efficiency of the l+1 times iteration
(7g) willDifference be compared with precision Δ: ifThen enable l=l+1, return step
(7d)；IfThe then best transmission power value of the first user equipment A in Optimized model P1
The best transmission power value of second user equipment BRelay the best transmission power value of RSystem it is optimal
Energy efficiency is
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