CN107172701A - A kind of power distribution method of non-orthogonal multiple access system - Google Patents
A kind of power distribution method of non-orthogonal multiple access system Download PDFInfo
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- CN107172701A CN107172701A CN201710156292.1A CN201710156292A CN107172701A CN 107172701 A CN107172701 A CN 107172701A CN 201710156292 A CN201710156292 A CN 201710156292A CN 107172701 A CN107172701 A CN 107172701A
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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
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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
-
- 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
- H04W52/30—TPC using constraints in the total amount of available transmission power
- H04W52/34—TPC management, i.e. sharing limited amount of power among users or channels or data types, e.g. cell loading
- H04W52/346—TPC management, i.e. sharing limited amount of power among users or channels or data types, e.g. cell loading distributing total power among users or channels
-
- 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
- H04W52/30—TPC using constraints in the total amount of available transmission power
- H04W52/36—TPC using constraints in the total amount of available transmission power with a discrete range or set of values, e.g. step size, ramping or offsets
- H04W52/367—Power values between minimum and maximum limits, e.g. dynamic range
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/04—Wireless resource allocation
- H04W72/044—Wireless resource allocation based on the type of the allocated resource
- H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/50—Allocation or scheduling criteria for wireless resources
- H04W72/53—Allocation or scheduling criteria for wireless resources based on regulatory allocation policies
Abstract
The present invention relates to a kind of power distribution method of non-orthogonal multiple access system, comprise the following steps：S1. the power allocation scheme that initialization iteration coefficient and one group meet constraints；S2. the channel equalization factor and slack variable of each user is calculated based on initial power allocative decision；S3. the power distribution of each user is optimized based on the value for calculating the gained channel equalization factor and slack variable；S4. the power distribution after each user optimization is integrated, obtains the power allocation scheme by optimization, then total utility of the computing system under the power scheme of optimization；S5. step S2 ~ S4 is repeated using the power allocation scheme by optimization until the convergence of system total utility, is exported the corresponding power allocation scheme by optimization as optimal allocative decision during convergence.
Description
Technical field
The present invention relates to wireless communication technology field, more particularly, to a kind of power of non-orthogonal multiple access system
Distribution method.
Background technology
With the fast development of mobile communication, frequency spectrum resource becomes more and more in short supply, in face of the mobile service being skyrocketed through
Demand, how to effectively improve the utilization rate of limited spectrum resources turns into the 5th generation (5G) GSM key urgently to be resolved hurrily
One of problem.Due to possessing the characteristics of effectively improving power system capacity, non-orthogonal multiple (Non-Orthogonal Multiple
Access, NOMA) technology is widely regarded as up-and-coming multiple access technology.NOMA basic thought is used in transmitting terminal
Power sharing technology is sent with non-orthogonal manner, actively introduces interference information, and serial interference elimination is passed through in receiving terminal
(Successive Interference Cancellation, SIC), receiver realizes correct demodulation, although receiver is answered
Miscellaneous degree is improved to some extent but can be very good to improve the availability of frequency spectrum.
In non-orthogonal multiple access system, allocation strategy of the power resource between multi-user be also research focus it
One.According to the decoding policy of receiving terminal serial interference elimination in non-orthogonal multiple technology, in order to reach system maximum throughput,
Transmitting terminal as far as possible can tilt power resource to strong user (i.e. the user nearer apart from transmitting terminal).Such case can pole
The earth damages the communication performance of weak user (i.e. apart from transmitting terminal user farther out), this list from the perspective of practical application
One strategy does not account for each user resources distributional equity of communication system.Therefore, it is necessary to take corresponding measure to avoid money
The utilization in source is insufficient while improving systematic function as far as possible.
The content of the invention
The problem to be solved in the present invention is：Proposition is a kind of to make system by optimizing reasonable distribution of the resource between multi-user
The power distribution method of the maximized non-orthogonal multiple access system of total utility.
The technical scheme that the present invention is proposed to achieve the above object is as follows：
A kind of power distribution method of non-orthogonal multiple access system, comprises the following steps：
S1. the power allocation scheme that initialization iteration coefficient and one group meet constraints；
S2. the channel equalization factor and slack variable of each user is calculated based on power allocation scheme；
S3. the channel equalization factor and the value of slack variable based on calculating is optimized to the power distribution of each user；
S4. the power distribution after each user optimization is integrated, obtains the power allocation scheme by optimization, so
Total utility of the computing system under the power scheme of optimization afterwards；
S5. step S2~S4 is repeated using the power allocation scheme by optimization until the convergence of system total utility, is received
The corresponding power allocation scheme by optimization is exported as optimal allocative decision when holding back.
Preferably, the detailed process for calculating the channel equalization factor is as follows：
Wherein
Wherein k represents iterations, hnRepresent base station to the channel response of nth user；PnExpression distributes to user n's
Transmission power；cnRepresent the channel equalization factor, enIt is defined as estimation signal snMean square error.
Preferably, the detailed process for calculating slack variable is as follows：
Preferably, the detailed process that the power distribution to each user is optimized is as follows：
Compared with prior art, the beneficial effects of the invention are as follows：
The present invention proposes a kind of power distribution method of non-orthogonal multiple access system, using the power distribution of proposition
Method, system can reach maximization of utility in the case where having fairness concurrently and improving as far as possible with speed.
Brief description of the drawings
The convergence process schematic diagram for the method that Fig. 1 provides for the present invention.
Fig. 2 is the variance responded for different channels, under different total transmit power constraints, the power based on the present invention
The comparison diagram of allocative decision and conventional uniform power allocation scheme on system total utility.
Fig. 3 is power allocation scheme and conventional uniform power point based on the present invention under different total transmit power constraints
Comparison diagram with scheme in system and speed.
The method flow diagram that Fig. 4 provides for the present invention.
Embodiment
Accompanying drawing being given for example only property explanation, it is impossible to be interpreted as the limitation to this patent；
In order to more preferably illustrate the present embodiment, some parts of accompanying drawing have omission, zoomed in or out, and do not represent actual production
The size of product；
To those skilled in the art, it is to be appreciated that some known features and its explanation, which may be omitted, in accompanying drawing
's.
Technical scheme is described further with reference to the accompanying drawings and examples.
Embodiment 1
The applicable model of communication system of the present invention is made up of a single-antenna base station and N number of single antenna reception user；Base station
Channel response to nth user is expressed as hn, whereinAssuming that base station end can be known completely
The channel condition information (Channel State Information, CSI) of road whole network system；Therefore, base station can be fitted
Locality distributes its transmission power to improve the communication performance of communication system；Without loss of generality, it is assumed that channel of the base station to each user
Response meets inequality | h1|≤|h2|≤…≤|hN|。
(NOMA) technical protocol is accessed according to non-orthogonal multiple, transmitting terminal uses supercomposed coding technology, therefore n-th of use
The reception signal at family is represented by：
Wherein pnRepresent that the transmit power of nth user is distributed in base station,Represent nth user end
Additive Gaussian noise.
Each user terminal is performed after serial interference elimination, can be by the decoding completely of the information of weak user and from interference signal
Remove, therefore the achievable rate expression formula at nth user end is：
In this non-orthogonal multiple wireless communication system, the plan of this smooth Frederick Colberg game is used between base station and multi-user
Slightly, base station (leader) is that the power for distributing to each user fixes a price for maximizing income, user (follower) determining according to base station
Valency determines that transmit power carrys out maximum utility.
Maximizing the optimization problem of base station (leader) income can be expressed as：
Maximizing the optimization problem of user (follower) effectiveness can be expressed as：
Wherein, Un=Rn-λnpn(λn),User n utility function is represented, the utility function is by receipts and expenditures
Two parts are constituted, and income part is provided by achievable rate, and expenditure part is obtained as the cost produced by power consumption.
Problem (3) and (4) constitute this smooth Frederick Colberg game, and (leader-followers games, base station is active person, and user terminal is driven
Person).
To solve leader-followers games problem, we are translated into common optimization problem with lemma 1 first, pass through convex optimization
Method the optimization problem is solved to find this smooth Frederick Colberg equilibrium point of former problem.
Lemma 1：Given unit priceWhen
When meeting condition, user n optimal transmit power meets equation
Prove：It can be obtained by the optimal solution of Solve problems (4)：
Explanation：WhenWhen, due to selling at exorbitant prices, user n will not participate in
Game；Now the communication system of N number of user will be changed into the communication system of (N-1) individual user；Therefore, we only consider that (5) formula is full
The situation of foot.
Thus, former problem can be redeveloped into：
WhereinProblem (8) is the optimization problem of object function non-convex, I
Handled by introducing slack variable.
Lemma 2：Order(a is arithmetic number), then have：
And the optimal solution on the right of equation is：A=21-b.；
Prove：F (a) is concave function, then optimal solution can be bySolution can be obtained.
User n perform serial interference elimination after reception signal be：
Definition estimation signal snMean square error (MSE) function：
Above formula can be obtained by unfolding calculation：
E can must be caused by convex optimization knowledgenObtain the optimal solution of minimum value
Taking back (12) formula then has：
As available from the above equation：
Then, using lemma 2 and (15), problem (8) is equivalently converted into mean square error minimization problem：
Wherein, anFor the slack variable of introducing.Work as anAnd CnWhen taking optimal solution, object function is
The object function of problem (16) is nonlinear, optimizes subproblems followed by being decoupled into three, and adopt
The channel equalization factor, slack variable and power distribution are solved with alternating iteration method.
It is exactly specifically that in kth step iteration, the optimal power value that (k-1) step iteration is tried to achieve is given firstKth time iteration preferred channels balance factor is now solved by solving following optimization problem：
The problem is convex problem and has closed solutions：
Obtain the optimal solution that kth walks iterationSubstitute into and solve following optimization problem to obtain slack variable anIn kth
Optimal value during secondary iteration：
The problem closed solutions can be obtained by lemma 2：
Wherein：
Obtain the optimal solution that kth walks iterationWithAfterwards, solving-optimizing problem is substituted into：
The problem is on variable pnA convex optimization problem, CVX tool boxes direct solution can be used.
From analysis above, problem (18) and (19) there are problems that enclosed optimal solution and (22) are convex problem, therefore
The target function value that each iteration is obtained is monotone nondecreasing；Because the total emission power of base station is constrained so that the value exists upper
Boundary, so the solution of the final iteration can converge to a stable solution.
On the basis of more than, the method that the present invention is provided includes below scheme：
Step 0：Systematic parameter is set；
Step 1：Iteration coefficient k=0 is initialized, one group of power distribution for meeting constraints is given
Step 2：Calculate the channel equalization factor and slack variable：
For n=1：N
Calculate
Calculate
Wherein
end for
Step 3：Solve power distribution problems：
Step 4：Computing system total utility, checks whether convergence, if convergence, terminates this process, current gained power distribution
As a result it is optimal power allocation scheme；Otherwise k=k+1 is set and is changed using power distribution result obtained by current iteration as next time
For initial value, step 2 is jumped to.
Embodiment 2
Effect of the present invention can be further illustrated by following the simulation experiment result, the basic procedure reference of emulation experiment
Fig. 4.
For Fig. 1, user's number N=3 in setting system.Base station is that average is 0, variance to the channel response of each user
RespectivelyIndependent same distribution multiple Gauss stochastic variable, and base station total transmission power is
P/σ2=20dB.
For Fig. 2 and Fig. 3, user's number N=2 in setting system.The channel variance of strong userWeak subscriber channel
Variance is respectively set toAnd
(6) simulation analysis and result
Under conditions of Fig. 1 is given transmit power, the convergence process figure of the iterative algorithm in the present invention.By simulation result
Figure can intuitively find out that the algorithm can converge to stable solution quickly.
Fig. 2 is the variance responded for different channels, under different total transmit power constraints, the power based on the present invention
The contrast of allocative decision and conventional uniform power allocation scheme on system total utility.As can be seen from Figure 2 in any power about
Under beam, the power allocation scheme based on the present invention is always better than conventional uniform power allocation scheme.
Fig. 3 is power allocation scheme and conventional uniform power point based on the present invention under different total transmit power constraints
Contrast with scheme in system and speed.As can be seen from Figure 3 based on the present invention power allocation scheme ensure system and
The fairness between strong and weak user has been taken into full account on the premise of rate capability.So being not difficult to find out, the power based on the present invention point
Performance with scheme is better than conventional uniform power allocation scheme scheme.
Obviously, the above embodiment of the present invention is only intended to clearly illustrate example of the present invention, and is not pair
The restriction of embodiments of the present invention.For those of ordinary skill in the field, may be used also on the basis of the above description
To make other changes in different forms.There is no necessity and possibility to exhaust all the enbodiments.It is all this
Any modifications, equivalent substitutions and improvements made within the spirit and principle of invention etc., should be included in the claims in the present invention
Protection domain within.
Claims (4)
1. a kind of power distribution method of non-orthogonal multiple access system, it is characterised in that：Comprise the following steps：
S1. the power allocation scheme that initialization iteration coefficient and one group meet constraints；
S2. the channel equalization factor and slack variable of each user is calculated based on initial power allocative decision；
S3. the power distribution of each user is optimized based on the value for calculating the gained channel equalization factor and slack variable；
S4. the power distribution after each user optimization is integrated, obtains the power allocation scheme by optimization, then calculate
Total utility of the system under the power scheme of optimization；
S5. step S2~S4 is repeated using the power allocation scheme by optimization until system total utility is restrained, during convergence
The corresponding power allocation scheme by optimization is exported as optimal allocative decision.
2. the power distribution method of non-orthogonal multiple access system according to claim 1, it is characterised in that：Calculate channel
The detailed process of balance factor is as follows：
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Wherein k represents iterations, hnRepresent base station to the channel response of nth user；PnUser n transmitting is distributed in expression
Power；cnRepresent the channel equalization factor, enIt is defined as estimation signal snMean square error.
3. the power distribution method of non-orthogonal multiple access system according to claim 2, it is characterised in that：Calculate relaxation
The detailed process of variable is as follows：
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4. the power distribution method of non-orthogonal multiple access system according to claim 3, it is characterised in that：Use each
The detailed process that the power distribution at family is optimized is as follows：
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| CN109005592A (en) * | 2018-08-03 | 2018-12-14 | 田心记 | Power distribution method in single antenna NOMA system |
| CN110149127A (en) * | 2019-06-19 | 2019-08-20 | 南京邮电大学 | A kind of D2D communication system precoding vector optimization method based on NOMA technology |
| CN110324888A (en) * | 2019-07-30 | 2019-10-11 | 山西大学 | Maximize the uplink user cluster-dividing method of NOMA sub-channel power distribution area of feasible solutions |
| CN110602777A (en) * | 2019-08-28 | 2019-12-20 | 华北电力大学（保定） | CR-NOMA bidirectional relay self-interference energy recovery transmission method |
| CN111194043A (en) * | 2020-03-17 | 2020-05-22 | 重庆邮电大学 | Power distribution method based on non-perfect serial interference elimination |
| CN111328144A (en) * | 2020-01-20 | 2020-06-23 | 赣江新区智慧物联研究院有限公司 | Wireless resource allocation method, device, readable storage medium and computer equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109005592A (en) * | 2018-08-03 | 2018-12-14 | 田心记 | Power distribution method in single antenna NOMA system |
| CN110149127A (en) * | 2019-06-19 | 2019-08-20 | 南京邮电大学 | A kind of D2D communication system precoding vector optimization method based on NOMA technology |
| CN110324888A (en) * | 2019-07-30 | 2019-10-11 | 山西大学 | Maximize the uplink user cluster-dividing method of NOMA sub-channel power distribution area of feasible solutions |
| CN110324888B (en) * | 2019-07-30 | 2021-03-30 | 山西大学 | Uplink user clustering method for maximizing feasible region of power distribution of NOMA (non-orthogonal multiple access) sub-channel |
| CN110602777A (en) * | 2019-08-28 | 2019-12-20 | 华北电力大学（保定） | CR-NOMA bidirectional relay self-interference energy recovery transmission method |
| CN110602777B (en) * | 2019-08-28 | 2022-04-26 | 华北电力大学（保定） | CR-NOMA bidirectional relay self-interference energy recovery transmission method |
| CN111328144A (en) * | 2020-01-20 | 2020-06-23 | 赣江新区智慧物联研究院有限公司 | Wireless resource allocation method, device, readable storage medium and computer equipment |
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