CN104320841B - A kind of cognitive system power distribution method based on transmitting antenna power constraint - Google Patents
A kind of cognitive system power distribution method based on transmitting antenna power constraint Download PDFInfo
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- CN104320841B CN104320841B CN201410498258.9A CN201410498258A CN104320841B CN 104320841 B CN104320841 B CN 104320841B CN 201410498258 A CN201410498258 A CN 201410498258A CN 104320841 B CN104320841 B CN 104320841B
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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
- H04W52/30—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
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- 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
Abstract
The invention discloses a kind of cognitive system power distribution methods based on transmitting antenna power constraint.It is main to include initially setting up cognitive base station end power allocation optimization problems, optimal beamforming vectors are secondly solved according to systematic parameter, and then the transmission power that user emission power and every antenna are distributed is obtained.To minimize the total transmission power of system as optimization aim, constraints is the optimization problem specially established：Every transmitting antenna transmission power constraint of Signal to Interference plus Noise Ratio constraint and cognitive base station end of interference constraints, cognitive user to primary user.Since the end for during practical communication, recognizing every antenna of base station end can all be equipped with power amplifier, the ability of antenna transmission power is mutually different, therefore considers that every antenna power constraint is more consistent with actual, has certain practical value.
Description
Technical field
The present invention is a kind of cognitive system power distribution method based on transmitting antenna power constraint, belongs to cognitive radio
The communications field.
Background technology
Federal Communications Commission (FCC) finds that radio spectrum resources are not fully utilized by investigation,
The utilization rate for the frequency range that FCC will point out to distribute at present in the end of the year 2003 is differed from 15%~85%, and some frequency bands are excess loads
(such as cell phone network frequency range) used, but the considerable frequency range such as ham radio is not made sufficiently
With.In the 21st century, wireless communication technique high speed development, the rare of frequency spectrum resource become increasingly serious.In order to solve this problem,
Doctor J.Mitola in 1999 proposes the concept of cognitive radio in his doctoral thesis.How he describe cognitive radio
The flexibility of individual radio business is improved by a kind of newspeak for being referred to as " radio knowledge-representation language ".Due to recognizing nothing
There are two kinds of users of primary user and cognitive user in line electric system, therefore the proposition of cognitive radio can effectively improve frequency range
Utilization rate, how to effectively reduce cognitive user becomes the emphasis studied at present to the interference of primary user.
It is analyzed from the angle of spatial domain, due to primary user and the heterogeneite of cognitive user spatial position, in cognition base
More antennas are set up at end of standing, and the transmitting signal of cognitive base station is formed tool by designing corresponding beamforming vectors in antenna end
There is the wave beam of certain orientation, and then reduce the interference to primary user, improve the compossibility of primary user and cognitive user.State at present
Research inside in this respect is relatively more, and different optimization problems is mainly established according to different systems, then using corresponding
Method is solved.In cognitive system known to the study portions channel such as Yongwei Huang, meet cognitive user clothes at the same time
Business limited mass and optimal Inferior obliqued overaction vector is designed primary user on the premise of interference-limited so that cognitive base station
Total transmission power minimizes, and then realizes the distribution of power.But the optimal beamforming vectors calculated are not examined
Consider the ability of the actual emission power of every antenna, but in some cases, in order to be optimal system, some antenna institutes
The transmission power that need to be undertaken may exceed the emissivities of transmitting antenna itself, it is therefore desirable to be further improved.
The content of the invention
Technical solution：The technical solution adopted by the present invention for it is a kind of applied to MIMO communication system based on transmitting antenna work(
The cognitive system power distribution method of rate constraint, it is intended to establish to inhibit primary user's interference, ensure cognitive user end Signal to Interference plus Noise Ratio
And meet every antenna transmission power of cognitive base station end and be limited the condition of being constrained to, it is mesh to minimize cognitive base station end transmission power
Target optimization problem realizes the distribution of power by solving Inferior obliqued overaction vector.Every antenna needs are finally obtained " to hold
The transmission power of load ", and the power does not exceed the threshold value of its transmission power.The technical solution adopted by the present invention includes following
Step：
Step 1：Based on cognitive system, the optimization problem for minimizing cognitive base station transmission power is established, is at the same time needed
Consider the threshold value of the transmission power of every antenna of cognitive base station end.
The optimization problem of foundation is every with primary user's interference threshold, cognitive user Signal to Interference plus Noise Ratio threshold value and cognitive base station end
Root antenna transmission power is limited to constraints, and the transmission power for minimizing cognitive base station is optimization object function.Due to antenna
Transmission power capabilities have nothing in common with each other, therefore consider every antenna transmission power be limited with practical communication more closely, having
Certain practical value.
The reason for considering the constraint of every antenna transmission power be due to during actual multi-antenna communication, every antenna
End configures a simulated power amplifier, therefore the emissivities of different antennae are different.In optimization power point
Timing is constrained discounting for every antenna power, the transmitting work(that some antennas needs gone out by optimization problem solving undertake
Rate is likely larger than the transmission power capabilities of the antenna, causes power distribution failure, can not realize the optimum allocation of system power.Cause
This accounts for every antenna transmission power constraint, meets the demand of practical communication.
Step 2：The non-convex optimization problem obtained in step 1 is converted into convex problem, convex optimization method is reused and is asked
Solution finally draws optimal Inferior obliqued overaction vector, realizes power distribution.
The optimization problem established in step 1 is a quadratically constrained quadratic programming (QCQP) optimization problem, can not be used common
Method solved, method for solving of the invention for former optimization problem first is converted into second-order coneprogram (SOCP) problem, with
It is solved afterwards using containing method, optimal power distribution method can be obtained according to the optimal beamforming vectors being obtained.
It is solved using SOCP methods, computation complexity is low, is conducive to what cognitive base station reduced power distribution and spent
Time reduces system delay, convenient for improving the real-time performance of system.
It is as follows：
(1) based on cognitive system, the optimization problem for minimizing cognitive base station transmission power is established.The pact of the optimization problem
Beam condition is：Every primary user's interference threshold, cognitive user Signal to Interference plus Noise Ratio thresholding and cognitive base station end antenna transmission power limit
System；Optimization aim is：Minimize the transmission power of cognitive base station.
H in formulak、glCognitive base station is represented respectively to the channel parameter information and cognitive base station between k-th of cognitive user
Channel parameter information between l-th of primary user.Cognitive base station end is used for the beamforming vectors of k-th of cognitive user design
tkIt represents.Assuming that the Signal to Interference plus Noise Ratio threshold value needed for cognitive user normal work is γ1...γK, primary user's normal work institute energy
The maximum interference threshold value born is β1...βL, and the transmission power thresholding of cognitive base station end N root antennas is followed successively by P1...PN。For the variance for the noise that k-th of cognitive user termination receives.
(2) optimization problem established in step (1) is changed into the optimization problem of SOCP forms：
Wherein, T=[t1 t2 .. tK].Pass through the optimal beamforming vectors solvedK=1...K.It can be with
The transmission power for calculating every antenna of cognitive base station transmitting terminal isWherein i represents i-th antenna,
[]i,iThe i-th row i row of representing matrix, and i=1...N.Distributing to the total transmission power of k-th of cognitive user is
Advantageous effect：Compared with prior art, the technical solution used is applied to cognition MIMO for one kind and leads to the present invention
The cognitive system power distribution method based on transmitting antenna power constraint of letter system, using convex optimum theory, and in constraint item
The transmission power limitation of every transmitting antenna of cognitive base station end is taken into full account in part, in solving-optimizing problem, original optimization is asked
Topic translates into simple SOCP forms and is solved, and finally obtains optimal beamforming vectors, realizes power distribution.The party
Method considers the limitation of practical communication system antenna transmission power, has certain practical value.
Description of the drawings
Fig. 1 is the system model figure of the present invention.
Fig. 2 is the flow chart of the present invention.
Fig. 3 is the simulated power distribution diagram of the present invention.
Specific embodiment
The present invention is further explained below in conjunction with the accompanying drawings：
Fig. 1 is the system model figure of the present invention.A cognition radio communication system is considered, wherein being furnished with M roots comprising one
The cognitive base station of antenna, the K cognitive users and L equipped with single antenna are furnished with single antenna primary user.PU(Primary
User), SU (Secondary User) represents primary user and cognitive user respectively.The signal that k-th of cognitive user receives can
To be expressed as：
Wherein, k=1...K, u in formulakRepresent that cognitive base station is sent to the signal of k-th of cognitive user, it is assumed that the signal
It is normalized, i.e. E | | uk||2=1.hkCognitive base station is represented to the channel parameter information between k-th of cognitive user.nk
Represent the noise that k-th of cognitive user termination receives, and nkThat obeys is distributed asCognitive base station end is
The beamforming vectors t of k-th of cognitive user designkIt represents.Therefore cognitive base station end distributes to k-th of cognitive user transmitting
Power pkIt can be expressed as：
pk=| | tk||2
Wherein, k=1...K.The power expression being assigned to according to different user can calculate cognitive base station end every
The transmission power that antenna undertakes：
Wherein, qi represents the transmission power that i-th antenna needs undertakes, []i,iThe i-th row i row of representing matrix, and i=
1...N.The expression formula of the signal received to k-th of cognitive user is analyzed, and can be obtained its Signal to Interference plus Noise Ratio and be represented as follows：
The signal that l-th of primary user's termination receives can be expressed as：
Wherein l=1...L, g in formulalRepresent cognitive base station to the channel parameter information between l-th of primary user.According to letter
Number expression formula, which can obtain the interference size that l-th of primary user is subject to, to be expressed as：
Assuming that the Signal to Interference plus Noise Ratio threshold value needed for cognitive user normal work is γ1...γK, primary user's normal work institute energy
The maximum interference threshold value born is β1...βL, and the transmission power thresholding of cognitive base station end N root antennas is followed successively by P1...PN。
Consider that every primary user's interference threshold, cognitive user Signal to Interference plus Noise Ratio thresholding and cognitive base station end antenna transmission power are limited as about
Beam condition, cognitive base station end transmission power minimization problem can be modeled as：
The optimization problem is a non-convex problem, can not direct solution obtain beamforming vectors, can change into convex excellent
Then change problem form is solved using Second-order cone programming (SOCP).The above problem can be converted into following form：
According to identityThe above problem is converted into again：
Wherein T=[t1 t2 .. tK].Above-mentioned optimization problem can use conventional optimization instrument to solve the problem
Optimal solution.
Simulation result
With reference to the performance of the simulation analysis present invention.There are 2 cognitive users and a master in hypothesis system in simulations
User, and cognitive base station is furnished with 10 antennas.The Signal to Interference plus Noise Ratio threshold settings of cognitive user are 1, the interference threshold of primary user
For 1, the noise variance of cognitive user receiving terminal is also 1.
Fig. 3 is the simulated power distribution diagram of the present invention.In every antenna of cognitive base station end there are under power limited situation, than
Every antenna transmission power constraint and the situation without considering every antenna power constraint are considered when relatively optimizing beam forming.By
Fig. 3 can be seen that in the case of being constrained without considering every antenna transmission power, and the transmission power that some antenna needs undertake will
More than the power limit of its own, such as the 1st, 4,5, cause power distribution failure, however the power that this method is distributed will not
There is such case, real-time distribution power can be carried out according to the actual conditions of antenna.
Claims (1)
1. it is a kind of based on transmitting antenna power constraint cognitive system power distribution method, which is characterized in that this method include with
Lower step：
Step 1)：Based on cognitive system, the optimization problem for minimizing cognitive base station transmission power is established, while considers cognitive base station
Hold the threshold value of the transmission power of every transmitting antenna；
Step 2)：The optimization problem that step 1 obtains is a non-convex problem, and now the non-convex optimization problem is converted, then is carried out
It solves, obtained beamforming vectors are optimal beamforming vectors value, and calculating cognitive base station by the value distributes to
The transmission power of different cognitive users and different transmitting antennas undertake the watt level of transmitting；
The optimization problem for minimizing cognitive base station transmission power is established according to cognitive system described in step 1), is specially：
The optimization problem of foundation is with every primary user's interference threshold, cognitive user Signal to Interference plus Noise Ratio threshold value and cognitive base station end antenna hair
Power limit is penetrated as constraints, the transmission power for minimizing cognitive base station is optimization object function；
Solution procedure 1 described in step 2)) in establish optimization problem, be specially：The optimization problem of foundation is in step 1)
Former optimization problem is first converted into second-order coneprogram (SOCP) problem by one quadratically constrained quadratic programming (QCQP) optimization problem, then
It is solved using containing method, optimal power distribution method is obtained according to the optimal beamforming vectors being obtained；
Said program is as follows：
(1) based on cognitive system, the optimization problem for minimizing cognitive base station transmission power is established；The constraint item of the optimization problem
Part is：Every primary user's interference threshold, cognitive user Signal to Interference plus Noise Ratio thresholding and cognitive base station end antenna transmission power limitation；It is excellent
Changing target is：Minimize the transmission power of cognitive base station；
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K represents the number of user, h in formulak、glCognitive base station is represented respectively to the channel parameter information between k-th of cognitive user
And cognitive base station is to the channel parameter information between l-th of primary user；The ripple that cognitive base station end designs for k-th of cognitive user
Beam shaping vector tkIt represents；Assuming that the Signal to Interference plus Noise Ratio threshold value needed for cognitive user normal work is γ1...γK, primary user
It is β to work normally the maximum interference threshold value that can bear1...βL, and the transmission power thresholding of cognitive base station end N root antennas according to
Secondary is P1...PN；For the variance for the noise that k-th of cognitive user termination receives；
(2) optimization problem established in step (1) is changed into the optimization problem of SOCP forms：
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Wherein, T=[t1 t2 .. tK]；Pass through the optimal beamforming vectors solvedIt calculates
The transmission power of every antenna of cognitive base station transmitting terminal isWherein i represents i-th antenna, []i,i
The i-th row i row of representing matrix, and i=1...N；Distributing to the total transmission power of k-th of cognitive user is
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