CN105227222B - A kind of extensive MIMO beam-forming method of high energy efficiency using statistical channel status information - Google Patents
A kind of extensive MIMO beam-forming method of high energy efficiency using statistical channel status information Download PDFInfo
- Publication number
- CN105227222B CN105227222B CN201510570001.4A CN201510570001A CN105227222B CN 105227222 B CN105227222 B CN 105227222B CN 201510570001 A CN201510570001 A CN 201510570001A CN 105227222 B CN105227222 B CN 105227222B
- Authority
- CN
- China
- Prior art keywords
- virtual
- optimization
- allocation vector
- link power
- downlink
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
- H04B7/0621—Feedback content
- H04B7/0626—Channel coefficients, e.g. channel state information [CSI]
-
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
-
- 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 extensive MIMO beam-forming methods of high energy efficiency using statistical channel status information.The invention firstly uses the optimization problems that statistical channel status information handles virtual up-link power distribution, and using the transfer problem of uplink downlink duality processing uplink downlink power distribution, to obtain the downlink power allocation vector of optimization；Secondly, downlink beamforming vector is calculated using instantaneous channel state information, to obtain the downlink beamforming vector of optimization.Method proposed by the present invention can be excessively high to avoid power renewal frequency, reduces computation complexity.Meanwhile system energy efficiency performance close in the prior art utilize its system energy efficiency performance of the method for instantaneous channel state information.Therefore, method proposed by the present invention can effectively trade off system energy efficiency performance and computation complexity.
Description
Technical field
The present invention relates to wireless communication technology field, in particular to extensive multiple-input and multiple-output (multiple-input
Multi-ple-output, MIMO) multi-user Cooperation transmission technology.
Background technique
In recent years, with universal and mobile broadband the fast development of smart phone, wireless data traffic shows explosion
Formula increases.In order to meet the needs of users, operator, which will take, increases the measures such as base station deployment and antenna configuration, this will bring
Energy consumption sharply increases, and how to weigh power system capacity and energy consumption becomes the research emphasis of wireless communication technique.
In order to weigh power system capacity and energy consumption, the prior art propose with energy efficiency (i.e. system weighted sum rate with
The ratio between total power consumption) it is optimization aim, it is a kind of using uplink downlink duality for example, in multi-user MIMO system
Efficiency beamforming design, disadvantage is that sacrifice spectrum efficiency as cost.
Extensive MIMO technology is one of the key technology in the 5th third-generation mobile communication technology (5G), which can be simultaneously
Spectrum efficiency and energy efficiency are improved, and there is very big Improvement in terms of robustness and reliability.If continued to use existing
Have the extensive MIMO efficiency beam forming solutions of Technology design, then power update operand is larger and power renewal frequency mistake
Height, computation complexity limit application of the prior art in extensive MIMO multi-user system.Therefore, extensive MIMO is more
User's efficiency transmission technology will face the problem of how reducing computation complexity.
Summary of the invention
In order to overcome the deficiencies in the prior art, the present invention proposes a kind of utilization statistical channel status information
The extensive MIMO efficiency beam-forming method of (channel state information, CSI), this method can be from two
Aspect reduces computation complexity: reducing the operand that a power updates, and reduces power renewal frequency.
A kind of extensive MIMO efficiency beam-forming method using statistical channel status information, step include:
Obtain the statistical channel status information between single base station and collaboration user；
Single base station handles the optimization problem of virtual up-link power distribution using statistical channel status information, is optimized
Virtual up-link power allocation vector；
Uplink and downlink is handled using uplink downlink duality according to the virtual up-link power allocation vector of the optimization
The transfer problem of link power distribution, obtains the downlink power allocation vector of optimization；
Obtain the instantaneous channel state information between single base station and collaboration user；
Downlink chain is calculated using instantaneous channel state information according to the virtual up-link power allocation vector of the optimization
Road beamforming vectors obtain the downlink beamforming vector of optimization.
A kind of efficiency suitable for extensive MIMO proposed by the invention optimizes transmission technology, its main feature is that first with
Statistical channel status information handles the optimization problem of virtual up-link power distribution, and using at uplink downlink duality
The transfer problem for managing uplink downlink power distribution, to obtain the downlink power allocation vector of optimization；Secondly, utilizing wink
When channel state information calculate downlink beamforming vector, to obtain the downlink beamforming vector of optimization.By
This it can be found that update downlink power allocation be using statistical channel status information rather than instantaneous channel state information,
So as to reduce the operand of power update.In addition, every updating downlink power point in duration time interval T
The downlink power allocation vector matched, and once updated before being maintained in duration time interval T；Also, every the duration
Downlink beamforming vector is updated in interval τ (T > > τ), it is excessively high to can be effectively avoided power renewal frequency in this way, into
One step reduces operand.Therefore, a kind of extensive MIMO efficiency wave beam using statistical channel status information proposed by the present invention
Manufacturing process can significantly reduce computation complexity.
Detailed description of the invention
Fig. 1 is the system model figure of the embodiment of the present invention；
Fig. 2 is a kind of extensive MIMO efficiency velocity of wave manufacturing process using statistical channel status information proposed by the present invention
Flow chart；
Fig. 3 is that single base station is asked using the virtual up-link power distribution optimization of statistical channel status information processing in the present invention
The flow chart of topic；
Fig. 4 is that single base station is asked using the virtual up-link power distribution optimization of statistical channel status information processing in the present invention
The graph of relation of efficiency optimization target values and the power consumption factor involved in inscribing；
Fig. 5 is the system energy efficiency performance of the mentioned method of the present invention and the graph of relation of single Base Transmitter number of antennas.
Specific embodiment
Below in conjunction with attached drawing, specific embodiments of the present invention will be described in further detail.It should be understood that these embodiments
It is only illustrative of the invention and is not intended to limit the scope of the invention, after reading this disclosure, those skilled in the art are to this
The modification of the various equivalent forms of invention falls within right appended by the present patent application.
Application scenarios: the multi-user downlink system of a single base station, the number of users K serviced, wherein base station section
Point configuration N root transmitting antenna and user node configure single received antenna, and system model figure is referring to Fig. 1.
Optimization aim: single base station to greatest extent transimission power and QoS of customer (quality of service,
QoS it) under the constraint conditions such as demand, maximizes system energy efficiency performance (energy efficiency, EE), i.e. system weighted sum speed
The ratio between rate and total power consumption, mathematic(al) representation are
Wherein,
W=[w1,...,wK],Indicate the beam vector of collaboration user k；
P=[p1,...,pK]T, pkIndicate the downlink power allocation value of collaboration user k；
Indicate the normalization channel coefficients vector between single base station and collaboration user k；
θk,γk,Respectively indicate the rate weighted factor and target Signal to Interference plus Noise Ratio of collaboration user k；
P,PC,P0Respectively indicate single base station transimission power to greatest extent, the fixed circuit-level power consumption of single antenna and
Single base station maintains the base power worked normally consumption；Indicate the poor efficiency of single base station power amplifier.
A kind of extensive MIMO efficiency beam-forming method using statistical channel status information, flow chart referring to fig. 2,
Specific implementation step includes:
Statistical channel status information between step 201, the single base station of acquisition and collaboration user；
Step 202, single base station handle the optimization problem of virtual up-link power distribution using statistical channel status information,
Obtain the virtual up-link power allocation vector of optimization；
Step 203 utilizes at uplink downlink duality according to the virtual up-link power allocation vector of the optimization
The transfer problem for managing uplink downlink power distribution, obtains the downlink power allocation vector of optimization；
Instantaneous channel state information between step 204, the single base station of acquisition and collaboration user；
Step 205 utilizes instantaneous channel state information meter according to the virtual up-link power allocation vector of the optimization
Downlink beamforming vector is calculated, the downlink beamforming vector of optimization is obtained.
It should be noted that step 201 to step 203 is to handle virtual uplink function using statistical channel status information
The optimization problem of rate distribution, and using the transfer problem of uplink downlink duality processing uplink downlink power distribution, it obtains
To the downlink power allocation vector of optimization；Step 204 and step 205 are to calculate downlink chain using instantaneous channel state information
Road beamforming vectors, the downlink beamforming vector optimized.
It will be exemplified below step 202, step 203, the specific feasible implementation method of step 205,
For example, the specific feasible implementation method of step 202, flow chart is referring to Fig. 3, comprising:
Step 301, initialization of virtual up-link power allocation vector；
It specifically can be and minimize power under single base station to greatest extent constraint conditions such as transimission power and QoS demand, i.e.,
It is distributed using the virtual up-link power of minimum power in the prior art (power minimization, PM) algorithm initialization
Vector, to obtain virtual up-link power allocation vector initial value q(0), whereinIt indicates
The virtual up-link power apportioning cost of collaboration user k.
Step 302, external iteration update the power consumption factor；
It specifically can be and determined according to linear search method
Wherein, n indicates external iteration number, initial value
Step 303 updates virtual up-link power allocation vector using statistical channel status information internal layer iteration；
Specific feasible implementation method includes the following steps:
According to the power consumption factor-alpha of current external iteration(n)Initialization of virtual up-link power allocation vector q(m),
In, m indicates internal layer the number of iterations, initial value m=0；
According to the virtual up-link power allocation vector q of current internal layer iteration(m)It calculates
It obtainsWherein, ΘkIndicate the normalization space correlation between single base station and collaboration user k
Matrix；
According to the power consumption factor-alpha of current external iteration(n)Virtual up-link power is updated using broad sense water-filling algorithm
Allocation vector, i.e.,
Alternatively,Search for optimum level of water lineMeet power constraints
Obtain updated virtual up-link power allocation vector q(m+1), wherein
Judge whether to stop internal layer iteration, ifThen the virtual up-link power is distributed
Vector q(m+1)Virtual up-link power allocation vector q as current external iteration*(n), otherwise, return and execute according to current
The virtual up-link power allocation vector of internal layer iteration calculates e, and wherein ζ is a preset threshold.
Step 303 it can be appreciated that if external iteration frequency n=0 when, according to the power consumption of current external iteration
The factorUsing statistical channel status information internal layer iteration update virtual up-link power distribute to
Amount, obtains the virtual up-link power allocation vector of current external iteration, is denoted asOtherwise, root
According to the power consumption factor of current external iterationIt is updated on virtual using statistical channel status information internal layer iteration
Uplink power allocation vector obtains the virtual up-link power allocation vector of current external iteration, is denoted as
Step 304 calculates efficiency optimization target values, and shortens the region of search using section elimination approach；
If specifically can be external iteration frequency n=0, according to the power consumption factor of current external iterationWith the virtual up-link power allocation vector of current external iteration
The efficiency optimization target values for calculating current external iteration, are denoted asOtherwise, according to current outer
The power consumption factor in stacking generationWith the virtual up-link power allocation vector of current external iterationThe efficiency optimization target values for calculating current external iteration, are denoted asWherein, efficiency optimizes mesh
The calculation formula of scale value is
Shorten the region of search using section elimination approach, ifThen Otherwise,
Step 305 judges whether to meet external iteration stop condition, ifThen follow the steps 306, it is no
Then return to step 302；
Step 306 is incited somebody to actionOrVirtual up-link power allocation vector q as optimization**。
In another example the specific feasible implementation method of step 203 includes the following steps:
According to the virtual up-link power allocation vector q of optimization**Uplink and downlink chain is handled using uplink downlink duality
The transfer problem of road power distribution, i.e. p=(Ao)-11, obtain the downlink power allocation vector p of optimization**, wherein 1 indicates
All elements are all 1 K dimensional vector,
Wherein,
Enable e'=[e'1,...,e'K]T, e'm=[e'1,m,...,e'K,m]T, then e'=(IK-J)-1V, e'm=(IK-J)- 1vm,
Wherein,
For another example the specific feasible implementation method of step 205 includes the following steps:
It specifically can be the virtual up-link power allocation vector q according to optimization**Utilize instantaneous channel state information meter
Downlink beamforming vector is calculated, the downlink beamforming vector W of optimization is obtained**, wherein calculation formula is as follows:
It should be noted that single base stations and multiuser MIMO efficiency beam-forming method that the prior art proposes is using instantaneous
Channel state information updates downlink power allocation vector sum downlink beamforming vector simultaneously, and what is once updated holds
Continuous time interval is τ.However, a kind of extensive MIMO efficiency beam forming using statistical channel status information proposed in this paper
Method is single base station using statistical channel state information updating downlink power allocation vector and utilizes instantaneous channel state
Information update downlink beamforming vector, the duration time interval that downlink power allocation vector once updates are T,
The duration time interval that downlink beamforming vector once updates is τ, wherein T > > τ.It is also understood that continuing
In time interval T, the method mentioned herein only needs to update a downlink power allocation vector, and the prior art needs more
New τ downlink power allocation vector of T/, that is, illustrate the mentioned method of this paper can be substantially reduced downlink power allocation to
The renewal frequency of amount, to further decrease computation complexity.
Below a kind of the extensive of statistical channel status information will be utilized by the way that MATLAB simulating, verifying is proposed by the present invention
The performance of MIMO efficiency beam-forming method.
Simulated environment parameter setting is as follows, and the number of users K of single base station service, base-station node configures N root transmitting antenna, uses
Family node configures single received antenna.Coverage radius of cell 500m, user's random distribution and with the distance between base station at least
35m.Using the flat fading model under the suburb non line of sight scene in 3GPP, path loss 38log10(d)+34.5,
Shadow fading obeys the logarithm normal distribution of zero-mean standard deviation 8dB and multipath fading coefficient obeys zero mean unit
The multiple Gauss random distribution of variance.The fixed circuit-level power consumption of single antenna is PC=30dBm, single base station maintain normal work
The base power consumption of work is P0=40dBm, and transmission power is P to greatest extent for single base station.Signal bandwidth W=10MHz is used
Family receiving end noise coefficient is 9dB, the poor efficiency of base station power amplifierAnd user rate weighted factor is set as θk=
1,Meanwhile having the method for a kind of united beam forming and power control in the prior art, beam forming uses high specific
(maximum ratio transmission, the MRT) technology of transmission, power control uses mean allocation strategy, by the method phase
The user's Signal to Interference plus Noise Ratio answered is as ownership goal Signal to Interference plus Noise Ratio γk,
Fig. 3 is that single base station is asked using the virtual up-link power distribution optimization of statistical channel status information processing in the present invention
The graph of relation of efficiency optimization target values and the power consumption factor involved in inscribing, according to different power consumption factor-alpha ∈
[0,1] virtual up-link power allocation vector is updated using statistical channel status information iteration, to obtain corresponding virtual
Up-link power allocation vector and calculate its efficiency optimization target values, wherein community user number K=2, Base Transmitter day
Line number mesh N=16.(a), (b), (c), (d) are single base station transmission power P=26dBm, P=34dBm to greatest extent respectively in figure,
Realize that the efficiency optimization target values under (H1, H2, H3, H4) disappear with power in four accidental channels when P=42dBm, P=46dBm
Consume the graph of relation of the factor.Simulation result shows when transmission power region is 26dBm≤P < 42dBm to greatest extent, most
The corresponding optimal power consumption factor-alpha of efficiency optimization target values greatly*=1, it also means that and makes full use of transimission powerWhen transmission power region is 42dBm≤P≤46dBm to greatest extent, efficiency optimization target values and power consumption
The factor (0≤α≤1) presentation first increases the relationship reduced afterwards.In this way, there are a 0≤α of the optimal power consumption factor*≤ 1 makes
Efficiency optimization target values are maximum, therefore can find α using linear search method*, then obtain the virtual uplink function of optimization
Rate allocation vector.
Fig. 5 is the graph of relation of the system energy efficiency performance and single Base Transmitter number of antennas of the mentioned method of the present invention,
In, community user number K=4, Dan Jizhan transmission power P=46dBm to greatest extent." instantaneous CSI " curve refers to use in figure
Single base stations and multiuser MIMO efficiency beam-forming method in the prior art using instantaneous channel state information, 1000 times with
The relation curve of average system performance efficiency and single Base Transmitter number of antennas under the realization of machine channel；" statistical CSI " is bent in figure
Line, which refers to, uses a kind of extensive MIMO efficiency beam-forming method using statistical channel status information proposed by the present invention,
The relation curve of average system performance efficiency and single Base Transmitter number of antennas under 1000 accidental channel realizations；" hundred in figure
Point ratio " curve refers to the ratio and list Base Transmitter number of antennas of both " statistical CSI " and " instantaneous CSI " average system efficiency
Relation curve.Simulation result shows that single base station user number is fixed (K=4), either utilizes instantaneous CSI or statistical CSI
All there is optimal antenna for base station configuration (N in efficiency beam-forming method*=8).When antenna for base station number N=5, " statistics
The ratio of both CSI " and " instantaneous CSI " average system efficiency is 89.46%；It is both above-mentioned when antenna for base station number N=64
Average system efficiency ratio be 98.68%.Also mean that the wave using statistical channel status information that the present invention is mentioned
Its system energy efficiency performance of beam forming method close in the prior art utilize instantaneous channel state information beam-forming method its
System energy efficiency performance, almost can achieve 90% or more.
In conclusion a kind of extensive MIMO efficiency beam forming using statistical channel status information proposed by the present invention
Method, its main feature is that the optimization problem of virtual up-link power distribution is handled first with statistical channel status information, and
Using the transfer problem of uplink downlink duality processing uplink downlink power distribution, to obtain the downlink function of optimization
Rate allocation vector；Secondly, downlink beamforming vector is calculated using instantaneous channel state information, to obtain under optimization
Downlink beam shapes vector.The advantage of the mentioned method of the present invention is, replaces transient channel using statistical channel status information
Status information handles the optimization problem of downlink power allocation vector, reduces and updates a downlink power allocation vector
Operand can simultaneously be effectively avoids downlink power allocation vector renewal frequency excessively high, to further decrease calculating
Complexity.In addition, its system energy efficiency performance of the method using statistical channel status information for being mentioned of the present invention is close to existing skill
Its system energy efficiency performance of the method for instantaneous channel state information is utilized in art.Therefore, a kind of utilize proposed by the present invention counts letter
The extensive MIMO efficiency beam-forming method of channel state information can weigh system energy efficiency performance and computation complexity.
Claims (6)
1. a kind of extensive MIMO beam-forming method of high energy efficiency using statistical channel status information characterized by comprising
Obtain the statistical channel status information between single base station and collaboration user；
Single base station handles the optimization problem of virtual up-link power distribution using statistical channel status information, obtains the void of optimization
Quasi- up-link power allocation vector；
Uplink downlink is handled using uplink downlink duality according to the virtual up-link power allocation vector of the optimization
The transfer problem of power distribution obtains the downlink power allocation vector of optimization；
Obtain the instantaneous channel state information between single base station and collaboration user；
Downlink wave is calculated using instantaneous channel state information according to the virtual up-link power allocation vector of the optimization
Beam shaping vector obtains the downlink beamforming vector of optimization；
The list base station includes: using the optimization problem that statistical channel status information handles virtual up-link power distribution
Initialization of virtual up-link power allocation vector q(0), meet target Signal to Interference plus Noise Ratio and power constraints and utilize function
Rate minimizes method and obtains q(0), wherein Indicate the virtual up-link power of collaboration user k
Apportioning cost, K indicate the number of users of single base station service；
External iteration updates power consumption factor-alpha(n), determined according to linear search methodWherein,
N indicates external iteration number, initial valueP refers to the transmission function to greatest extent of single base station
Rate value；
Virtual uplink function is updated using statistical channel status information internal layer iteration according to the power consumption factor of current external iteration
Rate allocation vector obtains the virtual up-link power allocation vector of current external iteration, is denoted as
According to the virtual up-link power allocation vector meter of the power consumption factor of current external iteration and current external iteration
The efficiency optimization target values for calculating current external iteration, are denoted as
Shorten the region of search using section elimination approach, ifThen Otherwise,
Judge whether to stop external iteration, ifThen willOrVirtual uplink as optimization
Power allocation vector q**, otherwise, return and execute the external iteration update power consumption factor, wherein ζ is a preset threshold.
2. the method according to claim 1, wherein the power consumption factor benefit of the current external iteration of the basis
Updating virtual up-link power allocation vector with statistical channel status information internal layer iteration includes:
According to the power consumption factor initialization of virtual up-link power allocation vector q of current external iteration(m), wherein m table
Show internal layer the number of iterations, initial value m=0；
It is calculated according to the virtual up-link power allocation vector of current internal layer iterationWherein
ΘkIndicate that the normalization spatial correlation matrix between single base station and collaboration user k, N indicate the transmission antenna of single base station configuration
Number；
According to the power consumption factor of current external iteration using broad sense water-filling algorithm update virtual up-link power distribute to
Amount, i.e.,
Alternatively, It indicates water level line, searches for optimum level of water lineMeet power constraintsObtain updated virtual up-link power allocation vector q(m+1), wherein
θkAnd γkThe rate weighted factor and target Signal to Interference plus Noise Ratio of collaboration user k are respectively indicated,Indicate single base station power amplifier
Poor efficiency, PCIndicate the fixed circuit-level power consumption of single antenna, P0Indicate that single base station maintains the base power worked normally
Consumption；
Judge whether to stop internal layer iteration, ifThen by the virtual up-link power allocation vector
q(m+1)Virtual up-link power allocation vector q as current external iteration*(n), otherwise, return and execute according to current internal layer
The virtual up-link power allocation vector of iteration calculates e.
3. according to the method described in claim 2, it is characterized in that, the power consumption factor of the current external iteration of the basis and
The efficiency optimization target values that the virtual up-link power allocation vector of current external iteration calculates current external iteration include:
According to the power consumption factor-alpha of current external iteration(n)With the virtual up-link power allocation vector of current external iteration
q*(n)Calculate the efficiency optimization target values EE of current external iteration(n), i.e.,
4. the method according to claim 1, wherein further include:
When external iteration frequency n >=1, then statistical channel state can be utilized according to the power consumption factor of current external iteration
Information internal layer iteration updates virtual up-link power allocation vector, obtains the virtual up-link power point of current external iteration
With vector, it is denoted asAlso, according to the virtual of the power consumption factor of current external iteration and current external iteration
Up-link power allocation vector calculates the efficiency optimization target values of current external iteration, is denoted as
5. according to the method described in claim 2, it is characterized in that, the virtual up-link power according to the optimization point
Include: using the transfer problem of uplink downlink duality processing uplink downlink power distribution with vector
According to the virtual up-link power allocation vector q of the optimization**Uplink and downlink chain is handled using uplink downlink duality
The transfer problem of road power distribution, i.e. p=(Ao)-11, obtain the downlink power allocation vector p of optimization**, wherein 1 indicates
The K dimensional vector that all elements are 1, Indicate the downlink power allocation value of collaboration user k,Wherein,
Enable e'=[e'1,...,e'K]T, e'i=[e'1,i,...,e'K,i]T, then e'=(IK-J)-1V, e'i=(IK-J)-1vi,
Wherein,
6. the method according to claim 1, wherein the virtual up-link power according to the optimization point
Calculating downlink beamforming vector using instantaneous channel state information with vector includes:
According to the virtual up-link power allocation vector q of the optimization**Downlink is calculated using instantaneous channel state information
Beamforming vectors obtain the downlink beamforming vector W of optimization**, wherein Indicate association
Make the downlink beamforming vector of user k, i.e.,
Wherein, hkIndicate the normalization channel fading coefficient between single base station and collaboration user k, qxIndicate that collaboration user x's is virtual
Up-link power allocation vector, K indicate the number of users of single base station service.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510570001.4A CN105227222B (en) | 2015-09-09 | 2015-09-09 | A kind of extensive MIMO beam-forming method of high energy efficiency using statistical channel status information |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510570001.4A CN105227222B (en) | 2015-09-09 | 2015-09-09 | A kind of extensive MIMO beam-forming method of high energy efficiency using statistical channel status information |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105227222A CN105227222A (en) | 2016-01-06 |
| CN105227222B true CN105227222B (en) | 2019-03-19 |
Family
ID=54995960
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510570001.4A Active CN105227222B (en) | 2015-09-09 | 2015-09-09 | A kind of extensive MIMO beam-forming method of high energy efficiency using statistical channel status information |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105227222B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109104225B (en) * | 2018-08-07 | 2020-06-16 | 东南大学 | Large-scale MIMO beam domain multicast transmission method with optimal energy efficiency |
| CN110311715B (en) * | 2019-07-12 | 2021-02-09 | 东南大学 | Large-scale MIMO non-orthogonal unicast and multicast transmission power distribution method with optimal energy efficiency |
| CN112332899B (en) * | 2020-09-14 | 2021-08-24 | 浙江大学 | Satellite-ground combined heaven-ground integrated large-scale access method |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102355294A (en) * | 2011-11-01 | 2012-02-15 | 东南大学 | Multipoint coordinated beam forming and power allocation method for single base station power constraint |
| CN102457951A (en) * | 2010-10-21 | 2012-05-16 | 华为技术有限公司 | Method for forming link combined wave beam in multi-cell collaborative communication, and base station |
| CN103781167A (en) * | 2014-01-23 | 2014-05-07 | 东南大学 | Downlink multi-user energy-efficiency beam forming method based on duality property |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140293904A1 (en) * | 2013-03-28 | 2014-10-02 | Futurewei Technologies, Inc. | Systems and Methods for Sparse Beamforming Design |
-
2015
- 2015-09-09 CN CN201510570001.4A patent/CN105227222B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102457951A (en) * | 2010-10-21 | 2012-05-16 | 华为技术有限公司 | Method for forming link combined wave beam in multi-cell collaborative communication, and base station |
| CN102355294A (en) * | 2011-11-01 | 2012-02-15 | 东南大学 | Multipoint coordinated beam forming and power allocation method for single base station power constraint |
| CN103781167A (en) * | 2014-01-23 | 2014-05-07 | 东南大学 | Downlink multi-user energy-efficiency beam forming method based on duality property |
Non-Patent Citations (1)
| Title |
|---|
| 多小区大规模协同功率分配及波束成形算法;施研如等;《信号处理》;20150625;第31卷(第6期);摘要，章节1 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105227222A (en) | 2016-01-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101222267B (en) | User matching method in MIMO transmission and method for confirming match factor | |
| CN101662824B (en) | Synergistic multi-point system, user equipment and uplink power control method | |
| CN102970256B (en) | Based on the multiple antennas D2D communication system interference elimination method of kernel | |
| CN103297104B (en) | Antenna array configuration method and aerial array | |
| CN102882570B (en) | Optimum transceiving combined processing method for communication among equipment in mobile communication network | |
| CN103249157B (en) | The resource allocation methods based on cross-layer scheduling mechanism under imperfect CSI condition | |
| CN106549697A (en) | The launch scenario of united beam form-endowing and day line options in cooperation communication system | |
| CN104868947A (en) | Method of realizing beam forming and base station | |
| CN104468055A (en) | Echo self-interference self-adaption suppression method for broadband wireless full-duplex MIMO communication system | |
| CN101369834B (en) | Combined power control method, system and equipment | |
| CN104869626A (en) | Uplink large-scale MIMO system power control method based on receiver with low complexity | |
| CN102185683B (en) | Signal-to-leakage-and-noise ratio (SLNR) rule statistic-based MIMO (Multiple Input Multiple Output) multi-user downlink transmission method | |
| CN104702557A (en) | Incomplete CSI (Channel State Information)-based distributed antenna system adaptive modulation method | |
| CN105188125A (en) | Power distribution method for integrally optimizing energy efficiency and spectrum efficiency of wireless network | |
| CN105227222B (en) | A kind of extensive MIMO beam-forming method of high energy efficiency using statistical channel status information | |
| CN106131855B (en) | The method for channel allocation of virtual subdistrict in a kind of 5G high density network | |
| CN102347820A (en) | Joint coding and decoding method of multi-cell cooperation wireless communication system | |
| CN111901812A (en) | Full-duplex cellular communication network base station and intelligent reflecting surface combined control method | |
| CN102291727B (en) | Distributed cooperative beam forming and designing method | |
| CN102291810B (en) | Open loop power control method and device | |
| CN104079335B (en) | The three-dimensional wave bundle shaping method of robustness under a kind of multi-cell OFDMA network | |
| CN103001685A (en) | Distributed coordinated multi-cell beam forming method applied to coordinated multi-point transmission | |
| CN103973345B (en) | Base station antenna dispatching method based on user distance | |
| CN102255701B (en) | Selecting and processing method for combinational codebook based on statistical channel status information feedback | |
| CN102655671B (en) | Power control method for satellite code division multiple access (CDMA) system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20210330 Address after: 201306 building C, No. 888, Huanhu West 2nd Road, Lingang New Area, Pudong New Area, Shanghai Patentee after: Shanghai Hanxin Industrial Development Partnership (L.P.) Address before: 210096 No. four archway, 2, Jiangsu, Nanjing Patentee before: SOUTHEAST University |
|
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20230914 Address after: 201615 room 301-6, building 6, no.1158, Jiuting Central Road, Jiuting Town, Songjiang District, Shanghai Patentee after: White box (Shanghai) Microelectronics Technology Co.,Ltd. Address before: 201306 building C, No. 888, Huanhu West 2nd Road, Lingang New Area, Pudong New Area, Shanghai Patentee before: Shanghai Hanxin Industrial Development Partnership (L.P.) |