CN104660314B - A kind of multiuser MIMO downlink user choosing method using fairness factor - Google Patents

A kind of multiuser MIMO downlink user choosing method using fairness factor Download PDF

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CN104660314B
CN104660314B CN201510067008.4A CN201510067008A CN104660314B CN 104660314 B CN104660314 B CN 104660314B CN 201510067008 A CN201510067008 A CN 201510067008A CN 104660314 B CN104660314 B CN 104660314B
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徐玉滨
冯雨晴
马琳
崔扬
刘宁庆
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Harbin Institute of Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0452—Multi-user MIMO systems

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Abstract

A kind of multiuser MIMO downlink user choosing method using fairness factor, it is related to a kind of multiuser MIMO downlink user choosing method, more particularly to considers the multiuser MIMO downlink user choosing method of fairness factor.Probability density function p (x) progress multiple integral of the present invention first to reception signal obtains the selected probability of t-th of time slot of user kIt is carried out into statistical average in timing statisticses T to obtainSo as to calculateAnd then try to achieve fairness factorThe levelling factor of the fairness factor F minimum values as MIMO downlink user systems of selection is chosen, based on the multiuser MIMO downlink user choosing method that fairness factor F designs fairness is optimal.The present invention is applied to the selection of the user of multiuser MIMO downlink.

Description

A kind of multiuser MIMO downlink user choosing method using fairness factor
Technical field
The present invention relates to a kind of multiuser MIMO downlink user choosing method, more particularly to consider fairness factor Multiuser MIMO downlink user choosing method.
Background technology
Multiple Input Multiple Output, i.e. MIMO technology, the system that can be multiplied and speed, improve the availability of frequency spectrum.However, It also brings quite serious spacing wave interference while a series of premium properties are brought.When etc. number of users to be serviced When being far longer than base station outfit antenna number, base station need to pass through user's selection algorithm and choose user's with high transfer rate Collection, avoid because wrong choice service user influences system and capacity.Conventional user's selection algorithm has total space ergodic algorithm, half Orthogonal users selection algorithm (SUS) and minimum inverse matrix norm algorithm (MFNPI) etc..
Fairness is to weigh two more important indexs of user's selection algorithm performance between system and capacity and user, and Prolong when in communication limited or subscriber channel it is uneven when, fairness is just particularly important.In fact, used in actual environment Fairness is critically important between family, even needs to carry out the poor use of giving consideration to channel condition by cost of certain power system capacity sometimes Family, prevent these users from cannot service for a long time, especially to service quality than more sensitive system.
The content of the invention
The present invention does not account for fairness factor to solve existing multiuser MIMO downlink user choosing method Caused by subscriber channel it is uneven the problem of and the poor user of channel condition less than service the problem of.
A kind of multiuser MIMO downlink user choosing method using fairness factor, comprise the following steps：
Step 1: probability density function p (x) the progress multiple integral to reception signal obtains t-th of time slot of user k and is chosen In probability Pt,k, such as formula (1)；
Wherein, N is total number of users；H is channel vector, and k is user's ordinal number, k ∈ (1, N), hkFor user k channel to Amount；Dt,kThe probability P being selected for t-th of time slot of user kt,kLimit of integration；For user's selection algorithm that limit of integration is more complicated, The integration can utilize Monte Carlo cultellation method to realize, and then calculate probability；
Step 2: the probability P that t-th of time slot of user k obtained by step 1 is selectedt,kCounted in timing statisticses T It is average, obtain the average probability P that user k is selected in timing statisticsesk, such as formula (2)
Step 3: by step 2 averaging of income probability PkIt is multiplied by timing statisticses T and obtains the selected total degree of user, Chu Yizong Selected number obtains user k and is chosen accounting γ of the number in total selected person-timek, such as formula (3)；
Wherein, always selected number is expressed as M × T；M is transmitting terminal antenna sum；
Step 4: according to accounting γkRelative arithmetic averageFairness factor F is tried to achieve, such as formula (5)
F physical significance is the fluctuation situation of different user being serviced time, i.e. the deviation feelings with respect to average service time Condition；F is bigger, and the fluctuating range of user's being serviced time is bigger, illustrates that the preferable user of channel condition and channel condition are poor User's being serviced lead time is bigger, and fairness is also poorer；Conversely, F is smaller, illustrate that each user's being serviced time is closer Average service time, fairness are better；
Fairness factor of the fairness factor F minimum values as MIMO downlink user systems of selection is chosen, based on this The optimal multiuser MIMO downlink user choosing method of fairness factor F designs fairness.
Beneficial effects of the present invention：
When system model is fixed, fairness factor of the present invention is only relevant with user's selection algorithm, and and iteration Number is unrelated, therefore this method eliminates influence of the successive ignition to fairness factor, i.e. fairness factor F can be retouched well State the fairness of multiuser MIMO downlink user's selection algorithm.F is bigger, and the fluctuating range of user's being serviced time is bigger, Illustrate that the preferable user of the channel condition user being serviced lead time poor with channel condition is bigger, fairness is also poorer； Conversely, F is smaller, illustrate that each user's being serviced time is better closer to average service time, fairness.
The optimal multiuser MIMO downlink user choosing method of fairness factor F minimal design fairness is selected, just Each user's being serviced time is built upon closer to average service time, on the basis of fairness is better, so compared to biography The fairness that user selects in the multiuser MIMO downlink user choosing method of system improves more than 30%, channel condition compared with The user of difference reduces by more than 50% less than the probability of service.
Brief description of the drawings
Fig. 1 typical multi-user MIMO down link structure figures；
Limit of integration D schematic diagrames during Fig. 2 N=2, M=1；
Limit of integration D schematic diagrames during Fig. 3 N=3, M=1.
Embodiment
Embodiment one：Illustrate present embodiment with reference to Fig. 1-Fig. 3, one kind of present embodiment using fairness because The multiuser MIMO downlink user choosing method of son, comprises the following steps：
Step 1: probability density function p (x) the progress multiple integral to reception signal obtains t-th of time slot of user k and is chosen In probability Pt,k, such as formula (1)；
Wherein, N is total number of users；H is channel vector, and k is user's ordinal number, k ∈ (1, N), hkFor user k channel to Amount；Dt,kThe probability P being selected for t-th of time slot of user kt,kLimit of integration；For user's selection algorithm that limit of integration is more complicated, The integration can utilize Monte Carlo cultellation method to realize, and then calculate probability；
Step 2: the probability P that t-th of time slot of user k obtained by step 1 is selectedt,kCounted in timing statisticses T It is average, obtain the average probability P that user k is selected in timing statisticsesk, such as formula (2)
Step 3: by step 2 averaging of income probability PkIt is multiplied by timing statisticses T and obtains the selected total degree of user, Chu Yizong Selected number obtains user k and is chosen accounting γ of the number in total selected person-timek, such as formula (3)；
Wherein, always selected number is expressed as M × T；M is transmitting terminal antenna sum；
Step 4: according to accounting γkRelative arithmetic averageFairness factor F is tried to achieve, such as formula (5)
F physical significance is the fluctuation situation of different user being serviced time, i.e. the deviation feelings with respect to average service time Condition；F is bigger, and the fluctuating range of user's being serviced time is bigger, illustrates that the preferable user of channel condition and channel condition are poor User's being serviced lead time is bigger, and fairness is also poorer；Conversely, F is smaller, illustrate that each user's being serviced time is closer Average service time, fairness are better；
Fairness factor of the fairness factor F minimum values as MIMO downlink user systems of selection is chosen, based on this The optimal multiuser MIMO downlink user choosing method of fairness factor F designs fairness.
Embodiment two：Probability density function p (x) described in step one in present embodiment is such as shown in formula (6)
Other steps and parameter are identical with embodiment one.
Embodiment three：Probability density function p (x) Rayleigh distributeds described in step one in present embodiment, System model is Rayleigh flat fading channel, channel vector hkCyclic Symmetry Gaussian Profile is obeyed, envelope | | hk| | obey Rayleigh point Cloth, phaseObedience is uniformly distributed.
Other steps and parameter are identical with embodiment one or two.
Embodiment four：P described in step one in present embodimentt,kLimit of integration Dt,kValue and user select Algorithm is relevant, limit of integration D when using subscriber channel gain maximum as user's selection criteriont,kFormula (7) can be expressed as, is Statement is convenient, by Dt,kState D,
Wherein, hkFor user k channel vector, hiFor user i channel vector.
Other steps and parameter are identical with one of embodiment one to three.
Embodiment five：Representations of the limit of integration D under algorithms of different described in step one in present embodiment It is as follows,
When using minimum inverse matrix norm (MFNPI) algorithm, limit of integration D is embodied as
And ml≠ k, makesAnd j ≠ ml；
And i ≠ ml,i≠k
Wherein,For user mlChannel vector；On the premise of existing l user is selected, if user k is next quilt The user chosen, the then selected user formed integrate as Ωl,k；Ωl,k,ΩM,k,ΩM,iIt is selected user's collection；H () is The composite channel matrix of selected user's composition；
When using semi-orthogonal user selection algorithm (SUS), limit of integration D is represented by
And ml≠ k, makesAnd i ≠ m1；
And i ≠ m1,2, whereing1=h1
And i ≠ m1,…,M-1, wherein
And i ≠ ml,i≠k.
Wherein, giFor with hiMutually orthogonal orthogonal vectors.
Due to 1≤l≤M-1, so D is by DMForm.
Other steps and parameter are identical with one of embodiment one to four.

Claims (2)

  1. A kind of 1. multiuser MIMO downlink user choosing method using fairness factor, it is characterised in that this method bag Include following steps：
    Step 1: the probability density function to reception signalCarry out multiple integral and obtain user k The selected probability P of t-th of time slott,k, such as formula (1)；
    <mrow> <msub> <mi>P</mi> <mrow> <mi>t</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> <mo>=</mo> <munder> <mrow> <mo>&amp;Integral;</mo> <mn>...</mn> <mo>&amp;Integral;</mo> </mrow> <msub> <mi>D</mi> <mrow> <mi>t</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> </munder> <munderover> <mo>&amp;Pi;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <mrow> <mo>(</mo> <mi>p</mi> <mo>(</mo> <mrow> <mo>|</mo> <mo>|</mo> <msub> <mi>h</mi> <mi>k</mi> </msub> <mo>|</mo> <mo>|</mo> </mrow> <mo>)</mo> <mo>)</mo> </mrow> <mi>d</mi> <mo>|</mo> <mo>|</mo> <msub> <mi>h</mi> <mn>1</mn> </msub> <mo>|</mo> <mo>|</mo> <mi>d</mi> <mo>|</mo> <mo>|</mo> <msub> <mi>h</mi> <mn>2</mn> </msub> <mo>|</mo> <mo>|</mo> <mo>...</mo> <mi>d</mi> <mo>|</mo> <mo>|</mo> <msub> <mi>h</mi> <mi>k</mi> </msub> <mo>|</mo> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow>
    Wherein, N is total number of users；H is channel vector, and k is user's ordinal number, k ∈ (1, N), hkFor user k channel vector；Dt,k The probability P being selected for t-th of time slot of user kt,kLimit of integration；
    The Pt,kLimit of integration Dt,kValue it is relevant with user's selection algorithm, when maximum as user's choosing using subscriber channel gain Limit of integration D when selecting criteriont,kFormula (7) can be expressed as, it is convenient for statement, by Dt,kState D,
    <mrow> <mi>D</mi> <mo>=</mo> <mo>{</mo> <mi>D</mi> <mo>&amp;Element;</mo> <msup> <mi>R</mi> <mi>N</mi> </msup> <mo>|</mo> <mo>|</mo> <mo>|</mo> <msub> <mi>h</mi> <mi>k</mi> </msub> <mo>|</mo> <mo>|</mo> <mo>&gt;</mo> <mo>|</mo> <mo>|</mo> <msub> <mi>h</mi> <mi>i</mi> </msub> <mo>|</mo> <mo>|</mo> <mo>}</mo> <mo>,</mo> <mo>&amp;ForAll;</mo> <mi>i</mi> <mo>&amp;Element;</mo> <mo>{</mo> <mn>1</mn> <mo>,</mo> <mo>...</mo> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>,</mo> <mi>k</mi> <mo>+</mo> <mn>1</mn> <mo>,</mo> <mo>...</mo> <mo>,</mo> <mi>N</mi> <mo>}</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>7</mn> <mo>)</mo> </mrow> </mrow>
    Wherein, hkFor user k channel vector, hiFor user i channel vector；
    Representations of the limit of integration D under algorithms of different is as follows,
    When using minimum inverse matrix norm algorithm, limit of integration D is embodied as
    DM：And ml≠ k, makesAnd j ≠ ml；
    And i ≠ ml,i≠k
    Wherein,For user mlChannel vector；On the premise of existing l user is selected, if user k is next selected User, then the selected user formed integrates as Ωl,k；Ωl,k,ΩM,k,ΩM,iIt is selected user's collection；H () is selected The composite channel matrix of user's composition；
    When using semi-orthogonal user's selection algorithm, limit of integration D is represented by
    DM:And ml≠ k, makesAnd i ≠ m1；
    And i ≠ m1,2, whereing1=h1
    And i ≠ m1,…,M-1, wherein
    And i ≠ ml,i≠k.
    Wherein, giFor with hiMutually orthogonal orthogonal vectors；
    Step 2: the probability P that t-th of time slot of user k obtained by step 1 is selectedt,kIt is flat that statistics is carried out in timing statisticses T , the average probability P that user k is selected in timing statisticses is obtainedk, such as formula (2)
    <mrow> <msub> <mi>P</mi> <mi>k</mi> </msub> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>t</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>T</mi> </munderover> <msub> <mi>P</mi> <mrow> <mi>t</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> <mo>/</mo> <mi>T</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow>
    Step 3: by step 2 averaging of income probability PkIt is multiplied by timing statisticses T and obtains the selected total degree of user, divided by it is total selected Number obtains user k and is chosen accounting γ of the number in total selected person-timek, such as formula (3)；
    <mrow> <msub> <mi>&amp;gamma;</mi> <mi>k</mi> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>P</mi> <mi>k</mi> </msub> <mo>&amp;times;</mo> <mi>T</mi> </mrow> <mrow> <mi>M</mi> <mo>&amp;times;</mo> <mi>T</mi> </mrow> </mfrac> <mo>=</mo> <mfrac> <msub> <mi>P</mi> <mi>k</mi> </msub> <mi>M</mi> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> </mrow>
    Wherein, always selected number is expressed as M × T；M is transmitting terminal antenna sum；
    Step 4: according to accounting γkRelative arithmetic averageFairness factor F is tried to achieve, such as formula (5)
    <mrow> <mi>F</mi> <mo>=</mo> <mfrac> <msqrt> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>&amp;gamma;</mi> <mi>k</mi> </msub> <mo>-</mo> <mover> <msub> <mi>&amp;gamma;</mi> <mi>k</mi> </msub> <mo>&amp;OverBar;</mo> </mover> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </msqrt> <mi>N</mi> </mfrac> <mo>=</mo> <mfrac> <msqrt> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <msup> <mrow> <mo>(</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>t</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>T</mi> </munderover> <msub> <mi>P</mi> <mrow> <mi>t</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> <mo>-</mo> <mfrac> <mrow> <mi>T</mi> <mi>M</mi> </mrow> <mi>N</mi> </mfrac> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </msqrt> <mrow> <msup> <mi>NT</mi> <mn>2</mn> </msup> <msup> <mi>M</mi> <mn>2</mn> </msup> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> </mrow>
    Fairness factor of the fairness factor F minimum values as MIMO downlink user systems of selection is chosen, based on the justice The optimal multiuser MIMO downlink user choosing method of sex factor F designs fairness.
  2. 2. a kind of multiuser MIMO downlink user choosing method using fairness factor according to claim 1, Characterized in that, probability density function p (x) Rayleigh distributeds described in step 1, system model is Rayleigh flat fading channel, Channel vector hkCyclic Symmetry Gaussian Profile is obeyed, envelope | | hk| | Rayleigh distributed, phaseObedience is uniformly distributed.
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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101834650A (en) * 2010-05-18 2010-09-15 华中科技大学 Multiuser MIMO (multiple-input multiple-output) downlink transmitting and dispatching method
CN103763782A (en) * 2014-01-13 2014-04-30 西安电子科技大学 Dispatching method for MU-MIMO down link based on fairness related to weighting users

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8849353B2 (en) * 2007-04-27 2014-09-30 Alcatel Lucent Method of grouping users to reduce interference in MIMO-based wireless network

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101834650A (en) * 2010-05-18 2010-09-15 华中科技大学 Multiuser MIMO (multiple-input multiple-output) downlink transmitting and dispatching method
CN103763782A (en) * 2014-01-13 2014-04-30 西安电子科技大学 Dispatching method for MU-MIMO down link based on fairness related to weighting users

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
USERSELECTION FORTHE MIMO BROADCAST CHANNELWITHAFAIRNESS CONSTRAINT;Jianqi Wang, David J Love, Michael D. Zoltowski;《2007 IEEE International Conference on Acoustics,Speech AND Signal Processing-ICASSP"07》;20070420;全文 *

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