CN104902557B - Small cell user radio method for optimizing resources - Google Patents

Small cell user radio method for optimizing resources Download PDF

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Publication number
CN104902557B
CN104902557B CN201510271828.5A CN201510271828A CN104902557B CN 104902557 B CN104902557 B CN 104902557B CN 201510271828 A CN201510271828 A CN 201510271828A CN 104902557 B CN104902557 B CN 104902557B
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user
small cell
represent
power
transimission power
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CN104902557A (en
Inventor
任乐乐
葛华勇
房树娟
柳姣姣
陈秀红
刘强
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Donghua University
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Donghua University
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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
    • H04W84/00—Network topologies
    • H04W84/02—Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
    • H04W84/04—Large scale networks; Deep hierarchical networks
    • H04W84/042—Public Land Mobile systems, e.g. cellular systems

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  • Engineering & Computer Science (AREA)
  • Quality & Reliability (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The present invention provides a kind of small cell user radio method for optimizing resources, are included in the heterogeneous network of cell containing small, macrocellular and D2D, establish the efficiency function mathematical model of small cell users；Then former three-dimensional optimized problem is converted into One Dimension Optimization Problems using constraints；Pass through theory deduction, it was demonstrated that this one-dimensional equivalent efficiency function has the curve characteristic for first increasing and subtracting afterwards, i.e. global optimum's power points exists；Then it designs the dichotomy algorithm based on derivative and solves optimal power point.The present invention can improve the efficiency of small cell users in heterogeneous network, meet the requirement of green communications.

Description

Small cell user radio method for optimizing resources
Technical field
The present invention relates to power of mobile communication control technology more particularly to a kind of small cell (small base station) user radios Method for optimizing resources.
Background technology
Small cell are the radio access nodes of low-power, are operated in mandate, unauthorized frequency spectrum, can cover 10 For rice to 200 meters of range, small cell are the important components of 3G data distributions, are the effective ways for managing LTE-A frequency spectrums.
As green communications are increasingly subject to the concern of people, how by power control to improve small in heterogeneous network The efficiency of cell is current small cell technology urgent problems to be solved.
Invention content
The technical problem to be solved in the present invention is to provide a kind of small cell user radio method for optimizing resources, to improve The efficiency of small cell users.
In order to solve the above-mentioned technical problem, the technical scheme is that providing a kind of small cell user radio resources Optimization method, it is characterised in that：This method is made of following 4 steps：
Step 1：In the heterogeneous network of the small base stations of cell containing small, macrocellular and D2D, small cell users are established The object function of efficiency, as shown in formula (1)：
The object function includes following constraints：
1st, the minimum transmission rate request of phone user, i.e. its minimum transmission rate cannot be less than δC：
2nd, the minimum transmission rate request of D2D, i.e. its minimum transmission rate cannot be less than δD：
3rd, the maximum transmission power of small cell users, D2D user and macrocell user limits：
PS, PC, PD≤Pmax
A small cell user is included in small cell；D2D centerings include two D2D users, one of them is User is received, another is sends user；Wherein：PSRepresent the transimission power of small cell users, hSDRepresent small Cell user and D2D are to the channel gain between receiving user, hSCRepresent the channel gain between small cell users and macro base station, hSRepresent the channel gain between small cell users and small base station, PDRepresent transimission powers of the D2D to transmitting user, hDIt represents Channel gain between D2D user, PCRepresent the transimission power of phone user, hCDRepresent phone user and D2D between reception user Channel gain, n0Represent noise power, PcircuitRepresent the circuit power consumption of D2D user, hCRepresent phone user and macro base Channel gain between standing, hDCRepresent channel gains of the D2D between transmitting user and macro base station, hDSRepresent D2D to transmitting user with Channel gain between small base station, hCSRepresent the channel gain between phone user and small base station, max function representations maximize small The object function of cell user's efficiency；
Step 2：Due to phone user's transimission power, D2D user's transimission power and small cell user's transimission powers Small cell user's efficiency optimization problems for independent variable are a non-convex problems, directly carry out solving extremely difficult；For Identical PSFor, small cell user's efficiencies USValue be with phone user's transimission power and D2D user's transimission power Increase and reduce, therefore, the minimum capacity requirement of phone user and D2D user in constraints 1 and constraints 2 is met In the case of when taking critical value small cell user's efficiencies be the largest；It can be obtained by constraints 1 and constraints 2：
I.e.：
It enables respectivelyIt can be in the hope of using small cell users transimission power as certainly by above formula Phone user's transimission power of variable and D2D user's transimission power are as follows respectively：
Formula (5) is updated to again can obtain equivalent majorized function in former optimization problem formula (1) is：
Bound for objective function is at this time：
PS≤P′max
Wherein
It in this way, will be with PS、PCAnd PDProper energy for independent variable is imitated optimization problem and is converted into only with PSFor independent variable etc. efficiency Imitate optimization problem；
Step 3：Using the object function of equivalent optimization problem in the provable formula of convex optimum theory (5) about PSHave stringent First increase the curve characteristic subtracted afterwards；
Step 4：It designs the dichotomy algorithm based on derivative and solves optimal transmission power points.
Preferably, in the step 4, optimal transmission power points is solved using the dichotomy algorithm based on derivative, it is specific to wrap Include following steps：
A) enables λ ＞ 1, j=0, and convergence threshold value is ε, is acquiredValue；
F) otherwise., enables PS 1=PS [j], PS 2=PS [j-1],
I) repeats e) .h) until
Wherein, λ represents step-length, and j represents cycle-index, PS [j]Represent the transmission of small cell users during jth time cycle Power, PS [0]Represent initial transmission power,Represent optimal solution transimission power, γ (PS) expression (5) efficiency function single order leads Several molecules, PS 1、PS 2、Represent median.
Method provided by the invention has filled up blank of the existing small cell technical research in heterogeneous network, builds for the first time The efficiency function mathematical model of small cell users in the heterogeneous network for including macrocellular, small cell and D2D has been found, and It is one-dimensional equivalent optimization problem by former three-dimensional optimized problem reduction, passes through the Curve Property of Researching The Equivalent optimization problem, it was demonstrated that The presence of optimal power point devises the dichotomy algorithm based on derivative and solves optimal power point, brought greatly to solve It is convenient；The efficiency of the small cell users in heterogeneous network is enabled to be optimal value using the present invention.
Specific embodiment
To be clearer and more comprehensible the present invention, hereby with a preferred embodiment, it is described in detail below.
Small cell user radio method for optimizing resources the specific implementation process is as follows：
Step 1：In the heterogeneous network of the small base stations of cell containing small, macrocellular and D2D, small cell users are established The object function of efficiency, as shown in formula (1)：
The object function includes following constraints：
1st, the minimum transmission rate request of phone user, i.e., minimum transmission rate cannot be less than δC：
2nd, the minimum transmission rate request of D2D, i.e., minimum transmission rate cannot be less than δD：
3rd, the maximum transmission power of small cell users, D2D user and macrocell user limits：
PS, PC, PD≤Pmax
A small cell user is included in small cell.D2D centerings include two D2D users, one of them is User is received, another is sends user.Wherein：PSRepresent the transimission power of small cell users, hSDRepresent small Cell user and D2D are to the channel gain between receiving user, hSCRepresent the channel gain between small cell users and macro base station, hSRepresent the channel gain between small cell users and small base station, PDRepresent transimission powers of the D2D to transmitting user, hDIt represents Channel gain between D2D user, PCRepresent the transimission power of phone user, hCDRepresent phone user and D2D between reception user Channel gain, n0Represent noise power, PcircuitRepresent the circuit power consumption of D2D user, hCRepresent phone user and macro base Channel gain between standing, hDCRepresent channel gains of the D2D between transmitting user and macro base station, hDSRepresent D2D to transmitting user with Channel gain between small base station, hCSRepresent the channel gain between phone user and small base station.(1) the max function representations in formula are most The efficiency function of bigization small cell users.
Step 2：Due to phone user's transimission power, D2D user's transimission power and small cell user's transimission powers Small cell user's efficiency optimization problems for independent variable are a non-convex problems, directly carry out solving extremely difficult.For Identical PSFor, small cell user's efficiencies USValue be with phone user's transimission power and D2D user's transimission power Increase and reduce, therefore, the minimum capacity requirement of phone user and D2D user in constraints 1 and constraints 2 is met In the case of when taking critical value (taking equal sign) small cell user's efficiencies be the largest.It can by constraints 1 and constraints 2 ：
I.e.：
It enables respectivelyIt can be in the hope of using small cell users transimission power as certainly by above formula Phone user's transimission power of variable and D2D user's transimission power are as follows respectively：
Formula (5) is updated to again can obtain equivalent optimization problem in former optimization problem formula (1) is：
Bound for objective function is at this time：
PS≤P′max
Wherein
It in this way, will be with PS、PCAnd PD(three-dimensional independent variable) is imitated optimization problem for the proper energy of independent variable and is converted into only with PS(one Tie up independent variable) be independent variable equivalent efficiency optimization problem.
Step 3：Using the object function of equivalent optimization problem in the provable formula of convex optimum theory (5) about PSHave stringent First increase the curve characteristic subtracted afterwards.Specific proof procedure is as follows：
Definition：One by the DUAL PROBLEMS OF VECTOR MAPPING in n dimensions real number convex set D into be after the function f of a real number intend it is recessed, if right In arbitrary x1, x2∈ D and x1≠x2Have：
f(λx1+(1-λ)x2) ＞ min { f (x1), f (x2), (9)
Wherein 0 ＜ λ ＜ 1, min function representations are minimized.
Arbitrary strictly monotone function be all intend it is recessed, and arbitrary strictly concave function be also all strictly intend it is recessed, it is but anti- Come over usually invalid.
Theorem：If R (PS) for PSIt is stringent concave function, then US(PS) it is exactly strictly to intend recessed, and it is first list It adjusts and is incremented by again monotone decreasing, so PSOptimal value be some limited positive value point.
It proves：It first can be in the hope of R (PS) second dervative
So R (PS) about PSIt is a strictly concave function.Define U (PS) superlevel collection it is as follows：
Sη={ PS＞ 0 | U (PS)≥η}
From literature it is known that if for arbitrary real number η, SηA stringent convex set, then U (PS) about PSIt is one tight Lattice quasiconcave function.The S as η ＜ 0ηDo not have on set boundaries a little, as η >=0：
Sη={ PS＞ 0 | η (PS+Pcircuit)-R(PS)≤0}。
Because R (PS) about PSIt is stringent concave function, so SηAbout PSIt is strictly convex sets.U (P are demonstrated in this wayS) be About PSStrictly quasi-concave function.U (P againS) first derivative be：
Therefore γ ' (PS) it is less than zero, γ (PS) monotone decreasing, and PSγ (P when going to zeroS) it is greater than zero, PSBecome γ (the P when infiniteS) zero is less than, so U (PS) be one and first increase the function subtracted afterwards.
Step 4：It designs the dichotomy algorithm based on derivative and solves optimal transmission power points, specifically comprise the following steps：
A) enables λ ＞ 1, j=0, and convergence threshold value is ε, is acquiredValue；
C) otherwise. enables PS [j+1]=λ PS [j], j=j+1；
F) otherwise., enables PS 1=PS [j], PS 2=PS [j-1],
I) repeats e) .h) until
Wherein, PS [0]Represent initial transmission power,Represent optimal solution transimission power, γ (PS) expression (5) efficiency function The molecule of first derivative, PS 1、PS 2、Represent median.λ represents step-length, and j represents cycle-index, PS [j]Represent jth time cycle When small cell users transimission power.

Claims (2)

1. a kind of small cell user radio method for optimizing resources, it is characterised in that：This method is made of following 4 steps：
Step 1：In the heterogeneous network of the small base stations of cell containing small, macrocellular and D2D, small cell user's efficiencies are established Object function, as shown in formula (1)：
The object function includes following constraints：
1st, the minimum transmission rate request of phone user, i.e. its minimum transmission rate cannot be less than δC：
2nd, the minimum transmission rate request of D2D, i.e. its minimum transmission rate cannot be less than δD：
3rd, the maximum transmission power of small cell users, D2D user and macrocell user limits：
PS,PC,PD≤Pmax
A small cell user is included in small cell；D2D centerings include two D2D users, one of them is receives User, another is sends user；Wherein：PSRepresent the transimission power of small cell users, hSDRepresent that small cell are used Family and D2D are to the channel gain between receiving user, hSCRepresent the channel gain between small cell users and macro base station, hSIt represents Channel gain between small cell users and small base station, PDRepresent transimission powers of the D2D to transmitting user, hDRepresent D2D user Between channel gain, PCRepresent the transimission power of phone user, hCDRepresent that phone user and D2D increase the channel between receiving user Benefit, n0Represent noise power, PcircuitRepresent the circuit power consumption of D2D user, hCRepresent the letter between phone user and macro base station Road gain, hDCRepresent channel gains of the D2D between transmitting user and macro base station, hDSRepresent D2D between transmitting user and small base station Channel gain, hCSRepresent the channel gain between phone user and small base station, max function representations maximize small cell users The object function of efficiency；
Step 2：Due to using phone user's transimission power, D2D user's transimission power and small cell users transimission power as certainly Small cell user's efficiency optimization problems of variable are a non-convex problems, directly carry out solving extremely difficult；For identical PSFor, small cell user's efficiencies USValue be increase with phone user's transimission power and D2D user's transimission power And reduce, therefore, the minimum capacity requirement situation of phone user and D2D user in constraints 1 and constraints 2 is met Under when taking critical value small cell user's efficiencies be the largest；It can be obtained by constraints 1 and constraints 2：
I.e.：
It enables respectivelyIt can be in the hope of using small cell users transimission power as independent variable by above formula Phone user's transimission power and D2D user's transimission power, respectively it is as follows：
Formula (5) is updated to again can obtain equivalent majorized function in former optimization problem formula (1) is：
Bound for objective function is at this time：
PS≤P'max
Wherein
It in this way, will be with PS、PCAnd PDProper energy for independent variable is imitated optimization problem and is converted into only with PSEquivalent efficiency for independent variable is excellent Change problem；
Step 3：Using the object function of equivalent optimization problem in the provable formula of convex optimum theory (5) about PSHas stringent elder generation The curve characteristic subtracted after increasing；
Step 4：It designs the dichotomy algorithm based on derivative and solves optimal transmission power points.
2. a kind of small cell user radio method for optimizing resources as described in claim 1, it is characterised in that：The step In 4, optimal transmission power points is solved using the dichotomy algorithm based on derivative, is specifically comprised the following steps：
A) enables λ ＞ 1, j=0, and convergence threshold value is ε, is acquiredValue；
If b)It enablesJ=j+1；
C) otherwise. enables PS [j+1]=λ PS [j], j=j+1；
D) repeats b) .c) until
If e)It enables
F) otherwise., is enabled
If g)It enablesIt asks
H) otherwise. is enabledIt asks
I) repeats step e)~step h), until
J) is returned
Wherein, λ represents step-length, and j represents cycle-index, PS [j]Represent the transimission power of small cell users during jth time cycle, PS [0]Represent initial transmission power,Represent optimal solution transimission power, γ (PS) expression (5) efficiency function first derivative point Son, PS 1、PS 2、Represent median.
CN201510271828.5A 2015-05-25 2015-05-25 Small cell user radio method for optimizing resources Expired - Fee Related CN104902557B (en)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011093992A2 (en) * 2010-01-28 2011-08-04 Tti Inventions D Llc System and method for resource allocation of a lte network integrated with femtocells
CN104185263A (en) * 2014-09-12 2014-12-03 东南大学 Multi-target power optimizing method based on heterogeneous network
CN104202716A (en) * 2014-09-12 2014-12-10 东南大学 D2D efficient power optimization method based on heterogeneous network

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011093992A2 (en) * 2010-01-28 2011-08-04 Tti Inventions D Llc System and method for resource allocation of a lte network integrated with femtocells
CN104185263A (en) * 2014-09-12 2014-12-03 东南大学 Multi-target power optimizing method based on heterogeneous network
CN104202716A (en) * 2014-09-12 2014-12-10 东南大学 D2D efficient power optimization method based on heterogeneous network

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