CN108430076A - A kind of more mobile operator method of rate allocation based on congestion cognition - Google Patents

A kind of more mobile operator method of rate allocation based on congestion cognition Download PDF

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Publication number
CN108430076A
CN108430076A CN201810037653.5A CN201810037653A CN108430076A CN 108430076 A CN108430076 A CN 108430076A CN 201810037653 A CN201810037653 A CN 201810037653A CN 108430076 A CN108430076 A CN 108430076A
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Prior art keywords
operator
congestion
user
formula
indicate
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CN201810037653.5A
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翟象平
陈坤
陈兵
赵蕴龙
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Nanjing University of Aeronautics and Astronautics
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Nanjing University of Aeronautics and Astronautics
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/02—Traffic management, e.g. flow control or congestion control
    • H04W28/0289—Congestion control
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
    • H04W28/18—Negotiating wireless communication parameters
    • H04W28/22—Negotiating communication rate
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/30—TPC using constraints in the total amount of available transmission power
    • H04W52/34—TPC management, i.e. sharing limited amount of power among users or channels or data types, e.g. cell loading
    • H04W52/343—TPC management, i.e. sharing limited amount of power among users or channels or data types, e.g. cell loading taking into account loading or congestion level

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

Abstract

The present invention proposes a kind of more mobile operator method of rate allocation recognized based on congestion, this method builds the problem of target problem minimum with total energy consumption model first, then the unique logarithm convexity attribute of a standard interference function is utilized can realize energy consumption smallization feasible solution to calculate one based on the planning of congestion to design one in more MNO, realize that energy efficiency when wireless network data transmission optimizes.The present invention overcomes the limitations of the nonconvex property of the signal-to-noise ratio of data transmission rate model, solve the problems, such as the technical issues of limitation of the nonconvex property of the signal-to-noise ratio of data transmission rate model can make planning that can not find out optimal solution.

Description

A kind of more mobile operator method of rate allocation based on congestion cognition
Technical field
Energy efficiency when being transmitted the present invention relates to wireless network data optimizes field, especially a kind of to be recognized based on congestion More mobile operator method of rate allocation.
Background technology
Because there is a large amount of battery powered mobile terminal in a network, energy efficiency is outstanding in next-generation mobile radio network Its is important.The trend of mobile network's operation is to separate wireless operator infrastructure from Information Mobile Service at hand.Example Such as, the multiple subscriber identification cards of Next generation cellular system (SIM card) can access two distinct types of cellular network.By more A Mobile Network Operator (operator) provides wireless, and each wireless network has different isomery rate function features, this New challenge is brought to the optimization of wireless network.
This requirement to mobile data service in several years becomes more and more important.This greatly have stimulated using existing wireless Cellular network provides the development of the wireless carriers of wireless service.Unlike traditional cellular carrier, operator does not need Possess the wireless operator physical equipment of oneself but from operator's leased equipment.Some have paddy using the example that multi-operator is applied The FI engineerings of song company, the engineering may be implemented later to switch between multiple and different operators using multiple SIM cards.Due to To the Decentralization of radio resource, this makes the shared aspect of radio resource become undesirable for different operators, therefore resources control Just become to be even more important with interference management.Energy consumption control can make each mobile subscriber each to access with a suitable energy consumption A operator simultaneously ensures that the interference to other users will not be caused while meeting service quality.
Invention content
Goal of the invention：By different operators it is difficult to manage radio resource concentratedly, so radio resource is shared to be likely difficult to reality Existing, as a result resources control and interference management are main technical problems.And energy consumption control can make each mobile subscriber with One appropriate energy consumption meets operator's access of service quality to realize, each operator can provide different rate functions Characteristic, and to solve energy consumption control problem, it is necessary to the nonconvex property for solving the signal-to-noise ratio limitation of data transmission rate model, due to number The nonconvex property limited according to the signal-to-noise ratio of transmission rate model can not then find the minimal solution of problem from problem planning, so nothing Method finds out the minimum power of the power problem, in addition, due to fixed resource allocation, unconformable wireless system can suffer from spy Determine the congestion effects of operator.
To solve the technical problem, the present invention proposes a kind of more rate-allocation sides mobile operator recognized based on congestion Method, this method have been probed into the design for the energy consumption efficiency control algolithm for using multiple operators in a network, have been utilized in research process Unique logarithm convexity attribute design of standard interference function is a set of to be determined with each operator's Congestion Level SPCC of dynamically adapting Point calculating method.
Technical solution：For the above-mentioned technique effect of realization, technical solution proposed by the present invention is：
Advantageous effect：Compared with prior art, the present invention has the advantage that：
A kind of more mobile operator method of rate allocation based on congestion cognition, including step：
(1) model the problem of to transmit total energy consumption minimum target problem is built：
Formula (1) while meeting restrictive condition：
In formula,Indicate energy of the user l by operator's m transmission datas when； Indicate rates of the user l by operator's m transmission datas；M indicates that the quantity of operator, L indicate total number of users；Indicate the signal-to-noise ratio of user l on operator m；Indicate the data transmission speed between user l and operator m Rate；Indicate maximum limitation power of the user l on operator m,Indicate irreducible minimums of the user l for message transmission rate System；
(4) it is convex restrictive condition by the non-convex restrictive condition relaxation in step (1), the restrictive condition after relaxation is：
In formula,The rate transmitted by operator m for the user l after relaxation；
(5) optimal solution of the problem of restrictive condition after meeting relaxation is found out by iteration model, including to each fortune Battalion quotient m executes step 1) to 5) respectively, m=1,2 ..., M：
1) it is cycle-index to define k and t, and initialization k is 0, t 0；Initialize pm(0) it is any one of problem model Group meets the solution of restrictive condition,Initialize xm(0) it is pm(0) corresponding amount of blockage,
2) weight of user's l transmission rates on operator m is calculated：
5) it calculates：
In formula,The channel gain between loser and first of recipient is passed for j-th on operator m；For Intermediate function, expression formula are：
Judge whether to meet：
||pm(k+1)-pm(k)||2≤ ε and | | xm(k+1)-xm(k)||2≤ε
If not satisfied, k=k+1 is then calculated, return to step 3)；If satisfied, thening follow the steps 4)；Wherein, ε is one infinite Small positive number；
6) calculating the weighted value planned based on congestion is：
Wherein,To multiply with the relevant Lagrange of Congestion Level SPCC Son, Lagrange multiplier value is smaller, indicates that Congestion Level SPCC is smaller；
5) judge whether to meet | | rm(t+1)-rm(t)||2≤ ε, | | | |2It indicates European length, that is, indicates two vectors Between length；If satisfied, then stopping iteration；Otherwise, t=t+1, return to step 3 are calculated).
Further, the SINR calculation formula of first of recipient on the operator m are：
In formula,Indicate the white Gaussian noise of upper first of the recipient of operator m.
The present invention proposes a biradical algorithm to avoid congestion, i.e., is gathered around using what logarithm convexity and Lagrange duality designed Adaptive algorithm is filled in avoid blocking, and is realized that energy efficiency when wireless network data transmission optimizes, is overcome data transmission rate The limitation of the nonconvex property of the signal-to-noise ratio of model solves the problems, such as that the limitation of the nonconvex property of the signal-to-noise ratio of data transmission rate model can make The technical issues of planning can not find out optimal solution.
Description of the drawings
Fig. 1 is the principle of the present invention flow chart.
Specific implementation mode
The present invention is further described below in conjunction with the accompanying drawings.
Fig. 1 show the flow chart of the present invention, and the present invention includes the following steps：
1. system model is analyzed
The network for considering a multi-user has M independent operators of L users to share.User l is passed through into operator m The energy of transmission is denoted asIt regard interference as noise, the signal-to-noise ratio computation formula of first of recipient on operator m is such as Under：
Wherein,Indicate upper j-th channel gain passed between loser and first of recipient of operator m；Indicate l White Gaussian noise when a user is by operator's m transmission datas.
Assuming that there are one fixed bit error rates, first of transmitter to carry out data biography by operator m at receiver Defeated rate can be calculated by Shannon capacity formula：
On the other hand, operator, which is based on average error rate, can have other kinds of message transmission rate function：
In formula, R is data transmission rate constant,
In the present embodiment, message transmission rate is calculated using first Shannon capacity formula.
The problem of structure one is minimised as problem target with total energy consumption model：
The restrictive condition of formula (1) is：
In formula, M indicates that the quantity of operator, L indicate total number of users；Table Show the signal-to-noise ratio of first of recipient in m-th of operator；Indicate the number between user l and operator m According to transmission rate,Indicate that user l limits the minimum of message transmission rate,Indicate the maximum limit of user l and operator m Power processed.
But above-mentioned problem model cannot be guaranteed that the data transmission rate of all users is both greater than the minimum-rate limit of itself System, and above problem model is difficult the nonconvex property solved in transmitted data rates constraint, this is because functionCaused by being overall nonlinear function and non-convex energy SINR functions.In addition to this, the above problem Model does not account for the Congestion Level SPCC of each MNO yet.
2, followed by a dynamically adapting congestion to which the method for each MNO data rate that standardize solves The shortcoming in problem model is stated, step is：
Join change method using a logarithm come model the problem of rewriteeing front：
Note
Target problem：
Restrictive condition：
In formula,Indicate energy of the user l by operator's m transmission datas when；Indicate that user l is passed by operator m The rate of transmission of data；Indicate maximum limitation power of the user l on operator m,Indicate user l for message transmission rate Minimum limitation.
Problem model after above-mentioned rewriting discloses the logarithm convexity attribute of standard interference function, while demonstrating functionIt is to convex standard interference function for all l and m.This is also meaned that for other arbitrary kinds For the data transmission rate function of class, problem model is solved, as long as meeting standard interference function contains logarithm convexity attribute Condition.
Solve revised problem model, it is also necessary to consider restrictive condition：
Herein in addition to restrictive conditionIt is not convex, other object functions and restrictive condition are equal For convex function.
It is finally based on convex approximate Lagrange duality, is convex limit by the non-convex restrictive condition relaxation in above problem model Condition processed, the MNO that this Lagrange duality can be used for that user is instructed to select less obstruction.Assuming that in a feasible field All meet for all lUnder conditions of provide the requirement of a series of independent data transfer rateIt connects down To consider the problem after following relaxation limitation：
Problem model：
Restrictive condition：
In formula,The rate transmitted by operator m for the user l after relaxation.
The Lagrange duality of this loose restricted problem can instruct user to select the MNO of minimum congestion.Gross energy The reduction of consumption can be realized by avoiding the interference of the multi-user on MNO.This means that selects one for users The MNO of less congestion is a better choice.Therefore a planning algorithm based on congestion is presented below, for solving this Problem model.
3, below based on the planning of congestion, an optimal solution of problem model is found out, step is：
Step 1) is executed respectively to 5) to each operator m, m=1,2 ..., M：
1) it is cycle-index to define k and t, and initialization k is 0, t 0；Initialize pm(0) it is any one of problem model Group meets the solution of restrictive condition,Initialize xm(0) it is pm(0) corresponding amount of blockage,
2) weight of user's l transmission rates on operator m is calculated：
3) it calculates：
In formula,The channel gain between loser and first of recipient is passed for j-th on operator m；For Intermediate function, expression formula are：
Judge whether to meet：
||pm(k+1)-pm(k)||2≤ ε and | | xm(k+1)-xm(k)||2≤ε
If not satisfied, k=k+1 is then calculated, return to step 3)；If satisfied, thening follow the steps 4)；Wherein, ε is one infinite Small positive number；
4) calculating the weighted value planned based on congestion is：
Wherein,For for the relevant Lagrange of Congestion Level SPCC Multiplier, Lagrange multiplier value is smaller, indicates that Congestion Level SPCC is smaller；
5) judge whether to meet | | rm(t+1)-rm(t)||2≤ ε, | | | |2It indicates European length, that is, indicates two vectors Between length；If satisfied, then stopping iteration；Otherwise, t=t+1, return to step 3 are calculated).
The above is only a preferred embodiment of the present invention, it should be pointed out that：For the ordinary skill people of the art For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered It is considered as protection scope of the present invention.

Claims (2)

1. a kind of more mobile operator method of rate allocation based on congestion cognition, which is characterized in that including step：
(1) model the problem of to transmit total energy consumption minimum target problem is built：
Formula (1) while meeting restrictive condition：
In formula, Indicate energy of the user l by operator's m transmission datas when； Table Show rates of the user l by operator's m transmission datas；M indicates that the quantity of operator, L indicate total number of users；Table Show the signal-to-noise ratio of user l on operator m；Indicate the message transmission rate between user l and operator m；It indicates to use Maximum limitation power of the family l on operator m,Indicate that user l limits the minimum of message transmission rate；
(2) it is convex restrictive condition by the non-convex restrictive condition relaxation in step (1), the restrictive condition after relaxation is：
In formula,The rate transmitted by operator m for the user l after relaxation；
(3) optimal solution of the problem of restrictive condition after meeting relaxation is found out by iteration model, including to each operator m Step 1) is executed respectively to 5), m=1,2 ..., M：
1) it is cycle-index to define k and t, and initialization k is 0, t 0；Initialize pm(0) item is limited for any one group of satisfaction of problem model The solution of part,Initialize xm(0) it is pm(0) corresponding amount of blockage,
2) weight of user's l transmission rates on operator m is calculated：
3) it calculates：
In formula,The channel gain between loser and first of recipient is passed for j-th on operator m；For centre Function, expression formula are：
Judge whether to meet：
||pm(k+1)-pm(k)||2≤ ε and | | xm(k+1)-xm(k)||2≤ε
If not satisfied, k=k+1 is then calculated, return to step 3)；If satisfied, thening follow the steps 4)；Wherein, ε is one infinitesimal Positive number；
4) calculating the weighted value planned based on congestion is：
Wherein, For with the relevant Lagrange multiplier of Congestion Level SPCC, glug Bright day multiplier value is smaller, indicates that Congestion Level SPCC is smaller；
5) judge whether to meet | | rm(t+1)-rm(t)||2≤ ε, | | | |2Indicate European length, i.e., between two vectors of expression Length；If satisfied, then stopping iteration；Otherwise, t=t+1, return to step 3 are calculated).
2. a kind of more mobile operator method of rate allocation based on congestion cognition according to claim 1, feature exist In the SINR calculation formula of first of recipient on the operator m are：
In formula,Indicate the white Gaussian noise of upper first of the recipient of operator m.
CN201810037653.5A 2018-01-16 2018-01-16 A kind of more mobile operator method of rate allocation based on congestion cognition Pending CN108430076A (en)

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Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105007210A (en) * 2015-08-05 2015-10-28 东南大学 Network virtualization frame in long term evolution system and resource blocks allocation method

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105007210A (en) * 2015-08-05 2015-10-28 东南大学 Network virtualization frame in long term evolution system and resource blocks allocation method

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
ZHAI XIANGPING等: "Rate-Constrained Energy Minimization in Networks with Multiple Mobile Network Operator Access", 《2017 IEEE GLOBAL COMMUNICATIONS CONFERENCE》 *
ZHU KUN等: "Wireless Virtualization as a Hierarchical Combinatorial Auction: An Illustrative Example", 《2017 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC)》 *

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