CN109451569A - A kind of resource allocation methods wirelessly taken in energy heterogeneous network - Google Patents

A kind of resource allocation methods wirelessly taken in energy heterogeneous network Download PDF

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Publication number
CN109451569A
CN109451569A CN201811535046.8A CN201811535046A CN109451569A CN 109451569 A CN109451569 A CN 109451569A CN 201811535046 A CN201811535046 A CN 201811535046A CN 109451569 A CN109451569 A CN 109451569A
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China
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base station
subchannel
user
energy
power
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隆青月
冯梦婷
张海君
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Beijing University of Technology
University of Science and Technology Beijing USTB
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Beijing University of Technology
University of Science and Technology Beijing USTB
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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
    • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
    • H04W52/241—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account channel quality metrics, e.g. SIR, SNR, CIR, Eb/lo
    • 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
    • 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
    • H04W52/346—TPC management, i.e. sharing limited amount of power among users or channels or data types, e.g. cell loading distributing total power among users or channels

Abstract

The present invention provides a kind of resource allocation methods wirelessly taken in energy heterogeneous network, can reduce energy consumption to the maximum extent, maximize energy efficiency.The described method includes: the gross energy being collected into according to system determines the Optimized model of maximization system total energy efficiency in conjunction with cross-layer interference constraints condition；Determine subchannel distribution matrix；According to determining subchannel distribution matrix, it is based on Lagrange duality decomposition method, Optimized model is converted into the criteria optimization problem with KKT condition about power, Lagrange multiplier is updated using subgradient algorithm, obtains power distribution matrix；According to obtained subchannel distribution matrix and power distribution matrix computing system total energy efficiency, if currently available power distribution matrix is optimal power allocation scheme with the preceding primary difference updated between the system total energy efficiency calculated in preset error range.The present invention relates to wireless communication fields.

Description

A kind of resource allocation methods wirelessly taken in energy heterogeneous network
Technical field
The present invention relates to wireless communication fields, particularly relate to a kind of resource allocation methods wirelessly taken in energy heterogeneous network.
Background technique
Wireless communication technique development very fast in recent decades is advanced, and the present 5G epoch have arrived.5G technology is A kind of more intelligent completely new wireless communication technique with stronger adaptive faculty, compared to 4G, 5G rate, energy efficiency, Resource utilization, coverage area and service quality etc., which have, significantly to be promoted, and can satisfy different business needs It asks and adapts to various network environments.With the arrival of 5G network, the extensive of mobile communication equipment is popularized, and people are in Service Quality Amount is also quickly increasing including the demand in terms of transmission capacity and data rate.It is a large amount of each that current numerous studies are conceived to deployment The base-station node of seed type improves the spectrum efficiency and coverage area of communication network.As 5G or more key technology it One, non-orthogonal multiple (NOMA) can obtain higher spectrum efficiency.And heterogeneous network be suggested meet 5G and with The great demand of mobile data service afterwards.Isomery small-sized honeycomb network greatly alleviates user data demand and exponentially increases Long pressure.Heterogeneous network can by disposing the low-power transmissions node such as small base station (BS) in macro base station coverage area, Effectively improve the performance of cordless communication network.
However, heterogeneous network is also faced with lot of challenges, such as energy consumption more and more prominent with the dense deployment of base station Problem and serious interference.In Wireless Heterogeneous Networks, energy resource is consumed with very fast speed, wherein the energy of base station Amount consumption is even more serious, accounts about 60% to the 80% or so of system total energy consumption, and energy consumption is increasing every year, causes The increase of operation cost.Energy consumption problem is extremely urgent at present, and energy resource is also required to reasonably to be distributed and benefit With.To guarantee coverage area and enhancing signal, a variety of different types of networks of heterogeneous network converged have been obviously improved communication system The spectrum efficiency of system.And this is also that heterogeneous network brings huge challenge, the cross-layer interference between each base station can reduce network Validity so that service quality is had a greatly reduced quality.Therefore, when carrying out resource allocation to heterogeneous network, interference is limited It is necessary.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of resource allocation methods wirelessly taken in energy heterogeneous network, can Energy consumption is reduced to the maximum extent, maximizes energy efficiency.
In order to solve the above technical problems, the embodiment of the present invention provides a kind of resource allocation side wirelessly taken in energy heterogeneous network Method, comprising:
S101 obtains the gross energy that system passes through energy harvesting module collection；
S102, the gross energy being collected into according to system determine maximization system gross energy in conjunction with cross-layer interference constraints condition The Optimized model of efficiency；
S103 is obtained according to the gain of each base station user and interchannel so that energy efficiency is maximum on cochannel Multiple users, and determine the matching relationship between base station user and channel, subchannel distribution matrix is determined according to the matching relationship, Wherein, the base station is small base station；
S104 is based on Lagrange duality decomposition method, Optimized model is converted according to determining subchannel distribution matrix For the criteria optimization problem with KKT condition about power, Lagrange multiplier is updated using subgradient algorithm, obtains power point With matrix；
S105, according to obtained subchannel distribution matrix and power distribution matrix computing system total energy efficiency, if with preceding The difference between the system total energy efficiency calculated is once updated in preset error range, then currently available power distribution Matrix is optimal power allocation scheme.
Further, the gross energy that system is collected into indicates are as follows:
Wherein, the gross energy that H (S, P) expression system is collected into；S indicates subchannel distribution matrix；P indicates power distribution square Battle array；MkIndicate the user terminal number of k-th of base station；N indicates the number of subchannel, and K indicates the number of base station；sk,m,nFor in S Element, sk,m,nIndicate the connection of the user m and subchannel n of base station k；pk,m,nFor the element in P, pk,m,nIndicate subchannel n The transimission power of the user m of upper base station k；hk,j,m,nFor the channel gain of the user m to base station j of base station k on subchannel n；λj,nFor The collection of energy coefficient of the energy harvesting module of base station j on subchannel n.
Further, the gross energy being collected into according to system determines in conjunction with cross-layer interference constraints condition and maximizes system System total energy efficiency Optimized model include:
Determine the rate r of the user m of base station k on subchannel nk,m,n；
The gross energy being collected into according to system determines total system power consumption U (S, P)；
According to the rate r of the user m of base station k on obtained subchannel nk,m,nAnd total system power consumption U (S, P), determine system It unites total energy efficiency EE (S, P)；
In conjunction with cross-layer interference constraints condition, system total energy efficiency EE (S, P) is modeled, maximizes system gross energy The Optimized model of efficiency.
Further, on subchannel n the user m of base station k rate rk,m,nIt indicates are as follows:
rk,m,n=Bsclog2(1+SINRk,m,n)
Wherein, BscIndicate the bandwidth of every sub-channels；SINRk,m,nIndicate that the signal of the user m of base station k on subchannel n is dry Disturb plus noise ratio；hk,k,m,nIndicate the channel gain of the user m to base station k of base station k on subchannel n；sk,r,nFor the element in S, sk,r,nIndicate the connection of the user r and subchannel n of base station k；pk,r,nFor the element in P, pk,r,nIndicate base on subchannel n Stand k user r transimission power；For the general power of base station j on subchannel n；sj,r,nFor the element in S, sj,r,nIndicate the connection of the user r and subchannel n of base station j；pj,r,nFor the element in P, pj,r,nIndicate base on subchannel n Stand j user r transimission power；σ2Indicate additive white Gaussian noise；
Total system power consumption U (S, P) is indicated are as follows:
Further, system total energy efficiency EE (S, P) is indicated are as follows:
Wherein,For the total rate of system；For system total power.
Further, the Optimized model indicates are as follows:
Wherein,Indicate the lower limit using the rate of the user m of base station k on subchannel nObtained system is total Rate；U (S, P) indicates total system power consumption；T is the efficiency parameter introduced for reducing computation complexity；
The qualifications χ of the Optimized model is indicated are as follows:
Wherein, Pk,maxIndicate the maximum transmission power of base station k；Rk,minIndicate the minimum transmission rate of base station k；ImaxIt indicates Maximum cross-layer interference constraints value；hk,K+1,nIndicate the gain from base station k to macro base station on subchannel n, wherein macro base station is K + 1 base station.
Further, on subchannel n the rate of the user m of base station k lower limitIt indicates are as follows:
Wherein, α, β are the parameter that computation rate lower limit introduces；Indicate the letter of the son obtained in upper primary iteration The value of the signal interference plus noise ratio of the user m of base station k on road n.
Further, the gain according to each base station user and interchannel obtains so that can dose-effect on cochannel The maximum multiple users of rate, and determine the matching relationship between base station user and channel, subchannel is determined according to the matching relationship Allocation matrix includes:
The energy efficiency formula that the gain of each base station user and interchannel is brought on the k subchannel n of base station is counted It calculates, acquisition enables to maximum two users of energy efficiency on the k subchannel n of base station；Wherein, the energy on base station k subchannel n Effectiveness formula EEk,nIt indicates are as follows:
Maximum two users of energy efficiency on the k subchannel n of base station are enabled to according to acquisition, determine that base station k is believed User's matching relationship on road n；
According to user's matching relationship on determining base station k subchannel n, subchannel distribution matrix is determined.
Further, described according to determining subchannel distribution matrix, it is based on Lagrange duality decomposition method, will be optimized Model conversion is the criteria optimization problem with KKT condition about power, updates Lagrange multiplier using subgradient algorithm, obtains Include: to power distribution matrix
According to determining subchannel distribution matrix, by step-length δ1Update Lagrangian μk, and drawing is acquired by analogy method Ge Lang operator νkWith the more new formula of ξ, the more new formula of Lagrangian are as follows:
Wherein,For according to Lagrangian, the power of the user m of base station k on determining subchannel n；For It usesThe rate being calculated；δ1, δ2And δ3Indicate step-length；Rk,maxIndicate the peak transfer rate of base station k；I indicates i-th Secondary iteration；
According to Lagrangian μk、νk, ξ, determine the power of the user m of base station k on subchannel nObtain power Allocation matrix.
Further,It indicates are as follows:
Wherein,For according to Lagrangian, the power of the user r of base station k on determining subchannel n；For According to Lagrangian, the power of the user t of base station j on determining subchannel n；hj,k,t,nIndicate base station j on subchannel n Channel gain of the user t to base station k；hj,j,t,nIndicate the channel gain of the user t to base station j of base station j on subchannel n；It is the shorthand in order to keep denominator easier；For power useSignal interference when expression Plus noise ratio.
The advantageous effects of the above technical solutions of the present invention are as follows:
In above scheme, determined maximum according to the gross energy of energy harvesting module collection in conjunction with cross-layer interference constraints condition The Optimized model of change system total energy efficiency；In the case where subchannel distribution matrix determines, principle is turned to efficiency maximum, is adopted With Lagrange duality decomposition method, the Optimized model of maximum efficiency is converted into the standard with KKT condition about power Optimization problem updates Lagrange multiplier using subgradient algorithm, the power optimized allocation plan of user terminal is determined, thus maximum The economic benefit for reducing to limit energy consumption, improving energy efficiency and mobile virtual network operator.
Detailed description of the invention
Fig. 1 is the flow diagram provided in an embodiment of the present invention for wirelessly taking the resource allocation methods in energy heterogeneous network.
Specific embodiment
To keep the technical problem to be solved in the present invention, technical solution and advantage clearer, below in conjunction with attached drawing and tool Body embodiment is described in detail.
As shown in Figure 1, the resource allocation methods provided in an embodiment of the present invention wirelessly taken in energy heterogeneous network, comprising:
S101 obtains the gross energy that system passes through energy harvesting module collection；
S102, the gross energy being collected into according to system determine maximization system gross energy in conjunction with cross-layer interference constraints condition The Optimized model of efficiency；
S103 is obtained according to the gain of each base station user and interchannel so that energy efficiency is maximum on cochannel Multiple users, and determine the matching relationship between base station user and channel, subchannel distribution matrix is determined according to the matching relationship, Wherein, the base station is small base station；
S104 is based on Lagrange duality decomposition method, Optimized model is converted according to determining subchannel distribution matrix For the criteria optimization problem with KKT (Karush-Kuhn-Tucker) condition about power, is updated and drawn using subgradient algorithm Ge Lang multiplier obtains power distribution matrix；
S105, according to obtained subchannel distribution matrix and power distribution matrix computing system total energy efficiency, if with preceding The difference between the system total energy efficiency calculated is once updated in preset error range, then currently available power distribution Matrix is optimal power allocation scheme.
The resource allocation methods in energy heterogeneous network are wirelessly taken described in the embodiment of the present invention, are received according to energy harvesting module The gross energy of collection determines the Optimized model of maximization system total energy efficiency in conjunction with cross-layer interference constraints condition；In subchannel point In the case where determining with matrix, principle is turned to efficiency maximum, using Lagrange duality decomposition method, by the excellent of maximum efficiency Changing model conversion is the criteria optimization problem with KKT condition about power, updates Lagrange multiplier using subgradient algorithm, The power optimized allocation plan of user terminal is determined, to reduce energy consumption to the maximum extent, improve energy efficiency and shifting The economic benefit of dynamic virtual operator.
Wirelessly taking in the present embodiment can communicate (Simultaneous Wireless Information and Power Transfer, SWIPT) it is a kind of novel wireless communication type, energy can be collected from radio wave.Therefore, it wirelessly takes Can communicate can acquire energy by energy harvesting module while transmitting radio signal with simultaneous transmission wireless messages and energy Amount, provides energy for wireless device, increases the stand-by time of system, greatly reduces the energy consumption of network, realizes wireless communication system It unites energy-saving and environment-friendly target, SWIPT, which is applied to communication system, can be effectively reduced system energy cost.
The resource allocation methods provided by the embodiment wirelessly taken in energy heterogeneous network in order to better understand, carry out it in detail Describe in detail bright, the method can specifically include following steps:
A11, initiation parameter
In the present embodiment, centered on a macro base station (MBS), within the scope of macro base station to small base station (SBS) and user into Row is spread a little at random, it is assumed that 6 small base station (abbreviation base station) and 70 user terminals divide in the region centered on macro base station Cloth, and the parameter of base station and user terminal is initialized, the parameter includes but is not limited to: the user m of base station k on subchannel n Transimission power pk,m,n, k-th base station user terminal number Mk, system bandwidth BW, N number of subchannel, the bandwidth of every sub-channels Bsc, on subchannel n the user m to base station j of base station k channel gain hk,j,m,nWhile initializing subchannel distribution matrix S and function Rate allocation matrix P.
In the present embodiment, the element in subchannel distribution matrix S can use subchannel distribution index sk,m,nIt indicates, sk,m,n The connection for indicating the user m and subchannel n of base station k, in a particular application, when the user m of base station k is assigned to subchannel n When upper, sk,m,n=1；When the user m of base station k is unallocated on subchannel n, sk,m,n=0.
In the present embodiment, the element of power distribution matrix P can use pk,m,nIt indicates, pk,m,nIndicate base station k on subchannel n User m transimission power.
A12 obtains the gross energy that system passes through energy harvesting module collection
In the present embodiment, the gross energy that system is collected into is indicated are as follows:
Wherein, the gross energy that H (S, P) expression system is collected into；S indicates subchannel distribution matrix；P indicates power distribution square Battle array；MkIndicate the user terminal number of k-th of base station；N indicates the number of subchannel, and K indicates the number of base station；sk,m,nFor in S Element, sk,m,nIndicate the connection of the user m and subchannel n of base station k；pk,m,nFor the element in P, pk,m,nIndicate subchannel n The transimission power of the user m of upper base station k；hk,j,m,nFor the channel gain of the user m to base station j of base station k on subchannel n；λj,nFor The collection of energy coefficient of the energy harvesting module of base station j, λ on subchannel nj,nFor the constant between 0 to 1；Indicate that the user m of base station k on subchannel n is collected into from the radio signal of other base stations Energy.
A13 determines the rate of the user m of base station k on subchannel n
In the present embodiment, the rate r of the user m of base station k on subchannel nk,m,nIt is one and signal interference plus noise ratio (Signal to Interference plus Noise Ratio, SINR) related logarithmic function, wherein rk,m,nIt indicates are as follows:
rk,m,n=Bsclog2(1+SINRk,m,n)
Wherein, BscIndicate the bandwidth of every sub-channels；SINRk,m,nIndicate that the signal of the user m of base station k on subchannel n is dry Disturb plus noise ratio；hk,k,m,nIndicate the channel gain of the user m to base station k of base station k on subchannel n；sk,r,nFor the element in S, sk,r,nIndicate the connection of the user r and subchannel n of base station k；pk,r,nFor the element in P, pk,r,nIndicate base on subchannel n Stand k user r transimission power；For the general power of base station j on subchannel n；sj,r,nFor the element in S, sj,r,nIndicate the connection of the user r and subchannel n of base station j；pj,r,nFor the element in P, pj,r,nIndicate base on subchannel n Stand j user r transimission power；σ2Indicate additive white Gaussian noise.
A14 determines system total energy efficiency
In the present embodiment, in order to determine that system total energy efficiency, the gross energy being first collected into according to system determine that system is total Power consumption U (S, P), wherein U (S, P) is indicated are as follows:
Then, according to the rate r of the user m of base station k on obtained subchannel nk,m,nAnd total system power consumption U (S, P), really Determine system total energy efficiency EE (S, P), EE (S, P) is indicated are as follows:
Wherein,For the total rate of system,For system total power, compared to collection The energy that energy, the circuit power very little of small base station, therefore general power subtract collection is total power consumption.
A15 determines the lower limit of the rate of the user m of base station k on subchannel n
In the present embodiment, using inequality (αk,m,nlog2(SINRk,m,n)+βk,m,n≤log2(1+SINRk,m,n)) think of Think, determines the lower limit of the rate of the user m of base station k on subchannel nWherein,It indicates are as follows:
Wherein, α, β are the parameter that computation rate lower limit introduces；Indicate the letter of the son obtained in upper primary iteration The value of the signal interference plus noise ratio of the user m of base station k on road n.
In the present embodiment, work as αk,m,n、βk,m,nWhen for above-mentioned formula, for arbitrary SINRk,m,n>=0, inequality αk,m, nlog2(SINRk,m,n)+βk,m,n≤log2(1+SINRk,m,n) set up.
A16 models system total energy efficiency EE (S, P), maximizes the Optimized model of system total energy efficiency
In the present embodiment, according to the lower limit of the rate of the user m of base station k on subchannel nIn conjunction with cross-layer interference constraints Condition models system total energy efficiency EE (S, P), maximizes the Optimized model of system total energy efficiency, wherein described Optimized model indicates are as follows:
Wherein,Indicate the total rate of system obtained using the lower limit of the rate of the user m of base station k on subchannel n； U (S, P) indicates total system power consumption；T is the efficiency parameter introduced for reducing computation complexity, definitionS*And P*Respectively optimal subchannel distribution matrix and optimal power allocation matrix,For the total rate of system obtained under optimal distributing scheme, U (S*,P*) it is that obtained system is total under optimal distributing scheme Power consumption, t*For the value i.e. system maximum power efficiency of the efficiency parameter t obtained under optimal distributing scheme；Parameter t can be according to repeatedly It is determined for algorithm, initiation parameter t first solves above-mentioned optimization problem at this value, obtains the subchannel point under current iteration With matrix and power distribution matrix, so that the energy efficiency values under calculating current iteration, the i.e. value of t, are brought into next iteration In, i.e., the value of t is the energy valid value of last iterative calculation in each iterative target function.Until the energy dose-effect that current iteration calculates The error between energy efficiency values that rate value and preceding an iteration obtain is less than the error range of setting, i.e. energy efficiency values reach Convergence.
In the present embodiment, the qualifications of the Optimized model are indicated are as follows:
Wherein, Pk,maxIndicate the maximum transmission power of base station k；Rk,minIndicate the minimum transmission rate of base station k；ImaxIt indicates Maximum cross-layer interference constraints value；hk,K+1,nIndicate the gain from base station k to macro base station on subchannel n, wherein macro base station is K + 1 base station；First and second qualifications are power constraint, and third and the 4th qualifications guarantee most two User distributes on same sub-channels, and the 5th qualifications through-rate constraint guarantees service quality, the 6th restriction article Part is cross-layer interference constraints.
A17 is obtained according to the gain of each base station user and interchannel so that energy efficiency is maximum more on cochannel A user, and determine the matching relationship between base station user and channel, subchannel distribution matrix is determined according to the matching relationship
In the present embodiment, the gain of each base station user and interchannel is brought into energy efficiency on the k subchannel n of base station Formula is calculated, and acquisition enables to maximum two users of energy efficiency on the k subchannel n of base station；Wherein, k in base station is believed Energy efficiency formula EE on road nk,nIt indicates are as follows:
Maximum two users of energy efficiency on the k subchannel n of base station are enabled to according to acquisition, determine that base station k is believed User's matching relationship on road n；
According to user's matching relationship on determining base station k subchannel n, subchannel distribution matrix is determined.
The subchannel distribution matrix that A18, fixing step A17 are obtained is based on Lagrange duality decomposition method, will optimize mould Type is converted to the criteria optimization problem with KKT condition about power, updates Lagrange multiplier using subgradient algorithm
In the present embodiment, the subchannel distribution matrix that fixing step A17 is obtained, by step-length δ1Update Lagrangian μk, And Lagrangian ν can similarly be acquired by analogy methodkWith the more new formula of ξ, the more new formula of Lagrangian are as follows:
Wherein,For according to Lagrangian, the power of the user m of base station k on determining subchannel n；For It usesThe rate being calculated；μk(i+1) indicate that Lagrange when i+1 time iteration for being associated with qualifications is calculated Son；δ1, δ2And δ3Indicate step-length；I indicates that the number of iterations, each iteration Lagrangian update primary.
A19, according to Lagrangian μk、νk, ξ, determine the power of the user m of base station k on subchannel nTo Update power distribution matrix, whereinIt indicates are as follows:
Wherein,For according to Lagrangian, the power of the user r of base station k on determining subchannel n；For According to Lagrangian, the power of the user t of base station j on determining subchannel n；hj,k,t,nIndicate base station j on subchannel n Channel gain of the user t to base station k；hj,j,t,nIndicate the channel gain of the user t to base station j of base station j on subchannel n；It is the shorthand in order to keep denominator easier；For power useSignal interference when expression Plus noise ratio.
In the present embodiment, with adding up for the number of iterations i, system energy efficiency can gradually be intended to a definite value, thus Realize the optimization to power distribution.
A20, the power distribution matrix that the subchannel distribution matrix and A19 obtained by step A17 obtains after updating, calculates this When system energy efficiency EE (S, P), update the parameter t that introduces in step A16.
A21, by step A20 update after obtain parameter t i.e. at this time the energy efficiency of system with it is preceding it is primary update obtain be The energy efficiency of system is compared, if the system total energy efficiency and the preceding primary energy dose-effect for updating calculating that are calculated after updating Difference between rate is in preset error range, then currently available power is optimal power allocation scheme；Otherwise, continue to hold Row step A18, until the system total energy efficiency recalculated and the preceding primary difference updated between the energy efficiency calculated Value (namely tends to definite value) in preset error range, at this point, reaching optimum optimization；If after reaching maximum number of iterations, Do not reach optimum optimization still, then returns to step A17.The optimal subchannel and power distribution that will be acquired, bring system into Energy efficiency is calculated, and the maximum energy efficiency values of system are obtained.
It should be noted that, in this document, relational terms such as first and second and the like are used merely to a reality Body or operation are distinguished with another entity or operation, are deposited without necessarily requiring or implying between these entities or operation In any actual relationship or order or sequence.
The above is a preferred embodiment of the present invention, it is noted that for those skilled in the art For, without departing from the principles of the present invention, several improvements and modifications can also be made, these improvements and modifications It should be regarded as protection scope of the present invention.

Claims (10)

1. a kind of resource allocation methods wirelessly taken in energy heterogeneous network characterized by comprising
S101 obtains the gross energy that system passes through energy harvesting module collection；
S102, the gross energy being collected into according to system determine maximization system total energy efficiency in conjunction with cross-layer interference constraints condition Optimized model；
S103 is obtained according to the gain of each base station user and interchannel so that energy efficiency is maximum multiple on cochannel User, and determine the matching relationship between base station user and channel, subchannel distribution matrix is determined according to the matching relationship, In, the base station is small base station；
S104 is based on Lagrange duality decomposition method, Optimized model is converted to pass according to determining subchannel distribution matrix In the criteria optimization problem with KKT condition of power, Lagrange multiplier is updated using subgradient algorithm, obtains power distribution square Battle array；
S105, according to obtained subchannel distribution matrix and power distribution matrix computing system total energy efficiency, if with preceding primary The difference between the system total energy efficiency calculated is updated in preset error range, then currently available power distribution matrix For optimal power allocation scheme.
2. the resource allocation methods according to claim 1 wirelessly taken in energy heterogeneous network, which is characterized in that system is collected The gross energy arrived indicates are as follows:
Wherein, the gross energy that H (S, P) expression system is collected into；S indicates subchannel distribution matrix；P indicates power distribution matrix；Mk Indicate the user terminal number of k-th of base station；N indicates the number of subchannel, and K indicates the number of base station；sk,m,nFor the element in S, sk,m,nIndicate the connection of the user m and subchannel n of base station k；pk,m,nFor the element in P, pk,m,nIndicate base on subchannel n Stand k user m transimission power；hk,j,m,nFor the channel gain of the user m to base station j of base station k on subchannel n；λj,nFor sub- letter The collection of energy coefficient of the energy harvesting module of base station j on road n.
3. the resource allocation methods according to claim 2 wirelessly taken in energy heterogeneous network, which is characterized in that the basis The gross energy that system is collected into determines the Optimized model packet of maximization system total energy efficiency in conjunction with cross-layer interference constraints condition It includes:
Determine the rate r of the user m of base station k on subchannel nk,m,n；
The gross energy being collected into according to system determines total system power consumption U (S, P)；
According to the rate r of the user m of base station k on obtained subchannel nk,m,nAnd total system power consumption U (S, P), determine that system is total Energy efficiency EE (S, P)；
In conjunction with cross-layer interference constraints condition, system total energy efficiency EE (S, P) is modeled, maximizes system total energy efficiency Optimized model.
4. the resource allocation methods according to claim 3 wirelessly taken in energy heterogeneous network, which is characterized in that subchannel n The rate r of the user m of upper base station kk,m,nIt indicates are as follows:
rk,m,n=Bsclog2(1+SINRk,m,n)
Wherein, BscIndicate the bandwidth of every sub-channels；SINRk,m,nIndicate that the signal interference of the user m of base station k on subchannel n adds Noise ratio；hk,k,m,nIndicate the channel gain of the user m to base station k of base station k on subchannel n；sk,r,nFor the element in S, sk,r,n Indicate the connection of the user r and subchannel n of base station k；pk,r,nFor the element in P, pk,r,nIndicate base station k on subchannel n The transimission power of user r；For the general power of base station j on subchannel n；sj,r,nFor the element in S, sj,r,n Indicate the connection of the user r and subchannel n of base station j；pj,r,nFor the element in P, pj,r,nIndicate base station j on subchannel n The transimission power of user r；σ2Indicate additive white Gaussian noise；
Total system power consumption U (S, P) is indicated are as follows:
5. the resource allocation methods according to claim 4 wirelessly taken in energy heterogeneous network, which is characterized in that system total energy Amount efficiency EE (S, P) is indicated are as follows:
Wherein,For the total rate of system；For system total power.
6. the resource allocation methods according to claim 5 wirelessly taken in energy heterogeneous network, which is characterized in that the optimization Model is expressed as:
Wherein,Indicate the lower limit using the rate of the user m of base station k on subchannel nThe total rate of obtained system；U (S, P) indicates total system power consumption；T is the efficiency parameter introduced for reducing computation complexity；
The qualifications χ of the Optimized model is indicated are as follows:
Wherein, Pk,maxIndicate the maximum transmission power of base station k；Rk,minIndicate the minimum transmission rate of base station k；ImaxIndicate maximum Cross-layer interference constraints value；hk,K+1,nIndicate the gain from base station k to macro base station on subchannel n, wherein macro base station is K+1 Base station.
7. the resource allocation methods according to claim 6 wirelessly taken in energy heterogeneous network, which is characterized in that subchannel n The lower limit of the rate of the user m of upper base station kIt indicates are as follows:
Wherein, α, β are the parameter that computation rate lower limit introduces；It indicates on the subchannel n obtained in upper primary iteration The value of the signal interference plus noise ratio of the user m of base station k.
8. the resource allocation methods according to claim 7 wirelessly taken in energy heterogeneous network, which is characterized in that the basis The gain of each base station user and interchannel obtains so that maximum multiple users of energy efficiency on cochannel, and determines base The matching relationship stood between user and channel determines that subchannel distribution matrix includes: according to the matching relationship
The energy efficiency formula that the gain of each base station user and interchannel is brought on the k subchannel n of base station is calculated, is obtained It takes and enables to maximum two users of energy efficiency on the k subchannel n of base station；Wherein, the energy efficiency on base station k subchannel n Formula EEk,nIt indicates are as follows:
Maximum two users of energy efficiency on the k subchannel n of base station are enabled to according to acquisition, are determined on the k subchannel n of base station User's matching relationship；
According to user's matching relationship on determining base station k subchannel n, subchannel distribution matrix is determined.
9. the resource allocation methods according to claim 8 wirelessly taken in energy heterogeneous network, which is characterized in that the basis Determining subchannel distribution matrix is based on Lagrange duality decomposition method, Optimized model is converted to having about power The criteria optimization problem of KKT condition updates Lagrange multiplier using subgradient algorithm, and obtaining power distribution matrix includes:
According to determining subchannel distribution matrix, by step-length δ1Update Lagrangian μk, and it is bright by analogy method to acquire glug Day operator νkWith the more new formula of ξ, the more new formula of Lagrangian are as follows:
Wherein,For according to Lagrangian, the power of the user m of base station k on determining subchannel n；To useThe rate being calculated；δ1, δ2And δ3Indicate step-length；Rk,maxIndicate the peak transfer rate of base station k；I indicates that i-th changes Generation；
According to Lagrangian μk、νk, ξ, determine the power of the user m of base station k on subchannel nObtain power distribution square Battle array.
10. the resource allocation methods according to claim 9 wirelessly taken in energy heterogeneous network, which is characterized in thatTable It is shown as:
Wherein,For according to Lagrangian, the power of the user r of base station k on determining subchannel n；According to Lagrangian, the power of the user t of base station j on determining subchannel n；hj,k,t,nIndicate the user of base station j on subchannel n Channel gain of the t to base station k；hj,j,t,nIndicate the channel gain of the user t to base station j of base station j on subchannel n；It is the shorthand in order to keep denominator easier；For power useSignal interference when expression Plus noise ratio.
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