CN105898851B - The high energy efficiency Poewr control method of collection of energy is considered in super-intensive network - Google Patents
The high energy efficiency Poewr control method of collection of energy is considered in super-intensive network Download PDFInfo
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- CN105898851B CN105898851B CN201610404364.5A CN201610404364A CN105898851B CN 105898851 B CN105898851 B CN 105898851B CN 201610404364 A CN201610404364 A CN 201610404364A CN 105898851 B CN105898851 B CN 105898851B
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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
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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]
- H04W52/265—TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service] taking into account the quality of service QoS
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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
- H04W52/30—TPC using constraints in the total amount of available transmission power
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Abstract
The invention discloses the high energy efficiency Poewr control methods that collection of energy is considered in a kind of super-intensive network, including step 1: setting the double-deck heterogeneous network scene；Step 2: carrying out subchannel distribution；Step 3: carrying out initial power distribution to every sub-channels of macro base station and each Home eNodeB；Step 4: judging whether all Home eNodeB power distributions restrain or the number of iterations has been more than the upper limit；Step 5: acquiring the optimal transmission power distribution of this Home eNodeB；Step 6: terminating this iteration, the radio resource allocation of each Home eNodeB is completed, and waiting is dispatched next time.The present invention had both considered the QoS demand of femtocell user, so that the energy efficiency of heterogeneous network is obtained very high promotion further through Energy Harvest technology.
Description
Technical field
The invention belongs to communication engineering fields, are related to super-intensive network deployment scenarios, and in particular to a kind of super-intensive network
The middle high energy efficiency Poewr control method for considering collection of energy.
Background technique
In recent years, with the rapid development of development of Mobile Internet technology, demand of the user to mobile data flow is increasing,
Exponentially increase.Contradiction between the sharp increase of mobile data services demand and rare radio spectrum resources has been increasingly becoming
The significant challenge that existing macrocellular network faces.Since LTE network uses high band mostly, the signal covering of indoor environment is not very
It is ideal.For the business demand for meeting user, especially indoor business demand, disposing low power access points in macrocellular network can
Further further user with service its base station at a distance from, reduce signal reach user when decaying, enhance network it is effective cover,
Unserviceable area is reduced, and is macrocellular network streamed data business load, improves frequency spectrum resource utilization efficiency.
Compared with common macro base station, Femtocell have it is small in size, transmission power is low, user voluntarily installs and safeguards,
, especially there are outstanding advantage, thus Home eNodeB in the features such as plug and play on the problems such as mitigating macrocellular network severe load
With boundless application prospect, Home eNodeB is given greatly to pay close attention in major operator, equipment commercial city both at home and abroad at present.
Due to the huge business potential and prospect of Femtocell, the standardization bodies such as International Organization for standardization 3GPP, 3GPP2 are all given
Femtocell is largely to pay close attention to.
Statistical data shows that the energy consumption of mobile radio communication accounts for the 15%~20% of information industry total energy consumption, and with movement
The further expansion of communication network and user group scale, the energy consumption of mobile communications network still can keep the situation of rapid growth.
The considerations of for environmental protection and cutting operating costs, the communications industry are more and more for the energy consumption for reducing mobile communications network
Pay attention to.Although the energy consumption of Home eNodeB is much smaller with respect to the energy consumption of macro base station, since the deployment quantity of Home eNodeB is remote
Much higher than the deployment quantity of macro base station, therefore, the energy consumption of entire home base station network is also a very important number.Together
When, it is also that Home eNodeB can obtain one of an important factor for promoting that the application of power-saving technology is combined with Home eNodeB.It passes
The mobile device of system needs battery to carry out energy supply, this has physical capacity, needs the limitation such as charge or replace, and such as
Natural environment is relied on very much by the energy harvesting of wind energy, solar energy etc. and the energy collected is uncontrollable, in contrast, radio frequency energy
It is a kind of more stable effectively energy-provision way that amount, which collects (Energy Harvest), and the energy being collected into is believed depending on radio frequency
Number the distance between wavelength, collecting device and signal source etc..RF energy collection refers to that user can obtain from radiofrequency signal
Energy is taken, direct current signal is converted into and is stored, data and equipment operation are used for transmission.Femtocell is logical in future wireless network
It is played an important role in letter, the orthogonal frequency division multiplexing access technology based on Femtocell is also by main wireless communication
Standard uses.But because of the deficiency of frequency spectrum resource, frequency spectrum is shared between Macrocell and Femtocell in more situations, this
The interference being just inevitably generated between same layer and cross-layer.In heterogeneous network deployment, the user of Home eNodeB can therefrom be received
Collect noise etc. of the radiofrequency signal of energy in the interference signal of the macro base station of same frequency or Home eNodeB and environment.This patent
The heterogeneous network resource allocator model for considering Energy Harvest is established according to this feature, studies the efficiency of Home eNodeB
Problem.
Summary of the invention
The purpose of the present invention is to solve the above problem, the high energy that collection of energy is considered in a kind of super-intensive network is proposed
Poewr control method is imitated, is pair by the way that Energy Harvest is added using the method to each Home eNodeB power iteration
User provides the constraint of reliable time delay QoS guarantee, changes the home base station network resource distribution mode of conventional dense deployment, reaches
The effect for having arrived energy-efficient has the characteristics that dense network deployment energy saving, efficient, is the large-scale application of Home eNodeB
Bring technology guarantee.
The present invention has also comprehensively considered the diversity of the QoS requirement of user, to realize optimization Femtocell energy
The target of amount efficiency.General user is divided into time delay sensitive type user and time delay tolerance type user, and (business is essentially according to time delay here
Different user demands are distinguished in the tolerance of sensitive and time delay, for example the business such as voice and live video stream are very sensitive to time delay, text
Part downloading and the service such as mail have certain tolerance to time delay), time delay sensitive type user has a minimum QoS demand, and when
Prolonging tolerance type user does not have minimum transmission rate request.So this patent also considers house simultaneously when considering resource allocation
The QoS of front yard user is ensured.
The high energy efficiency Poewr control method that collection of energy is considered in super-intensive network of the invention, divides following steps:
Step 1: setting the double-deck heterogeneous network scene, have several with the Home eNodeB of frequency deployment under a macro base station, examine
Consider downlink, domestic consumer's (it is assumed that domestic consumer is closed access) of each Home eNodeB service equal amount, and divides
It Gei not Home eNodeB and its domestic consumer serviced number；
Step 2: setting overall system bandwidth and the number of subchannels with frequency, and to subchannel number and carry out subchannel point respectively
Match；
Step 3: setting the upper limit of emission power of Home eNodeB, and give every sub-channels of macro base station and each Home eNodeB
Initial power distribution is carried out, notices that the value of initial power distribution is comprehensive no more than corresponding base station maximum transmission power；
Step 4: judging whether all Home eNodeB power distributions are optimal point and (restrain, convergence refers to total energy
0.1%) the efficiency variation ratio of effect and last iteration is no more than or the number of iterations has been more than the upper limit, if it is, being transferred to
Step 6, otherwise, each domestic consumer calculates the interference of other Home eNodeB and macro base station that every sub-channels are subject to, reports
To servicing its Home eNodeB, and it is transferred to step 5；
Step 5: for each Home eNodeB, the QoS guarantee of the interference information and user that are received according to last round of iteration
And each Home eNodeB maximum transmission power limitation, the optimal transmission power of this Home eNodeB is acquired using following dichotomy
Distribution；
(1), setting the efficiency sufficiently large upper limit (10000000000bit/J) and lower limit (0), if every time in iterative process
Efficiency and the capacity acquired according to power and the ratio of energy consumption are not much different (ratio differs within 0.1%), then jump out two
Point-score iteration carries out step 6, otherwise, repeats step (2), (3)；
(2), energy valid value and subgradient algorithm as obtained in step (1) find out the power distribution of the Home eNodeB；
(3), the total capacity and total power consumption of the small base station are found out by power distribution in step (2)；
(4) if, the energy valid value that finds out in step (1) and the performance number product found out in step (3) be less than in step (3)
Capability value, reset efficiency upper limit value be step (1) in upper limit value and lower limit value sum half；Otherwise lower limit value is set as step
(1) half of upper limit value and lower limit value sum, is transferred to step 4 in；
Step 6: terminating this iteration, the radio resource allocation of each Home eNodeB is completed, and waiting is dispatched next time.
In affiliated step 1, the closed access of domestic consumer refers to that domestic consumer is only serviced by one family base station；
In affiliated step 2, subchannel distribution carries out subchannel distribution using the method for Round-Robin-Scheduling；
In affiliated step 4, the method for judging whether all Home eNodeB power distributions are optimal value is to guarantee this
All Femtocell of whole system obtained by iterating to calculate can imitate variation and be less than some specific ratio, the number of iterations
The upper limit is in any primary scheduling, and the maximum value of power distribution the number of iterations set by system is a constant,
Since entire isomery double-layer network is made of many Home eNodeB, each base station have make in oneself coverage area own
The maximized trend of user's energy efficiency, so whole network constitutes non-cooperative game, each Home eNodeB is according to every other
The transmission power of Home eNodeB determines oneself transmission power, and it is (in this state, any to be finally reached an optimal state
One participant changes alone the benefit that strategy all will not be oneself and is increased, referred to as Nash Equilibrium).Before step 4, need
Utilize game theory theory, it was demonstrated that in the model, the existence and uniqueness of Nash Equilibrium, the two characteristics can guarantee most
The presence of the figure of merit；
In the step 4, the energy valid value EE of k-th of Home eNodeB are as follows:
Wherein, K, F, N respectively indicate total Home eNodeB number, each femtocell user number and number of subchannels, pk,u,nFor
Transmission power in corresponding Home eNodeB subchannel, gk,u,nFor corresponding gain, PTIndicate that the circuit power of the Home eNodeB disappears
Consumption, ε0Indicating the power loss factor, latter three of denominator part are respectively the energy being collected by Energy Harvest technology,
Wherein η1, η2, η3The efficiency that Energy Harvest is carried out from useful new number, interference and noise is respectively indicated,It is k-th
The noise that front yard base station is subject to,It indicates total interference suffered by n-th of subchannel of k-th of Home eNodeB, is expressed as
SINRk,u,nIt indicates the Signal to Interference plus Noise Ratio in the subchannel, is expressed as
Wherein, gj,k,w,nTransmission power gain for j-th of Home eNodeB in k-th of Home eNodeB respective sub-channel, pw,n
The transmission power for being macro base station in respective sub-channel, gk,w,nFor corresponding gain.
The above technical method can be seen that technical method of the invention by comprehensively considering the Home eNodeB net of dense deployment
The Energy Harvest technology of network and the time delay qos requirement of user, pass through non-cooperative game Developing Tactics Home eNodeB
Transmission power, so that both ensure that Home eNodeB was used using energy efficiency as the sum of each Home eNodeB energy efficiency of parameter highest
The time delay qos requirement at family, and the efficiency of each Home eNodeB is improved, realize the energy-saving wireless resource pipe of home base station network
Reason.
The present invention has the advantages that
(1) present invention had both considered the QoS demand of femtocell user, made isomery further through Energy Harvest technology
The energy efficiency of network obtains very high promotion；
(2) Energy Harvest mechanism is added in the present invention in the scene of double-deck heterogeneous network deployment, so that efficiency has
There is a degree of promotion；
(3) present invention considers the QoS demand of user in resource allocation, guarantees the reliability of transmission；
When (4) present invention is with Home eNodeB progress resource allocation each in the double-deck heterogeneous network of Energy Harvest
The existence of the Nash Equilibrium of non-cooperative game model and the proof of uniqueness, and then the method for making efficiency approach optimal value has
Theory guarantees.
Detailed description of the invention
Fig. 1 is the flow chart in the present invention in embodiment about Home eNodeB power distribution；
Specific embodiment
It is clearer to describe technical method advantage of the invention, with reference to the accompanying drawing to specific implementation of the invention
Mode is described in further detail, it is clear that and described embodiment is section Example of the invention, rather than whole
Embodiment, according to an embodiment of the invention, those skilled in the art can be real on the basis of without creative work
Existing every other embodiment of the invention, belongs to protection scope of the present invention.
Fig. 1 is the flow chart in the present invention in embodiment about Home eNodeB power distribution, and each step is specific real
Mode is applied,
Step 101: setting the double-deck heterogeneous network scene, have 20 Home eNodeB with frequency deployment under a macro base station, often
A Home eNodeB services 3 domestic consumers；
Step 102: setting overall system bandwidth 90MHz and the number of subchannels 45 with frequency, and go forward side by side respectively to subchannel number
Row subchannel distribution；
Step 103: setting the upper limit of emission power 0.1W of Home eNodeB, and give each of macro base station and each Home eNodeB
Subchannel carries out initial power and distributes 0.001W；
Step 104: judging whether all Home eNodeB power distributions are optimal a little or the number of iterations has been more than upper
Limit, if it is, being transferred to step 110, otherwise, repeats step 105-109；
Step 105: each domestic consumer calculates the interference of other Home eNodeB and macro base station that every sub-channels are subject to,
It is reported to the Home eNodeB for servicing it；
Step 106: setting the efficiency sufficiently large upper limit 100000000000 and lower limit 0；
Step 107: the energy valid value and subgradient algorithm iteration that are determined by this find out the power distribution of the Home eNodeB；
Step 108: two points of values are carried out to the upper lower limit value of efficiency；
Step 109: efficiency and the ratio according to the power capacity acquired and energy consumption in each iterative process are judged, if phase
It is poor less then to jump out dichotomy iteration and carry out step 104, otherwise, repeat step 107,108；
Step 110: terminating this iteration, the radio resource allocation of each Home eNodeB is completed, and waiting is dispatched next time.
Claims (5)
1. the high energy efficiency Poewr control method of collection of energy is considered in super-intensive network, including the following steps:
Step 1: setting the double-deck heterogeneous network scene；
There are several with the Home eNodeB of frequency deployment under one macro base station, each Home eNodeB services the home-use of equal amount
Family, and respectively to Home eNodeB and its domestic consumer serviced number, domestic consumer is closed access；
Step 2: setting overall system bandwidth and the number of subchannels with frequency, and to subchannel number and carry out subchannel distribution respectively；
Step 3: setting the upper limit of emission power of Home eNodeB, and carried out to every sub-channels of macro base station and each Home eNodeB
The value summation of initial power distribution, initial power distribution is no more than corresponding base station maximum transmission power；
Step 4: judge whether all Home eNodeB power distributions restrain or the number of iterations has been more than the upper limit, if it is,
It is transferred to step 6, otherwise, each domestic consumer calculates the interference letter of other Home eNodeB and macro base station that every sub-channels are subject to
Breath is reported to the Home eNodeB for servicing it, and is transferred to step 5；
Step 5: for each Home eNodeB, the QoS guarantee of the interference information and user that are subject to according to last round of iteration and
Each Home eNodeB maximum transmission power limitation, the optimal transmission power point of this Home eNodeB is acquired using following dichotomy
Match；
(1), efficiency upper and lower bound is set, if efficiency and the capacity acquired according to power and general power disappear in iterative process every time
Within the ratio difference preset ratio of consumption, then jumps out execution step 6 and be otherwise transferred to step (2)；
(2), the efficiency as obtained in step (1) and subgradient algorithm find out the power distribution of the Home eNodeB；
(3), the total capacity and total power consumption of the Home eNodeB are found out by power distribution in step (2)；
(4) if, the efficiency that finds out in step (1) and the total power consumption product found out in step (3) be less than in step (3)
Capacity resets the half that efficiency upper limit value is upper limit value and lower limit value sum in step (1)；Otherwise lower limit value is set as in step (1)
The half of upper limit value and lower limit value sum, is transferred to step 4；
The efficiency EE of k-th of Home eNodeB are as follows:
Wherein, K, F, N respectively indicate total Home eNodeB number, each femtocell user number and number of subchannels, pk,u,nIt is corresponding
Transmission power in Home eNodeB subchannel, gk,u,nFor corresponding gain, PTIndicate the circuit power consumption of the Home eNodeB, ε0
Indicate the power loss factor, latter three of denominator part are respectively the energy being collected by energy collection technology, wherein η1, η2, η3
The efficiency that collection of energy is carried out from useful signal, interference and noise is respectively indicated,For the noise that k-th of Home eNodeB is subject to,It indicates total interference suffered by n-th of subchannel of k-th of Home eNodeB, is expressed as
SINRk,u,nIt indicates the Signal to Interference plus Noise Ratio in the subchannel, is expressed as
Wherein, gj,k,u,nTransmission power gain for j-th of Home eNodeB in k-th of Home eNodeB respective sub-channel, pw,nIt is macro
Transmission power of the base station in respective sub-channel, gk,w,nFor corresponding gain；
Step 6: terminating this iteration, the radio resource allocation of each Home eNodeB is completed, and waiting is dispatched next time.
2. the high energy efficiency Poewr control method of collection of energy is considered in super-intensive network according to claim 1, it is described
In step 1, the closed access of domestic consumer refers to that domestic consumer is only serviced by one family base station.
3. the high energy efficiency Poewr control method of collection of energy is considered in super-intensive network according to claim 1, it is described
In step 2, subchannel distribution is carried out using Round-Robin-Scheduling.
4. the high energy efficiency Poewr control method of collection of energy is considered in super-intensive network according to claim 1, it is described
In step 4, judge whether all Home eNodeB power distributions are optimal the method for value are as follows: obtained by current iteration calculating
All Home eNodeB of whole system can imitate variation and be less than predetermined ratio, then all Home eNodeB power distributions are optimal
Value.
5. the high energy efficiency Poewr control method of collection of energy is considered in super-intensive network according to claim 1, it is described
In step 4, the number of iterations upper limit is the maximum value of preset power distribution the number of iterations.
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| CN107046690A (en) * | 2016-11-29 | 2017-08-15 | 西南交通大学 | A kind of cognitive Femtocell mixture of networks frequency spectrum access method |
| CN107426775B (en) * | 2017-05-22 | 2020-05-08 | 东南大学 | Distributed multi-user access method for high-energy-efficiency heterogeneous network |
| CN107509202B (en) * | 2017-07-10 | 2020-05-08 | 东南大学 | Ultra-dense network resource allocation method based on variation prediction of access user number |
| CN107734700B (en) * | 2017-08-23 | 2021-09-14 | 南京邮电大学 | Network resource allocation method for guaranteeing QoS (quality of service) requirements of users in ultra-dense network |
| CN108712777B (en) * | 2018-03-16 | 2021-04-02 | 南京邮电大学 | Energy acquisition wireless transmission system power distribution method considering energy loss |
| CN108449149B (en) * | 2018-03-26 | 2020-12-15 | 南京邮电大学 | Energy acquisition small base station resource allocation method based on matching game |
| CN108966248B (en) * | 2018-06-15 | 2021-07-20 | 燕山大学 | Millimeter wave return stroke optimization method capable of being applied to millimeter wave wireless return stroke system |
| CN111328087B (en) * | 2018-12-17 | 2021-09-14 | 上海大学 | Deep learning-based high-energy-efficiency heterogeneous network sub-channel distribution and power distribution method |
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