CN108307510A - A kind of power distribution method in isomery subzone network - Google Patents
A kind of power distribution method in isomery subzone network Download PDFInfo
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- CN108307510A CN108307510A CN201810165880.6A CN201810165880A CN108307510A CN 108307510 A CN108307510 A CN 108307510A CN 201810165880 A CN201810165880 A CN 201810165880A CN 108307510 A CN108307510 A CN 108307510A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/04—Wireless resource allocation
- H04W72/044—Wireless resource allocation based on the type of the allocated resource
- H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/50—Allocation or scheduling criteria for wireless resources
- H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/50—Allocation or scheduling criteria for wireless resources
- H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
- H04W72/541—Allocation or scheduling criteria for wireless resources based on quality criteria using the level of interference
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The present invention provides the power distribution method in a kind of isomery subzone network, can improve the energy efficiency and handling capacity of cell to greatest extent.The method includes：It obtains delay parameter and the energy efficiency of small base station is determined according to the delay parameter of acquisition；Power distribution problems are described as to maximize the energy efficiency of small base station；Determine transmission power when power distribution problems reach nash banlance；Based on determining transmission power, regards the energy efficiency in power distribution as return value function in Q study, optimal power allocation scheme is solved by multi-user's Q learning algorithms based on guess.The present invention is operated suitable for power distribution.
Description
Technical field
The present invention relates to mobile communication field, the power distribution method in a kind of isomery subzone network is particularly related to.
Background technology
With the rapid development of science and technology, the arriving in 5G epoch is not remote, as more and more Intelligent mobile equipments connect
Enter wireless network, frequency resource is fewer and fewer, and white elephant is caused to macrocell.The deployment of small base station, which can mitigate, to be come
Current-carrying capacity is crossed from macrocell, increases power system capacity.But the interference of same layer and cross-layer is increasingly severe, so as to cause system
The reduction of capacity and service quality (QoS).In order to preferably handle such case, a kind of more reasonable efficient power distribution side
Method needs are suggested.In orthogonal frequency division multiple access spectrum sharing network, there is a large amount of research to be used for mitigating interference, improve
Energy efficiency.But in the prior art, there are no using deferred constraint come the research of (QoS) of improving service quality.
Invention content
The technical problem to be solved in the present invention is to provide the power distribution methods in a kind of isomery subzone network, existing to solve
Have present in technology not yet using deferred constraint come the problem of improving service quality.
In order to solve the above technical problems, the embodiment of the present invention provides the power distribution method in a kind of isomery subzone network,
Including：
It obtains delay parameter and the energy efficiency of small base station is determined according to the delay parameter of acquisition；
Power distribution problems are described as to maximize the energy efficiency of small base station；
Determine transmission power when power distribution problems reach nash banlance；
Based on determining transmission power, regards the energy efficiency in power distribution as return value function in Q study, lead to
It crosses multi-user's Q learning algorithms based on guess and solves optimal power allocation scheme.
Further, the delay parameter according to acquisition determines that the energy efficiency of small base station includes：
According to the delay parameter of acquisition, determines and receive Signal to Interference plus Noise Ratio；
According to determining reception Signal to Interference plus Noise Ratio, total reception data rate is determined；
According to determining total reception data rate, available capacity is determined；
According to determining available capacity, the energy efficiency of small base station is determined.
Further, the reception Signal to Interference plus Noise Ratio is expressed as：
Wherein,Indicate the reception Signal to Interference plus Noise Ratio of small base station k user f on subchannel n；Indicate small
Channel power gains of the type base station k to user f on subchannel n；Indicate transmission powers of the small base station k on subchannel n；Indicate the transmission power of other small base stations other than small base station k；For delay parameter, indicate on subchannel n
The interference of user f under k-th of small base station of other small base stations and macrocell pair other than small base station k；δ2Indicate high
This white noise.
Further, total reception data rate is expressed as：
Wherein,Indicate that reception data rate total user f on subchannel n, K indicate the number of small base station
Mesh,It isShorthand,Indicate the reception data of small base station k user f on subchannel n
Rate, TfIndicate that transmission time, B indicate bandwidth,It isShorthand.
Further, the available capacity is expressed as：
Wherein,For available capacity, indicate that small base station k can support the maximum data rate of user f；θkfTable
Show the Service Quality Index of the user f at small base station k；E () indicates error function；ForWrite a Chinese character in simplified form shape
Formula.
Further, the energy efficiency of the small base station is expressed as：
Wherein,Indicate the energy efficiency of user f under small base station k, TfIndicate transmission time, PkIndicate total
Downlink transmission power, PcIndication circuit power.
Further, power distribution problems are described as maximizing the energy efficiency of small base station：
Wherein,It isShorthand,Indicate preset Signal to Interference plus Noise Ratio threshold value, pmaskIndicate default
Hiding about beam power, K’Indicate the set of small base station, F’Indicate the user for including under small base station set, N’Indicate son letter
The set in road,The minimum and maximum transmission power of small base station k is indicated respectively,It is defined as
Further, the update of Q values is regular in Q learning algorithmsFor：
Wherein,s'kAnd skRespectively represent states of the small base station k in time slot t and t+1, αtIt represents
Learning rate,Indicate return value function, akIndicate the action in the behavior aggregate of small base station k, a-kIndicate in addition to
Action in the behavior aggregate of other small base stations other than small base station k, A-kIt is expressed as removing all small except small base station k
The behavior aggregate of type base station, β indicate the work factor in Q study, βkIndicate the behavior aggregate A of small base station kkIn action,Table
Show the set of strategies of small base station j, Expression acts αkLower small base station k is on subchannel n
Transmission power, IkIndicate the state of the reception Signal to Interference plus Noise Ratio of user f under small base station k.
Further, to the update rule of Q values in Q learning algorithmsIt is updated, obtains the Q based on guess
The update rule of value is：
Wherein,Indicate the linear function based on guess.
Further, the linear function based on guess is expressed as：
Wherein,It is constant parameter, is positive scalar invariant value；WithRespectively indicate guess,
Set of strategies and set of strategies, τ indicate hot value.
The above-mentioned technical proposal of the present invention has the beneficial effect that：
In said program, obtains delay parameter and the energy efficiency of small base station is determined according to the delay parameter of acquisition；It will
Power distribution problems are described as maximizing the energy efficiency of small base station；Determine hair when power distribution problems reach nash banlance
Penetrate power；Based on determining transmission power, regards the energy efficiency in power distribution as return value function in Q study, lead to
It crosses multi-user's Q learning algorithms based on guess and solves optimal power allocation scheme.In this way, (can also by introducing delay parameter
Referred to as：Delay constraint) to ensure the service quality of cell, and power distribution problems are modeled as non-cooperation equilibria of Supermodular Games, it determines
Power distribution problems reach transmission power when nash banlance, based on determining transmission power, pass through the multi-user Q based on guess
Learning algorithm solves optimal power allocation scheme, and this method can ensure service quality and consider the premise of energy efficiency
Under, the energy efficiency and handling capacity of cell are improved to greatest extent, disclosure satisfy that the access demand of sharp increase.
Description of the drawings
Fig. 1 is the flow diagram of the power distribution method in isomery subzone network provided in an embodiment of the present invention；
Fig. 2 is the structural schematic diagram of system model provided in an embodiment of the present invention.
Specific implementation mode
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.
The present invention is for existing small there are no a kind of isomery the problem of improving service quality, is provided using deferred constraint
Power distribution method in area's network.
As shown in Figure 1, the power distribution method in isomery subzone network provided in an embodiment of the present invention
S101 obtains delay parameter and determines the energy efficiency of small base station according to the delay parameter of acquisition；
Power distribution problems are described as maximizing the energy efficiency of small base station by S102；
S103 determines transmission power when power distribution problems reach nash banlance；
S104 regards the energy efficiency in power distribution as return value letter in Q study based on determining transmission power
Number solves optimal power allocation scheme by multi-user's Q learning algorithms based on guess.
The power distribution method in isomery subzone network described in the embodiment of the present invention obtains delay parameter, according to acquisition
Delay parameter, determine the energy efficiency of small base station；Power distribution problems are described as to maximize the energy dose-effect of small base station
Rate；Determine transmission power when power distribution problems reach nash banlance；It, will be in power distribution based on determining transmission power
Energy efficiency regards the return value function in Q study as, and optimal power point is solved by multi-user's Q learning algorithms based on guess
With scheme.In this way, (being referred to as by introducing delay parameter：Delay constraint) ensure the service quality of cell, and by work(
Rate assignment problem is modeled as non-cooperation equilibria of Supermodular Games, determines transmission power when power distribution problems reach nash banlance, is based on
Determining transmission power solves optimal power allocation scheme by multi-user's Q learning algorithms based on guess, and this method can be
Under the premise of ensureing service quality and considering energy efficiency, the energy efficiency and handling capacity of cell, energy are improved to greatest extent
It is enough to meet the access demand to increase severely.
Power distribution method in isomery subzone network described in embodiment for a better understanding of the present invention, carries out it
It is described in detail, the method may include：
Step 1, establish orthogonal frequency division multiple access (Orthogonal Frequency Division Multiple Access,
OFDMA) the system model of cell downlink data link, for example, as shown in Fig. 2, use a radius for 500 meters of macrocell,
Small base station (Small cell) is freely distributed in macrocell, and the minimum range between small base station and macrocell is 40 meters,
Minimum range between small base station is 300 meters, and carrier frequency is 2G Hz, and bandwidth B is 1M Hz, and number of subchannels N is 30,Wherein, N0It is the power spectral density of additive gaussian white noise, N0Value can be -174dBm/Hz, σ2It indicates to increase
The white Gaussian noise power added.The relevant parameter in the system model is initialized, for example, small base station k is on subchannel n
Transmission power, the channel power of link and small base station k to user f on subchannel n between small base station k to user f
Gain and channel power gain from small base station j to user f on subchannel n.
It should be noted that：
1) due to foundation be OFDMA cell downlink data link system model, so, it is same in cell subchannel
Time slot only allows to be accessed there are one user.
2) small base station is a kind of radio access node of low-power, and transmission power is small, between 100mW to 5W, weight
Amount is light, 2 between 10kg, is covered for hot zones.
Step 2, it calculates and receives Signal to Interference plus Noise Ratio and reception data rate
1) delay parameter is introducedAccording to the delay parameter of introducingIt calculates and receives Signal to Interference plus Noise Ratio：
Wherein,Indicate the reception Signal to Interference plus Noise Ratio of small base station k user f on subchannel n；Indicate small
Channel power gains of the type base station k to user f on subchannel n；Indicate transmission powers of the small base station k on subchannel n；Indicate the transmission power of other small base stations other than small base station k；For delay parameter, indicate on subchannel n
The interference of user f under k-th of small base station of other small base stations and macrocell pair other than small base station k；δ2Indicate high
This white noise.
2) it according to obtained reception Signal to Interference plus Noise Ratio, calculates in transmission time TfInterior reception data rate：
Wherein,Indicate the reception data rate of small base station k user f on subchannel n, TfIndicate transmission
Time, B indicate bandwidth,It isShorthand.
3) total reception data rate is calculated:
Wherein,Indicate that reception data rate total user f on subchannel n, K indicate the number of small base station
Mesh,It isShorthand.
Step 3, according to the total reception data rate being calculatedCalculate available capacity
Wherein,For available capacity, indicate that small base station k can support the maximum data rate of user f；θkfTable
Show the Service Quality Index of the user f at small base station k；E () indicates error function；ForWrite a Chinese character in simplified form shape
Formula,ForShorthand.
In the present embodiment, it is energy efficiency to define the ratio that available capacity is consumed with total cell energies, in known circuit
In the case of power and transmission power, according to obtained available capacity, the energy efficiency of user f under small base station k is calculated
Wherein,It isShorthand, indicate the energy efficiency of user f under small base station k, TfIt indicates
Transmission time, PkIndicate the transmission power of total downlink, PcIndication circuit power.
In the present embodiment,
Step 4, in the present embodiment, general objective is to maximize the energy efficiency of small base stationTherefore, power distribution is just
It can be described as problem：
In the present embodiment, the reception Signal to Interference plus Noise Ratio γ of user f under small base station kkfAlso to meet make an uproar dry more than preset letter
Than threshold value, for the purposes of ensureing the service quality of macrocell user, transmission powerIt is less than equal to the hiding constraint work(introduced
Rate pmask, i.e.,：Therefore, power distribution problems can be described as it is following it is convex optimization ask
Topic：
Wherein,Indicate preset Signal to Interference plus Noise Ratio threshold value, pmaskIt indicates preset and hides about beam power, K ' indicates small-sized base
The set stood, F ' indicate that the user for including under small base station set, N ' indicate the set of subchannel,It indicates respectively
The minimum and maximum transmission power of small base station k,It is defined as
Step 5, regard power distribution problems as a non-cooperative game, it is suitable for each small base station selection one
Strategy, work as energy efficiencyIt is optimal value or close to optimal with regard to claiming to reach Nash Equilibrium.
Step 6, by verifying, the power allocation scheme in step 5 meets the condition of equilibria of Supermodular Games, can rewriteTable
Up to formula, and at least up to one group of nash banlance.
In the present embodiment, after meeting equilibria of Supermodular Games, signal work(that interference and noise ratio from other cells receive
Small more of rate, therefore the energy efficiency of systemIt can be updated to：
Step 7, under the conditions of equilibria of Supermodular Games, when small base station network reaches maximum return and the best sound of each user
Should be monodrome, then user updates transmission power scheme since the maximum value (or minimum value) of its policy space, can converge to
Nash banlance, after reaching nash banlance, newer transmission power is expressed as
Wherein,Indicate the condition for reaching nash banlance, transmission powers of the small base station k on subchannel n；It indicates
The condition for reaching nash banlance, the transmission power of other small base stations other than k.
Step 8, according to determining transmission powerPower distribution is carried out, multi-user's Q study is introduced in power distribution and is calculated
Method, each user is mutual indepedent and does not exchange any information, and definition is using small base station as agency, and power distribution is as dynamic
Make, and define behavior aggregate, updates energy efficiency at this timeSpecifically：
1) during multi-user's Q learning algorithms solve convex optimization problem, definition status
In the present embodiment,Wherein,Indicate small base station k time slot t state,Expression acts αkTransmission powers of the lower small base station k on subchannel n, IkValue be { 0,1 }, indicate small base station k
The state of the reception Signal to Interference plus Noise Ratio of lower user f, is defined as
Wherein, γkfIndicate the reception Signal to Interference plus Noise Ratio of user f under small base station k,Indicate preset Signal to Interference plus Noise Ratio threshold value,Indicate the reception Signal to Interference plus Noise Ratio of small base station k user f on subchannel n,Indicate small base station k on subchannel n
Behavior aggregate in action,Indicate the behavior aggregate of other small base stations on subchannel n other than small base station k.
2) by the energy efficiency in power distributionRegard the return value function in Q study asSuch as
Under：
Wherein, skIndicate the state discrete collection of small base station k.
3) small base station k is in state skWhen power selection to ensure service quality and maximum energy efficiencyFor mesh
Mark, i.e.,：Wherein, πk() indicates the plan of small base station k
Slightly collect；π-k() indicates to remove the set of strategies of other small base stations other than small base station k, β indicate the cost in Q study because
Son, β value belong to 0 to 1.
Step 9, current state is initializedThen selection any action a is concentrated from actionkIt is iterated, reaches next
StateQ value update rules areWhen return value reaches maximum value, then optimal solution is obtained
In the present embodiment, Q value update rules are：
Wherein,s'kAnd skRespectively represent states of the small base station k in time slot t and t+1, αtIt represents
Learning rate, akIndicate the action in the behavior aggregate of small base station k, a-kIndicate other small base stations other than small base station k
Behavior aggregate in action, A-kIt is expressed as removing the behavior aggregate of all small base stations except small base station k, βkIndicate small-sized base
Stand the behavior aggregate A of kkIn action.
When return value reaches maximum value, then optimal solution is obtainedAccording to obtained optimal solution
Determine power allocation scheme.
Step 10, since the information of all small base stations is difficult to whole acquisitions, so proposing that the Q study based on multi-user is calculated
Method is guessed, linear function is providedExpression formula, and Q functions are rewritten based on guess, obtain the linear function based on guess
In the present embodiment, the obtained linear function based on guessIt can be expressed as：
Wherein,It is a positive scalar invariant value,WithGuessing in the last one time slot is indicated respectively
Think and set of strategies.
In the present embodiment, after the completion of the strategy based on guess, the Q value update rules in step 9 become：
Step 11, reinforce the choosing to power policy during study
It is beneficial to select, and greediness selection is a kind of effective means that balance is explored and utilized, but status selects that drawback can be caused on an equal basis,
In the present embodiment, ANALOGY OF BOLTZMANN DISTRIBUTION is introduced, selection acts α in next stepkIt is iterated, until obtaining optimal power distribution side
Case.
In the present embodiment, the set of strategies based on ANALOGY OF BOLTZMANN DISTRIBUTIONIt can be expressed as：
Wherein, τ is a positive parameter, indicates hot value.
In the present embodiment, hot value τ to be analyzed, difference is smaller between the more big corresponding probability values of τ, to illustrate,
The power distribution method in isomery subzone network described in the present embodiment, can improve energy efficiency and cell to the maximum extent
Handling capacity.
To sum up, the power distribution method in isomery subzone network described herein, in the cell by introducing time delay about
Beam and available capacity ensure service quality, power distribution problems are modeled as non-cooperation equilibria of Supermodular Games, and prove that it is converged on
Nash Equilibrium is then converted to convex optimization problem, is solved by multi-user's Q learning algorithms based on guess, is improved to greatest extent
The handling capacity of energy efficiency and cell.
It should be noted that herein, 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 the 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. the power distribution method in a kind of isomery subzone network, which is characterized in that including：
It obtains delay parameter and the energy efficiency of small base station is determined according to the delay parameter of acquisition；
Power distribution problems are described as to maximize the energy efficiency of small base station；
Determine transmission power when power distribution problems reach nash banlance；
Based on determining transmission power, regards the energy efficiency in power distribution as return value function in Q study, pass through base
Optimal power allocation scheme is solved in multi-user's Q learning algorithms of guess.
2. the power distribution method in isomery subzone network according to claim 1, which is characterized in that described according to acquisition
Delay parameter, determine that the energy efficiency of small base station includes：
According to the delay parameter of acquisition, determines and receive Signal to Interference plus Noise Ratio；
According to determining reception Signal to Interference plus Noise Ratio, total reception data rate is determined；
According to determining total reception data rate, available capacity is determined；
According to determining available capacity, the energy efficiency of small base station is determined.
3. the power distribution method in isomery subzone network according to claim 2, which is characterized in that the reception letter is dry
It makes an uproar than being expressed as：
Wherein,Indicate the reception Signal to Interference plus Noise Ratio of small base station k user f on subchannel n；Indicate small-sized base
It stands channel power gains of the k to user f on subchannel n；Indicate transmission powers of the small base station k on subchannel n；
Indicate the transmission power of other small base stations other than small base station k；For delay parameter, expression removes on subchannel n
The interference of user f under other small base stations and macrocell pair k-th of small base station other than small base station k；δ2Indicate Gauss
White noise.
4. the power distribution method in isomery subzone network according to claim 3, which is characterized in that total reception
Data rate is expressed as：
Wherein,Indicate that reception data rate total user f on subchannel n, K indicate the number of small base station,It isShorthand,Indicate the reception data speed of small base station k user f on subchannel n
Rate, TfIndicate that transmission time, B indicate bandwidth,It isShorthand.
5. the power distribution method in isomery subzone network according to claim 4, which is characterized in that the available capacity
It is expressed as：
Wherein,For available capacity, indicate that small base station k can support the maximum data rate of user f；θkfIt indicates
The Service Quality Index of user f under small base station k；E () indicates error function；ForShorthand.
6. the power distribution method in isomery subzone network according to claim 5, which is characterized in that the small base station
Energy efficiency be expressed as：
Wherein,Indicate the energy efficiency of user f under small base station k, TfIndicate transmission time, PkUnder indicating total
The transmission power of line link, PcIndication circuit power.
7. the power distribution method in isomery subzone network according to claim 6, which is characterized in that ask power distribution
Topic is described as maximizing the energy efficiency of small base station：
Wherein,It isShorthand,Indicate preset Signal to Interference plus Noise Ratio threshold value, pmaskIndicate preset hidden
About beam power is hidden, K ' indicates that the set of small base station, F ' indicate that the user for including under small base station set, N ' indicate subchannel
Set,The minimum and maximum transmission power of small base station k is indicated respectively,It is defined as
8. the power distribution method in isomery subzone network according to claim 1, which is characterized in that Q in Q learning algorithms
The update rule of valueFor：
Wherein,s'kAnd skRespectively represent states of the small base station k in time slot t and t+1, αtRepresent study
Rate,Indicate return value function, akIndicate the action in the behavior aggregate of small base station k, a-kIt indicates in addition to small-sized
Action in the behavior aggregate of other small base stations other than the k of base station, A-kIt is expressed as removing all small-sized bases except small base station k
The behavior aggregate stood, β indicate the work factor in Q study, βkIndicate the behavior aggregate A of small base station kkIn action,Indicate small
The set of strategies of type base station j, Expression acts αkHairs of the lower small base station k on subchannel n
Penetrate power, IkIndicate the state of the reception Signal to Interference plus Noise Ratio of user f under small base station k.
9. the power distribution method in isomery subzone network according to claim 8, which is characterized in that Q learning algorithms
The update rule of middle Q valuesIt is updated, the update rule for obtaining the Q values based on guess is：
Wherein,Indicate the linear function based on guess.
10. the power distribution method in isomery subzone network according to claim 9, which is characterized in that described to be based on guessing
The linear function thought is expressed as：
Wherein,It is constant parameter, is positive scalar invariant value；WithGuess, strategy are indicated respectively
Collection and set of strategies, τ indicate hot value.
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| CN110049565A (en) * | 2019-04-18 | 2019-07-23 | 天津大学 | A kind of 5G network power distribution method based on available capacity |
| CN110049315A (en) * | 2019-04-26 | 2019-07-23 | 山西大学 | A method of improving live video system user Quality of experience |
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| CN109474980A (en) * | 2018-12-14 | 2019-03-15 | 北京科技大学 | A kind of wireless network resource distribution method based on depth enhancing study |
| CN109474980B (en) * | 2018-12-14 | 2020-04-28 | 北京科技大学 | Wireless network resource allocation method based on deep reinforcement learning |
| CN110049565A (en) * | 2019-04-18 | 2019-07-23 | 天津大学 | A kind of 5G network power distribution method based on available capacity |
| CN110049565B (en) * | 2019-04-18 | 2021-11-02 | 天津大学 | 5G network power distribution method based on effective capacity |
| CN110049315A (en) * | 2019-04-26 | 2019-07-23 | 山西大学 | A method of improving live video system user Quality of experience |
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