CN108156620A - A kind of super-intensive network small station dormancy method based on channel and queue aware - Google Patents

A kind of super-intensive network small station dormancy method based on channel and queue aware Download PDF

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CN108156620A
CN108156620A CN201810086759.4A CN201810086759A CN108156620A CN 108156620 A CN108156620 A CN 108156620A CN 201810086759 A CN201810086759 A CN 201810086759A CN 108156620 A CN108156620 A CN 108156620A
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CN108156620B (en
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潘志文
李沛
刘楠
尤肖虎
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White Box Shanghai Microelectronics Technology Co ltd
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Southeast University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • 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
    • H04W52/02—Power saving arrangements
    • H04W52/0203—Power saving arrangements in the radio access network or backbone network of wireless communication networks
    • H04W52/0206—Power saving arrangements in the radio access network or backbone network of wireless communication networks in access points, e.g. base stations
    • 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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  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The present invention provides a kind of super-intensive network small station dormancy method based on channel and queue aware, including：Acquire the network information；Optimal suspend mode ratio is calculated according to gradient descent method；Calculate the number for wanting suspend mode small station；It is 0 to enable base station switch ratio, calculates average queue length and average transmission rate of each small station in certain time length in each time interval；Small station ascending order is arranged according to the product of each small station average queue length and user's average transmission rate；Obtain suspend mode number；Small station is closed successively according to sequence.The base station dormancy method that the present invention is proposed for super-intensive heterogeneous network, pass through gathered data portfolio, with reference to the channel status between base station and user, perform base station dormancy strategy, it can be perfectly suitable for real system, and can bring than conventional method better performance gain, significantly reduce system energy consumption under conditions of user's delay character is ensured.

Description

A kind of super-intensive network small station dormancy method based on channel and queue aware
Technical field
The invention belongs to wireless communication technology fields, and in particular to a kind of in wireless communication system to be based on channel and queue sense The super-intensive network small station dormancy method known.
Background technology
Mobile communication amount explosive growth in 5G (the fifth generation) network, gives Mobile Network Operator band Greatly challenge.In order to meet following mobile data demand, significant increase power system capacity and user experience quality, traditional big Deployment super-intensive low-power small station can obtain huge in the especially heavy traffic hot spot region of the overlay area of power macro station Throughput gain.Since super-intensive network middle and small stations are often deployed in some positions for being difficult to arrive at, this is to fiber optic backhaul link Installation brings difficulty, and to solve the problems, such as this, core net is transmitted to the backhaul chain in small station using Radio Transmission Technology in operator Road information.But wireless backhaul technology can generate the propagation delay time of return link compared to traditional optical fiber transmission technique.In addition, Ever-increasing number of base stations in super-intensive heterogeneous network, will necessarily consume more power energies.Moreover, the energy of return link Amount consumption can also bring huge pressure to energy saving of system.A kind of effective power-saving technology is to perform base station according to the business of user Dormancy strategy reduces system energy consumption.However base station dormancy strategy causes available base stations number to reduce the time delay so as to influence user Characteristic in order to ensure the service quality of user, while reduces the energy consumption of system, to come according to well-designed base station dormancy strategy The base station to be closed is selected, to realize the tradeoff of energy consumption and time delay.
Existing base station dormancy technology selects the base station to be closed based on customer service perception or channel status, and does not have Have and combine service condition and channel information, and be all that backhaul link information is transmitted using optical fiber technology, do not consider back Influence of the time delay and energy consumption of journey link to overall system performance, cause existing dormancy strategy be difficult to suitable for it is practical based on The super-intensive heterogeneous network of wireless backhaul.
Invention content
To solve the above problems, the invention discloses a kind of super-intensive network small station suspend mode based on channel and queue aware System energy consumption and time delay trade-off problem are described as minimizing system cost function problem, in customer service and channel shape by method In the case of state dynamic change, the base station dormancy strategy of channel and queue aware has been formulated.
Existing base station dormancy technology selects the base station to be closed based on customer service perception or channel status.And I In discovery system user's time delay it is not only related with portfolio, it is also related with channel status.Portfolio is got over large user and is waited in line Time it is longer, meanwhile, the channel status between user and base station is better, and user's propagation delay time is smaller.
Based on this, this method calculates optimum base station suspend mode ratio first, and the base of suspend mode is wanted according to the calculating of base station dormancy ratio It stands number, that is, determines the number of base stations to be closed under conditions of user's delay character is met.Secondly, consider that each base station is averaged Team leader obtains average transmission rate with the user for being associated with the base station, and small station is averaged according to average queue length and user The product ascending order arrangement of transmission rate, selects the base station to be closed, so as to reduce system energy consumption successively according to the sequence.
In order to achieve the above object, the present invention provides following technical solution：
A kind of super-intensive network small station dormancy method based on channel and queue aware, includes the following steps：
Step 1, the network information is acquired
Measure user in region area, macro station, small station and gateway total number Nu、Nm、Ns、Ng, obtain the region Intranet Pass, macro station, small station and user distribution density λg,λm,λsAnd λu；
Customer flow arrival meets pool process, counts customer flow service condition in a period of time and show that customer flow reaches The rate λ and especially big small l of the average specific each wrapped；
Obtain being deployed in the wireless return link bandwidth W in small station in the regionb, macro station use wireless access bandwidth Wm, it is small Stand the wireless access bandwidth W useds, macro station transimission power Pmt, small station transimission power Pst, gateway transimission power Pgt；
Record the average energy consumption of each gatewayThe average energy consumption in suspend mode small stationThe energy of macro station and small station static link ConsumptionWith
Path loss factor alpha in wireless channel is obtained using channel estimation methods；
Determine user-association to the bias A in small station according to network operation situationb, macro station and small station the relevant energy of load Consume factor Δ pmWith Δ ps, signal interference ratio thresholding β, weight factor ω, iterative search step-length δ, iterative search accuracy ξ, time interval T, duration T values determine as needed；
All macro stations are completely in state of activation；
The base station dormancy ratio in small station is denoted as θ, the initial value θ of base station dormancy ratio0It is voluntarily true according to network operation situation Fixed, optimal suspend mode ratio is θ*, the value of base station dormancy ratio is θ during nth iterationn；
Step 2, it is iterated according to gradient descent method, iterations initial value is n=0, during nth iteration, is calculated Base station dormancy ratio θ=θnUnder, the average data packet delay of macro station and small station userWithAnd whole network mean time Prolong
The probability P r that user is connected to small station is calculated firstSUE(θ)
Gateway, macro station and small station are M/G/1 queues, so the time delay of user includes propagation delay time and queuing delay；
User is divided into two parts：First part is the user for connecting macro station, and second part is the user for connecting small station；
For connecting the user of macro station, average delayFor the time delay of wireless access links, mean transit delay is includedAnd average queuing delayI.e.It is calculated by following formula：
Wherein,Represent that user accesses the average transmission rate obtained during macro station；
WithFor macro station and the average transmission probability in small station, obtained by dichotomy by following two formula：
In above formula,
For accessing the user in small station, the average delay each wrapped is respectively wireless access links average delayWith it is wireless Return link average delayThe sum of；Similarly, access link average delayWith wireless backhaul link average delay Mean transit delay is all included respectivelyAnd average queuing delayI.e. Wherein,It is calculated by following formula：
Wherein,For the average transmission rate of small station user radio transmission link,Represent gateway to the backhaul chain in small station Road average transmission rate；
It is calculated by following formula：
Wherein,For the average transmission probability of gateway, calculated by following formula：
So as to obtain network average delaySuch as following formula：
Step 3, current base station suspend mode ratio θ=θ is calculated by following formulanLower system average energy consumptionWith cost function F (θ)：
Step 4, when solving current nth iteration by following formula, cost function F (θ) is about base station dormancy ratio θ=θn's Derived function
Wherein,
Step 5, base station dormancy ratio θ, during (n+1)th iteration, base station dormancy ratio θ=θ are updatedn+1, by following formula more Newly：
Step 6, judge under current base station suspend mode ratio, whole network cost function F (θ)=F (θn) whether reach minimum Value point；As F (θn+1)-F(θn) ＜ ξ when, show to reach optimum point, perform step 8 and exit iterative process；Otherwise, step is performed 7；
Step 7：Current iteration frequency n+1 is updated, performs step 2-6；
Step 8：Iterative process is exited, obtains the optimal suspend mode ratio θ in base station*；
Step 9：θ=0 is enabled, i.e., all small stations are active, and update user's connection status；Statistics is in time interval t The team leader in upper all small stations and the average transmission rate of user, and then calculate average queue length and average transmission rate in duration T；
Step 10：Small station ascending order is arranged according to the product of each small station average queue length and user's average transmission rate；
Step 11：The optimal suspend mode ratio θ obtained according to step 8*, calculate the number of base stations N for wanting suspend modeoff=[θ*Ns]；
Step 12：It sorts according to the small station obtained in step 10, N before closing successivelyoffA small station.
Specifically, the base station dormancy ratio θ minimum values of step 1 middle and small stations are θmin=0, maximum value θmax=1.
Specifically, user accesses the average transmission rate obtained during macro station in the step 2Small station user radio The average transmission rate of transmission linkGateway is to the return link average transmission rate in small stationIt is asked according to shannon formula .
Compared with prior art, the invention has the advantages that and advantageous effect：
The base station dormancy method that the present invention is proposed for super-intensive heterogeneous network, by gathered data portfolio, with reference to base The channel status stood between user performs base station dormancy strategy, can be perfectly suitable for real system, and can bring than tradition Method better performance gain significantly reduces system energy consumption under conditions of user's delay character is ensured.With existing service-aware It is compared with channel-aware base station dormancy scheme, small station business variation and channel information, selection can be made full use of to want the base station of suspend mode Set, the energy saving trade-off problem between QoS of customer of flexible control system.
Description of the drawings
Fig. 1 is the super-intensive network small station dormancy method flow chart provided by the invention based on channel and queue aware.
Specific embodiment
Technical solution provided by the invention is described in detail below with reference to specific embodiment, it should be understood that following specific Embodiment is only illustrative of the invention and is not intended to limit the scope of the invention.
The angle that the present invention weighs from energy consumption and time delay, minimum system is corresponded to by energy consumption and time delay trade-off problem Cost function problem.Operator can select specific weighting factor according to energy saving and QoS of customer relative importance, So that it is determined that want the number of base stations of suspend mode.
The present invention considers that the discharge model of user meets poisson arrival process, is analyzed first according to M/G/1 queuing models The time delay and energy consumption of Radio Access Network and backhaul network are iteratively solved out by gradient descent method and weighed about energy consumption and time delay The minimum point of cost function corresponding to problem is to get having gone out the optimum base station suspend mode ratio of system, and then according to optimal base Suspend mode ratio of standing selects the set of optimal suspend mode base station so that QoS of customer is able to minimize system energy under conditions of ensureing Consumption.
Specifically, the super-intensive network small station dormancy method provided by the invention based on channel and queue aware, such as Fig. 1 It is shown, include the following steps：
Step 1：Acquire the network information
Operator measures user in region area, macro station, small station and gateway total number, is denoted as N respectivelyu, Nm, Ns, Ng, So as to obtain area's intradomain gateway, macro station, small station and the distribution density of user λg,λm,λsAnd λu.Customer flow, which reaches, meets pool Process, operator's statistics a period of time (can according to circumstances setting time length), interior customer flow service condition obtained customer flow The arrival rate λ and especially big small l of the average specific each wrapped.Obtain being deployed in the backhaul chain that small station is wireless in the region by operator Road bandwidth Wb, macro station use wireless access bandwidth Wm, small station use wireless access bandwidth Ws, macro station transimission power Pmt, small station Transimission power Pst, gateway transimission power Pgt.Operator records the average energy consumption of each gatewayThe average energy consumption in suspend mode small station PS, the energy consumption of macro station and small station static linkWithPath loss factor alpha in wireless channel is obtained using channel estimation methods.With Family is associated with the bias A in small stationb, macro station and small station the relevant Energy consumption factor Δ p of loadmWith Δ ps, signal interference ratio thresholding β, power Repeated factor ω, iterative search step-length δ, iterative search accuracy ξ, time interval t, duration T values are transported by operator according to network Market condition voluntarily determines.All macro stations are completely in state of activation.
The base station dormancy ratio in small station is denoted as θ, minimum value θmin=0, maximum value θmax=1.Base station dormancy ratio Initial value θ0It is voluntarily determined according to network operation situation by operator, optimal suspend mode ratio is θ*.Iterations initial value is n =0, the value of base station dormancy ratio is θ during nth iterationn。
Optimum base station suspend mode ratio θ is then iteratively solved according to gradient descent method*。
Step 2：During nth iteration, calculate in base station dormancy ratio θ=θnUnder, the average data of macro station and small station user Packet delay is denoted as respectivelyWithAnd whole network average delay
The probability P r that user is connected to small station is calculated firstSUE(θ)
Gateway, macro station and small station are M/G/1 queues, so the time delay of user includes propagation delay time and queuing delay.User Mean transit delay it is slowAnd average queuing delayIt is expressed as：
HereIt represents average transmission rate, can be obtained by shannon formula.ρ expression average transmission probability, macro station and small station Average transmission probability, is denoted as respectivelyWithMeet the following conditions respectively：
Here x represents integration variable, without actual physical meaning.
Dichotomy can be utilized, the average transmission probability under current traffic state is obtained from formula (4) and (5)With
User is divided into two parts：First part is the user for connecting macro station, and second part is the user for connecting small station.It is right In the user of connection macro station, average delayFor the time delay of wireless access links, mean transit delay is includedWith it is average Queuing delayI.e.According to formula (2), (3) can obtain
HereIt represents that user accesses the average transmission rate obtained during macro station, can be acquired according to shannon formula.
For accessing the user in small station, the average delay each wrapped is respectively wireless access links average delayIt is returned with wireless Journey link average delayThe sum of.Similarly, access link average delayWith wireless backhaul link average delayAlso all divide It Bao Han not mean transit delayAnd average queuing delayI.e. Similarly, it can be obtained by formula (2)
Here,For the average transmission rate of small station user radio transmission link,Represent gateway to the backhaul chain in small station Road average transmission rate.WithIt can be acquired according to shannon formula.
It can be obtained according to formula (3)
For the average transmission probability of gateway,
So as to obtain network average delay
Step 3：Calculate current base station suspend mode ratio θ=θnLower system average energy consumptionWith cost function F (θ)
Here, the value of weight factor ω is determined by operator according to network operation situation.
Step 4：When solving current nth iteration, cost function F (θ) is about base station dormancy ratio θ=θnDerived function
Here
Step 5：Update base station dormancy ratio θ, during (n+1)th iteration, base station dormancy ratio θ=θn+1, it is updated to
Here, the value of iterative search step-length δ is determined by operator according to network operation situation.
Step 6：Judge under current base station suspend mode ratio, whole network cost function F (θ)=F (θn) whether reach minimum Value point：As F (θn+1)-F(θn) ＜ ξ when, show to reach optimum point, perform step 8 and exit iterative process；Otherwise, step is performed 7.Here, the value of iterative search accuracy ξ is determined by operator according to network operation situation.
Step 7：Current iteration frequency n+1 is updated, performs step 2-6.
Step 8：Iterative process is exited, obtains the optimal suspend mode ratio θ in base station*。
Step 9：θ=0 is enabled, i.e., all small stations are active, and update user's connection status.Operator transports according to network Market condition determines duration T and time interval t, counts the average transmission of the team leader in all small stations and user speed on time interval t Rate, and then calculate average queue length and average transmission rate in duration T.
Step 10：Small station ascending order is arranged according to the product of each small station average queue length and user's average transmission rate.
Step 11：The optimal suspend mode ratio θ obtained according to step 8*, calculate the number of base stations N for wanting suspend modeoff=[θ*Ns]。
Step 12：It sorts according to the small station obtained in step 10, N before closing successivelyoffA small station.
The technical means disclosed in the embodiments of the present invention is not limited only to the technological means disclosed in the above embodiment, further includes By more than technical characteristic arbitrarily the formed technical solution of combination.It should be pointed out that for those skilled in the art For, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also considered as Protection scope of the present invention.

Claims (3)

1. a kind of super-intensive network small station dormancy method based on channel and queue aware, which is characterized in that include the following steps：
Step 1, the network information is acquired
Measure user in region area, macro station, small station and gateway total number Nu、Nm、Ns、Ng, obtain area's intradomain gateway, macro It stands, the distribution density λ of small station and userg,λm,λsAnd λu；
Customer flow arrival meets pool process, counts customer flow service condition in a period of time and obtains customer flow arrival rate λ And the especially big small l of average specific each wrapped；
Obtain being deployed in the wireless return link bandwidth W in small station in the regionb, macro station use wireless access bandwidth Wm, small station adopts Wireless access bandwidth Ws, macro station transimission power Pmt, small station transimission power Pst, gateway transimission power Pgt；
Record the average energy consumption of each gatewayThe average energy consumption in suspend mode small stationThe energy consumption of macro station and small station static link With
Path loss factor alpha in wireless channel is obtained using channel estimation methods；
Determine user-association to the bias A in small station according to network operation situationb, macro station and small station the relevant energy consumption of load because Sub- Δ pmWith Δ ps, signal interference ratio thresholding β, weight factor ω, iterative search step-length δ, iterative search accuracy ξ, time interval t, when Long T values determine as needed；
All macro stations are completely in state of activation；
The base station dormancy ratio in small station is denoted as θ, the initial value θ of base station dormancy ratio0It is voluntarily determined according to network operation situation, most Excellent suspend mode ratio is θ*, the value of base station dormancy ratio is θ during nth iterationn；
Step 2, it is iterated according to gradient descent method, iterations initial value is n=0, during nth iteration, is calculated in base station Suspend mode ratio θ=θnUnder, the average data packet delay of macro station and small station userWithAnd whole network average delay
The probability P r that user is connected to small station is calculated firstSUE(θ)
Gateway, macro station and small station are M/G/1 queues, so the time delay of user includes propagation delay time and queuing delay；
User is divided into two parts：First part is the user for connecting macro station, and second part is the user for connecting small station；
For connecting the user of macro station, average delayFor the time delay of wireless access links, mean transit delay is includedWith Average queuing delayI.e. It is calculated by following formula：
Wherein,Represent that user accesses the average transmission rate obtained during macro station；
WithFor macro station and the average transmission probability in small station, obtained by dichotomy by following two formula：
In above formula,
For accessing the user in small station, the average delay each wrapped is respectively wireless access links average delayAnd wireless backhaul Link average delayThe sum of；Similarly, access link average delayWith wireless backhaul link average delayAlso all divide It Bao Han not mean transit delayAnd average queuing delayI.e. Wherein,It is calculated by following formula：
Wherein,For the average transmission rate of small station user radio transmission link,Represent that the return link in gateway to small station is put down Equal transmission rate；
It is calculated by following formula：
Wherein,For the average transmission probability of gateway, calculated by following formula：
So as to obtain network average delaySuch as following formula：
Step 3, current base station suspend mode ratio θ=θ is calculated by following formulanLower system average energy consumptionWith cost function F (θ)：
Step 4, when solving current nth iteration by following formula, cost function F (θ) is about base station dormancy ratio θ=θnLead letter Number
Wherein,
Step 5, base station dormancy ratio θ, during (n+1)th iteration, base station dormancy ratio θ=θ are updatedn+1, updated by following formula：
Step 6, judge under current base station suspend mode ratio, whole network cost function F (θ)=F (θn) whether reach minimum point； As F (θn+1)-F(θn) ＜ ξ when, show to reach optimum point, perform step 8 and exit iterative process；Otherwise, step 7 is performed；
Step 7：Current iteration frequency n+1 is updated, performs step 2-6；
Step 8：Iterative process is exited, obtains the optimal suspend mode ratio θ in base station*；
Step 9：θ=0 is enabled, i.e., all small stations are active, and update user's connection status；Statistics institute on time interval t There are the team leader in small station and the average transmission rate of user, and then calculate average queue length and average transmission rate in duration T；
Step 10：Small station ascending order is arranged according to the product of each small station average queue length and user's average transmission rate；
Step 11：The optimal suspend mode ratio θ obtained according to step 8*, calculate the number of base stations N for wanting suspend modeoff=[θ*Ns]；
Step 12：It sorts according to the small station obtained in step 10, N before closing successivelyoffA small station.
2. the super-intensive network small station dormancy method according to claim 1 based on channel and queue aware, feature exist In：The base station dormancy ratio θ minimum values in small station are θmin=0, maximum value θmax=1.
3. the super-intensive network small station dormancy method according to claim 1 based on channel and queue aware, feature exist In：User accesses the average transmission rate obtained during macro stationThe average transmission rate of small station user radio transmission linkGateway is to the return link average transmission rate in small stationIt is acquired according to shannon formula.
CN201810086759.4A 2018-01-30 2018-01-30 Ultra-dense network small station sleeping method based on channel and queue sensing Active CN108156620B (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111050364A (en) * 2019-01-29 2020-04-21 北京中科晶上科技股份有限公司 Switching management method for 5G ultra-dense network
CN112153727A (en) * 2020-10-10 2020-12-29 哈尔滨工业大学（深圳） Low-delay low-energy-consumption base station caching and sleeping method, base station and system

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111050364A (en) * 2019-01-29 2020-04-21 北京中科晶上科技股份有限公司 Switching management method for 5G ultra-dense network
CN111050364B (en) * 2019-01-29 2021-12-21 北京中科晶上科技股份有限公司 Switching management method for 5G ultra-dense network
CN112153727A (en) * 2020-10-10 2020-12-29 哈尔滨工业大学（深圳） Low-delay low-energy-consumption base station caching and sleeping method, base station and system

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