CN103607759B - Micro-base station scaling dormancy method and equipment in a kind of cellular network - Google Patents

Abstract

The invention discloses micro-base station scaling dormancy method and equipment in a kind of cellular network, the method includes: network equipment determines hot spot region unit are service rate and ratio ν of non-focus territorial unit area service rate_m, and determine hot spot region area and ratio γ of non-focus region area_m；Described network equipment utilizes described ν_mWith described γ_mDetermine the micro-base station scaling dormancy strategy in heterogeneous network；Wherein, described micro-base station scaling dormancy strategy is particularly as follows: micro-base station dormancy or micro-base station range keep constant or micro-base station range to expand or micro-base station range reduces.In the embodiment of the present invention, power and the resource utilization of frequency spectrum in heterogeneous network can be improved, meet the business transmission demand of hot spot region user and non-focus zone user simultaneously, hot spot region user and the service quality of non-focus zone user are effectively ensured, significantly improve system transfers energy efficiency and throughput of system.

Description

Micro-base station scaling dormancy method and equipment in a kind of cellular network

Technical field

The present invention relates to communication technical field, especially relate to scaling dormancy method in micro-base station in a kind of cellular network And equipment.

Background technology

In recent years, cordless communication network scale and service rate all in growing trend of quickly exploding, communication system rapid Development also enables it to consumption problem and day by day highlights.According to statistics, more than 40 industry in the whole nation, telecommunications industry power consumption is ranked first 4, Become major power consumer worthy of the name.Further, the energy consumption of cordless communication network is also rising year by year.With China Mobile As a example by, base station number increases to 500000 from 200000, the power consumption of China Mobile in recent five years by double.Cause This, mobile communication system has developed into high energy consumption industry, and along with to higher transfer rate and the pursuit of wider region overlay Present quick growing trend.Therefore, Developing Green communication research, run, planning etc. is all highly desirable to.Future mobile communications Development with network technology have to be in the face of resource and the double constraints of energy consumption, it is desirable to while optimizing Internet resources significantly Reduce the energy consumption of unit portfolio, Green communication and network.

User can have obvious group behavior rule, to wireless network in multiple dimensions such as time, space, business tines Efficiency affect greatly.But, currently in the research to wireless network efficiency, how to stand alone as mutually with user's individual behavior Research premise, lacks of the quantitative analysis that network energy efficiency is affected by user group's behavior, therefore user group's behavior and network The incidence relation of efficiency is still not clear.

Additionally, one of current heterogeneous network just developing direction becoming future wireless network, and micro-in heterogeneous network The problems such as base station dormancy and micro-base station range change will receive significant attention.

In existing homogeneous network, there is not the problem that micro-base station covers, the therefore side of micro-base station dormancy in homogeneous network Formula can not be applied in heterogeneous network, i.e. needs to rethink user group's difference that different layers base station services in heterogeneous network Impacts that the control of micro-base station is brought different with coverage.

Summary of the invention

The embodiment of the present invention provides micro-base station scaling dormancy method and equipment in a kind of cellular network, to rethink micro-base Stand and scale dormancy strategy, improve frequency spectrum resource utilization rate.

For reaching above-mentioned purpose, the embodiment of the present invention provides scaling dormancy method in micro-base station in a kind of cellular network, described Method comprises the following steps:

Network equipment determines hot spot region unit are service rate and non-focus territorial unit area service rate Ratio ν_m, and determine hot spot region area and ratio γ of non-focus region area_m；

Described network equipment utilizes described ν_mWith described γ_mDetermine the micro-base station scaling dormancy strategy in heterogeneous network；Its In, described micro-base station scaling dormancy strategy is particularly as follows: micro-base station dormancy or micro-base station range keep constant or micro- Base station range expands or micro-base station range reduces.

Described network equipment utilizes described ν_mWith described γ_mDetermine the micro-base station scaling dormancy strategy in heterogeneous network, tool Body includes: described network equipment utilizes ν_mWith described γ_mJudge whether micro-base station meets dormancy condition；If it is, described network Side apparatus determines that described micro-base station scaling dormancy strategy is micro-base station dormancy；If it does not, as described ν_mWith described γ_mMeet micro-base In limited time, described network equipment determines that described micro-base station scaling dormancy strategy is that micro-base station is covered to the trigger gate that coverage of standing expands Lid expanded range；As described ν_mWith described γ_mMeet trigger gate that micro-base station range reduces in limited time, described network equipment Determine that described micro-base station scaling dormancy strategy is that micro-base station range reduces；As described ν_mWith described γ_mIt is unsatisfactory for micro-base station to cover The triggering thresholding of lid expanded range, and it is unsatisfactory for trigger gate that micro-base station range reduces in limited time, described network equipment is true Fixed described micro-base station scaling dormancy strategy is that micro-base station range keeps constant.

Described network equipment utilizes described ν_mWith described γ_mJudge whether micro-base station meets the process of dormancy condition, enter one Step includes: described network equipment is utilizing described ν_mWith described γ_mWhen the relation that is defined below is set up, determine that micro-base station meets not Dormancy condition；Otherwise, it determines micro-base station does not meets dormancy condition；

$\frac{{\mathrm{\λ}}_m{P}_m^c+{\mathrm{\λ}}_M{P}_M^c}{{\mathrm{\λ}}_m{P}_m^s+{\mathrm{\λ}}_M{P}_M^c}>\frac{1+{\mathrm{\γ}}_m}{1+v_m};$

Wherein, λ_mFor the density of micro-base station, λ_MFor the density of macro base station,For the static power of micro-base station,For grand base The static power stood,Dormancy power for micro-base station.

Described method farther includes: described network equipment is utilizing described ν_mWith described γ_mThe relation that is defined below is set up Time, determine described ν_mWith described γ_mMeet the triggering thresholding that micro-base station range expands；

$\left\{\begin{array}{c}\frac{P_m^c}{P_M^c}>\max (\frac{{\mathrm{\&gamma;}}_m^2}{v_m},{\mathrm{\&gamma;}}_m),v_m>1\\ v_m>{\mathrm{\&gamma;}}_m,\frac{P_m^c}{P_M^c}>\frac{{\mathrm{\&gamma;}}_m^2}{v_m},v_m<1\end{array}\right.;$

Described network equipment is utilizing described ν_mWith described γ_mWhen the relation that is defined below is set up, determine described ν_mWith described γ_mMeet the triggering thresholding that micro-base station range reduces；

$\left\{\begin{array}{c}{v}_m<{\mathrm{\&gamma;}}_m,\frac{P_m^c}{P_M^c}<\frac{{\mathrm{\&gamma;}}_m^2}{v_m},v_m>1\\ \frac{P_m^c}{P_M^c}<\min (\frac{{\mathrm{\&gamma;}}_m^2}{v_m},{\mathrm{\&gamma;}}_m),v_m<1\end{array}\right.;$

Wherein, at described ν_mWith described γ_mMeeting the trigger gate of micro-base station range expansion in limited time, described network side sets The standby optimum coverage utilizing equation below to calculate micro-base station:

$\left\{\begin{array}{c}{\widetilde{\mathrm{\&gamma;}}}_m^{\mathrm{opt}}=\max (\sqrt{v_m\frac{P_m^c}{P_M^c}},\frac{P_m^c}{P_M^c}),v_m>1\\ {\widetilde{\mathrm{\&gamma;}}}_m^{\mathrm{opt}}=\sqrt{v_m\frac{P_m^c}{P_M^c}},v_m<1\end{array}\right.;$

Wherein, at described ν_mWith described γ_mMeeting trigger gate that micro-base station range reduces in limited time, described network side sets The standby optimum coverage utilizing equation below to calculate micro-base station:

${\widetilde{\mathrm{\&gamma;}}}_m^{\mathrm{opt}}=\min (\sqrt{v_m\frac{P_m^c}{P_M^c}},\frac{P_m^c}{P_M^c});$

Wherein,For the static power of micro-base station,Static power for macro base station.

Described network equipment determines hot spot region unit are service rate and non-focus territorial unit area business speed Ratio ν of rate_m, and determine hot spot region area and ratio γ of non-focus region area_mAfterwards, described method also includes: described Network equipment utilizes described ν_mWith described γ_mDetermine that the user convergence factor h in heterogeneous network, described user convergence factor h are fixed Amount reflects user group's Behavior law, and user group's Behavior law is characterized by user behavior curve；User behavior curve Transverse axis corresponding cumulative time in observation interval or cumulative area or accumulative content, the longitudinal axis represents accumulative service rate, uses The recessed degree of family behavior curve represents user behavior aggregation extent, if user behavior curve is the most flat, then and explanation user's row The least for diversity, if user behavior curve is the most recessed, then explanation user behavior diversity is the biggest.

Described network equipment utilizes described ν_mWith described γ_mDetermine the user convergence factor h in heterogeneous network, specifically wrap Include: described network equipment utilizes equation below to determine the user convergence factor h in heterogeneous network:

$h=\left\{\begin{array}{cc}\frac{{\mathrm{\&gamma;}}_m{v}_m}{{\mathrm{\&gamma;}}_m{v}_m+1}-\frac{{\mathrm{\&gamma;}}_m}{{\mathrm{\&gamma;}}_m+1}& v_m>1\\ \frac{{\mathrm{\&gamma;}}_m}{{\mathrm{\&gamma;}}_m+1}-\frac{{\mathrm{\&gamma;}}_m{v}_m}{{\mathrm{\&gamma;}}_m{v}_m+1}& v_m<1\end{array}\right..$

The embodiment of the present invention provides a kind of network equipment, and described network equipment specifically includes:

First determines module, is used for determining hot spot region unit are service rate and non-focus territorial unit area business Ratio ν of speed_m, and determine hot spot region area and ratio γ of non-focus region area_m；

Second determines module, is used for utilizing described ν_mWith described γ_mDetermine the micro-base station scaling dormancy plan in heterogeneous network Slightly；Wherein, described micro-base station scaling dormancy strategy particularly as follows: micro-base station dormancy or micro-base station range keep constant or The micro-base station range of person expands or micro-base station range reduces.

Described second determines module, specifically for utilizing ν_mAnd γ_mJudge whether micro-base station meets dormancy condition；If it is, Determine that described micro-base station scaling dormancy strategy is micro-base station dormancy；If it does not, as described ν_mWith described γ_mMeet micro-base station to cover The trigger gate of expanded range in limited time, determines that described micro-base station scaling dormancy strategy is that micro-base station range expands；As described ν_m With described γ_mMeet trigger gate that micro-base station range reduces in limited time, determine that described micro-base station scaling dormancy strategy is micro-base Coverage of standing reduces；As described ν_mWith described γ_mIt is unsatisfactory for the triggering thresholding that micro-base station range expands, and is unsatisfactory for micro- The trigger gate that base station range reduces in limited time, determines that described micro-base station scaling dormancy strategy is that micro-base station range keeps not Become.

Described second determines module, is further used for utilizing described ν_mWith described γ_mWhen the relation that is defined below is set up, really Fixed micro-base station meets dormancy condition；Otherwise, it determines micro-base station does not meets dormancy condition；

$\frac{{\mathrm{\&lambda;}}_m{P}_m^c+{\mathrm{\&lambda;}}_M{P}_M^c}{{\mathrm{\&lambda;}}_m{P}_m^s+{\mathrm{\&lambda;}}_M{P}_M^c}>\frac{1+{\mathrm{\&gamma;}}_m}{1+v_m};$

Utilizing described ν_mWith described γ_mWhen the relation that is defined below is set up, determine described ν_mWith described γ_mMeet micro-base station The triggering thresholding that coverage expands；

$\left\{\begin{array}{c}\frac{P_m^c}{P_M^c}>\max (\frac{{\mathrm{\&gamma;}}_m^2}{v_m},{\mathrm{\&gamma;}}_m),v_m>1\\ v_m>{\mathrm{\&gamma;}}_m,\frac{P_m^c}{P_M^c}>\frac{{\mathrm{\&gamma;}}_m^2}{v_m},v_m<1\end{array}\right.;$

Utilizing described ν_mWith described γ_mWhen the relation that is defined below is set up, determine described ν_mWith described γ_mMeet micro-base station The triggering thresholding that coverage reduces；

$\left\{\begin{array}{c}{v}_m<{\mathrm{\&gamma;}}_m,\frac{P_m^c}{P_M^c}<\frac{{\mathrm{\&gamma;}}_m^2}{v_m},v_m>1\\ \frac{P_m^c}{P_M^c}<\min (\frac{{\mathrm{\&gamma;}}_m^2}{v_m},{\mathrm{\&gamma;}}_m),v_m<1\end{array}\right.;$

Wherein, at described ν_mWith described γ_mMeet the trigger gate of micro-base station range expansion in limited time, utilize equation below Calculate the optimum coverage of micro-base station:

$\left\{\begin{array}{c}{\widetilde{\mathrm{\&gamma;}}}_m^{\mathrm{opt}}=\max (\sqrt{v_m\frac{P_m^c}{P_M^c}},\frac{P_m^c}{P_M^c}),v_m>1\\ {\widetilde{\mathrm{\&gamma;}}}_m^{\mathrm{opt}}=\sqrt{v_m\frac{P_m^c}{P_M^c}},v_m<1\end{array}\right.;$

Wherein, at described ν_mWith described γ_mMeet trigger gate that micro-base station range reduces in limited time, utilize equation below Calculate the optimum coverage of micro-base station:

${\widetilde{\mathrm{\&gamma;}}}_m^{\mathrm{opt}}=\min (\sqrt{v_m\frac{P_m^c}{P_M^c}},\frac{P_m^c}{P_M^c});$

Wherein, λ_mFor the density of micro-base station, λ_MFor the density of macro base station,For the static power of micro-base station,For grand base The static power stood,Dormancy power for micro-base station.

Also include: the 3rd determines module, be used for utilizing described ν_mWith described γ_mDetermine that the user in heterogeneous network assembles system Number h, described user's convergence factor h quantitative response user group's Behavior law, and user group's Behavior law pass through user behavior Curve characterizes；The transverse axis of user behavior curve corresponding cumulative time in observation interval or cumulative area or accumulative content, vertical Axle represents accumulative service rate, and the recessed degree of user behavior curve represents user behavior aggregation extent, if user's row The most flat for curve, then explanation user behavior diversity is the least, if user behavior curve is the most recessed, then and explanation user behavior difference Property is the biggest；

Described 3rd determines that module utilizes equation below to determine the user convergence factor h in heterogeneous network:

$h=\left\{\begin{array}{cc}\frac{{\mathrm{\&gamma;}}_m{v}_m}{{\mathrm{\&gamma;}}_m{v}_m+1}-\frac{{\mathrm{\&gamma;}}_m}{{\mathrm{\&gamma;}}_m+1}& v_m>1\\ \frac{{\mathrm{\&gamma;}}_m}{{\mathrm{\&gamma;}}_m+1}-\frac{{\mathrm{\&gamma;}}_m{v}_m}{{\mathrm{\&gamma;}}_m{v}_m+1}& v_m<1\end{array}\right..$

Compared with prior art, the embodiment of the present invention at least has the advantage that in the embodiment of the present invention, based on hot zone Territory unit are service rate and ratio ν of non-focus territorial unit area service rate_mAnd hot spot region area and non-thermal Ratio γ of some region area_m, determine the micro-base station scaling dormancy strategy in heterogeneous network, thus improve power in heterogeneous network With the resource utilization of frequency spectrum, meet the business transmission demand of hot spot region user and non-focus zone user simultaneously, effectively protect Card hot spot region user and the service quality of non-focus zone user, significantly improve system transfers energy efficiency and system throughput Amount.

Accompanying drawing explanation

In order to be illustrated more clearly that technical scheme, the required accompanying drawing used in embodiment being described below It is briefly described, it should be apparent that, the accompanying drawing in describing below is only some embodiments of the present invention, general for this area From the point of view of logical technical staff, on the premise of not paying creative work, it is also possible to obtain other accompanying drawing according to these accompanying drawings.

Fig. 1 is the application scenarios schematic diagram of isomery hierarchical network in the embodiment of the present invention one；

Fig. 2 is scaling dormancy method flow chart in micro-base station in a kind of cellular network in the embodiment of the present invention one；

Fig. 3 is the user behavior distribution curve schematic diagram proposed in the embodiment of the present invention one；

Fig. 4-Fig. 6 is the schematic diagram of the technique effect produced in the embodiment of the present invention one；

Fig. 7 is a kind of network equipment structural representation that the embodiment of the present invention two provides.

Detailed description of the invention

Below in conjunction with the accompanying drawing in the present invention, the technical scheme in the present invention is clearly and completely described, aobvious So, described embodiment is only a part of embodiment of the present invention rather than whole embodiments.Based in the present invention Embodiment, all other embodiments that those of ordinary skill in the art are obtained under not making creative work premise, all Belong to the scope of protection of the invention.

Embodiment one

For problems of the prior art, the embodiment of the present invention one provides micro-base station scaling in a kind of cellular network to stop Dormancy method, as a example by the application scenarios schematic diagram of the isomery hierarchical network shown in Fig. 1, the method is applied at least include macro base station And in the heterogeneous network of micro-base station.Where it is assumed that macro base station is ground floor, and density λ is obeyed in the position of macro base station_MPoisson Distribution；Micro-base station is the second layer, and density λ is obeyed in the position of micro-base station_mPoisson distribution；Additionally, the transmit power of macro base station For P_M, the transmit power of micro-base station is P_m, the received signal to noise ratio threshold value of macro base station is β_M, the received signal to noise ratio thresholding of micro-base station Value is β_m；Additionally, subscript M represents macro base station, subscript m represents micro-base station；Additionally, macro base station is responsible for covering non-hot spot region, micro- Base station is responsible for covering hot spot region.

Under above-mentioned application scenarios, as in figure 2 it is shown, the method at least comprises the following steps:

Step 201, network equipment determines hot spot region unit are service rate and non-focus territorial unit area industry Ratio ν of business speed_m, and determine hot spot region area and ratio γ of non-focus region area_m。

During concrete implementation, can be by modes such as measurements so that network equipment can know hot spot region Unit are service rate, and non-focus territorial unit area service rate can be known, then determine hot spot region unit plane Long-pending service rate and ratio ν of non-focus territorial unit area service rate_m；Can be by modes such as measurements so that network side Equipment can know hot spot region area, and can know non-focus region area, then determines hot spot region area and non-thermal Ratio γ of some region area_m。

In the embodiment of the present invention, according to correlation theorys such as random geometries, in the case of double-deck heterogeneous network covers, Hot spot region unit are service rate and ratio ν of non-focus territorial unit area service rate_m, can be further by following Formula determines:Additionally, hot spot region area and ratio γ of non-focus region area_m, can further by Below equation determines:

In above-mentioned formula, λ_mFor micro-base station density, λ_MFor macro base station density, P_mFor the transmit power of micro-base station, P_MFor grand The transmit power of base station, α is the path loss factor, and 2≤α≤5.

Step 202, network equipment utilizes hot spot region unit are service rate and non-focus territorial unit area industry Ratio ν of business speed_mAnd determine hot spot region area and ratio γ of non-focus region area_mDetermine in heterogeneous network is micro- Base station scaling dormancy strategy；Wherein, this micro-base station scaling dormancy strategy is particularly as follows: micro-base station dormancy or micro-base station cover model Enclose and keep constant or micro-base station range expansion or micro-base station range to reduce.

In the embodiment of the present invention, based on hot spot region unit are service rate and non-focus territorial unit area business speed Ratio ν of rate_mAnd hot spot region area and ratio γ of non-focus region area_m, network equipment can configure heterogeneous network In micro-base station scaling dormancy strategy so that the efficiency of heterogeneous network reaches optimal value, simultaneously ensure meet in network use The business demand feature of family group behavior.

In a kind of preferred implementation of the embodiment of the present invention, network equipment utilizes ν_mAnd γ_mDetermine in heterogeneous network Micro-base station scaling dormancy strategy, be specifically including but not limited to following manner: network equipment utilizes ν_mAnd γ_mJudge micro-base station Whether meet dormancy condition；If it is, network equipment determines that micro-base station scaling dormancy strategy is micro-base station dormancy；If No, then work as ν_mAnd γ_mMeeting the trigger gate of micro-base station range expansion in limited time, network equipment determines that micro-base station scales dormancy Strategy is that micro-base station range expands；Work as ν_mAnd γ_mMeeting trigger gate that micro-base station range reduces in limited time, network side sets For determining that micro-base station scaling dormancy strategy is that micro-base station range reduces；Work as ν_mAnd γ_mIt is unsatisfactory for micro-base station range to expand Triggering thresholding, and be unsatisfactory for trigger gate that micro-base station range reduces in limited time, network equipment determines that micro-base station scaling is stopped Strategy of sleeping is that micro-base station range keeps constant (i.e. launch power and keep constant).

Further, network equipment utilizes ν_mAnd γ_mJudge whether micro-base station meets the process of dormancy condition, further Include but not limited to following manner: network equipment is utilizing ν_mAnd γ_mWhen the relation that is defined below is set up, determine that micro-base station meets Dormancy condition；Otherwise, it determines micro-base station does not meets dormancy condition.

$\frac{{\mathrm{\&lambda;}}_m{P}_m^c+{\mathrm{\&lambda;}}_M{P}_M^c}{{\mathrm{\&lambda;}}_m{P}_m^s+{\mathrm{\&lambda;}}_M{P}_M^c}>\frac{1+{\mathrm{\&gamma;}}_m}{1+v_m};$

In above-mentioned formula, λ_mFor the density of micro-base station, λ_MFor the density of macro base station,For the static power of micro-base station,For the static power of macro base station,Dormancy power for micro-base station.

Further, network equipment is utilizing ν_mAnd γ_mWhen the relation that is defined below is set up, it may be determined that ν_mAnd γ_mMeet The triggering thresholding that micro-base station range expands:

$\left\{\begin{array}{c}\frac{P_m^c}{P_M^c}>\max (\frac{{\mathrm{\&gamma;}}_m^2}{v_m},{\mathrm{\&gamma;}}_m),v_m>1\\ v_m>{\mathrm{\&gamma;}}_m,\frac{P_m^c}{P_M^c}>\frac{{\mathrm{\&gamma;}}_m^2}{v_m},v_m<1\end{array}\right..$

Further, network equipment is utilizing ν_mAnd γ_mWhen the relation that is defined below is set up, it may be determined that ν_mAnd γ_mMeet The triggering thresholding that micro-base station range reduces:

$\left\{\begin{array}{c}{v}_m<{\mathrm{\&gamma;}}_m,\frac{P_m^c}{P_M^c}<\frac{{\mathrm{\&gamma;}}_m^2}{v_m},v_m>1\\ \frac{P_m^c}{P_M^c}<\min (\frac{{\mathrm{\&gamma;}}_m^2}{v_m},{\mathrm{\&gamma;}}_m),v_m<1\end{array}\right..$

Wherein, at ν_mAnd γ_mMeeting the trigger gate of micro-base station range expansion in limited time, network equipment can also utilize The optimum coverage of the micro-base station of equation below calculating:

$\left\{\begin{array}{c}{\widetilde{\mathrm{\&gamma;}}}_m^{\mathrm{opt}}=\max (\sqrt{v_m\frac{P_m^c}{P_M^c}},\frac{P_m^c}{P_M^c}),v_m>1\\ {\widetilde{\mathrm{\&gamma;}}}_m^{\mathrm{opt}}=\sqrt{v_m\frac{P_m^c}{P_M^c}},v_m<1\end{array}\right..$

Wherein, at ν_mAnd γ_mMeeting trigger gate that micro-base station range reduces in limited time, network equipment can also utilize The optimum coverage of the micro-base station of equation below calculating:

${\widetilde{\mathrm{\&gamma;}}}_m^{\mathrm{opt}}=\min (\sqrt{v_m\frac{P_m^c}{P_M^c}},\frac{P_m^c}{P_M^c}).$

In above-mentioned formula,For the static power of micro-base station,Static power for macro base station.

Below in conjunction with concrete application, the generation process of above-mentioned formula is further elaborated.

First pass through below equation and calculate heterogeneous network efficiency when completely covering hot spot region in micro-base station:

${\mathrm{EE}}_{\mathrm{opt}}\&ap;\frac{D(\mathrm{\&alpha;},{\mathrm{\&beta;}}_{\mathrm{th}}){\mathrm{\&gamma;}}_m(1+v_m)}{(1+{\mathrm{\&gamma;}}_m)(P_m^c{v}_m+P_M^c{\mathrm{\&gamma;}}_m)}.$

Further, by above-mentioned heterogeneous network efficiency expression formula to ν_mDerivation, can obtain heterogeneous network efficiency and ν_m Relation.Wherein, existInterval, heterogeneous network efficiency is ν_mIncreasing function, i.e. completely cover hot zone in micro-base station Under conditions of territory, micro-base station unit are power consumption values in its overlay area is less than macro base station unit in its overlay area During area power consumption values, heterogeneous network efficiency is along with ν_mIncrease and increase.?Interval, heterogeneous network efficiency is ν_mSubtract Function, i.e. under conditions of micro-base station completely covers hot spot region, micro-base station unit are power consumption values in its overlay area During higher than macro base station unit are power consumption values in its overlay area, heterogeneous network efficiency is along with ν_mIncrease and reduce.

By to heterogeneous network efficiency expression formula to γ_mDerivation, available heterogeneous network efficiency and γ_mRelation.?Interval, heterogeneous network efficiency is γ_mIncreasing function, i.e. completely cover the condition of hot spot region in micro-base station Under, micro-base station unit are power consumption values in its overlay area is higher than macro base station unit are energy consumption in its overlay area Value is multiplied byTime, heterogeneous network efficiency is along with γ_mIncrease and increase.?Interval, heterogeneous network efficiency is γ_mSubtraction function, i.e. under conditions of micro-base station completely covers hot spot region, micro-base station unit are in its overlay area Power consumption values is multiplied by less than macro base station unit are power consumption values in its overlay areaTime, heterogeneous network efficiency is along with γ_mIncrease Add and reduce.

Based on above-mentioned analysis, the heterogeneous network energy when using equation below calculating completely to cover hot spot region in micro-base station Effect:And, heterogeneous network efficiency during use equation below micro-base station dormancy of calculating:Time, by the comparison of two formulas, it can be deduced that heterogeneous network efficiency based on user group's behavior The strategy of optimum microcell base station dormancy.Therefore, ν is being utilized_mAnd γ_mIt is defined below relationBecome Immediately, it is determined that micro-base station meets dormancy condition；Otherwise, it determines micro-base station does not meets dormancy condition, open micro-base station service heat Point region.Under special circumstances: when the transmitting power of micro-base station is equal to dormancy powerTime, dormancy condition is reduced to γ_m ＞ ν_m。

Further, ν is being utilized_mAnd γ_mIt is defined below relation $\left\{\begin{array}{c}\frac{P_m^c}{P_M^c}>\max (\frac{{\mathrm{\&gamma;}}_m^2}{v_m},{\mathrm{\&gamma;}}_m),v_m>1\\ v_m>{\mathrm{\&gamma;}}_m,\frac{P_m^c}{P_M^c}>\frac{{\mathrm{\&gamma;}}_m^2}{v_m},v_m<1\end{array}\right.$ During establishment, permissible Determine ν_mAnd γ_mMeeting the triggering thresholding that micro-base station range expands, now efficiency based on user group's behavior optimum is micro- Base station optimum coverage is $\left\{\begin{array}{c}{\widetilde{\mathrm{\&gamma;}}}_m^{\mathrm{opt}}=\max (\sqrt{v_m\frac{P_m^c}{P_M^c}},\frac{P_m^c}{P_M^c}),v_m>1\\ {\widetilde{\mathrm{\&gamma;}}}_m^{\mathrm{opt}}=\sqrt{v_m\frac{P_m^c}{P_M^c}},v_m<1\end{array}\right..$

Further, ν is being utilized_mAnd γ_mIt is defined below relation $\left\{\begin{array}{c}{v}_m<{\mathrm{\&gamma;}}_m,\frac{P_m^c}{P_M^c}<\frac{{\mathrm{\&gamma;}}_m^2}{v_m},v_m>1\\ \frac{P_m^c}{P_M^c}<\min (\frac{{\mathrm{\&gamma;}}_m^2}{v_m},{\mathrm{\&gamma;}}_m),v_m<1\end{array}\right.$ During establishment, it may be determined that ν_mAnd γ_mMeeting the triggering thresholding that micro-base station range reduces, micro-base station that now efficiency based on user group's behavior is optimum is Excellent coverage isFurther, random geometry theory is used to can get the one-tenth of isomery hierarchical network Merit transmission probability.Wherein, $P_{\mathrm{out}}=1-\underset{i=m,M}{\mathrm{\&Sigma;}}2\mathrm{\&pi;}{\mathrm{\&lambda;}}_i\underset{0}{\overset{\&infin;}{\&Integral;}}\exp (-B(\mathrm{\&alpha;},{\mathrm{\&beta;}}_i))\mathrm{rdr},B(\mathrm{\&alpha;},{\mathrm{\&beta;}}_i)=C\left(\mathrm{\&alpha;}\right)r^2{{\mathrm{\&beta;}}_i}^{\frac{2}{\mathrm{\&alpha;}}}\left(\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{\mathrm{\&lambda;}}_k{P_k}^{\frac{2}{\mathrm{\&alpha;}}}\right){P_i}^{\frac{2}{\mathrm{\&alpha;}}}-\frac{{\mathrm{\&beta;}}_i{\mathrm{\&sigma;}}^2}{P_i{r}^{-\mathrm{\&alpha;}}},$ Assume for interference limiting system,And signal-noise ratio threshold value all phases of every layer Deng, the most above-mentioned formula can also continue to abbreviation and is:It can be seen that these public affairs from this result Formula is the most irrelevant with transmitting power and base station density, the base station number of plies etc..

Utilization random geometry is theoretical, it is also possible to obtain in the ergodic capacity under the multiple cell in heterogeneous network, heterogeneous network The ergodic capacity of single base station user, the total capacity of the whole network in heterogeneous network.Wherein,

$D(\mathrm{\&alpha;},{\mathrm{\&beta;}}_{\mathrm{th}})=\frac{\mathrm{\&pi;}\log (1+{\mathrm{\&beta;}}_{\mathrm{th}})}{C\left(\mathrm{\&alpha;}\right){{\mathrm{\&beta;}}_{\mathrm{th}}}^{2/\mathrm{\&alpha;}}}+\frac{F_1^2(\mathrm{1,2}/\mathrm{\&alpha;},1+2/\mathrm{\&alpha;},-1/{\mathrm{\&beta;}}_{\mathrm{th}})\mathrm{\&alpha;\&pi;}}{2C\left(\mathrm{\&alpha;}\right){{\mathrm{\&beta;}}_{\mathrm{th}}}^{2/\mathrm{\&alpha;}}},C\left(\mathrm{\&alpha;}\right)=\frac{2{\mathrm{\&pi;}}^2}{\mathrm{\&alpha;}}\csc \left(\frac{2\mathrm{\&pi;}}{\mathrm{\&alpha;}}\right),$ Further, $D(\mathrm{\&alpha;},{\mathrm{\&beta;}}_{\mathrm{th}})=\frac{\mathrm{\&pi;}\log (1+{\mathrm{\&beta;}}_{\mathrm{th}})}{C\left(\mathrm{\&alpha;}\right){{\mathrm{\&beta;}}_{\mathrm{th}}}^{2/\mathrm{\&alpha;}}}+\frac{F_1^2(\mathrm{1,2}/\mathrm{\&alpha;},-1/{\mathrm{\&beta;}}_{\mathrm{th}})\mathrm{\&alpha;\&pi;}}{2C\left(\mathrm{\&alpha;}\right){{\mathrm{\&beta;}}_{\mathrm{th}}}^{2/\mathrm{\&alpha;}}},C\left(\mathrm{\&alpha;}\right)=\frac{{2\mathrm{\&pi;}}^2}{\mathrm{\&alpha;}}\csc \left(\frac{2\mathrm{\&pi;}}{\mathrm{\&alpha;}}\right),$ ₂F₁For Hypergeometric function, repeats in the concrete hypergeometric function embodiment of the present invention the most in detail.

In above-mentioned formula, α is the path loss factor, and 2≤α≤5, β_thFor received signal to noise ratio, λ_hHot zone for micro-base station Territory density, λ_mFor micro-base station density, λ_MFor macro base station density, σ²For thermal noise power, R_MFor macro base station layer capacity, R_mFor micro-base station Layer capacity, P_mFor micro-base station power, P_MFor macro base station power,For micro-base station constant power,For macro base station constant power, EE For network energy efficiency, π is pi, SINR_edgeFor cell edge signal to noise ratio, P_edgeFor cell edge access probability.

In the embodiment of the present invention, network equipment determines hot spot region unit are service rate and non-focus territorial unit Ratio ν of area service rate_m, and determine hot spot region area and ratio γ of non-focus region area_mAfterwards, network side sets For utilizing ν_mAnd γ_mDetermine the user convergence factor h in heterogeneous network, this user's convergence factor h quantitative response customer group Body Behavior law, and user group's Behavior law characterized by user behavior curve；Wherein, the transverse axis of user behavior curve is corresponding Cumulative time in observation interval or cumulative area or accumulative content, the longitudinal axis represents accumulative service rate, and user behavior is bent The recessed degree of line represents user behavior aggregation extent, if user behavior curve is the most flat, then and explanation user behavior diversity The least, if user behavior curve is the most recessed, then explanation user behavior diversity is the biggest.

Further, network equipment utilizes ν_mAnd γ_mDetermine the user convergence factor h in heterogeneous network, specifically include: Network equipment utilizes equation below to determine the user convergence factor h in heterogeneous network:

$h=\left\{\begin{array}{cc}\frac{{\mathrm{\&gamma;}}_m{v}_m}{{\mathrm{\&gamma;}}_m{v}_m+1}-\frac{{\mathrm{\&gamma;}}_m}{{\mathrm{\&gamma;}}_m+1}& v_m>1\\ \frac{{\mathrm{\&gamma;}}_m}{{\mathrm{\&gamma;}}_m+1}-\frac{{\mathrm{\&gamma;}}_m{v}_m}{{\mathrm{\&gamma;}}_m{v}_m+1}& v_m<1\end{array}\right..$

Below in conjunction with concrete application scenarios, the content of user group's Behavior law is described in detail.

In the embodiment of the present invention, according to user group's behavioral characteristic in network, set up user group's behavior model, to network Quantitative description is done in middle user group's behavior, portrays user group's behavior characteristics.Concrete, owing to user group's behavior refers to user Behavior mould in a network in units of colony, under the various dimensions such as mechanics, business demand, access frequency, aggregation properties Formula and characteristic rule, therefore can set up user behavior curve: service area space is divided into difference by (1) through the following steps Interval u_i, subscript i=1...n represents different interval sequence number；(2) the service rate t (u in each interval is calculated_i)；(3) right These are interval, are ranked up according to service rate size；(4) definition user behavior distribution curve is (in the region of cumulative area x Service rate accounts for the ratio of total service rate) be:

From user behavior distribution curve it can be seen that the corresponding cumulative time/area/content in observation interval of transverse axis, The longitudinal axis represents accumulative service rate, and therefore on user behavior distribution curve, the physical meaning of every bit is, corresponding observation interval The interior service rate in cumulative time/area/content accounts for the percentage ratio of total service rate.If user behavior is without the slightest difference, Then service rate statistics on cumulative time or cumulative area or accumulative content dimension is uniform, and in the cumulative time or tired Should have x%, i.e. user behavior distribution curve in the region of meter area or x% corresponding to accumulative content is 45 degree of lines.With this Contrary, it is contemplated that an extreme case, user behavior difference is huge, and only a user has applied for business, and other owns User does not the most apply for business, and now user behavior distribution curve is always 0, until statistics area is 100%, then and user behavior Distribution curve is $\left\{\begin{array}{c}\mathrm{\&rho;}\left(x\right)=\mathrm{0,0}\&le;x<1\\ \mathrm{\&rho;}\left(x\right)=1,x=1\end{array}\right.,$ I.e. one horizontal line and a vertical line.

Further, the recessed degree (curvature) of this user behavior distribution curve represents the journey that user behavior is assembled Degree, if user behavior distribution curve the most flat (curvature is the least), just closer to the user behavior distribution curve (45 degree of zero difference Line), corresponding user behavior diversity is the least.If this user behavior distribution curve the most recessed (curvature is the biggest), more connect The user behavior distribution curve (horizontal line and a vertical line) that nearly difference is maximum, corresponding user behavior diversity is more Greatly.

In order to quantify the difference of different user behavior distribution curve, user behavior distribution curve schematic diagram as shown in Figure 3, Three user behavior distribution curves in Fig. 3 define two regions of A, B, and these three user behavior distribution curves are respectively: The user behavior distribution curve that service rate is average, the user behavior distribution curve that service rate is definitely concentrated, business speed The user behavior distribution curve that rate is typically distributed.Based on this, the embodiment of the present invention proposes user convergence factor h, this user Convergence factor quantitative response user group's Behavior law, and can assemble according to region A area and region B areal calculation user Coefficient, or based on hot spot region unit are service rate and ratio ν of non-focus territorial unit area service rate_mAnd heat Point region area and ratio γ of non-focus region area_mCalculate user's convergence factor, as follows.

$h=\frac{A}{A+B}=\left\{\begin{array}{cc}\frac{{\mathrm{\&gamma;}}_m{v}_m}{{\mathrm{\&gamma;}}_m{v}_m+1}-\frac{{\mathrm{\&gamma;}}_m}{{\mathrm{\&gamma;}}_m+1}& v_m>1\\ \frac{{\mathrm{\&gamma;}}_m}{{\mathrm{\&gamma;}}_m+1}-\frac{{\mathrm{\&gamma;}}_m{v}_m}{{\mathrm{\&gamma;}}_m{v}_m+1}& v_m<1\end{array}\right..$

In sum, in the embodiment of the present invention, based on hot spot region unit are service rate and non-focus territorial unit Ratio ν of area service rate_mAnd hot spot region area and ratio γ of non-focus region area_m, determine in heterogeneous network Micro-base station scaling dormancy strategy, i.e. for the strategy of micro-base station dynamic dormancy in low traffic region, thus improves heterogeneous network Middle power and the resource utilization of frequency spectrum, meet the business transmission demand of hot spot region user and non-focus zone user simultaneously, The energy efficiency making this heterogeneous network high energy efficiency based on user group's behavior micro-base station scaling dormancy scheme reaches optimal.Enter One step, aforesaid way can be effectively ensured hot spot region user and the service quality of non-focus zone user, significantly improves and is System transmission energy efficiency and throughput of system.Further, aforesaid way is applicable to various wireless communication network, it is possible to be applicable to All heterogeneous wireless networks, and without considering the restriction of concrete network formats, there is good popularizing application prospect.Further , aforesaid way can save network energy consumption to greatest extent, improves overall network energy efficiency.Further, aforesaid way Measurement model based on user's aggregation extent, sets up heterogeneous network efficiency optimization problem, utilizes mathematical optimization theoretical, is given In heterogeneous network, the unlatching dormancy strategy of micro-base station, area coverage expand strategy, and area coverage reduces strategy, and obtaining can be adaptive Micro-base station area coverage optimal value of user group's behavior in network, as shown in Figure 4.

Below in conjunction with Fig. 5 and Fig. 6, the technique effect of the embodiment of the present invention is further detailed.

In fig. 5 and fig., the wireless communication system for using MATLAB simulation software to build simulation reality carries out emulation in fact Execute the result curve figure after test, the curve of Fig. 5 and Fig. 6 be completely orthogonal in the case of, the energy efficiency of system is along with focus The change of the ratio of region area and non-focus region area, different curves represent different hot spot region unit are business Speed and the ratio of non-focus territorial unit area service rate.Visible at dormancy power than in the case of relatively low, micro-base station one Straight dormancy, system energy efficiency is higher, in the case of dormancy power is higher, only in hot spot region area and non-focus area surface In the case of long-pending ratio is less, micro-base station dormancy efficiency improves.In hot spot region area and the ratio of non-focus region area In the case of less, micro-base station range extends, and absorbs a part of grand user, and system energy efficiency improves；At hot spot region area In the case of the large percentage of non-focus region area, micro-base station range shrinks, and macro base station absorbs a part of micro-base station User, system energy efficiency improves.

Embodiment two

Based on the inventive concept as said method, the embodiment of the present invention additionally provides a kind of network equipment, as Shown in Fig. 7, described network equipment specifically includes:

First determines module 11, is used for determining hot spot region unit are service rate and non-focus territorial unit area industry Ratio ν of business speed_m, and determine hot spot region area and ratio γ of non-focus region area_m；

Second determines module 12, is used for utilizing described ν_mWith described γ_mDetermine the micro-base station scaling dormancy plan in heterogeneous network Slightly；Wherein, micro-base station scaling dormancy strategy is particularly as follows: micro-base station dormancy or micro-base station range keep constant or micro- Base station range expands or micro-base station range reduces.

Described second determines module 12, specifically for utilizing ν_mAnd γ_mJudge whether micro-base station meets dormancy condition；If It is to determine that described micro-base station scaling dormancy strategy is micro-base station dormancy；If it does not, as described ν_mAnd γ_mMeet micro-base station and cover model Enclose the trigger gate of expansion in limited time, determine that described micro-base station scaling dormancy strategy is that micro-base station range expands；As described ν_mWith Described γ_mMeet trigger gate that micro-base station range reduces in limited time, determine that described micro-base station scaling dormancy strategy is micro-base station Coverage reduces；As described ν_mWith described γ_mIt is unsatisfactory for the triggering thresholding that micro-base station range expands, and is unsatisfactory for micro-base The trigger gate that coverage of standing reduces in limited time, determines that described micro-base station scaling dormancy strategy is that micro-base station range keeps not Become.

Described second determines module 12, is further used for utilizing described ν_mWith described γ_mWhen the relation that is defined below is set up, Determine that micro-base station meets dormancy condition；Otherwise, it determines micro-base station does not meets dormancy condition；

$\frac{{\mathrm{\&lambda;}}_m{P}_m^c+{\mathrm{\&lambda;}}_M{P}_M^c}{{\mathrm{\&lambda;}}_m{P}_m^s+{\mathrm{\&lambda;}}_M{P}_M^c}>\frac{1+{\mathrm{\&gamma;}}_m}{1+v_m};$

Utilizing described ν_mWith described γ_mWhen the relation that is defined below is set up, determine described ν_mWith described γ_mMeet micro-base station The triggering thresholding that coverage expands；

$\left\{\begin{array}{c}\frac{P_m^c}{P_M^c}>\max (\frac{{\mathrm{\&gamma;}}_m^2}{v_m},{\mathrm{\&gamma;}}_m),v_m>1\\ v_m>{\mathrm{\&gamma;}}_m,\frac{P_m^c}{P_M^c}>\frac{{\mathrm{\&gamma;}}_m^2}{v_m},v_m<1\end{array}\right.;$

Utilizing described ν_mWith described γ_mWhen the relation that is defined below is set up, determine described ν_mWith described γ_mMeet micro-base station The triggering thresholding that coverage reduces；

$\left\{\begin{array}{c}{v}_m<{\mathrm{\&gamma;}}_m,\frac{P_m^c}{P_M^c}<\frac{{\mathrm{\&gamma;}}_m^2}{v_m},v_m>1\\ \frac{P_m^c}{P_M^c}<\min (\frac{{\mathrm{\&gamma;}}_m^2}{v_m},{\mathrm{\&gamma;}}_m),v_m<1\end{array}\right.;$

Wherein, at described ν_mWith described γ_mMeet the trigger gate of micro-base station range expansion in limited time, utilize equation below Calculate the optimum coverage of micro-base station:

$\left\{\begin{array}{c}{\widetilde{\mathrm{\&gamma;}}}_m^{\mathrm{opt}}=\max (\sqrt{v_m\frac{P_m^c}{P_M^c}},\frac{P_m^c}{P_M^c}),v_m>1\\ {\widetilde{\mathrm{\&gamma;}}}_m^{\mathrm{opt}}=\sqrt{v_m\frac{P_m^c}{P_M^c}},v_m<1\end{array}\right.;$

Wherein, at described ν_mWith described γ_mMeet trigger gate that micro-base station range reduces in limited time, utilize equation below Calculate the optimum coverage of micro-base station:

${\widetilde{\mathrm{\&gamma;}}}_m^{\mathrm{opt}}=\min (\sqrt{v_m\frac{P_m^c}{P_M^c}},\frac{P_m^c}{P_M^c});$

Wherein, λ_mFor the density of micro-base station, λ_MFor the density of macro base station,For the static power of micro-base station,For grand base The static power stood,Dormancy power for micro-base station.

Network equipment also includes: the 3rd determines module 13, is used for utilizing described ν_mWith described γ_mDetermine in heterogeneous network User convergence factor h, user's convergence factor h quantitative response user group's Behavior law, and user group's Behavior law passes through User behavior curve characterizes；The transverse axis of user behavior curve corresponding cumulative time in observation interval or cumulative area or accumulative Content, the longitudinal axis represents accumulative service rate, and the recessed degree of user behavior curve represents user behavior aggregation extent, if User behavior curve is the most flat, then explanation user behavior diversity is the least, if user behavior curve is the most recessed, user behavior is described Diversity is the biggest；Described 3rd determines that module 13 utilizes equation below to determine the user convergence factor h in heterogeneous network:

$h=\left\{\begin{array}{cc}\frac{{\mathrm{\&gamma;}}_m{v}_m}{{\mathrm{\&gamma;}}_m{v}_m+1}-\frac{{\mathrm{\&gamma;}}_m}{{\mathrm{\&gamma;}}_m+1}& v_m>1\\ \frac{{\mathrm{\&gamma;}}_m}{{\mathrm{\&gamma;}}_m+1}-\frac{{\mathrm{\&gamma;}}_m{v}_m}{{\mathrm{\&gamma;}}_m{v}_m+1}& v_m<1\end{array}\right..$

Wherein, the modules of apparatus of the present invention can be integrated in one, it is also possible to separates and disposes.Above-mentioned module can be closed And be a module, it is also possible to it is further split into multiple submodule.

Through the above description of the embodiments, those skilled in the art is it can be understood that can be by the present invention Software adds the mode of required general hardware platform and realizes, naturally it is also possible to by hardware, but a lot of in the case of the former is more Good embodiment.Based on such understanding, prior art is contributed by technical scheme the most in other words Part can embody with the form of software product, and this computer software product is stored in a storage medium, if including Dry instruction is with so that a computer equipment (can be personal computer, server, or the network equipment etc.) performs this Method described in each embodiment bright.

It will be appreciated by those skilled in the art that accompanying drawing is the schematic diagram of a preferred embodiment, the module in accompanying drawing or stream Journey is not necessarily implemented necessary to the present invention.

It will be appreciated by those skilled in the art that the module in the device in embodiment can describe according to embodiment to carry out point It is distributed in the device of embodiment, it is also possible to carry out respective change and be disposed other than in one or more devices of the present embodiment.On The module stating embodiment can merge into a module, it is also possible to is further split into multiple submodule.

The invention described above embodiment sequence number, just to describing, does not represent the quality of embodiment.

The several specific embodiments being only the present invention disclosed above, but, the present invention is not limited to this, any ability What the technical staff in territory can think change all should fall into protection scope of the present invention.

Claims (5)

1. scaling dormancy method in micro-base station in a cellular network, it is characterised in that said method comprising the steps of:

Network equipment determines hot spot region unit are service rate and the ratio of non-focus territorial unit area service rate ν_m, and determine hot spot region area and ratio γ of non-focus region area_m；

Described network equipment utilizes described ν_mWith described γ_mDetermine the micro-base station scaling dormancy strategy in heterogeneous network；Wherein, Described micro-base station scaling dormancy strategy is particularly as follows: micro-base station dormancy or micro-base station range keep constant or micro-base station Coverage expands or micro-base station range reduces；

Described network equipment utilizes described ν_mWith described γ_mDetermine the micro-base station scaling dormancy strategy in heterogeneous network, specifically wrap Include:

Described network equipment utilizes described ν_mWith described γ_mJudge whether micro-base station meets dormancy condition；

If it is, described network equipment determines that described micro-base station scaling dormancy strategy is micro-base station dormancy；

If it does not, as described ν_mWith described γ_mMeet the trigger gate of micro-base station range expansion in limited time, described network equipment Determine that described micro-base station scaling dormancy strategy is that micro-base station range expands；As described ν_mWith described γ_mMeet micro-base station to cover In limited time, described network equipment determines that described micro-base station scaling dormancy strategy is micro-base station range to the trigger gate of range shorter Reduce；As described ν_mWith described γ_mIt is unsatisfactory for the triggering thresholding that micro-base station range expands, and is unsatisfactory for micro-base station covering model Enclosing the trigger gate reduced in limited time, described network equipment determines that described micro-base station scaling dormancy strategy is that micro-base station range is protected Hold constant；

Described network equipment utilizes described ν_mWith described γ_mJudge whether micro-base station meets the process of dormancy condition, wrap further Include:

Described network equipment is utilizing described ν_mWith described γ_mWhen the relation that is defined below is set up, determine that micro-base station meets dormancy bar Part；Otherwise, it determines micro-base station does not meets dormancy condition；

$\frac{{\mathrm{\&lambda;}}_m{P}_m^c+{\mathrm{\&lambda;}}_M{P}_M^c}{{\mathrm{\&lambda;}}_m{P}_m^s+{\mathrm{\&lambda;}}_M{P}_M^c}>\frac{1+{\mathrm{\&gamma;}}_m}{1+v_m};$

Wherein, λ_mFor the density of micro-base station, λ_MFor the density of macro base station,For the static power of micro-base station,Quiet for macro base station State power,Dormancy power for micro-base station；

Described network equipment is utilizing described ν_mWith described γ_mWhen the relation that is defined below is set up, determine described ν_mWith described γ_mFull The triggering thresholding that the micro-base station range of foot expands；

$\left\{\begin{array}{cc}\frac{P_m^c}{P_M^c}>max(\frac{{\mathrm{\&gamma;}}_m^2}{v_m},{\mathrm{\&gamma;}}_m),& v_m>1\\ v_m>{\mathrm{\&gamma;}}_m,\frac{P_m^c}{P_M^c}>\frac{{\mathrm{\&gamma;}}_m^2}{v_m},& v_m<1\end{array}\right.;$

Described network equipment is utilizing described ν_mWith described γ_mWhen the relation that is defined below is set up, determine described ν_mWith described γ_mFull The triggering thresholding that the micro-base station range of foot reduces；

$\left\{\begin{array}{cc}{v}_m<{\mathrm{\&gamma;}}_m,\frac{P_m^c}{P_M^c}<\frac{{\mathrm{\&gamma;}}_m^2}{v_m},& v_m>1\\ \frac{P_m^c}{P_M^c}<min(\frac{{\mathrm{\&gamma;}}_m^2}{v_m},{\mathrm{\&gamma;}}_m),& v_m<1\end{array}\right.;$

Wherein, at described ν_mWith described γ_mMeet the trigger gate of micro-base station range expansion in limited time, described network equipment profit Optimum coverage with the micro-base station of equation below calculating:

$\left\{\begin{array}{cc}{\widetilde{\mathrm{\&gamma;}}}_m^{opt}=max(\sqrt{v_m\frac{P_m^c}{P_M^c}},\frac{P_m^c}{P_M^c}),& v_m>1\\ {\widetilde{\mathrm{\&gamma;}}}_m^{opt}=\sqrt{v_m\frac{P_m^c}{P_M^c}},& v_m<1\end{array}\right.;$

Wherein, at described ν_mWith described γ_mMeet trigger gate that micro-base station range reduces in limited time, described network equipment profit Optimum coverage with the micro-base station of equation below calculating:

${\widetilde{\mathrm{\&gamma;}}}_m^{opt}=min(\sqrt{v_m\frac{P_m^c}{P_M^c}},\frac{P_m^c}{P_M^c});$

Wherein,For the static power of micro-base station,Static power for macro base station.

2. the method for claim 1, it is characterised in that described network equipment determines hot spot region unit are business Speed and ratio ν of non-focus territorial unit area service rate_m, and determine hot spot region area and non-focus region area Ratio γ_mAfterwards, described method also includes:

Described network equipment utilizes described ν_mWith described γ_mDetermining the user convergence factor h in heterogeneous network, described user gathers Collect coefficient h quantitative response user group's Behavior law, and user group's Behavior law is characterized by user behavior curve；Wherein, The transverse axis of user behavior curve corresponding cumulative time in observation interval or cumulative area or accumulative content, the longitudinal axis represents accumulative Service rate, the recessed degree of user behavior curve represents user behavior aggregation extent, if user behavior curve is the most flat, Then explanation user behavior diversity is the least, if user behavior curve is the most recessed, then explanation user behavior diversity is the biggest.

3. method as claimed in claim 2, it is characterised in that described network equipment utilizes described ν_mWith described γ_mDetermine different User convergence factor h in network forming network, specifically includes:

Described network equipment utilizes equation below to determine the user convergence factor h in heterogeneous network:

$h=\left\{\begin{array}{cc}\frac{{\mathrm{\&gamma;}}_m{v}_m}{{\mathrm{\&gamma;}}_m{v}_m+1}-\frac{{\mathrm{\&gamma;}}_m}{{\mathrm{\&gamma;}}_m+1}& v_m>1\\ \frac{{\mathrm{\&gamma;}}_m}{{\mathrm{\&gamma;}}_m+1}-\frac{{\mathrm{\&gamma;}}_m{v}_m}{{\mathrm{\&gamma;}}_m{v}_m+1}& v_m<1\end{array}\right..$

4. a network equipment, it is characterised in that described network equipment specifically includes:

First determines module, is used for determining hot spot region unit are service rate and non-focus territorial unit area service rate Ratio ν_m, and determine hot spot region area and ratio γ of non-focus region area_m；

Second determines module, is used for utilizing described ν_mWith described γ_mDetermine the micro-base station scaling dormancy strategy in heterogeneous network；Its In, described micro-base station scaling dormancy strategy is particularly as follows: micro-base station dormancy or micro-base station range keep constant or micro- Base station range expands or micro-base station range reduces；

Described second determines module, specifically for utilizing ν_mAnd γ_mJudge whether micro-base station meets dormancy condition；If it is, determine Described micro-base station scaling dormancy strategy is micro-base station dormancy；If it does not, as described ν_mWith described γ_mMeet micro-base station range The trigger gate expanded in limited time, determines that described micro-base station scaling dormancy strategy is that micro-base station range expands；As described ν_mAnd institute State γ_mMeet trigger gate that micro-base station range reduces in limited time, determine that described micro-base station scaling dormancy strategy is that micro-base station is covered Lid range shorter；As described ν_mWith described γ_mIt is unsatisfactory for the triggering thresholding that micro-base station range expands, and is unsatisfactory for micro-base station The trigger gate that coverage reduces in limited time, determines that described micro-base station scaling dormancy strategy is that micro-base station range keeps constant；

Described second determines module, is further used for utilizing described ν_mWith described γ_mWhen the relation that is defined below is set up, determine micro- Base station meets dormancy condition；Otherwise, it determines micro-base station does not meets dormancy condition；

$\frac{{\mathrm{\&lambda;}}_m{P}_m^c+{\mathrm{\&lambda;}}_M{P}_M^c}{{\mathrm{\&lambda;}}_m{P}_m^s+{\mathrm{\&lambda;}}_M{P}_M^c}>\frac{1+{\mathrm{\&gamma;}}_m}{1+v_m};$

Utilizing described ν_mWith described γ_mWhen the relation that is defined below is set up, determine described ν_mWith described γ_mMeet micro-base station and cover model Enclose the triggering thresholding of expansion；

$\left\{\begin{array}{cc}\frac{P_m^c}{P_M^c}>max(\frac{{\mathrm{\&gamma;}}_m^2}{v_m},{\mathrm{\&gamma;}}_m),& v_m>1\\ v_m>{\mathrm{\&gamma;}}_m,\frac{P_m^c}{P_M^c}>\frac{{\mathrm{\&gamma;}}_m^2}{v_m},& v_m<1\end{array}\right.;$

Utilizing described ν_mWith described γ_mWhen the relation that is defined below is set up, determine described ν_mWith described γ_mMeet micro-base station and cover model Enclose the triggering thresholding reduced；

$\left\{\begin{array}{cc}{v}_m<{\mathrm{\&gamma;}}_m,\frac{P_m^c}{P_M^c}<\frac{{\mathrm{\&gamma;}}_m^2}{v_m},& v_m>1\\ \frac{P_m^c}{P_M^c}<min(\frac{{\mathrm{\&gamma;}}_m^2}{v_m},{\mathrm{\&gamma;}}_m),& v_m<1\end{array}\right.;$

Wherein, at described ν_mWith described γ_mMeet the trigger gate of micro-base station range expansion in limited time, utilize equation below to calculate The optimum coverage of micro-base station:

$\left\{\begin{array}{cc}{\widetilde{\mathrm{\&gamma;}}}_m^{opt}=max(\sqrt{v_m\frac{P_m^c}{P_M^c}},\frac{P_m^c}{P_M^c}),& v_m>1\\ {\widetilde{\mathrm{\&gamma;}}}_m^{opt}=\sqrt{v_m\frac{P_m^c}{P_M^c}},& v_m<1\end{array}\right.;$

Wherein, at described ν_mWith described γ_mMeet trigger gate that micro-base station range reduces in limited time, utilize equation below to calculate The optimum coverage of micro-base station:

${\widetilde{\mathrm{\&gamma;}}}_m^{opt}=min(\sqrt{v_m\frac{P_m^c}{P_M^c}},\frac{P_m^c}{P_M^c});$

Wherein, λ_mFor the density of micro-base station, λ_MFor the density of macro base station,For the static power of micro-base station,For macro base station Static power,Dormancy power for micro-base station.

5. network equipment as claimed in claim 4, it is characterised in that also include:

3rd determines module, is used for utilizing described ν_mWith described γ_mDetermine the user convergence factor h in heterogeneous network, described user Convergence factor h quantitative response user group's Behavior law, and user group's Behavior law characterized by user behavior curve；Its In, the transverse axis of user behavior curve corresponding cumulative time in observation interval or cumulative area or accumulative content, the longitudinal axis represents Accumulative service rate, the recessed degree of user behavior curve represents user behavior aggregation extent, if user behavior curve The most flat, then explanation user behavior diversity is the least, if user behavior curve is the most recessed, then explanation user behavior diversity is more Greatly；

Described 3rd determines that module utilizes equation below to determine the user convergence factor h in heterogeneous network:

$h=\left\{\begin{array}{cc}\frac{{\mathrm{\&gamma;}}_m{v}_m}{{\mathrm{\&gamma;}}_m{v}_m+1}-\frac{{\mathrm{\&gamma;}}_m}{{\mathrm{\&gamma;}}_m+1}& v_m>1\\ \frac{{\mathrm{\&gamma;}}_m}{{\mathrm{\&gamma;}}_m+1}-\frac{{\mathrm{\&gamma;}}_m{v}_m}{{\mathrm{\&gamma;}}_m{v}_m+1}& v_m<1\end{array}\right..$