CN102892125A - interference coordination method for energy-saving communication of heterogeneous network - Google Patents

Abstract

An interference coordination method for energy-saving communication of a heterogeneous network comprises the steps of: pre-setting a protection region and an interference region during heterogeneous same-frequency networking, and concentrating same-frequency interference causing energy loss in the interference region; (2) determining an energy loss model of small base stations; (3) determining the respective energy-saving equation of a macro base station and the small base stations; (4) determining the total number of the set small base station and the coverage range of the small base station; and (5) reasonably configuring the existing heterogeneous network according to the optimal parameter values of the total number and the coverage range of the set small base station. The interference coordination method provided by the invention has an innovation feature that the method can effectively reduce the interference in the heterogeneous network mode while ensuring the service quality of edge users as well as the throughput of cell edge users by combining the sensing technology with the base station power control technology and the distributive optimization technology, thereby realizing the optimized goal of the largest energy efficiency and the lowest energy consumption of the system.

Description

The disturbance coordination method of the energy-conservation communication of heterogeneous network

Technical field

The disturbance coordination method of energy-conservation communication when the present invention relates to a kind of isomery with the networking of frequency division layer belongs to the technical field of radio communication.

Background technology

Entered since 21 century; countries in the world recognize that generally growing energy resource consumption has badly influenced human living environment in the global range; therefore; the active demand of reduce greenhouse effect, preserving the ecological environment has changed energy problem into unavoidable significant challenge and the common mission that the whole mankind faces.

At present, the global electric energy ratio of information industry consumption has reached 3 ~ 4%, and under the use pattern of the existing energy, this proportional numerical value also increases rapidly in the speed of doubling with per ten years.Along with fast development and the extensive use of cellular network, the research of its energy consumption problem also becomes the emphasis of current green communications work.In addition traditional cellular network planning is that its focus is concentrated in the lifting of performance (for example: the transmission service quality of edge customer, residential quarter total throughout etc.), and the worry about energy does not consume.Therefore, how to reduce the energy consumption of cellular network, promote the energy service efficiency of whole residential quarter, having become next generation mobile communication system needs one of top-priority subject matter.

The isomery hierarchical network is the typical way of LTE-A network design.Based on having frequency spectrum now and introducing little base station (Picocell, Femtocell or Relay) and realize that the identical networking of multilayer heterogeneous network is best solution.In addition, fast-developing business demand also more and more becomes a kind of trend so that the same frequency between the hierarchical network is multiplexing, and simultaneously, it also causes the interference between each little base station or the residential quarter more complicated and serious.

Interference in the isomery common-frequency network mainly is co-channel interference.So-called co-channel interference refers to that the carrier frequency of unwanted signal is identical with the carrier frequency of useful signal, and the interference that causes receiving the same frequently receiver of useful signal.Common co-channel interference mainly concentrates on the edge of residential quarter, mainly contains two kinds at the downlink transfer passage: the interference between macrocellular and the microcellulor, and the interference between the microcellulor.

The coordination technique of presence of intercell interference is a kind of scheduling strategy that improves the Cell Edge User message transmission rate by the interference that reduces the minizone, namely by the scheduler in the residential quarter resource of up link and down link is made rational planning for and limit use, with this Quality of experience of controlling the interference of minizone and promoting edge customer.

Yet interference coordination technique is no longer in full force and effect between the conventional cell that adopts among the Release-8/9 of LTE.Because in heterogeneous network, the deployment of little base station not only can improve the throughput of system and the service quality of edge customer, and simultaneously its operation also needs energy consumption expense to a certain degree.And, in the time of little base station deployment, also can bring the conflict of calling between the sub-carrier resources, thereby cause the waste of energy.These all are the problems that must solve when considering energy-conservation communication.So, so far for this reason, a kind of technical scheme for considering the interference coordination of energy-conservation communication under the isomery identical networking is proposed not yet all both at home and abroad at present.

Summary of the invention

In view of this, the purpose of this invention is to provide a kind of disturbance coordination method for the energy-conservation communication of heterogeneous network, the method can provide the interference coordination management strategy that conserve energy consumes for isomery identical networking pattern.

In order to achieve the above object, the invention provides a kind of disturbance coordination method for the energy-conservation communication of heterogeneous network, it is characterized in that: described method comprises following operating procedure:

(1) during the isomery identical networking, set in advance protection zone and interference region, and the co-channel interference that will cause energy loss concentrates in the interference region: when a macro base station coverage area is disposed little base station, determine first the border circular areas of a roundlet as the center of circle take this macro base station website, as the protection zone of not disposing little base station, and all little base stations all are arranged between the outside, this protection zone and this macro base station maximum coverage range in the formed annular interference region; Then, determine respectively the radius value of this roundlet and macro base station maximum coverage range, and all initial total numbers in little base station;

(2) determine little base station energy consumption model: because only having a macro base station, consider that little base station can bring energy expense, and little base station number and covering radius thereof are variable, comprise dynamically and the linear energy consumption model of static two-part little base station so set up, wherein, dynamic part depends on number of users and business demand; Static part is the actual consumption that little base station comprises power amplification circuit and battery reserve, the basic energy of the required consumption in namely little base station;

(3) determine macro base station and little base station energy-conservation equation separately: the current carrier wave operating position of macro base station that detects according to little base station, and the subcarrier collisions situation of macro base station and little base station, calculate respectively macro base station and little base station and comprise the various energy losses that cause because of wave carrier conflict; Then, to the carrier information that adopts the perception of little base station, detection with do not adopt the energy loss of above-mentioned technology to compare, obtain adopting the macro base station of cognition technology and little base station energy consumption separately to save computing formula, i.e. energy-conservation equation;

(4) the definite total number in little base station and coverage thereof that arranges: adopt the particle swarm optimization algorithm based on the parallel vector evaluation in the multi-objective nonlinear optimization method, little base station and macro base station energy-conservation equation separately are optimized, obtain the total number in little base station and the coverage thereof that should arrange in this network system;

The total number in little base station of the setting that (5) obtains according to above-mentioned steps and the optimal value of the parameter of coverage thereof carry out reasonable disposition to existing heterogeneous network.

The innovative characteristics of the disturbance coordination method of the energy-conservation communication of heterogeneous network of the present invention is: cognition technology, base station power control technology and distributed optimization technology are mutually combined, under the prerequisite that guarantees edge customer service quality, effectively reduce the interference conflict under the heterogeneous network pattern, improved the energy efficiency of system.In brief, the energy-conservation Communication Jamming coordination approach of isomery hierarchical network based on cognition technology of the present invention can on the basis of as far as possible satisfying QoS of customer and these two main singal reporting codes of Cell Edge User throughput, realize that the efficiency of system is maximum, the minimum optimum target of energy consumption.

In addition, the inventive method is done a choice and balance take system as whole in the throughput that strengthens edge customer and QoS of customer and system capacity consumption, has proposed optimum interference coordination schemes, has realized entire system energy consumption optimization.Therefore, the present invention has good popularizing application prospect.

Description of drawings

Fig. 1 is the application scenarios of the inventive method: the network architecture of isomery identical networking forms schematic diagram.

Fig. 2 is the disturbance coordination method operating procedure flow chart of the energy-conservation communication of heterogeneous network of the present invention.

Fig. 3 is in the disturbance coordination method of the energy-conservation communication of heterogeneous network of the present invention, the determination portion administration flow chart of the total number N in little base station and perception factor ε.

Fig. 4 is that isomery hierarchical network system adopts specific implementation process schematic diagram of the present invention.

Embodiment

For making the purpose, technical solutions and advantages of the present invention clearer, the present invention is described in further detail below in conjunction with drawings and Examples.

The thinking of the inventive method is: in the communication system of isomery identical networking, the introducing of little base station can be guaranteed the service quality of Cell Edge User, increases cell throughout; But when introduced little base station, the transmission that can increase inside, residential quarter was disturbed; In addition, setting up of little base station self also has energy consumption.Therefore, the present invention adopts the use information by little base station perception subcarrier, adopt the distributed optimization algorithm that the system energy consumption equation is optimized, draw optimum little base station deployment number and covering radius thereof, and then realize the Inter-Cell Interference Coordination management that efficiency is preferential.

Referring to Fig. 1 and Fig. 2, introduce the operating procedure of the disturbance coordination method of the energy-conservation communication of heterogeneous network of the present invention:

Step 1, during the isomery identical networking, set in advance protection zone and interference region (referring to Fig. 1), and the co-channel interference that will cause energy loss concentrates in the interference region: when a macro base station coverage area is disposed little base station, determine first the border circular areas of a roundlet as the center of circle take this macro base station website, as the protection zone of not disposing little base station, and all little base stations all are arranged between the outside, this protection zone and this macro base station maximum coverage range in the formed annular interference region; Then, determine respectively the radius value of this roundlet and macro base station maximum coverage range, and all initial total numbers in little base station.This step comprises following content of operation:

(11) determine interior radius of circle α R and the exradius R of the interference region of annular, wherein, α is interior radius of circle and the ratio of exradius; Described inner circle be take the macro base station website as the center of circle, α R determined a border circular areas by radius, as not existing outside little base station its internal user to be produced the protection zone of descending interference; Be simplified model, draw concrete energy-conservation expression formula, it is considered herein that co-channel interference exists only in the interference region of annular, and only consider macro base station and little base station to the interference of downlink user, and do not consider between each little base station and the interference of adjacent area macro base station.This hypothesis does not affect applicability of the present invention, model further can be expanded in real system.

(12) in the interference region of annular, adopt two-dimentional Poisson method to determine the distribution density of little base station, i.e. the little base station number λ of unit are.Although the little base station in the real system distributes when obeying user empty, and normally obeys the feature of power-law distribution, Poisson distribution also is the common random distribution that has closed solutions, can not produce too much impact to real system, still has universality.

Step 2, determine little base station energy consumption model: because only having a macro base station, consider that little base station can bring energy expense, and little base station number and covering radius thereof are variable, comprise dynamically and the linear energy consumption model of static two-part little base station so set up, wherein, dynamic part depends on number of users and business demand; Static part is the actual consumption that little base station comprises power amplification circuit and battery reserve, the basic energy of the required consumption in namely little base station.

This step comprises following content of operation: determine first the linear energy consumption model of little base station, i.e. the energy P of each little base station mean consumption _SubFor: P _Sub=L * (a _Sub* P _Tx+ b _Sub), in the formula, L is based on the coefficient of energy dissipation of the current dynamic change of user and business, the expression dynamic energy consumption; P _Tx, a _SubAnd b _SubThe radiant power fissipation factor that is respectively the radiant power of each little base station, changes with amplifier and feeder loss, with and depend on the energy consumption compensating parameter that battery reserve and signal are processed, a _SubAnd b _SubBoth change (a with antenna number and sector _Sub* P _Tx+ b _Sub) represent static energy consumption, the basic energy consumption of namely little base station.

Step 3, determine macro base station and little base station energy-conservation equation separately: the current carrier wave operating position of macro base station that detects according to little base station, and the subcarrier collisions situation of macro base station and little base station, calculate respectively macro base station and little base station and comprise the various energy losses that cause because of wave carrier conflict; Then, to the carrier information that adopts the perception of little base station, detection with do not adopt the energy loss of above-mentioned technology to compare, obtain adopting the macro base station of cognition technology and little base station energy consumption separately to save computing formula, i.e. energy-conservation equation.This step comprises following content of operation:

(31) obeying density because of little base station is the two-dimentional Poisson distribution of λ, so namely can there be the probability P of macro base station and little base station subcarrier collisions in the probability that the subcarrier information of the user in interference region and use thereof is not detected by little base station group coverage _UCFor:

In the formula,

Be the covering gross area of all little base stations, distribution density

The little base station total number of N for arranging, R is the covering radius of macro base station, r is the covering radius of little base station, f (α)=1-α ², α is inside and outside circle radius ratio (referring to Fig. 1), α R is macro base station protection zone radius.

(32) change covering radius because of little base station, just can perception, detect more user's subcarrier and use information, so optimize first the covering radius of little base station: at first determine each critical covering radius in little base station, namely do not exist between all little base stations and cover when overlapping radius value r during just with the area covering ratio μ cover jamming zone gross area ₀, namely by formula: μ * f (α) π R ²=N * π r ₀ ²Obtain

In the formula, μ is all little base station area coverage sums, namely under the macro base station coverage, dispose the ratio that the actual interference zone that exists behind the little base station accounts for whole annular interference region gross areas;

(33) the covering radius r=ε * r of each little base station is set ₀, wherein, perception factor variable ε is not less than 1 arithmetic number, is used for showing that little base station is ready to adopt increases its sensing range at interference region and detect more user's subcarrier and use information; Like this, obtain user's subcarrier and use the probability P that is not detected by little base station group coverage _UC: $P_{\mathrm{UC}}=\exp \{-\frac{N}{f\left(\mathrm{\α}\right)\mathrm{\π}{R}^2}\×\mathrm{\π}\×{[\mathrm{\ϵR}\×\sqrt{\frac{\mathrm{\μ}\·f\left(\mathrm{\α}\right)}{N}}]}^2\}=e^{{-\mathrm{\ϵ}}^2\mathrm{\μ}};$

(34) according to collision probability and the energy consumption model of abovementioned steps, set up respectively little base station And macro base station

Energy-conservation equation separately be respectively:

The energy-conservation total amount of all little base stations:

Formula (1);

The energy-conservation total amount of macro base station:

Formula (2):

Wherein, β is the active user's number in the interference region, P ₁Be the downlink transmission power of little base station, P ₀Downlink transmission power for macro base station; When energy consumption feedback factor sigma may was single macro base station, user and the business of macro base station were shared in set little base station; Namely set up the energy consumption that little base station produces, be equivalent to Substitute For Partial macro base station and professional dynamic energy consumption thereof;

Energy-conservation total amount when being macro base station employing perception detection, wherein the difference of expected loss energy consumption and collision loss energy consumption is the energy that adopts the perception detection technique to save, and deducts the operation energy consumption of cognition technology self energy consumption and all little base stations again; The energy-conservation equation of macro base station and the energy-conservation equation of all little base stations are basic identical, and its difference is just according to the feedback energy consumption, and macro base station partial dynamic energy consumption has been reduced in the little base station of foundation.

Step 4, determine the total number in little base station and the coverage thereof of setting: adopt the particle swarm optimization algorithm based on the parallel vector evaluation in the multi-objective nonlinear optimization method, little base station and macro base station energy-conservation equation separately are optimized, obtain the total number in little base station and the coverage thereof that should arrange in this network system.

Particle swarm optimization algorithm in this step is a kind of distributed computing method, and its computational complexity is relatively low, is convenient to practical operation.This particle swarm optimization algorithm be two energy-conservation equations with all little base stations and macro base station respectively as two population, the optimal particle of each population is used for upgrading the speed of another population and the Optimized Iterative computing that position equation carries out; This step comprises following content of operation:

(41) following each parameter initialization value is set: initial time t=0, the population in the population is M, initialized location

And speed

Local optimum position initial value

With global optimum's position initial value $P_{\mathrm{gb}}^{\left[1\right]}=\mathrm{globalbestof}{P}_i^{\left[2\right]}$ With $P_{\mathrm{gb}}^{\left[2\right]}=\mathrm{globalbestlof}{P}_i^{\left[1\right]};$ And cognitive speed With social learning's speed

In the formula, sequence number j is 1 and 2, represents respectively all little base station and macro base stations;

(42) update time: time parameter is updated to t=t+1, and is arranged on [0,1] upper equally distributed two random number r ₁, r ₂Initial value;

(43) iteration renewal speed: with all little base stations and macro base station t constantly the global optimum position and the optimal location of each particle respectively following two computing formula of substitution substitute, obtain both in (t+1) speed constantly

With

$V_i^{\left[1\right]}(t+1)=k^{\left[1\right]}\×[w_i^{\left[1\right]}\·V_i^{\left[1\right]}\left(t\right)+c_1^{\left[1\right]}\×r_1\×\{P_i^{\left[1\right]}-S_i^{\left[1\right]}\left(t\right)\}+c_2^{\left[1\right]}\×r_2\×\{P_{\mathrm{gb}}^{\left[2\right]}-S_i^{\left[1\right]}\left(t\right)\left\}\right],$ Formula (3);

$V_i^{\left[2\right]}(t+1)=k^{\left[2\right]}\×[w_i^{\left[2\right]}\·V_i^{\left[2\right]}\left(t\right)+c_1^{\left[2\right]}\×r_1\×\{P_i^{\left[2\right]}-S_i^{\left[2\right]}\left(t\right)\}+c_2^{\left[2\right]}\×r_2\×\{P_{\mathrm{gb}}^{\left[1\right]}-S_i^{\left[2\right]}\left(t\right)\left\}\right],$ Formula (5);

In the formula, k is convergence factor, and w is inertia weight, c ₁And c ₂Respectively cognitive learning speed and the social learning's rate factor that all depends on empirical value;

Above-mentioned two speed more new formula are comprised of following three parts respectively: the previous speed with the whole population with seeking the local optimum ability of balance, make population can search out global optimum, avoid being subjected to the cognitive learning renewal speed of local optimum restriction, social learning's renewal speed of the information interaction ability between the reflection population;

(44) iteration is upgraded local location: according to the new velocity amplitude that obtains in the step (43), following two computing formula of substitution are upgraded respectively, obtain all little base stations and each leisure of macro base station (t+1) reposition constantly $S_i^{\left[1\right]}(t+1)$ With $S_i^{\left[2\right]}(t+1):$

$S_i^{\left[1\right]}(t+1)=S_i^{\left[1\right]}\left(t\right)+V_i^{\left[1\right]}(t+1),$ Formula (4);

$S_i^{\left[2\right]}(t+1)=S_i^{\left[2\right]}\left(t\right)+V_i^{\left[2\right]}(t+1),$ Formula (6);

(45) upgrade all little base stations and macro base station particle local optimum positional value separately: according to reposition corresponding Parameter N and ε, following two computing formula of substitution are upgraded respectively, obtain the local optimum positional value that both upgrade

With

Little base station:

Macro base station:

(46) upgrade all little base stations and macro base station particle global optimum positional value separately: compared by the local optimum of this moment t+1 and the global optimum of a upper moment t, again according to formula

With

Draw both the up-to-date global optimum positional values after each iteration;

(47) judge the termination of iterations operation: judge whether the iterative operation number of times reaches set point number, if not, then continue to carry out iteration, namely return execution in step (42); Otherwise, stop iterative operation; Perhaps when all particle optimal result after continuous tens of iteration, when not changing all the time, also be considered as finishing iteration.

Step 5, the total number in little base station that should arrange that obtains according to above-mentioned steps and the optimal value of the parameter of coverage thereof carry out reasonable disposition to existing heterogeneous network.

The present invention has carried out repeatedly implementing test, below brief description implement the situation of test:

Referring to Fig. 3, introduce each step content of the operating process of the λ value of determining in the wireless broadcast multicast layered modulation power distribution method of first embodiment of the invention:

Step 210 is determined the initiation parameter value: initial time t=0 is set, determines the population M that comprises in the population, the initialized location value of two population

And velocity amplitude (j=1,2).Initial local optimum position is set to

The initial global optimum position of two population is set to respectively $P_{\mathrm{gb}}^{\left[1\right]}=\mathrm{globalbestof}{P}_i^{\left[2\right]}$ With $P_{\mathrm{gb}}^{\left[2\right]}=\mathrm{globalbestof}{P}_i^{\left[1\right]}.$ Two learning rates cognitive and society are set again is

(j=1,2).

Step 220, the time upgrades: the modification time parameter is t=t+1, and initial setting up is at [0,1] upper equally distributed random parameter.

Step 230, velocity amplitude upgrades: utilize optimal location substitution formula (3) and the formula (5) of t global optimum position constantly and each particle to substitute, obtain t+1 speed constantly

Step 240, the position is upgraded: according to the new velocity amplitude that step 230 obtains, utilize expression formula 4 and 6 to upgrade t+1 position constantly

All particles move to new position.

Step 250, particle local optimum positional value upgrades: according to reposition corresponding Parameter N and ε, substitution formula (1) and formula (2), the local optimum positional value that obtains upgrading.

Step 260, global optimum's positional value upgrades: according to formula

With

Upgrade the up-to-date global optimum positional value after each iteration.

Step 270, judge end condition: during implementation, a program iterations is set, when iterations reaches this settings and counts, the program termination.In addition, when all particle optimal result did not change in continuous tens of (for example 20 times) iteration all the time, the program that also is considered as stopped.

Referring to Fig. 3, introduce the operating process that the embodiment of the invention is applied to carry out disturbance coordination method:

Step S310 determines the configuration parameter of heterogeneous network system, comprising the downlink transmission power P of macro base station and little base station ₀, P ₁And covering radius R, r also has the initial distribution density λ of little base station.

Step S320 determines the channel path loss factor, and embodiments of the invention are defined as n=2, in order to simplify two energy-conservation equations of system, obtains the optimization method after following two Bi-objectives are simplified:

$U_{\mathrm{BS}}(\mathrm{\ϵ},N)=\mathrm{\β}\×\mathrm{\μf}\left(\mathrm{\α}\right)\×P_0\×(1-e^{-{\mathrm{\ϵ}}^2\mathrm{\μ}})+\mathrm{\σ}\×N\×P_{\mathrm{sub}},$ Formula (7);

$U_{\mathrm{SN}}(\mathrm{\ϵ},N)=\mathrm{\β}\×\mathrm{\μf}\left(\mathrm{\α}\right)\×P_1\×(1-e^{{-\mathrm{\ϵ}}^2\mathrm{\μ}})-N\×p_{\mathrm{cs}}\×{\left(\mathrm{\ϵ}{r}_0\right)}^2-N\×P_{\mathrm{sub}},$ Formula (8);

Step S330 carries out the optimization computing of network parameter according to the distributed particle swarm optimization algorithm of Fig. 2, and according to optimum results, obtains optimum energy-conservation configuration parameter N and ε, and this step is by the macro base station computing.

Step S340 passes to little base station with the configuration information of one group of optimum obtaining in the step 330 by macro base station, and controls next deployment quantity and sensor coverage radius value constantly of little base station.

Step S350, the wave carrier conflict information reporting that is perceived by little base station be to macro base station, and then macro base station is for the carrier wave independently of the user assignment in the corresponding interference region.

In the embodiments of the invention, cognition technology is dissolved in the little base station deployment of heterogeneous network, can be guaranteed QoS of customer, and reduce to the utmost the energy loss that wave carrier conflict brings.The technical scheme that the embodiment of the invention provides can be directly used among the new generation of wireless mobile communication system IMT-A, also can be applied in the isomery hierarchical network interference management, has extensive use at the framework of the Wireless Heterogeneous Networks in future.

Although the disclosed execution mode of the present invention as above, the execution mode that described content just adopts for the ease of understanding the present invention is not to limit the present invention.Technical staff in any the technical field of the invention; under the prerequisite that does not break away from the disclosed spirit and scope of the present invention; can do any modification and variation in the details that reaches of implementing in form; but scope of patent protection of the present invention still must be as the criterion with the scope that appending claims was defined.

Claims (5)

1. the disturbance coordination method of the energy-conservation communication of heterogeneous network, it is characterized in that: described method comprises following operating procedure:

(1) during the isomery identical networking, set in advance protection zone and interference region, and the co-channel interference that will cause energy loss concentrates in the interference region: when a macro base station coverage area is disposed little base station, determine first the border circular areas of a roundlet as the center of circle take this macro base station website, as the protection zone of not disposing little base station, and all little base stations all are arranged between the outside, this protection zone and this macro base station maximum coverage range in the formed annular interference region; Then, determine respectively the radius value of this roundlet and macro base station maximum coverage range, and all initial total numbers in little base station;

(2) determine little base station energy consumption model: because only having a macro base station, consider that little base station can bring energy expense, and little base station number and covering radius thereof are variable, comprise dynamically and the linear energy consumption model of static two-part little base station so set up, wherein, dynamic part depends on number of users and business demand; Static part is the actual consumption that little base station comprises power amplification circuit and battery reserve, the basic energy of the required consumption in namely little base station;

(3) determine macro base station and little base station energy-conservation equation separately: the current carrier wave operating position of macro base station that detects according to little base station, and the subcarrier collisions situation of macro base station and little base station, calculate respectively macro base station and little base station and comprise the various energy losses that cause because of wave carrier conflict; Then, to the carrier information that adopts the perception of little base station, detection with do not adopt the energy loss of above-mentioned technology to compare, obtain adopting the macro base station of cognition technology and little base station energy consumption separately to save computing formula, i.e. energy-conservation equation;

(4) the definite total number in little base station and coverage thereof that arranges: adopt the particle swarm optimization algorithm based on the parallel vector evaluation in the multi-objective nonlinear optimization method, little base station and macro base station energy-conservation equation separately are optimized, obtain the total number in little base station and the coverage thereof that should arrange in this network system;

The total number in little base station of the setting that (5) obtains according to above-mentioned steps and the optimal value of the parameter of coverage thereof carry out reasonable disposition to existing heterogeneous network.

2. method according to claim 1, it is characterized in that: described step (1) comprises following content of operation:

(11) determine interior radius of circle α R and the exradius R of the interference region of annular, wherein, α is interior radius of circle and the ratio of exradius; Described inner circle be take the macro base station website as the center of circle, α R determined a border circular areas by radius, as not existing outside little base station its internal user to be produced the protection zone of descending interference; Be simplified model, think that co-channel interference exists only in the interference region of annular, and only consider macro base station and little base station to the interference of downlink user, and do not consider between each little base station and the interference of adjacent area macro base station;

(12) in the interference region of annular, adopt two-dimentional Poisson method to determine the distribution density of little base station, i.e. the little base station number λ of unit are.

3. method according to claim 2, it is characterized in that: described step (2) comprises following content of operation: determine first the linear energy consumption model of little base station, i.e. the energy P of each little base station mean consumption _SubFor: P _Sub=L * (a _Sub* P _Tx+ b _Sub), in the formula, L is based on the coefficient of energy dissipation of the current dynamic change of user and business, the expression dynamic energy consumption; P _Tx, a _SubAnd b _SubThe radiant power fissipation factor that is respectively the radiant power of each little base station, changes with amplifier and feeder loss, with and depend on the energy consumption compensating parameter that battery reserve and signal are processed, a _SubAnd b _SubBoth change (a with antenna number and sector _Sub* P _Tx+ b _Sub) represent static energy consumption, the basic energy consumption of namely little base station.

4. method according to claim 1, it is characterized in that: described step (3) comprises following content of operation:

(31) obeying density because of little base station is the two-dimentional Poisson distribution of λ, so the probability that the subcarrier information of the user in interference region and use thereof is not detected by little base station group coverage, the i.e. probability P of macro base station and little base station subcarrier collisions _UCFor:

In the formula,

Be the covering gross area of all little base stations, distribution density

The little base station total number of N for arranging, R is the covering radius of macro base station, r is the covering radius of little base station, f (α)=1-α ², α is the inside and outside circle radius ratio, α R is macro base station protection zone radius;

(32) change just energy perception of covering radius, detect more user's subcarrier use information because of little base station, so optimize first its covering radius: at first determine each critical covering radius in little base station, namely do not exist between all little base stations and cover when overlapping radius value r during just with the area covering ratio μ cover jamming zone gross area ₀, namely by formula: μ * f (α) π R ²=N * π r ₀ ²Obtain

In the formula, μ is all little base station area coverage sums, namely under the macro base station coverage, dispose the ratio that the actual interference zone that exists behind the little base station accounts for whole annular interference region gross areas;

(33) the covering radius r=ε * r of each little base station is set ₀, wherein, perception factor variable ε is not less than 1 arithmetic number, is used for showing that little base station is ready to adopt increases its sensing range at interference region and detect more user's subcarrier and use information; Like this, obtain user's subcarrier and use the probability P that is not detected by little base station group coverage _UC: $P_{\mathrm{UC}}=\exp \{-\frac{N}{f\left(\mathrm{\α}\right)\mathrm{\π}{R}^2}\×\mathrm{\π}\×{[\mathrm{\ϵR}\×\sqrt{\frac{\mathrm{\μ}\·f\left(\mathrm{\α}\right)}{N}}]}^2\}=e^{{-\mathrm{\ϵ}}^2\mathrm{\μ}};$

(34) according to collision probability and energy consumption model, set up respectively little base station

And macro base station

Energy-conservation equation separately be respectively:

The energy-conservation total amount of all little base stations:

Formula (1) formula (2)

The energy-conservation total amount of macro base station:

Wherein, β is the active user's number in the interference region, P ₁Be the downlink transmission power of little base station, P ₀Downlink transmission power for macro base station; When energy consumption feedback factor sigma may was single macro base station, user and the business of macro base station were shared in set little base station; Namely set up the energy consumption that little base station produces, be equivalent to Substitute For Partial macro base station and professional dynamic energy consumption thereof;

Energy-conservation total amount when being macro base station employing perception detection, wherein the difference of expected loss energy consumption and collision loss energy consumption is the energy that adopts the perception detection technique to save, and deducts the operation energy consumption of cognition technology self energy consumption and all little base stations again; The energy-conservation equation of macro base station and the energy-conservation equation of all little base stations are basic identical, and its difference is just according to the feedback energy consumption, and macro base station partial dynamic energy consumption has been reduced in the little base station of foundation.

5. method according to claim 1, it is characterized in that: the particle swarm optimization algorithm in the described step (4) be two energy-conservation equations with all little base stations and macro base station respectively as two population, the optimal particle of each population is used for upgrading speed and the position equation of this population and another population; This Optimized Iterative calculation step comprises following content of operation:

(41) following each parameter initialization value is set: initial time t=0, the population in the population is M, initialized location

And speed

Local optimum position initial value With global optimum's position initial value $P_{\mathrm{gb}}^{\left[1\right]}=\mathrm{globalbestof}{P}_i^{\left[2\right]}$ With $P_{\mathrm{gb}}^{\left[2\right]}=\mathrm{globalbestof}{P}_i^{\left[1\right]};$ And cognitive speed

With social learning's speed

In the formula, sequence number j is 1 and 2, represents respectively all little base station and macro base stations;

(42) update time: time parameter is updated to t=t+1, and is arranged on [0,1] upper equally distributed two random number r ₁, r ₂Initial value;

(43) iteration renewal speed: with all little base stations and macro base station t constantly the global optimum position and the optimal location of each particle respectively following two computing formula of substitution substitute, obtain both in (t+1) speed constantly With

Little base station: $V_i^{\left[1\right]}(t+1)=k^{\left[1\right]}\×[w_i^{\left[1\right]}\·V_i^{\left[1\right]}\left(t\right)+c_1^{\left[1\right]}\×r_1\×\{P_i^{\left[1\right]}-S_i^{\left[1\right]}\left(t\right)\}+c_2^{\left[1\right]}\×r_2\×\{P_{\mathrm{gb}}^{\left[2\right]}-S_i^{\left[1\right]}\left(t\right)\left\}\right],$

Macro base station: $V_i^{\left[2\right]}(t+1)=k^{\left[2\right]}\×[w_i^{\left[2\right]}\·V_i^{\left[2\right]}\left(t\right)+c_1^{\left[2\right]}\×r_1\×\{P_i^{\left[2\right]}-S_i^{\left[2\right]}\left(t\right)\}+c_2^{\left[2\right]}\×r_2\×\{P_{\mathrm{gb}}^{\left[1\right]}-S_i^{\left[2\right]}\left(t\right)\left\}\right],$

In the formula, k is convergence factor, and w is inertia weight, c ₁And c ₂Respectively cognitive learning speed and the social learning's rate factor that all depends on empirical value;

Above-mentioned two speed more new formula are comprised of following three parts respectively: the previous speed with the whole population with seeking the local optimum ability of balance, make population can search out global optimum, avoid being subjected to the cognitive learning renewal speed of local optimum restriction, social learning's renewal speed of the information interaction ability between the reflection population;

(44) iteration is upgraded local location: according to the new velocity amplitude that obtains in the step (43), following two computing formula of substitution are upgraded respectively, obtain all little base stations and each leisure of macro base station (t+1) reposition constantly With $S_i^{\left[2\right]}(t+1):S_i^{\left[1\right]}(t+1)=S_i^{\left[1\right]}\left(t\right)+V_i^{\left[1\right]}(t+1),S_i^{\left[2\right]}(t+1)=S_i^{\left[2\right]}\left(t\right)+V_i^{\left[2\right]}(t+1);$

(45) upgrade all little base stations and macro base station particle local optimum positional value separately: according to reposition corresponding Parameter N and ε, following two computing formula of substitution are upgraded respectively, obtain the local optimum positional value that both upgrade With

Little base station:

Macro base station:

(46) upgrade all little base stations and macro base station particle global optimum positional value separately: compared by the local optimum of this moment t+1 and the global optimum of a upper moment t, again according to formula

With

Draw both the up-to-date global optimum positional values after each iteration;

(47) judge the termination of iterations operation: judge whether the iterative operation number of times reaches set point number, if not, then continue to carry out iteration, namely return execution in step (42); Otherwise, stop iterative operation; Perhaps when all particle optimal result after continuous tens of iteration, when not changing all the time, also be considered as finishing iteration.

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