CN108260074A - Combined optimization method is configured in energy source locations deployment and transmission power in a kind of RF energy capture wireless sense network - Google Patents

Combined optimization method is configured in energy source locations deployment and transmission power in a kind of RF energy capture wireless sense network Download PDF

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CN108260074A
CN108260074A CN201710593931.0A CN201710593931A CN108260074A CN 108260074 A CN108260074 A CN 108260074A CN 201710593931 A CN201710593931 A CN 201710593931A CN 108260074 A CN108260074 A CN 108260074A
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transmission power
energy source
energy
particle
position vector
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CN108260074B (en
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池凯凯
林民
林一民
俞湛威
汤泽锋
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Zhejiang University of Technology ZJUT
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/023—Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/28—TPC being performed according to specific parameters using user profile, e.g. mobile speed, priority or network state, e.g. standby, idle or non transmission
    • H04W52/283—Power depending on the position of the mobile
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/30—TPC using constraints in the total amount of available transmission power
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Feedback Control In General (AREA)

Abstract

Combined optimization method is configured in energy source locations deployment and transmission power in a kind of RF energy capture wireless sense network, for K energy source, determine the deployed position (x of each energy source, and transmission power p y), while the energy capture demand of sensing node each disposed is met, the total transmission power of energy source that reaches relatively low；Based on genetic algorithm, the 3K that K energy source locations and transmission power are corresponded to each particle first ties up position vector, then the position vector and velocity vector of iteration more new particle, when the corresponding scheme of a particle meets all node energy capture demands, then the fitness value of particle is defined as the total transmission power of energy source, is otherwise defined as K times of maximum transmission power；When reaching defined iterations, preferably energy source locations deployment and transmission power configuration are found.This method can find out preferably energy source deployment and transmission power configuration, the total transmission power of energy source for reaching relatively low, energy saving are preferable.

Description

Energy source locations deployment and transmission power in a kind of RF energy capture wireless sense network Combined optimization method is configured
Technical field
The present invention relates to a kind of RF energies to capture energy source locations deployment and transmission power configuration connection in wireless sense network Optimization method is closed, this method, which is suitable for sensor node, can capture the wireless sensor network of RF energy.
Background technology
Electromagnetic wave is as a kind of ubiquitous, environmentally protective and sustainable energy, increasingly by academia and industry The attention on boundary.RF energy capture wireless sense network is exactly the radio frequency energy in a kind of capturing ambient and is converted to electric energy with Zhi Chijie Point continues the new network of sex work.
But at this stage RF energy capture sensor node capturing ambient in radio frequency energy rate still very it is low, This is one of widely applied bottleneck of such new network.In order to overcome this weakness, deployment-specific energy source is powered to node It is a kind of feasible effective method.Since certain energy can be lost in radio frequency energy in transmission process, i.e., energy source is apart from node More remote, the radio frequency energy that node captures is fewer, therefore reasonable Arrangement each energy source so that network can be utmostly using penetrating Frequency energy, becoming one has the problem of important research.
Meanwhile from energy conservation and environmental protection angle, the radio frequency energy beyond node energy demand will waste in vain, Er Qieneng Amount source will also consume a large amount of energy, therefore, the problem of transmission power of each energy source of reasonable disposition is also one significant.
Invention content
In order to which overcome existing RF energy capture wireless sense network can not minimize energy source transmission power summation, energy saving Property poor deficiency, for RF energy capture sensor node is deployed in network and coordinate known case, the present invention carry Energy source locations deployment and transmission power configuration joint in a kind of preferable RF energy capture wireless sense network of energy saving are gone out Optimization method,
In order to solve the above technical problem, the present invention provides following technical solutions：
Combined optimization method is configured in energy source locations deployment and transmission power in a kind of RF energy capture wireless sense network, Include the following steps：
(1.1) according to the sensor node coordinate that can capture RF energy of given position N number of in wireless sense network, really The fixed unique minimum circle-cover in the region；Wherein, N is sensor node total number, and the minimum circle-cover of N number of node refers to cover All N number of nodes and the circle with least radius；
(1.2) a specific energy source is represented with the position vector of a particle in particle cluster algorithm to dispose and send Power configuration scheme initializes the initial position vector of M particle：For i=1,2 ..., M, the position vector of i-th of particle ForNumbers of the wherein K for energy source, the horizontal seat of j-th of energy source Mark and ordinateWithFor the abscissa and ordinate of a point chosen at random in minimum circle-cover, j-th energy source Transmission powerBy the transmission power randomly selected in the range of transmission power that transmission circuit is supported；The value mode of M As particle number value mode in conventional particle group's algorithm；
(1.3) the initial velocity vector v of i-th of particle is initializedi=0 and initialize i-th of particle optimal location Vectorial piFor its initial position vector, i.e. pi←xi；
(1.4) for i=1,2 ..., M, position vector p is calculatediK corresponding energy source transmission power summation f (pi), then find out the p of energy source transmission power summation minimumiAnd by global optimum position pgIt is set as pi, i.e. pg←pi；
(1.5) t ← 1 is enabled；
(1.6) if t >=Iteration_times, step (1.9) is jumped to, otherwise updates i-th according to formula (1) The current velocity vector v of soniWith position vector xi；
Wherein, Iteration_times is iterations, its value depends on the acceptable operation duration of institute, takes The bigger value cycle-index of value is more but can find better position vector, rpAnd rgIt is the random number between two (0,1), w, WithIt is constant value, for controlling velocity vector viMore New steps, the value in value mode and conventional particle group's algorithm Mode is the same；
(1.7) for i=1,2 ..., M, if position vector xiK corresponding energy source transmission power summation f (xi) Less than position vector piK corresponding energy source transmission power summation f (pi), then enable pi←xi；If position vector xiInstitute is right The K energy source transmission power summation f (x answeredi) less than position vector pgK corresponding energy source transmission power summation f (pg), then enable pg←xi；
(1.8) t ← t+1, return to step (1.6) are enabled；
(1.9) end operation, with position vectorInstitute is right The energy source deployment answered and transmission power are configured to final scheme, i.e., the deployment coordinate position of j-th energy source is determined asIts transmission power is determined as
Further, it is position vector in the step (1.4) and step (1.7) Calculate each energy source transmission power summation f (p corresponding to iti), include the following steps：
Step1 for j=1,2 ..., K, the abscissa setting of j-th of energy sourceOrdinate is set asSend work( Rate is set as
Step2 is each sensor node nu, u=1,2 ..., N, according to formula (2) calculate node nuFrom K radio frequency energy Measure total power of transmission source capture
Wherein η is rectification efficiency, GsIt is source antenna gain, GrIt is receiving antenna gain, LpIt is polarization loss, λ is wavelength, du,jIt is node nuThe distance between j-th RF energy transmission source；
If the energy capture power of each nodes of Step3 is all higher than being equal to its energy requirement, i.e.,U=1, 2 ..., N then calculate each energy source transmission power summation f (p according to formula (3)i) be
Otherwise f (p are enabledi) it is Kpmax, wherein pmaxThe maximum transmission power supported by energy source transmission circuit.
Beneficial effects of the present invention are：The present invention is to solve source of radio frequency energy deployment and hair using particle swarm optimization algorithm Power configuration problem is sent, by the position and the transmission power that are continuously updated energy source so that in the energy for meeting each node It captures on Demand Base, minimizes energy source transmission power summation, reach energy-efficient purpose.
Specific embodiment
The present invention will be further described below.
It is a kind of based on particle group optimizing RF energy capture the minimized method for arranging in wireless sense network energy source, including with Lower step：
(1.1) according to the sensor node coordinate that can capture RF energy of given position N number of in wireless sense network, really The fixed unique minimum circle-cover in the region；Wherein, N is sensor node total number, and the minimum circle-cover of N number of node refers to cover All N number of nodes and the circle with least radius；
(1.2) a specific energy source is represented with the position vector of a particle in particle cluster algorithm to dispose and send Power configuration scheme initializes the initial position vector of M particle：For i=1,2 ..., M, the position vector of i-th of particle ForNumbers of the wherein K for energy source, the horizontal seat of j-th of energy source Mark and ordinateWithFor the abscissa and ordinate of a point chosen at random in minimum circle-cover, j-th energy source Transmission powerBy the transmission power randomly selected in the range of transmission power that transmission circuit is supported；The value mode of M As particle number value mode in conventional particle group's algorithm；
(1.3) the initial velocity vector v of i-th of particle is initializedi=0 and initialize i-th of particle optimal location Vectorial piFor its initial position vector, i.e. pi←xi；
(1.4) for i=1,2 ..., M, position vector p is calculatediK corresponding energy source transmission power summation f (pi), then find out the p of energy source transmission power summation minimumiAnd by global optimum position pgIt is set as pi, i.e. pg←pi；
(1.5) t ← 1 is enabled；
(1.6) if t >=Iteration_times, step (1.9) is jumped to, otherwise updates i-th according to formula (1) The current velocity vector v of soniWith position vector xi；
Wherein, Iteration_times is iterations, its value depends on the acceptable operation duration of institute, takes The bigger value cycle-index of value is more but can find better position vector, rpAnd rgIt is the random number between two (0,1), w, WithIt is constant value, for controlling velocity vector viMore New steps, the value in value mode and conventional particle group's algorithm Mode is the same；
(1.7) for i=1,2 ..., M, if position vector xiK corresponding energy source transmission power summation f (xi) Less than position vector piK corresponding energy source transmission power summation f (pi), then enable pi←xi；If position vector xiInstitute is right The K energy source transmission power summation f (x answeredi) less than position vector pgK corresponding energy source transmission power summation f (pg), then enable pg←xi；
(1.8) t ← t+1, return to step (1.6) are enabled；
(1.9) end operation, with position vectorInstitute is right The energy source deployment answered and transmission power are configured to final scheme, i.e., the deployment coordinate position of j-th energy source is determined asIts transmission power is determined as
Further, it is position vector in the step (1.4) and step (1.7) Calculate each energy source transmission power summation f (p corresponding to iti), include the following steps：
Step1 for j=1,2 ..., K, the abscissa setting of j-th of energy sourceOrdinate is set asSend work( Rate is set as
Step2 is each sensor node nu, u=1,2 ..., N, according to formula (2) calculate node nuFrom K radio frequency energy Measure total power of transmission source capture
Wherein η is rectification efficiency, GsIt is source antenna gain, GrIt is receiving antenna gain, LpIt is polarization loss, λ is wavelength, du,jIt is node nuThe distance between j-th RF energy transmission source；
If the energy capture power of each nodes of Step3 is all higher than being equal to its energy requirement, i.e.,U=1, 2 ..., N then calculate each energy source transmission power summation f (p according to formula (3)i) be
Otherwise f (p are enabledi) it is Kpmax, wherein pmaxThe maximum transmission power supported by energy source transmission circuit.
Illustrate this hair for the radio frequency energy capture sensor network for giving each sensor node physical location Bright specific embodiment.
The minimum circle-cover center of circle of the sensor node of N number of given position is calculated first.
Each energy source it needs to be determined that 3 parameters, be respectively the abscissa of its deployed position, ordinate and its send work( Rate size.K source of radio frequency energy forms a particle, therefore each corresponding position vector of particle is 3K dimensional vectors, then i-th The initial position vector of particle can be set asInitializationWithFor most Random coordinate points, initialization in small covering circleFor a random performance number in the range of the adjustable transmission power of energy source, and And the initial velocity vector of i-th of particle of initialization is 0 and i-th of particle optimal location of initialization is its initial position.
Then the total of energy that each node captured from each energy source is calculated using Friis free space propagation models With if the energy that node captures meets its own required energy, calculate each energy source corresponding to each particle and send Power summation, if not satisfied, each energy source transmission power summation then is set as the sum of each energy source maximum transmission power. Single particle and global optimal vector are updated, the optimal vector of each particle is set as the sum of power that the particle search arrives Global optimum's vector is set as vector during the sum of power minimum in all particles by vector when minimum.
Or else break and perform particle optimization operation, the operation is by controlling the vector parameter and velocity vector of each particle, no It is disconnected that update is iterated to the deployed position and transmission power of energy source, until reaching fixed iterations and terminating.
Final available optimal vectorFor j=1, The deployment coordinate position of 2 ..., K, j-th energy source is determined asIts transmission power is determined as

Claims (2)

1. combined optimization method is configured in energy source locations deployment and transmission power in a kind of RF energy capture wireless sense network, It is characterized in that：It the described method comprises the following steps：
(1.1) according to the sensor node coordinate that can capture RF energy of given position N number of in wireless sense network, determining should The unique minimum circle-cover in region；Wherein, N is sensor node total number, and the minimum circle-cover of N number of node refers to cover institute There are N number of node and the circle with least radius；
(1.2) a specific energy source deployment and transmission power are represented with the position vector of a particle in particle cluster algorithm Allocation plan initializes the initial position vector of M particle：For i=1,2 ..., M, the position vector of i-th of particle isNumbers of the wherein K for energy source, the abscissa of j-th of energy source And ordinateWithFor the abscissa and ordinate of a point chosen at random in minimum circle-cover, j-th energy source Transmission powerBy the transmission power randomly selected in the range of transmission power that transmission circuit is supported；The value mode of M As particle number value mode in conventional particle group's algorithm；
(1.3) the initial velocity vector v of i-th of particle is initializedi=0 and the optimal location vector of i-th particle of initialization piFor its initial position vector, i.e. pi←xi；
(1.4) for i=1,2 ..., M, position vector p is calculatediK corresponding energy source transmission power summation f (pi), so The p of energy source transmission power summation minimum is found out afterwardsiAnd by global optimum position pgIt is set as pi, i.e. pg←pi；
(1.5) t ← 1 is enabled；
(1.6) if t >=Iteration_times, step (1.9) is jumped to, otherwise according to formula (1) i-th of particle of update Current velocity vector viWith position vector xi；
Wherein, Iteration_times is iterations, its value depends on the acceptable operation duration of institute, and value is got over Big value cycle-index is more but can find better position vector, rpAnd rgIt is the random number between two (0,1), w,With It is constant value, for controlling velocity vector viMore New steps, the value mode in value mode and conventional particle group's algorithm Equally；
(1.7) for i=1,2 ..., M, if position vector xiK corresponding energy source transmission power summation f (xi) be less than Position vector piK corresponding energy source transmission power summation f (pi), then enable pi←xi；If position vector xiCorresponding K A energy source transmission power summation f (xi) less than position vector pgK corresponding energy source transmission power summation f (pg), then it enables pg←xi；
(1.8) t ← t+1, return to step (1.6) are enabled；
(1.9) end operation, with position vectorCorresponding Energy source is disposed and transmission power is configured to final scheme, i.e., the deployment coordinate position of j-th energy source is determined asIts transmission power is determined as
2. energy source locations deployment and transmission in a kind of RF energy capture wireless sense network as described in claim 1 Power configuration combined optimization method, it is characterised in that：It is position vector in the step (1.4) and step (1.7)Calculate each energy source transmission power summation f corresponding to it (pi), include the following steps：
Step1 for j=1,2 ..., K, the abscissa setting of j-th of energy sourceOrdinate is set asTransmission power is set It is set to
Step2 is each sensor node nu, u=1,2 ..., N, according to formula (2) calculate node nuIt is sent from K RF energy Total power of source capture
Wherein η is rectification efficiency, GsIt is source antenna gain, GrIt is receiving antenna gain, LpIt is polarization loss, λ is wavelength, du,jIt is Node nuThe distance between j-th RF energy transmission source；
If the energy capture power of each nodes of Step3 is all higher than being equal to its energy requirement, i.e., Each energy source transmission power summation f (p are then calculated according to formula (3)i) be
Otherwise f (p are enabledi) it is Kpmax, wherein pmaxThe maximum transmission power supported by energy source transmission circuit.
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