CN108260074B - Energy source position and transmission power optimization method for wireless energy supply sensor network - Google Patents

Energy source position and transmission power optimization method for wireless energy supply sensor network Download PDF

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CN108260074B
CN108260074B CN201710593931.0A CN201710593931A CN108260074B CN 108260074 B CN108260074 B CN 108260074B CN 201710593931 A CN201710593931 A CN 201710593931A CN 108260074 B CN108260074 B CN 108260074B
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energy source
energy
transmission power
position vector
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CN108260074A (en
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池凯凯
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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  • Mobile Radio Communication Systems (AREA)
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Abstract

A joint optimization method for energy source position deployment and transmission power configuration in a radio frequency energy capture wireless sensor network is characterized in that for K energy sources, the deployment position (x, y) and the transmission power p of each energy source are determined, and the total transmission power of the lower energy sources is achieved while the energy capture requirement of each deployed sensing node is met; based on a genetic algorithm, firstly, corresponding K energy source positions and transmission powers to a 3K-dimensional position vector of each particle, and then iteratively updating the position vectors and the velocity vectors of the particles, wherein when a scheme corresponding to one particle meets the energy capture requirements of all nodes, the fitness value of the particle is defined as the total transmission power of the energy source, otherwise, the fitness value is defined as the maximum transmission power which is K times; when the specified iteration number is reached, finding out the optimal energy source position deployment and sending power configuration. The method can find out better energy source deployment and transmitting power configuration, achieves lower total transmitting power of the energy source, and has better energy-saving property.

Description

Energy source position and transmission power optimization method for wireless energy supply sensor network
Technical Field
The invention relates to a method for optimizing the energy source position and the transmitting power of a wireless energy supply sensor network, which is suitable for a wireless sensor network with sensor nodes capable of capturing radio frequency energy.
Background
Electromagnetic waves are increasingly receiving attention from both academic and industrial circles as a ubiquitous, environmentally friendly and sustainable energy source. The radio frequency energy capturing wireless sensor network is a novel network for capturing radio frequency energy in an environment and converting the radio frequency energy into electric energy so as to support continuous work of nodes.
However, at present, the rate of capturing the radio frequency energy in the environment by the radio frequency energy capturing sensor node is still very low, which is one of the bottlenecks in the wide application of this kind of new networks. To overcome this weakness, it is a viable and efficient way to deploy a dedicated energy source to power the nodes. Because the radio frequency energy can lose certain energy in the transmission process, namely the farther the energy source is away from the node, the less the radio frequency energy captured by the node, each energy source is reasonably arranged, so that the network can utilize the radio frequency energy to the maximum extent, and the problem of important research is solved.
Meanwhile, from the perspective of energy conservation and environmental protection, radio frequency energy exceeding the energy requirement of the node will be wasted uselessly, and the energy source will consume a large amount of energy, so that it is a significant problem to configure the transmission power of each energy source reasonably.
Disclosure of Invention
Aiming at the situations that the radio frequency energy capturing sensor nodes in the network are already deployed and the coordinates are known, the invention provides a method for jointly optimizing the energy source position deployment and the transmission power configuration in the radio frequency energy capturing wireless sensor network with better energy saving performance,
in order to solve the technical problems, the invention provides the following technical scheme:
a method for optimizing the energy source position and the transmission power of a wireless energy supply sensing network comprises the following steps:
(1.1) determining a unique minimum coverage circle of the area according to the coordinates of sensor nodes which can capture radio frequency energy at N given positions in the wireless sensor network; the minimum coverage circle of the N nodes is a circle which covers all the N nodes and has the minimum radius;
(1.2) representing a specific energy source deployment and transmission power configuration scheme by using a position vector of one particle in a particle swarm optimization, initializing initial position vectors of M particles: for i-1, 2, …, M, the position vector of the ith particle is
Figure GDA0002421215880000021
Where K is the number of energy sources, the transverse axis of the jth energy sourceCoordinates and ordinate
Figure GDA0002421215880000022
And
Figure GDA0002421215880000023
the abscissa and ordinate of a randomly selected point in the smallest coverage circle, the transmission power of the jth energy source
Figure GDA0002421215880000024
A transmit power randomly selected within a transmit power range supported by a transmit circuit; the value mode of M is the same as the value mode of the number of particles in the traditional particle swarm algorithm;
(1.3) initializing the initial velocity vector v of the ith particlei0, and initializing the optimal position vector p of the ith particleiIs its initial position vector, i.e. pi←xi；
(1.4) for i 1,2, …, M, a position vector p is calculatediThe sum of the corresponding K energy source transmitting powers f (p)i) Then finding out p with minimum sum of energy source transmitting poweriAnd will global optimum position pgIs set as piI.e. pg←pi；
(1.5) making t ← 1;
(1.6) if t is more than or equal to the Iteration _ times, jumping to the step (1.9), otherwise, updating the current velocity vector v of the ith particle according to the formula (1)iAnd a position vector xi；
Figure GDA0002421215880000025
Wherein, Iteration _ times is Iteration times, the value of the Iteration times depends on the acceptable running time, the larger the value is, the more the cycle times are, the better position vector can be found, and r ispAnd rgIs a random number between two (0,1), w,
Figure GDA0002421215880000031
And
Figure GDA0002421215880000032
is a constant value and is used to control the velocity vector viThe updating step of (2) has a value-taking mode same as that of the traditional particle swarm algorithm;
(1.7) for i ═ 1,2, …, M, if position vector xiThe sum of the transmission power f (x) of the corresponding K energy sourcesi) Smaller than the position vector piThe sum of the corresponding K energy source transmitting powers f (p)i) Then let pi←xi(ii) a If the position vector xiThe sum of the transmission power f (x) of the corresponding K energy sourcesi) Smaller than the position vector pgThe sum of the corresponding K energy source transmitting powers f (p)g) Then let pg←xi；
(1.8) returning to step (1.6) by making t ← t + 1;
(1.9) ending the operation with the position vector
Figure GDA0002421215880000033
The corresponding energy source deployment and transmission power configuration is the final scheme, namely the deployment coordinate position of the jth energy source is determined as
Figure GDA0002421215880000034
Its transmission power is determined as
Figure GDA0002421215880000035
Further, in the step (1.4) and the step (1.7), the position vector is obtained
Figure GDA0002421215880000036
Calculating the total power f (p) of the energy sourcesi) The method comprises the following steps:
step1 is set for the abscissa of the jth energy source with j equal to 1,2, …, K
Figure GDA0002421215880000037
The ordinate is set as
Figure GDA0002421215880000038
Transmission power setting
Figure GDA0002421215880000039
Step2 for each sensor node nuN, NuTotal power captured from K radio frequency energy transmitting sources
Figure GDA00024212158800000310
Figure GDA00024212158800000311
Wherein η is the rectification efficiency, GsIs the source antenna gain, GrIs the receive antenna gain, LpIs the polarization loss, λ is the wavelength, du,jIs node nuDistance from the jth rf energy source;
step3 if the energy capture power of each node is larger than or equal to the energy demand, that is to say
Figure GDA0002421215880000041
The sum f (p) of the transmission powers of the energy sources is calculated according to the formula (3)i) Is composed of
Figure GDA0002421215880000042
Otherwise let f (p)i) Is KpmaxWherein p ismaxThe maximum transmit power supported by the energy source transmit circuitry.
The invention has the beneficial effects that: the invention solves the problems of deployment and transmission power configuration of the radio frequency energy source by utilizing a particle swarm optimization algorithm, and minimizes the total transmission power of the energy source on the basis of meeting the energy capture requirement of each node by continuously updating the position and the transmission power of the energy source, thereby achieving the purpose of energy conservation.
Detailed Description
The present invention is further explained below.
A method for optimizing the energy source position and the transmission power of a wireless energy supply sensing network comprises the following steps:
(1.1) determining a unique minimum coverage circle of the area according to the coordinates of sensor nodes which can capture radio frequency energy at N given positions in the wireless sensor network; the minimum coverage circle of the N nodes is a circle which covers all the N nodes and has the minimum radius;
(1.2) representing a specific energy source deployment and transmission power configuration scheme by using a position vector of one particle in a particle swarm optimization, initializing initial position vectors of M particles: for i-1, 2, …, M, the position vector of the ith particle is
Figure GDA0002421215880000043
Where K is the number of energy sources, the abscissa and ordinate of the jth energy source
Figure GDA0002421215880000051
And
Figure GDA0002421215880000052
the abscissa and ordinate of a randomly selected point in the smallest coverage circle, the transmission power of the jth energy source
Figure GDA0002421215880000053
A transmit power randomly selected within a transmit power range supported by a transmit circuit; the value mode of M is the same as the value mode of the number of particles in the traditional particle swarm algorithm;
(1.3) initializing the initial velocity vector v of the ith particlei0, and initializing the optimal position vector p of the ith particleiIs its initial position vector, i.e. pi←xi；
(1.4) for i 1,2, …, M, a position vector p is calculatediThe sum of the corresponding K energy source transmitting powers f (p)i) Then finding out the minimum sum of the transmitting power of the energy sourcesP of (a)iAnd will global optimum position pgIs set as piI.e. pg←pi；
(1.5) making t ← 1;
(1.6) if t is more than or equal to the Iteration _ times, jumping to the step (1.9), otherwise, updating the current velocity vector v of the ith particle according to the formula (1)iAnd a position vector xi；
Figure GDA0002421215880000054
Wherein, Iteration _ times is Iteration times, the value of the Iteration times depends on the acceptable running time, the larger the value is, the more the cycle times are, the better position vector can be found, and r ispAnd rgIs a random number between two (0,1), w,
Figure GDA0002421215880000055
And
Figure GDA0002421215880000056
is a constant value and is used to control the velocity vector viThe updating step of (2) has a value-taking mode same as that of the traditional particle swarm algorithm;
(1.7) for i ═ 1,2, …, M, if position vector xiThe sum of the transmission power f (x) of the corresponding K energy sourcesi) Smaller than the position vector piThe sum of the corresponding K energy source transmitting powers f (p)i) Then let pi←xi(ii) a If the position vector xiThe sum of the transmission power f (x) of the corresponding K energy sourcesi) Smaller than the position vector pgThe sum of the corresponding K energy source transmitting powers f (p)g) Then let pg←xi；
(1.8) returning to step (1.6) by making t ← t + 1;
(1.9) ending the operation with the position vector
Figure GDA0002421215880000061
The corresponding energy source deployment and transmit power configuration is the final scenario, i.e. secondThe deployment coordinate positions of the j energy sources are determined as
Figure GDA0002421215880000062
Its transmission power is determined as
Figure GDA0002421215880000063
Further, in the step (1.4) and the step (1.7), the position vector is obtained
Figure GDA0002421215880000064
Calculating the total power f (p) of the energy sourcesi) The method comprises the following steps:
step1 is set for the abscissa of the jth energy source with j equal to 1,2, …, K
Figure GDA0002421215880000065
The ordinate is set as
Figure GDA0002421215880000066
Transmission power setting
Figure GDA0002421215880000067
Step2 for each sensor node nuN, NuTotal power captured from K radio frequency energy transmitting sources
Figure GDA0002421215880000068
Figure GDA0002421215880000069
Wherein η is the rectification efficiency, GsIs the source antenna gain, GrIs the receive antenna gain, LpIs the polarization loss, λ is the wavelength, du,jIs node nuDistance from the jth rf energy source;
step3 if the energy capture power of each node is larger than or equal to the energy demand, that is to say
Figure GDA00024212158800000610
The sum f (p) of the transmission powers of the energy sources is calculated according to the formula (3)i) Is composed of
Figure GDA00024212158800000611
Otherwise let f (p)i) Is KpmaxWherein p ismaxThe maximum transmit power supported by the energy source transmit circuitry.
Particular embodiments of the present invention are described with respect to a wireless radio frequency energy capture sensor network given the physical location of each sensor node.
The center of a minimum coverage circle of the sensor nodes at N given positions is calculated firstly.
Each energy source needs to determine 3 parameters, respectively the abscissa and ordinate of its deployment position and its transmit power magnitude. K radio frequency energy sources form one particle, so that the position vector corresponding to each particle is a 3K-dimensional vector, and the initial position vector of the ith particle can be set as
Figure GDA0002421215880000071
Initialization
Figure GDA0002421215880000072
And
Figure GDA0002421215880000073
for random coordinate points within the smallest coverage circle, initializing
Figure GDA0002421215880000074
A random power value within the transmission power range is adjusted for the energy source and the initial velocity vector of the ith particle is initialized to 0 and the optimal position of the ith particle is initialized to its initial position.
And then, calculating the sum of the energy captured by each node from each energy source by using a Friis free space propagation model, if the energy captured by the node meets the energy required by the node, calculating the sum of the transmitting power of each energy source corresponding to each particle, and if the energy captured by the node does not meet the energy required by the node, setting the sum of the transmitting power of each energy source as the sum of the maximum transmitting power of each energy source. Updating the optimal vectors of the single particle and the global, setting the optimal vector of each particle as the vector when the sum of the searched powers of the particle is minimum, and setting the global optimal vector as the vector when the sum of the searched powers of all the particles is minimum.
And continuously executing particle optimization operation, wherein the operation continuously carries out iterative updating on the deployment position and the transmission power of the energy source by controlling the vector parameter and the velocity vector of each particle until a fixed iteration number is reached and the operation is finished.
The final obtainable optimal vector
Figure GDA0002421215880000075
For j ═ 1,2, …, K, the deployment coordinate location of the jth energy source is determined as
Figure GDA0002421215880000076
Its transmission power is determined as
Figure GDA0002421215880000077

Claims (1)

1. A method for optimizing the energy source position and the transmission power of a wireless energy supply sensor network is characterized by comprising the following steps: the method comprises the following steps:
(1.1) determining a unique minimum coverage circle of an area according to the coordinates of sensor nodes which can capture radio frequency energy at N given positions in a wireless sensor network; the minimum coverage circle of the N nodes is a circle which covers all the N nodes and has the minimum radius;
(1.2) representing a specific energy source deployment and transmission power configuration scheme by using a position vector of one particle in a particle swarm optimization, initializing initial position vectors of M particles: for i-1, 2, …, M, the position vector of the ith particle is
Figure FDA0002391168460000011
Where K is the number of energy sources, the abscissa and ordinate of the jth energy source
Figure FDA0002391168460000012
And
Figure FDA0002391168460000013
the abscissa and ordinate of a randomly selected point in the smallest coverage circle, the transmission power of the jth energy source
Figure FDA0002391168460000014
A transmit power randomly selected within a transmit power range supported by a transmit circuit; the value mode of M is the same as the value mode of the number of particles in the traditional particle swarm algorithm;
(1.3) initializing the initial velocity vector v of the ith particlei0, and initializing the optimal position vector p of the ith particleiIs its initial position vector, i.e. pi←xi；
(1.4) for i 1,2, …, M, a position vector p is calculatediThe sum of the corresponding K energy source transmitting powers f (p)i) Then finding out p with minimum sum of energy source transmitting poweriAnd will global optimum position pgIs set as piI.e. pg←pi；
(1.5) making t ← 1;
(1.6) if t is more than or equal to the Iteration _ times, jumping to the step (1.9), otherwise, updating the current velocity vector v of the ith particle according to the formula (1)iAnd a position vector xi；
Figure FDA0002391168460000015
Wherein, Iteration _ times is Iteration times, the value of the Iteration times depends on the acceptable running time, the larger the value is, the more the cycle times are, the better position vector can be found, and r ispAnd rgIs two of0,1) random number, w,
Figure FDA0002391168460000016
And
Figure FDA0002391168460000017
is a constant value and is used to control the velocity vector viThe updating step of (2) has a value-taking mode same as that of the traditional particle swarm algorithm;
(1.7) for i ═ 1,2, …, M, if position vector xiThe sum of the transmission power f (x) of the corresponding K energy sourcesi) Smaller than the position vector piThe sum of the corresponding K energy source transmitting powers f (p)i) Then let pi←xi(ii) a If the position vector xiThe sum of the transmission power f (x) of the corresponding K energy sourcesi) Smaller than the position vector pgThe sum of the corresponding K energy source transmitting powers f (p)g) Then let pg←xi；
(1.8) returning to step (1.6) by making t ← t + 1;
(1.9) ending the operation with the position vector
Figure FDA0002391168460000021
The corresponding energy source deployment and transmission power configuration is the final scheme, namely the deployment coordinate position of the jth energy source is determined as
Figure FDA0002391168460000022
Its transmission power is determined as
Figure FDA0002391168460000023
In the step (1.4) and the step (1.7), the position vector is
Figure FDA0002391168460000024
Calculating the total power f (p) of the energy sourcesi) The method comprises the following steps:
step1 for j equal to 1,2…, K, the abscissa setting of the jth energy source
Figure FDA0002391168460000025
The ordinate is set as
Figure FDA0002391168460000026
Transmission power setting
Figure FDA0002391168460000027
Step2 for each sensor node nuN, NuTotal power captured from K radio frequency energy transmitting sources
Figure FDA0002391168460000028
Figure FDA0002391168460000029
Wherein η is the rectification efficiency, GsIs the source antenna gain, GrIs the receive antenna gain, LpIs the polarization loss, λ is the wavelength, du,jIs node nuDistance from the jth rf energy source;
step3 if the energy capture power of each node is larger than or equal to the energy demand, that is to say
Figure FDA00023911684600000210
If u is 1,2, …, N, the sum of the transmission powers f (p) of the energy sources is calculated according to the formula (3)i) Is composed of
Figure FDA00023911684600000211
Otherwise let f (p)i) Is KpmaxWherein p ismaxThe maximum transmit power supported by the energy source transmit circuitry.
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