CN106254008B - A kind of frequency spectrum sensing method of energy acquisition green cognitive radio - Google Patents
A kind of frequency spectrum sensing method of energy acquisition green cognitive radio Download PDFInfo
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Abstract
The present invention is to provide a kind of frequency spectrum sensing methods of energy acquisition green cognitive radio.One, establish the frequency spectrum perception system model of energy acquisition green cognitive radio；Two, initialization population；Three, the fitness of all quantum individual in all populations is evaluated；Four, mixing quantum differential evolution is carried out to the quantum individual inside each population respectively；Five, extinction processing is carried out to the individual in population if globally optimal solution is all the same in the number of iterations globally optimal solution between lower more each population that meets some requirements；Six, it is not terminated if evolved, otherwise return step four executes step 7；Seven, iteration is terminated, the quantum state of global optimum's quantum individual of any population is exported, feasible solution is mapped as according to mapping ruler.The present invention is directed to combine to obtain optimal the energy acquisition factor and channel-aware number, under the conditions of known to the handling capacity needed for secondary user, seeks the least energy acquisition rate of system, realize the theory of green communications.
Description
Technical field
The present invention relates to a kind of methods of the frequency spectrum perception of cognitive radio.
Background technique
With the rapid development of telecommunications, the problem of frequency spectrum resource shortage becomes increasingly severe.Simultaneously with communication
Terminal diversification, intelligent and widescreen development, the power consumption of mobile device also become increasingly to can not be ignored.How to mention
It is current urgent problem, the concept of " green communications " that the availability of frequency spectrum of high communication system, which reduces energy consumption simultaneously,
It comes into being.
Compared to common communication system, cognitive radio system needs to perceive wireless electromagnetic environment, passes through perception
Function finds available channel, and adaptive adjustment system parameter, optimal under the precondition for not interfering authorized user
Maximum data transmission throughput is obtained using frequency spectrum cavity-pocket, realizes that cognitive user and authorized user share same frequency range, with
This utilization rate to improve radio resource.
Nearly 2 years, energy acquisition technology was increasingly taken seriously, because energy acquisition technology can not only greatly mitigate energy
Source is insufficient, and is a kind of low-carbon environment-friendly technology.Wireless signal also carries energy while carrying information, in such environment
Various interference signals will be turned waste into wealth by energy acquisition technology.Therefore, the frequency spectrum perception of energy acquisition cognitive radio
Technology has obtained extensive concern." the cognition based on improvement shuffled frog leaping algorithm that Zheng Shilian etc. is delivered on " Acta Physica Sinica "
Radio collaboration frequency spectrum perception " proposes the spectrum sensing scheme of improved shuffled frog leaping algorithm, does not utilize energy acquisition skill
Art only studies detection probability.Yin Sixing etc. is in IEEE International Conference on
" the Optimal Saving-Sensing-Transmitting Structurein delivered in Communications meeting
Self-Powered Cognitive Radio Systems with Wireless Energy Harvesting " adopts energy
Secondary user throughput problem in the cognitive radio frequency spectrum cognition technology of collection is discussed, but cannot acquire time user institute
The least energy acquisition rate needed has room for improvement.
Summary of the invention
It is minimum that the purpose of the present invention is to provide a kind of energy requirements, the energy acquisition low to the hardware requirement of energy acquisition
The frequency spectrum sensing method of green cognitive radio.
The object of the present invention is achieved like this:
Step 1 establishes the frequency spectrum perception system model of energy acquisition green cognitive radio；
Step 2, initialization population；
Step 3 evaluates the fitness of all quantum individual in all populations；
Step 4 carries out mixing quantum differential evolution to the quantum individual of its inside respectively for each population；
Step 5, the globally optimal solution between more each population, if globally optimal solution is all the same, in population
Body carries out extinction processing；
Step 6 does not terminate if evolved, otherwise return step four executes step 7；
Step 7 terminates iteration, exports the quantum state of global optimum's quantum individual of any population, will according to mapping ruler
It is mapped as feasible solution, the scheme as cognitive radio frequency spectrum perception.
The present invention may also include:
1, step 1 specifically includes: transmitting i.e. SST (saving-sensing- using energy acquisition-frequency spectrum perception-data
One time slot is divided into three time slo segments, is respectively used to energy by structure of time slot transmitting), the structure of time slot
Acquisition, frequency spectrum perception and data are transmitted, and the total time of each time slot is T, and the energy acquisition factor is ρ, for energy acquisition when
Between fragment length be ρ T, if channel perception number be q, perceive a channel time cost be Ts, for frequency spectrum perception when
Between length be qTs, remaining time slo segments are for data transmission；
After structure of time slot based on SST is introduced energy acquisition technology, if each time slot time user needs the system obtained
Handling capacity is R, energy acquisition rate X (ρ, q) are as follows:
Wherein EsFor the energy that one channel of detection is spent, M is number of available channels；
Channel status meet parameter be p Bernoulli be distributed, p be channel idle probability, thus M be parameter be (q,
P) bi-distribution stochastic variable, desired value are as follows:
E [M]=qp
Energy acquisition rate minimum value optimization problem equation is as follows:
Constraint condition are as follows: ρ-qEs/ TX (ρ, q) >=0,1- ρ-qTs/ T >=0,0≤ρ≤1
Wherein q ∈ { 0,1,2 ..., N }, N indicate institute energy channel perception maximum number, ρ-qEs/ TX (ρ, q) >=0 and 1-
ρ-qTs/ T >=0 is constraint condition, and will not run out of all energy ensuring frequency spectrum perception process both will not run out of institute
Some remaining times；
It is defined as follows penalty:
WhereinWithIt is penalty factor, and [x]+=max { x, 0 }.
2, step 2 specifically includes: having I population, H quantum individual in each population, t in Symbiotic evolution on multiple populations
H-th of quantum individual is expressed as in i-th of population of generationWhereinIndicate i-th kind of t generation
The quantum state of h-th of quantum individual ρ of group,Indicate the quantum state of t generation i-th of population, h-th of quantum individual q,
WhereinIt is to each population first
Inside is evolved, by h-th of quantum individual in i-th of population'sComponent is mapped as integer solution, andComponent remains unchanged, and enables Mapping ruler is as follows: enablingWherein, l is the lower bound of channel perception number, and u is the upper bound of channel perception number, is reflected
Penetrating rule is Expression pairDownward bracket function,Mapping
Result afterwards is
3, the fitness of all quantum individual in all populations is carried out in evaluation procedure, h-th of quantum in population i
IndividualFitness is calculated by following formula:
Energy acquisition rate required for the smaller representative of fitness value is lower, and fitness is better, selects in each population i and adapts to
Spend global optimum's quantum individual that best quantum individual is the population
4, step 4 specifically includes: the evolutionary process of population i is as follows:
(1) mutation process: to h-th of quantum individual in i-th of populationCarry out mutation operation, quantum rotation
The renewal equation of angle and quantum bit is as follows:
Wherein, ξ1、ξ2、ξ3WithIt is the uniform random number between [0,1], sign () indicates sign function,It is mean value is the Gauss number that 0 variance is 1, a ∈ { 1,2 ..., H } is a random integers, and expression is chosen at random
Quantum individual label,It is the global optimum quantum individual of population k (k ≠ i), n=1,
2；
(2) crossover process: renewal equation is as follows:
Wherein ξ4It is the uniform random number between one [0,1], CR=0.01+ (0.4t)/K, K are maximum number of iterations；
(3) selection course: by quantum position'sComponent is mapped as integer solution, andComponent is protected
It holds constant, forms new mapping solutionIt calculatesWithFitness, later to each population inside
Quantum individual and global optimum's quantum individual are updated, ifThanFitness it is good,OtherwiseIt enablesB is that wherein fitness is most
Good quantum individual label, ifFitness be better than Otherwise gt+1(i)=gt
(i)。
5, carrying out the specific method of extinction processing to the individual in population is every KaAfter secondary iteration, more each population it
Between globally optimal solution, if globally optimal solution is all the same, choose a random integers w (w ∈ { 1,2 ..., I }), population w
Interior half quantum individual re-starts initialization and generates.
The invention proposes a kind of frequency spectrum sensing method of energy acquisition green cognitive radio, the handling capacity needed for system
Under the conditions of known, seek the least energy acquisition rate of system, cognitive radio system is realized by wireless energy transfer and acquisition
The self energizing of system, without additional energy supply device.
The thoughts such as energy acquisition and " green communications " are applied to cognitive radio frequency spectrum perception problems by the present invention, to solve
The smallest energy acquisition rate, the present invention devises quantum mixing difference Symbiotic evolution evolving mechanism on multiple populations, compared to existing
Frequency spectrum sensing method, the invention has the following advantages that
(1) known to the handling capacity needed for secondary family of the invention under the conditions of, devise quantum on multiple populations mix difference symbiosis into
Change evolving mechanism as the method for solving least energy collecting efficiency, designed method performance is stablized, can be in a short time
Find out optimal spectrum sensing scheme.
(2) present invention response theories such as " green communications " and " low-carbon communication " can find out the optimal energy acquisition factor and sense
Know channel number, obtain least energy acquisition rate, energy requirement minimum may be implemented, avoid energy redundancy and energy dissipation,
The hardware requirement of energy acquisition can achieve it is minimum, save hardware resource, avoid the wasting of resources.
(3) quantum, the mixing thoughts such as difference algorithm and Symbiotic evolution on multiple populations are combined by the present invention, devise solution
The quantum on multiple populations of MIXED INTEGER and Continuous Variable Problems mixes difference Symbiotic evolution method, can be to solve the problems, such as Other Engineering
Provide new thinking.
Detailed description of the invention
The frequency spectrum sensing method schematic diagram of Fig. 1 energy acquisition green cognitive radio.
Fig. 2 is averaged the relationship between least energy acquisition rate and handling capacity.
Fig. 3 optimum capacity acquires the relationship between the factor and handling capacity.
Fig. 4 optimum channel perceives the relationship between number and handling capacity.
Specific embodiment
It illustrates below and the present invention is described in more detail.
In conjunction with Fig. 1, the frequency spectrum sensing method of energy acquisition green cognitive radio of the invention mainly includes the following steps:
Step 1, establishes the frequency spectrum perception system model of energy acquisition green cognitive radio, and the present invention proposes a kind of energy
Measure acquisition-frequency spectrum perception-data transmission (saving-sensing-transmitting, SST) structure of time slot, the time slot knot
One time slot is divided into three time slo segments by structure, is respectively used to energy acquisition, frequency spectrum perception and data and is transmitted.Each time slot
Total time is T, and the energy acquisition factor is ρ (measure energy acquires the percentage that time slo segments account for total time), then adopts for energy
The time slice length integrated is ρ T.The length of frequency spectrum perception time slo segments depends on the channel number of perception, it is assumed that channel perception
Number is q, and the time cost for perceiving a channel is Ts, then it is qT for the time span of frequency spectrum perceptions.Feeler when remaining
Duan Ze is transmitted for data.
After structure of time slot based on SST is introduced energy acquisition technology, if each time slot time user needs the system obtained
Handling capacity is R, energy acquisition rate X (ρ, q) are as follows:
Wherein q is channel perception number, EsFor the energy that one channel of detection is spent, T is the total time of each time slot,
ρ is the energy acquisition factor, TsFor the time cost for perceiving a channel, R is the handling capacity that each time slot time user needs to obtain,
M is number of available channels.
Channel status meets the Bernoulli that parameter is p (probability of channel idle) and is distributed, so that it is (q, p) that M, which is parameter,
Bi-distribution stochastic variable, desired value are as follows:
E [M]=qp
Therefore, energy acquisition rate needed for secondary user is a stochastic variable.Due to secondary it is an object of the present invention to minimize
The long-term mean value E [X (ρ, q)] of energy acquisition rate needed for user, therefore energy acquisition rate minimum value optimization problem side of the invention
Journey is as follows:
Constraint condition are as follows: ρ-qEs/ TX (ρ, q) >=0,1- ρ-qTs/ T >=0,0≤ρ≤1
Wherein q ∈ { 0,1,2 ..., N }, N indicate institute energy channel perception maximum number, ρ-qEs/ TX (ρ, q) >=0 and 1-
ρ-qTs/ T >=0 is constraint condition, and will not run out of all energy ensuring frequency spectrum perception process both will not run out of institute
Some remaining times.
In order to which Constrained Optimization is converted into unconstrained optimization problem, the concept of penalty factor is introduced, is defined as follows
Penalty:
WhereinWithIt is penalty factor, and [x]+=max { x, 0 }.
Step 2, initialization population have I population (for the problem I=2), each population in Symbiotic evolution on multiple populations
Middle H quantum individual, t are expressed as h-th of quantum individual in i-th of populationWhereinIndicate the quantum state of t generation i-th of population, h-th of quantum individual ρ,It indicates i-th h-th of population of t generation
The quantum state of quantum individual q, whereinIt is to inside each population first
It evolves, by h-th of quantum individual in i-th of population'sComponent is mapped as integer solution, andPoint
Amount remains unchanged, and enables Mapping ruler is as follows: enabling first
Wherein, l is the lower bound of channel perception number, and u is the upper bound of channel perception number.Because channel perception number is that an integer is excellent
Real solution is mapped as integer solution by change problem, and mapping ruler is It indicates
It is rightDownward bracket function,Result after mapping is
The fitness of all quantum individual in all populations is evaluated, h-th of quantum individual in population iFitness is calculated by following formula:
Energy acquisition rate required for the smaller representative of fitness value is lower, and fitness is better.It selects in each population i and adapts to
Spend global optimum's quantum individual that best quantum individual is the population
Step 3,
For each population, mixing quantum differential evolution, the evolution of population i are carried out to the quantum individual of its inside respectively
Process is as follows:
1. mutation process: to h-th of quantum individual in i-th of populationCarry out mutation operation, quantum rotation
The renewal equation of angle and quantum bit is as follows:
Wherein, ξ1、ξ2、ξ3WithIt is the uniform random number between [0,1], sign () indicates sign function,It is mean value is the Gauss number that 0 variance is 1, a ∈ { 1,2 ..., H } is a random integers, and expression is chosen at random
Quantum individual label,It is the global optimum quantum individual of population k (k ≠ i), n=1,
2。
2. crossover process: in order to increase population diversity, crossover process is carried out, renewal equation is as follows:
Wherein ξ4It is the uniform random number between one [0,1], CR=0.01+ (0.4t)/K, K are maximum number of iterations.
3. selection course: by quantum position'sComponent is mapped as integer solution, andComponent is kept
It is constant, form new mapping solutionIt calculatesWithFitness.Later to the amount inside each population
Sub- individual and global optimum's quantum individual are updated.IfThanFitness it is good,OtherwiseIt enablesB is that wherein fitness is most
Good quantum individual label, ifFitness be better than Otherwise gt+1(i)=gt
(i)。
Step 4, every KaAfter secondary iteration, globally optimal solution between more each population, if globally optimal solution is homogeneous
Together, certain individuals in certain populations are carried out with extinction processing, specific method be choose a random integers w (w ∈ 1,
2 ..., I }), the half quantum individual in population w re-starts initialization and generates.
Step 5, if evolved without terminating (usually being determined by preset maximum number of iterations K), return step
Three, otherwise, iteration is terminated, the quantum state of global optimum's quantum individual of any population is exported, is mapped according to mapping ruler
For feasible solution, the scheme perceived as cognitive radio frequency spectrum.
In the frequency spectrum perception model for assuming cognitive radio in emulation, N=10, T=1, Ts=0.03, population number I=2,
Each population scale and termination the number of iterations are both configured to identical, population size H=50, Ka=K/5, maximum number of iterations K
=1000, Es=0.6, penalty factorThe secondary desired handling capacity of user changes to 13 from 5.
In the case that Fig. 2 depicts the difference handling capacity needed for secondary user, the green cognitive radio based on energy acquisition
The least energy acquisition rate of spectrum allocation system, it can be seen that be a kind of approximately linear between least energy acquisition rate and handling capacity
Relationship shows that the energy of acquisition is fully utilized by the distribution mechanism proposed.
In the case that Fig. 3 and Fig. 4 is difference handling capacity needed for time user, optimum capacity acquires the factor and optimal spectrum perception
The number of channel, it can be seen that with the increase of throughput demand, frequency spectrum perception system be more likely to the higher energy acquisition factor and
More frequency spectrum perception channel numbers.
The above content is specific embodiment is combined, further detailed description of the invention, and it cannot be said that this hair
Bright specific implementation is only limited to these instructions.For those of ordinary skill in the art to which the present invention belongs, it is not taking off
Under the premise of from present inventive concept, a number of simple deductions or replacements can also be made, all shall be regarded as belonging to protection of the invention
Range.
Claims (5)
1. a kind of frequency spectrum sensing method of energy acquisition green cognitive radio, it is characterized in that:
Step 1 is established the frequency spectrum perception system model of energy acquisition green cognitive radio, is specifically included:
It is the structure of time slot of SST using energy acquisition-frequency spectrum perception-data transmission, the structure of time slot divides a time slot
For three time slo segments, it is respectively used to energy acquisition, frequency spectrum perception and data and transmits, the total time of each time slot is T, and energy is adopted
Integrate the factor as ρ, the time slice length for energy acquisition is that ρ T if channel perception number is q perceives the time of a channel
Cost is Ts, the time span for frequency spectrum perception is qTs, remaining time slo segments are for data transmission；
After structure of time slot based on SST is introduced energy acquisition technology, if each time slot time user needs the system throughput obtained
Amount is R, energy acquisition rate X (ρ, q) are as follows:
Wherein EsFor the energy that one channel of detection is spent, M is number of available channels；
Channel status meets the Bernoulli that parameter is p and is distributed, and p is the probability of channel idle, so that it is (q, p) that M, which is parameter,
Bi-distribution stochastic variable, desired value are as follows:
E [M]=qp
Energy acquisition rate minimum value optimization problem equation is as follows:
Constraint condition are as follows: ρ-qEs/ TX (ρ, q) >=0,1- ρ-qTs/ T >=0,0≤ρ≤1
Wherein q ∈ { 0,1,2 ..., N }, N indicate institute energy channel perception maximum number, ρ-qEs/ TX (ρ, q) >=0 and 1- ρ-qTs/
T >=0 is constraint condition, will not run out of ensuring frequency spectrum perception process both all energy will not run out of it is all surplus
The remaining time；
It is defined as follows penalty:
WhereinWithIt is penalty factor, and [x]+=max { x, 0 }；
Step 2, initialization population；
Step 3 evaluates the fitness of all quantum individual in all populations；
Step 4 carries out mixing quantum differential evolution to the quantum individual of its inside respectively for each population；
Step 5, the globally optimal solution between more each population, if globally optimal solution is all the same, to the individual in population into
Row extinction processing；
Step 6 does not terminate if evolved, otherwise return step four executes step 7；
Step 7 terminates iteration, exports the quantum state of global optimum's quantum individual of any population, reflected according to mapping ruler
It penetrates as feasible solution, the scheme perceived as cognitive radio frequency spectrum.
2. the frequency spectrum sensing method of energy acquisition green cognitive radio according to claim 1, it is characterized in that step 2
It specifically includes: having I population in Symbiotic evolution on multiple populations, H quantum individual in each population, t is for h in i-th of population
A quantum individual is expressed asWhereinIndicate t generation i-th of population, h-th of quantum individual ρ
Quantum state,Indicate the quantum state of t generation i-th of population, h-th of quantum individual q, whereinH=1,2 ..., H, i=1,2 ..., I are carried out to inside each population first
It evolves, by h-th of quantum individual in i-th of population'sComponent is mapped as integer solution, andComponent is kept
It is constant, it enables Mapping ruler is as follows: enablingWherein, l is perception
The lower bound of channel number, u are the upper bounds of channel perception number, and mapping ruler is Expression pairDownward bracket function,Result after mapping is
3. the frequency spectrum sensing method of energy acquisition green cognitive radio according to claim 2, it is characterized in that: to all
The fitness of all quantum individual in population carries out in evaluation procedure, h-th of quantum individual in population iFitness
It is calculated by following formula:
Energy acquisition rate required for the smaller representative of fitness value is lower, and fitness is better, selects in each population i fitness most
Good quantum individual is global optimum's quantum individual of the population
4. the frequency spectrum sensing method of energy acquisition green cognitive radio according to claim 3, it is characterized in that step 4
Specifically include: the evolutionary process of population i is as follows:
(1) mutation process: to h-th of quantum individual in i-th of populationCarry out mutation operation, quantum rotation angle and
The renewal equation of quantum bit is as follows:
Wherein, ξ1、ξ2、ξ3WithIt is the uniform random number between [0,1], sign () indicates sign function,It is equal
Value is the Gauss number that 0 variance is 1, and a ∈ { 1,2 ..., H } is a random integers, indicates the quantum chosen at random individual
Label,It is the global optimum quantum individual of population k, k ≠ i, n=1,2；
(2) crossover process: renewal equation is as follows:
Wherein ξ4It is the uniform random number between one [0,1], CR=0.01+ (0.4t)/K, K are maximum number of iterations；
(3) selection course: by quantum position'sComponent is mapped as integer solution, andComponent is kept not
Become, forms new mapping solutionIt calculatesWithFitness, later to the quantum inside each population
Individual and global optimum's quantum individual are updated, ifThanFitness it is good,
OtherwiseIt enablesB is the wherein best quantum individual label of fitness,
IfFitness be better than Otherwise gt+1(i)=gt(i)。
5. the frequency spectrum sensing method of energy acquisition green cognitive radio according to claim 4, it is characterized in that: to population
The specific method that interior individual carries out extinction processing is every KaAfter secondary iteration, globally optimal solution between more each population,
If globally optimal solution is all the same, random integers w, w a ∈ { 1,2 ..., I } is chosen, the half quantum individual in population w
Initialization is re-started to generate.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102238670A (en) * | 2011-07-14 | 2011-11-09 | 东北大学 | Method for switching multi-user mobile terminal to access network in next generation Internet |
| CN102316464A (en) * | 2011-09-19 | 2012-01-11 | 哈尔滨工程大学 | Multi-target spectrum allocation method based on undisposal order preference quantum goose group algorithm |
| CN104168592A (en) * | 2014-07-09 | 2014-11-26 | 天津工业大学 | Recognition parameter adjustment method based on multi-target artificial physics optimization |
| CN105405118A (en) * | 2015-10-16 | 2016-03-16 | 哈尔滨工程大学 | Underwater sonar image target detection method based on hybrid quantum derivative frog leaping |
| CN105611543A (en) * | 2016-01-07 | 2016-05-25 | 西安电子科技大学 | Hierarchical matching method based on channel quality prediction in cognitive wireless network |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB0106459D0 (en) * | 2001-03-15 | 2001-05-02 | Marconi Comm Ltd | Hardware design using evolutionary algorithms |
-
2016
- 2016-10-09 CN CN201610880913.6A patent/CN106254008B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102238670A (en) * | 2011-07-14 | 2011-11-09 | 东北大学 | Method for switching multi-user mobile terminal to access network in next generation Internet |
| CN102316464A (en) * | 2011-09-19 | 2012-01-11 | 哈尔滨工程大学 | Multi-target spectrum allocation method based on undisposal order preference quantum goose group algorithm |
| CN104168592A (en) * | 2014-07-09 | 2014-11-26 | 天津工业大学 | Recognition parameter adjustment method based on multi-target artificial physics optimization |
| CN105405118A (en) * | 2015-10-16 | 2016-03-16 | 哈尔滨工程大学 | Underwater sonar image target detection method based on hybrid quantum derivative frog leaping |
| CN105611543A (en) * | 2016-01-07 | 2016-05-25 | 西安电子科技大学 | Hierarchical matching method based on channel quality prediction in cognitive wireless network |
Non-Patent Citations (3)
| Title |
|---|
| 基于粒子群优化和差分进化的智能算法研究;刘俊芳;《万方数据》;20100913;全文 |
| 混合量子差分进化算法及应用;任子武; 熊蓉; 褚健;《控制理论与应用》;20111112;第28卷(第10期);全文 |
| 量子差分进化算法研究与应用;陈杰;《万方数据》;20150520;全文 |
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