KR101986054B1 - Method and system for sensing interval decision and pso-based dynamic resource allocation in multi-channel cognitive radio network - Google Patents

Abstract

The present invention provides a method and a system for setting sensing intervals and allocating particle swarm optimization (PSO)-based dynamic resources in a cognitive radio network using multiple channels which satisfy energy saving requirements of member nodes. According to an embodiment of the present invention, the method for allocating PSO-based dynamic resources comprises: a step where a cluster header of a cluster consisting of cognitive radio users in a cognitive radio network uses idle time statistics for each channel and priority user protection conditions to determine sensing intervals for each channel and build a frame structure for each channel by usable channel information collection obtained from member nodes belonging to the cluster; and a step of using particle swarm optimization to dynamically allocate channels to be used by the member nodes and data slots.

Description

METHOD AND SYSTEM FOR SENSING INTERVAL DECISION AND PSO-BASED DYNAMIC RESOURCE ALLOCATION IN MULTI-CHANNEL COGNITIVE RADIO NETWORK BACKGROUND OF THE INVENTION 1. Field of the Invention [

The present invention relates to a dynamic resource allocation method and system based on PSO (Particle Swarm Optimization) based on sensing interval setting in a cognitive radio network using a multi-channel channel. ) Header is based on information obtained from a member node, and a method and system for dynamically selecting a channel and a data slot to be used by each member node using a PSO.

A cognitive wireless ad-hoc network that selectively uses a plurality of channels is a technology capable of wirelessly configuring a network without a base station based on a wired backbone network by searching an unassigned channel.

The cognitive wireless ad hoc network may utilize the idle bandwidth of the priority users using the authenticated frequency band so that the cognizant wireless users can communicate with each other only to the extent that they do not interfere with the communication of the users.

After detecting the idle band, the perceptual wireless ad-hoc network firstly considers different parameters for each channel due to users, and efficiently selects a frequency resource that can be used to individually satisfy the requirement of each member node Is required.

Korean Patent No. 10-1275007 describes a technique for group-based dynamic channel allocation in such a cognitive radio network.

Korean Patent No. 10-1275007

In embodiments of the present invention, a cluster header of a cluster consisting of cognitive radio users in an ad-hoc or wireless network environment determines a period in which a user is first detected per channel, and a channel to be used by the member node And a data slot.

In addition, embodiments of the present invention satisfy each member node required data rate with respect to elements considered to dynamically determine the channel and data slot, ensure fairness between member nodes, satisfy the energy saving requirement of each member node There is another purpose in providing a method to do this.

A PSO-based dynamic resource allocation method according to an exemplary embodiment of the present invention is a method for allocating a cluster header of a cluster consisting of cognitive radio users in a cognitive radio network to the idle time per channel through collecting available channel information obtained from member nodes belonging to the cluster Determining a sensing interval for each channel using a statistical and priority user protection condition, and constructing a frame structure for each channel; And Particle Swarm Optimization (PSO) to dynamically allocate channels and data slots to be used by each of the member nodes.

Determining a sensing interval for each channel and configuring a frame structure for each channel includes constructing a channel list by grasping channel information through channel information exchange between the cluster header and the member node in a cluster header part; And calculating a sensing interval for each channel in the sensing interval determination unit.

Wherein the step of dynamically allocating channels and data slots to be used by the member nodes comprises: using a fitness function to use the PSO (Particle Swarm Optimization) in the PSO optimization unit, And calculate the particle, which is its channel and data slot.

The step of dynamically allocating channels and data slots to be used by the member nodes may include: satisfying a transfer requirement amount or an energy saving requirement amount of each member node using a fitness function for a data transfer requirement amount or an energy saving requirement amount necessary for operating the PSO If more than a certain amount of data slots are allocated or an energy saving demand is secured, the utility value is relaxed to prevent excessive allocation of data slots or excessive energy saving.

In particular, the step of determining a sensing interval for each channel and configuring a frame structure for each channel includes: sensing the broadband spectrum of the member nodes and the cluster head; After starting a timer for sensing the wideband spectrum, the member nodes grasp the channel information through channel information exchange and transmit the channel information to the cluster head. Wherein the cluster head comprises: calculating a sensing interval for each channel and available common channels; Reconstructing a frame structure based on a sensing interval for each channel; And the cluster head may include defining a particle structure based on the domain length.

In addition, dynamically allocating channels and data slots to be used by the member nodes may include: performing a PSO optimization process on the cluster head; Allocating channel and data slot positions of each member node based on the derived optimal PSO particles and broadcasting the allocated information; The member node performing communication using an assigned channel and a data slot location; Removing the corresponding channel from the common usable channel list and recalculating the available channel and the sensing interval when the user is first detected in the operating channels in the narrowband spectrum sensing; And re-sensing the broadband spectrum when the timer for sensing the broadband spectrum is complete.

The PSO-based dynamic resource allocation system according to another embodiment is a system in which a cluster header of a cluster consisting of cognitive radio users in a cognitive radio network collects usable channel information obtained from member nodes belonging to the cluster, A sensing interval determining unit for determining a sensing interval for each channel using the statistical and priority user protection conditions and configuring a frame structure for each channel; And a PSO optimizer that dynamically allocates channels and data slots to be used by each of the member nodes using a PSO (Particle Swarm Optimization).

According to embodiments of the present invention, the sensing interval for each channel is determined using the idle time statistics and the priority user protection condition for each channel through the collection of usable channel information in the cluster, and the frame structure for each channel is configured accordingly A channel and a data slot that reflect the requirements of each member node can be allocated.

In addition, according to embodiments of the present invention, it is possible to satisfy the transfer request amount of each member node using the fitness function for the data transfer request amount necessary for operating the PSO optimization, and when the data slot is allocated to a certain amount or more, It is possible to secure the fairness among the member nodes by preventing an excessive allocation of data slots.

In addition, according to embodiments of the present invention, the energy saving requirement amount of each member node can be satisfied by using the fitness function for the energy saving requirement amount necessary for operating the PSO optimization, and when the energy saving requirement amount exceeding a certain amount is secured, By mitigating excessive energy conservation, fairness among member nodes can be ensured.

In addition, according to embodiments of the present invention, it is possible to operate fluidly according to the purpose of the system by using a total fitness function that is a weighted sum of the fitness function for the data transfer requirement amount and the energy saving requirement amount necessary for operating the PSO optimization.

FIG. 1 is a diagram illustrating an overview of a cognitive wireless network using multiple channels according to an embodiment of the present invention. Referring to FIG.
2 is a diagram illustrating a multiple access method considering a multi-channel cognitive wireless network according to an embodiment of the present invention.
3 is a diagram illustrating an overall system operation process of a cognitive radio network using multiple channels according to an embodiment of the present invention.
4 is a diagram illustrating a situation in which an average channel gain is obtained in a cognitive radio network using multiple channels according to an embodiment of the present invention.
FIG. 5 is a diagram showing a general configuration of a dynamic resource allocation system based on the setting of a sensing interval and a PSO in a cognitive radio network using multiple channels according to an embodiment of the present invention.
6 is a diagram illustrating a situation in which a specific sensing interval is set for each channel in a cognitive radio network using multiple channels according to an embodiment of the present invention.
7 is a diagram illustrating a situation in which idle time of a priority user for each channel is calculated in a cognitive radio network using multiple channels according to an embodiment of the present invention.
8 is a diagram illustrating a requirement of a sensing interval in a cognitive wireless network using multiple channels according to an embodiment of the present invention.
9 is a diagram illustrating a frame structure for each channel in a cognitive radio network using multiple channels according to an embodiment of the present invention.
10 is a diagram illustrating data exchange with neighboring member nodes in a cognitive radio network using multiple channels according to an embodiment of the present invention.
11 is a diagram illustrating a convergence operation of a PSO in an optimal value direction in a cognitive radio network using multiple channels according to an embodiment of the present invention.
12 is a diagram illustrating a maximum value of an idle slot length in a cognitive radio network using multiple channels according to an embodiment of the present invention.
13 is a diagram illustrating a particle structure of a PSO algorithm proposed in a cognitive radio network using multiple channels according to an embodiment of the present invention.
14 is a diagram illustrating allocation of channels and data slots for member nodes having a high energy saving requirement according to an embodiment of the present invention.
15 is a diagram illustrating channel and data slot allocation for a member node having a high data transfer requirement according to an embodiment of the present invention.
16 is a flowchart illustrating a method of setting a sensing interval and a PSO-based dynamic resource allocation in a cognitive radio network using multiple channels according to an embodiment of the present invention.
17 and 18 are diagrams showing an overall flowchart of an optimal resource allocation process proposed in a cognitive radio network using multiple channels according to an embodiment of the present invention.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It is to be understood, however, that the invention is not to be limited to the specific embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

Like reference numerals are used for similar elements in describing each drawing.

The terms first, second, etc. may be used to describe various elements, but the elements should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another.

For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. The term " and / or " includes any combination of a plurality of related listed items or any of a plurality of related listed items.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Should not.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS [0028] Hereinafter, a method for setting a sensing interval and a PSO-based dynamic resource allocation in a cognitive radio network using multiple channels according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

In the following description, well-known functions or constructions are not described in detail to avoid unnecessarily obscuring the present invention.

The present invention provides a method of dynamically allocating resources by setting a sensing interval for each channel using channel information obtained from member nodes in a cognitive radio ad-hoc network using multiple channels and using a PSO.

In the present invention, the following terms and their meanings are defined as follows.

The cluster head (CH) constructs a set of available channels based on the sensing result report from the member nodes in the cluster. The cluster head uses the requested data transmission amount, the energy storage requirement, the average priority user idle time, A channel availability list, a channel availability list, and a channel gain status, and transmits the channel sensing period to the member cluster nodes (MCNs), a usable channel for each member node, and a data slot location.

A cluster is defined as a set of manageable nodes whose cluster head (CH) is one hop distance which is its communicable radius.

A member node (MN) transmits and receives data in a cluster, and defines the presence or absence of a user, the gain state of each channel, and the idle time of an average priority user for each channel to the cluster head.

Embodiments of the present invention are directed to a method for dynamically selecting a channel and a data slot to be used by each member node by setting a frame structure based on information obtained from a member node of a cluster header and using a Particle Swarm Optimization (PSO). More specifically, the embodiments provide a method for calculating the sensing interval based on the idle time of the priority user for each channel obtained from the cluster headers of the cluster headers in the cluster-based or wireless ad-hoc network and the constraint for priority user protection, A transmission capacity fitness function design method for allocating channels and data slots satisfying the transmission capacity and the member node fairness requested by the member nodes, energy saving for allocating channels and data slots satisfying energy saving requirements of each member node A fitness function design method, and a method of allocating dynamic channels and data slots using a PSO.

In the proposed method, the member nodes detect the channel and determine the period in which the cluster header senses the idle band through the obtained data. Since the cognizant wireless user senses the idle band, the operation of the user again in the corresponding channel during the time of data transmission in using the corresponding channel causes a problem of giving interference to the user first, so consideration thereof is required .

Also, in the proposed method, the cluster header allocates channels and data slots using the PSO to satisfy the fairness of the different data request transmission amounts of the member nodes, the transmission amount allocation among the member nodes, and the energy saving requirement of each member node. Member nodes in a cluster require different application services, satisfy the fairness of allocation of the amount of transmission among member nodes, and energy needs to be saved according to the situation of each member node in order to maintain the network stably. .

Therefore, there is a need for a method for satisfying the data request transmission amount of each member node belonging to the cluster and the fairness among the nodes and maintaining the energy of each member node stably while maximizing the gain obtained from the frequency resource by the corresponding network in the aware wireless ad hoc network Do.

FIG. 1 is a diagram illustrating an overview of a cognitive wireless network using multiple channels according to an embodiment of the present invention. Referring to FIG.

As shown in FIG. 1, a cognitive radio network using multiple channels according to an embodiment of the present invention includes a cluster head (CH) 110 and a plurality of users And member nodes (MN) 120 and 130 of FIG.

Each member node (120, 130) i is first performed periodically wideband spectrum sensing to determine the presence or absence of a user (140, 150) and may send the result to the cluster head 110. The unique information related to the channel may be an available channel list (ACL), a channel gain status (G), and an average primary idle time (I). In addition, the member nodes 120 and 130 may transmit data related to a service request of energy saving demand ( E _D ) and a data transmission demand ( T _D : data traffic demand) to the cluster head.

2 is a diagram illustrating a multiple access method considering a multi-channel cognitive wireless network according to an embodiment of the present invention.

As shown in FIG. 2, a cognitive radio network using multiple channels according to an embodiment of the present invention includes a time division multiple access (TDMA) based Medium Access Control (MAC) Access Control) method.

In the multi-channel cognitive radio network according to an exemplary embodiment of the present invention, the cluster head 110 periodically receives information from the member nodes 120 and 130, reconfigures the medium access control structure, The channel and the data slot position can be allocated. The control information including the sensing result from the member node and the channel and data slot assignment from the cluster head may be exchanged via a predetermined common control channel.

3 is a diagram illustrating an overall system operation process of a cognitive radio network using multiple channels according to an embodiment of the present invention.

Referring to FIG. 3, in a multi-channel cognitive radio network according to an embodiment of the present invention, each member node performs local spectrum sensing and transmits channel state and service request information to the cluster head. The cluster head can derive a list of possible common channels that can communicate with all the network member nodes based on the channel information received from the member nodes. The cluster head can then calculate the sensing interval on each available channel based on the average priority user idle time and priority user protection requirements. The cluster head can select the optimal channel and data slot set to be used by each member node using the PSO, and can broadcast allocation information to the member node. Each member node can transmit data using the assigned data slot until the next media control access control configuration is reconfigured.

4 is a diagram illustrating a situation in which an average channel gain is obtained in a cognitive radio network using multiple channels according to an embodiment of the present invention.

; K: 가용한 총 채널개수;

: 채널 k에서 노드 i의 채널이득), 그리고 개별적인 에너지 저장 요구량과 요구 전송량을 클러스터 헤드에게 전송할 수 있다.Referring to FIG. 4, in a cognitive radio network using a multi-channel according to an embodiment, a member node i ( n _i ) can represent a situation in which an average channel gain with neighboring member nodes is obtained for a channel k ( ch _k ) have. I member nodes in a wireless network, whether using a multi-channel in accordance with one embodiment of the present invention, the channel gains for the K channel in available channel list (ACL ^i), the node i (

; K : total number of available channels;

: The channel gain of node i in channel k ), and the individual energy storage requirements and the required throughput to the cluster head.

The channel gain of node i in channel k can be estimated by Equation (1).

[Equation 1]

), 그리고 채널 k(ch _k )에서 멤버 노드 i(n _i )의 간섭이 가산된 평균잡음(

)을 사용하여 계산될 수 있다.4 and Equation 1 when the reference channel k (ch _k) the channel gain of a node i is channel k (ch _k) an average channel gain between member nodes i (n _i) and the peripheral member node in the (

), And the average noise of the interference of the member node i ( n _i ) in the channel k ( ch _k )

). ≪ / RTI >

Referring to FIG. 4, the average channel gain of the member node i ( n _i ) and the neighboring member nodes in the channel k ( ch _k ) can be calculated by Equation (2).

&Quot; (2) "

에 속한 멤버 노드 j(n _i )와의 평균채널이득, 그리고 채널 k(ch _k )에서 멤버 노드 i(n _i )의 주변 멤버 노드들의 개수(

)를 사용하여 계산될 수 있다.4 and Equation (2) to see if the channel k (ch _k) member node i (n _i) an average channel gain of the surrounding member node is channel k (ch _k) member node i (n _i) and members in A set of peripheral nodes of node i ( n _i )

The average channel gain between the member nodes j (n _i) belong to, and the number of neighboring member node of the channel k (ch _k) member node i (n _i) from (

). ≪ / RTI >

FIG. 5 is a diagram showing a general configuration of a dynamic resource allocation system based on the setting of a sensing interval and a PSO in a cognitive radio network using multiple channels according to an embodiment of the present invention.

5, a sensing interval setting and a PSO-based dynamic resource allocation system in a cognitive radio network using a multi-channel according to an exemplary embodiment of the present invention includes a sensing interval determiner 540, (550).

The sensing interval determining unit 540 determines the cluster headers of clusters of the cognitive radio users in the cognitive radio network by collecting usable channel information obtained from the member nodes 510 belonging to the cluster, By using the user protection condition, the sensing interval for each channel can be determined and a frame structure for each channel can be configured.

The PSO optimizer 550 may dynamically allocate channels and data slots to be used by the member nodes 510 using a Particle Swarm Optimization (PSO).

), 가속상수(

), 위치 및 속도 제한조건(

)에 대한 정보를 받는다. 멤버 노드들(510)은 클러스터 헤더부(530)로부터 각 채널에서의 센싱 간격, 사용 가능한 채널 및 데이터슬롯에 대한 정보를 받을 수 있다.Cluster header portion 530 is available channel list from the member node (510), (ACL), the channel gain state (G), an average first user idle time (I), an energy storage requirement (E _D), the requested data transmission rate (T _D ) and member node information from the PSO parameter unit 520 to obtain an inertial weight constant (for use in the PSO optimizing unit 550)

), An acceleration constant (

), Position and speed limit conditions (

). ≪ / RTI > The member nodes 510 can receive information on the sensing interval, usable channel, and data slot in each channel from the cluster header unit 530.

In a multi-channel cognitive radio network according to an embodiment of the present invention, each member node 510 knows a designated common control channel and receives a set of available channels broadcast by a cluster header over a common control channel Receive. Such a common control channel may be predetermined or the cluster may dynamically select one of the available common channels of the cluster.

Here, the PSO optimizing unit 550 may include a particle position and velocity memory unit, a fitness function calculator, a particle extractor, an optimal particle memory unit, and a PSO position and velocity update unit.

In particular, the particle position and velocity memory may store and provide channel and data slot assignments of each member node 510 updated by the PSO optimizer 550.

And the fitness function calculation unit may include a transmission capacity fitness function, an energy conservation fitness function, and a total fitness function. The transfer capacity fitness function can calculate the utility of each member node 510 on the transfer demand amount and the energy conservation fitness function can calculate the utility of the energy saving requirement amount of each member node 510. In addition, the total fitness function can comprehensively calculate the effect of the transfer requirement amount and the energy saving requirement amount of each member node 510.

The particle extractor may include a local optimal particle extractor and a global best particle extractor.

The local optimum particle extractor may extract particles having a maximum total fitness function for each particle among the particles updated by the PSO optimizing unit 550 and the global optimum particle extractor may be updated by the PSO optimizing unit 550 The particle having the maximum total fitness function among the local optimum particles can be extracted.

In addition, the optimal particle memory section may include a local optimal particle memory section and a global optimum particle memory section.

The local optimal particle memory portion may store and provide particles having a maximum total fitness function from the local optimal particle extractor and the global optimal particle memory portion may store and provide particles with a maximum total fitness function from the global best particle extractor have.

6 is a diagram illustrating a situation in which a specific sensing interval is set for each channel in a cognitive radio network using multiple channels according to an embodiment of the present invention.

In a cognitive radio network using multi-channels according to an embodiment of the present invention, first, user systems have different probability of minimum priority protection, or statistical characteristics such as idle time and usage time according to protocols of each priority user system Can be different. Therefore, the periodic narrow-band sensing interval for each channel should be set differently due to such a problem. A channel requiring a short sensing interval may be allocated to the member node 510 in consideration of an energy saving requirement of each member node 510. [

Referring to FIG. 6, each channel is composed of time division multiple access slots, and each slot length can be predetermined. Here, the narrow-band sensing time is relatively shorter than the data transmission slot time, and the sensing time can be obtained so as to satisfy the required priority user detection probability. The sensing interval (SI) for each channel is a multiple of the data transmission slots, which can be calculated based on the average idle time of the user first in each channel.

7 is a diagram illustrating a situation in which idle time of a priority user for each channel is calculated in a cognitive radio network using multiple channels according to an embodiment of the present invention.

을 계산하고 채널 k에서의 평균유휴시간(

)은 최근의 유휴시간정보에 가중치를 주어 추세를 판단하는 지수가중이동평균(EWMA: Exponentially Weighted Moving Average)을 사용하여 계산될 수 있다.Referring to FIG. 7, each member node i receives the idle time

And calculates the average idle time in channel k (

May be computed using an exponentially weighted moving average (EWMA) that weights the recent idle time information to determine the trend.

)를 사용하여 계산되고, 클러스터 헤드는 가용한 각 채널(ch _k )에 대한 평균유휴시간을 계산하며 이는 [수학식 3]에 의해 산정될 수 있다.Referring to FIG. 7, the determination of the sensing interval of channel k ( ch _k ) depends on the idle time

), And the cluster head calculates the average idle time for each available channel ( ch _k ), which can be estimated by Equation (3).

&Quot; (3) "

The average idle time for each channel ( ch _k ) available with reference to FIG. 7 and [Equation 3] is calculated using the sum of the idle times calculated by all the member nodes for channel k and the number of member nodes ( N ) Can be calculated.

8 is a diagram illustrating a requirement of a sensing interval in a cognitive wireless network using multiple channels according to an embodiment of the present invention.

라고 할 때, 우선사용자의 유휴시간

가 특정시간 t보다 작을 확률은 [수학식 4]에 의해 산정될 수 있다.Referring to FIG. 8, a random variable for the idle time of the priority user in channel k ( ch _k )

First, the user's idle time

Is less than a specific time t can be estimated by [Equation (4)].

&Quot; (4) "

) 동안 우선사용자 시스템이 유휴모드에서 동작모드로 변경할 확률을

라 하면 우선사용자를 보호하기 위해 센싱 간격(

)은

에 대한 요구확률을 만족하기 위해 계산되어야 한다.Referring to FIG. 8,

), The probability that the user system will change from idle mode to operating mode

First, in order to protect the user,

)silver

Lt; RTI ID = 0.0 > a < / RTI >

보다 작을 확률은 [수학식 5]에 의해 산정될 수 있다. Referring to FIG. 8, when the idle time of the user is greater than the specific time t

Can be calculated by the following equation (5). &Quot; (5) "

&Quot; (5) "

Equation (5) can be estimated by Equation (6) by the memoryless property of the exponential distribution.

&Quot; (6) "

값을 위해 짧은 센싱 간격이 요구되고 우선사용자의 평균유휴시간(

)이 긴 경우에는 동일한

값에 비해 긴 센싱 간격이 요구될 수 있다.Referring to FIG. 8 and [Equation 6]

A short sensing interval is required for the value and the average user idle time (

) Is long, the same

A longer sensing interval than the value may be required.

Referring to FIG. 8 and [Equation 6], the sensing interval of each channel may be calculated by Equation (7) so as to satisfy the protection condition of the user.

&Quot; (7) "

Referring to FIG. 8 and FIG. 7, the sensing interval is proportional to the average idle time of the priority user calculated by the cluster head for a particular channel.

)는 [수학식 8]에 의해 산정될 수 있다. Referring to FIG. 8 and [Equation 7], the actual sensing interval (

) Can be calculated by the following equation (8).

&Quot; (8) "

)은 데이터 슬롯시간(

)과 프레임 구조의 슬롯 수(

)를 사용하여 산정될 수 있다. Referring to FIG. 8 and [Equation 8], the actual sensing interval

) Is the data slot time (

) And the number of slots of the frame structure (

). ≪ / RTI >

9 is a diagram illustrating a frame structure for each channel in a cognitive radio network using multiple channels according to an embodiment of the present invention.

는 채널 k(ch _k )의 연속적인 센싱 시간 사이의 슬롯 개수를 나타내고, 채널 k(ch _k )의 센싱 간격(

)은 채널 k(ch _k )의 평균유휴시간(

)과

에 의해 계산되기 때문에 프레임을 구성하는 슬롯의 개수는 채널마다 다르게 된다. 멤버 노드들에게 할당된 프레임의 슬롯들의 순서는 프레임 구조가 다시 재구성될 때까지 반복된다.9,

Sensing interval indicates the number of slots between consecutive sensing time of the channel _k (ch k), the channel _k (ch k) (

) Is the average idle time of channel k ( ch _k )

)and

The number of slots constituting the frame is different for each channel. The order of the slots of the frame assigned to the member nodes is repeated until the frame structure is reconstructed again.

10 is a diagram illustrating data exchange with neighboring member nodes in a cognitive radio network using multiple channels according to an embodiment of the present invention.

Referring to FIG. 10, the cluster head broadcasts the allocated channel and slot information to all the member nodes so that each member node can know the resource allocation schedule (data reception slots) of other nodes. Because the ad hoc network uses multiple channels, the transmitter must know which channel the receiver is listening on. The member node i to transmit data to a member node j should use the allocated channel and the time slot of the member node j. If there are no members of the node i is data to send to the peripheral node during another time slot member node j it can be switched to a sleep mode (sleep mode).

5, the PSO optimizing unit 550 in the cluster header unit 530 includes a particle position and velocity memory unit 551, a fitness function calculating unit 552, a particle extractor 553, A particle memory unit 554 and a PSO position and velocity update unit 555. [

개의 각 파티클은

차원(dimension)개의 메모리로 구성되며 차원의 수는 각 채널의 프레임 슬롯의 합으로 [수학식 9]에 의해 산정될 수 있다. 5, in the particle position and velocity memory unit 551,

Each particle of the dog

And the number of dimensions is the sum of frame slots of each channel, and can be calculated by Equation (9).

&Quot; (9) "

)는 센싱 간격 결정부(540)에 의해 결정될 수 있다.Referring to FIGS. 5, 9 and 9, the number of frame slots for each channel (

May be determined by the sensing interval determination unit 540. [

)은 각 멤버 노드에게 할당된 채널 및 데이터 슬롯을 의미하고, PSO가 시작하는 초기에 랜덤한 값으로 시작되며, 속도에 대한 파티클(

)는 비어있는 값(모든 값이 0)으로 시작한다. 위치에 대한 각 파티클들은 해결하고자 하는 적합도 함수의 해를 나타내며 적합도 함수 계산부(552)에 입력되어 각 파티클에 대한 총 적합도 함수를 계산한다. 최적 파티클 추출기(553)는 국부 최적 파티클 추출기(556)와 전역 최적 파티클 추출기(557)로 구성될 수 있으며, PSO 최적화부(550)가 반복적으로 수행되면서 각 파티클이 PSO 위치 및 속도 갱신부(555)에 의해 변화하는 값들 중 총 적합도 함수가 최대값인 파티클을 추출한다. 국부 최적 파티클 추출기(556)는

개의 위치에 대한 각 파티클에 대해서 총 적합도 함수가 최대인 파티클의 경우를 추출하고, 전역 최적 파티클 추출기(557)은 모든 파티클에 대해서 총 적합도 함수가 최대인 파티클의 경우를 추출한다. 최적 파티클 메모리부(554)는 국부 최적 파티클 메모리부(558)와 전역 최적 파티클 메모리부(559)로 구성될 수 있으며 국부 최적 파티클 메모리부(558)는 국부 최적 파티클 추출기(556)로부터의 파티클의 경우를 저장하고, 전역 최적 파티클 메모리부(559)는 전역 최적 파티클 추출기(557)로부터의 파티클의 경우를 저장한다. PSO 위치 및 속도 갱신부(555)는 최적 파티클 메모리부(554)로부터 국부 최적 파티클들(

)과 전역 최적 파티클(

)을 받고 파티클 위치 및 속도 메모리부(551)로부터 위치에 대한 파티클들(

)과 속도에 대한 파티클(

)을 받아 위치와 속도에 대한 파티클을 갱신한다. PSO 위치 및 속도 갱신부(555)는 [수학식 10]과 [수학식 11]에 의해 산정될 수 있다. Referring to FIG. 5, each of the particles (for each particle position and velocity memory unit 551)

) Refers to the channel and data slot assigned to each member node, starting with a random value at the beginning of the PSO,

) Starts with an empty value (all values are 0). Each particle with respect to the position represents a solution of the fitness function to be solved and is input to the fitness function calculation unit 552 to calculate a total fitness function for each particle. The optimal particle extractor 553 may be composed of a local optimal particle extractor 556 and a global best particle extractor 557. The PSO optimizer 550 may repeatedly perform each of the particles to generate a PSO position and a velocity update unit 555 ) Extracts the particles whose total fitness function is the maximum value among the values varying by the maximum likelihood function. The local optimal particle extractor 556

Extracts the case of the particle having the maximum total fitness function for each particle with respect to each position, and the global best particle extractor 557 extracts the case of the particle having the maximum total fitness function for all the particles. The optimal particle memory unit 554 may be constituted by a local optimal particle memory unit 558 and a global optimum particle memory unit 559. The local optimal particle memory unit 558 may include a local optimum particle memory unit 558, And the global optimal particle memory unit 559 stores the case of the particle from the global optimum particle extractor 557. [ The PSO position and velocity update unit 555 updates the PSO position and velocity from the optimal particle memory unit 554 to the local optimal particles (

) And the global optimal particle (

And receives particles from the particle position and velocity memory 551 for the position (

) And particles for velocity (

) To update the particle for position and velocity. The PSO position and speed update unit 555 can be calculated by the following equations (10) and (11).

&Quot; (10) "

&Quot; (11) "

과

는 가속상수,

과

는

구간 내의 랜덤한 값을 나타낸다.Referring to Equation (10) and Equation (11), t represents the number of repetitions in which the PSO optimizing unit (550) is performed,

and

Is an acceleration constant,

and

The

Represents a random value within the interval.

11 is a diagram showing a convergence operation of a PSO in an optimal value direction in a cognitive radio network using multiple channels according to an embodiment of the present invention.

는 관성중량상수로서 큰

는 PSO 최적화부(550)가 국부최소로부터 탈출하여 전역 최적을 탐색하기 용이하게 하고, 작은

는 국부 최적탐색을 용이하게 하고 PSO 최적화부(550)가 수렴하기 용이하게 한다. 파티클들이 국부 최적에 빠질 경우

는 증가하고, 파티클들이 발산할 경우

는 감소된다. 위치 파티클은 시스템이 사용할 파라미터에 대한 값을 나타내고, 속도에 대한 파티클은 최적값으로 향하는 방향으로의 변환 정도를 나타낸다. 속도에 대한 파티클 값들(

)과 위치에 대한 파티클 값들(

)은 정해진 영역을 탐색하도록 해당 값들이 각각 속도구간

과 위치구간

으로 제한된다. [수학식 10]을 참조하여 첫 번째 항은 다음에 갱신될 속도 파티클에 대해 현재의 속도 파티클과 전역적 최적값 및 국부적 최적값에 대한 검색의 기여도를 나타내고, 두 번째 항은 현재위치에서 국부 최적 방향으로의 속도 갱신에 대한 기여도를 나타내며, 세 번째 항은 현재위치에서 전역 최적 방향으로의 속도 갱신에 대한 기여도를 나타낸다. [수학식 10]과 [수학식 11]을 참조하여 [수학식 10]에 의해 수행된 속도 파티클의 갱신 값은 [수학식 11]에 의해 위치 파티클의 갱신 값이 산정될 수 있다. Referring to FIG. 11 and [Equation 10]

Is the inertia weight constant,

The PSO optimizing unit 550 may escape from the local minimum to facilitate searching for the global optimum,

Facilitates local optimal search and facilitates PSO optimizer 550 to converge. If the particles fall into local optimal

Increases, and when the particles diverge

Is reduced. The position particle represents the value for the parameter to be used by the system, and the particle for velocity represents the degree of conversion to the direction toward the optimum value. Particle values for velocity (

) And particle values for position (

≪ / RTI >< RTI ID = 0.0 >

And position interval

. Referring to Equation (10), the first term represents the contribution of the search for the current velocity particle and the global optimal value and the local optimal value for the velocity particle to be updated next, and the second term represents the local optimum And the third term represents the contribution to the rate update from the current position to the global optimal direction. Referring to Equation 10 and Equation 11, the updated value of the velocity particle performed by Equation 10 can be calculated by Equation 11. < EMI ID = 11.0 >

)에 대한 적합도 함수의 계산은 적합도 함수 계산부(552)에서 수행된다. 적합도 함수 계산부(552)는 전송용량 적합도 함수(560), 에너지 보존 함수(561), 총 적합도 함수(562)로 구성될 수 있다.Referring to FIG. 5, in the PSO optimizing unit 550, which is repeatedly performed, the location particles

) Is performed in the fitness function calculation unit 552. [ The fitness function calculation unit 552 may be configured with a transmission capacity fitness function 560, an energy conservation function 561, and a total fitness function 562. [

The calculation of the total fitness function 562 of the total fitness function calculation unit 552 of FIG. 5 can be calculated by Equation (12).

&Quot; (12) "

)와 에너지 절약 요구량에 대한 적합도 함수(

)의 가중합으로 수행되고,

과

는 가중치를 나타낸다.Referring to FIG. 5 and (12), the calculation of the total fitness function 562 is performed using a fitness function (

) And a fitness function for the energy saving requirement (

), ≪ / RTI >

and

Represents a weight.

The calculation of the transmission capacity fitness function 560 with reference to FIG. 5 and (Equation 12) can be calculated by Equation (13).

&Quot; (13) "

)의 합, 모든 채널 k에 대한 프레임 슬롯 수(

)의 합, 모든 가용 채널에 대한 평균 채널용량에 의해 결정될 수 있다.5 and calculates the transmission capacity fitness function 560 with reference to Equation 13] transmission capacity fitness function for all member nodes i (

), The number of frame slots for all channels k (

), And the average channel capacity for all available channels.

The calculation of the average channel capacity for all available channels with reference to Equation (13) can be calculated by Equation (14).

&Quot; (14) "

)과 모든 멤버 노드 i에 대한 평균전송전력에 의해 산정될 수 있다. The calculation of the average channel capacity for all available channels with reference to Equation (14) is based on the average channel gain < RTI ID = 0.0 >

) And the average transmit power for all member nodes i .

)의 계산은 [수학식 15]에 의해 산정될 수 있다. See equation 13] by the transmission capacity of the member nodes i fitness function (

) Can be calculated by the following equation (15).

&Quot; (15) "

)의 계산은 멤버 노드 i의 실제 데이터 사용비율(

)과 전송용량 요구비율(

)의 값이

인 경우와

인 경우로 나뉜다.

인 경우, 멤버 노드의 데이터 사용효율은 선형적으로 증가하고,

인 경우, 데이터 사용효율은 로그함수적으로 증가하도록 하여 멤버 노드들에게 부여되는 전송용량이 요구 전송량보다 상당히 크지 않도록 고려되었다. 따라서 [수학식 15]에 의해 멤버 노드 간에 공정성이 확보될 수 있다.See equation 15] by the transmission capacity of the member nodes i fitness function (

) Is calculated using the actual data usage rate of member node i (

) And transmission capacity requirement ratio (

) Is the value of

And

.

, The data use efficiency of the member node linearly increases,

, The data usage efficiency is increased logarithmically so that the transfer capacity given to the member nodes is considered not to be considerably larger than the required transfer amount. Therefore, the fairness among the member nodes can be secured by the formula (15).

내에 할당된 슬롯들에 대한 멤버 노드 i(n _i )의 전송용량의 정규화는 [수학식 16]에 의해 산정될 수 있다. Referring to Equation (15)

A normalization of the transmission capacity of the member node i ( n _i ) for the slots allocated within the slot _i can be estimated by (16).

&Quot; (16) "

는 채널 k(ch _k )에서 한 프레임 내에 멤버 노드 i(n _i )에게 할당된 데이터 슬롯의 수이고,

와

는 정규화를 위해 한 클러스터 내에서 얻어진 최대 채널이득과 최대전송전력을 나타낸다.Referring to Equation (16)

Is the number of data slots allocated to member node i ( n _i ) in one frame on channel k ( ch _k )

Wow

Represents the maximum channel gain and maximum transmit power obtained within a cluster for normalization.

에 대한 전송용량의 기댓값은 [수학식 17]에 의해 산정될 수 있다. Referring to Equation (16), channel k allocated to member node i , slot

The expected value of the transmission capacity can be estimated by the following equation (17).

&Quot; (17) "

는 노드 i(n _i )의 전송전력을 나타낸다.Referring to Equation (17)

_Represents the transmission power of the node i ( n _i ).

)의 계산은 [수학식 18]을 사용하여 산정될 수 있다. Referring to Equation (16), the transmission capacity requirement ratio (

) Can be calculated using the following equation (18). &Quot; (18) "

&Quot; (18) "

는 멤버 노드 i의 요구 전송량을 나타낸다.Referring to Equation (18)

Represents the required transmission amount of the member node i .

)의 계산은 [수학식 19]를 사용하여 산정될 수 있다. Referring to Equation (16), the actual data usage ratio (

) Can be estimated using the following equation (19).

&Quot; (19) "

는 모든 멤버 노드에 대한 클러스터의 평균 정규화 데이터 전송용량을 나타내며 [수학식 20]을 사용하여 계산될 수 있다.Referring to Equation (19)

Represents the average normalized data transmission capacity of the cluster for all the member nodes and can be calculated using Equation (20).

&Quot; (20) "

)의 계산은 [수학식 21]에 의해 산정될 수 있다. Referring to Equation (12), the fitness function (

) Can be calculated by the following equation (21).

&Quot; (21) "

)는 각 멤버 노드

의 에너지 절약 요구량에 대한 적합도 함수(

)와 클러스터 네트워크의 에너지 절약을 위한 평균데이터 슬롯길이(

)를 사용하여 계산될 수 있다.Referring to Equation (21), the fitness function (

) ≪ / RTI >

The fitness function for the energy saving requirement of

) And average data slot length for energy conservation in the cluster network (

). ≪ / RTI >

)는 [수학식 22]에 의해 산정될 수 있다. Referring to Equation (21), the average data slot length (

) Can be calculated by the following equation (22).

&Quot; (22) "

는 채널 k가 할당된 멤버 노드 i의 에너지 절약을 위한 정규화 데이터 슬롯 길이를 나타내며 [수학식 23]에 의해 계산될 수 있다.Referring to Equation (22)

Represents the length of the normalized data slot for energy saving of the member node i to which the channel k is allocated, and can be calculated by Equation (23).

&Quot; (23) "

는 모든 채널 k에 대한 센싱 간격(

) 의 최대값이고(

),

는 모든 채널 k에서 모든 멤버 노드 i의 유휴슬롯(idle slot)의 개수 중 최대값(

)을 나타내며

,

는 가중치를 나타낸다.Referring to Equation 23,

Is the sensing interval for all channels k

) Is the maximum value of (

),

Is the maximum value of the number of idle slots of all member nodes i on all channels k

)

,

Represents a weight.

12 is a diagram illustrating a maximum value of an idle slot length in a cognitive radio network using multiple channels according to an embodiment of the present invention.

)을 계산하고 각 멤버 노드 i에게 할당된 채널에 대한 유휴슬롯길이(

)의 최대값을 계산한다. 각 멤버 노드 i에게 할당된 채널에 대한 유휴슬롯길이(

)의 최대값은 다음 센싱까지 혹은 다음 데이터 전송시간까지의 최대슬롯간격으로 정의된다. 멤버 노드 i는 유휴슬롯길이(

) 동안 휴면모드(sleep mode)로 전환되어 에너지 절약이 가능하다.12 and the sensing distance of the reference to Equation 8, 23] to cluster head channel _k (ch k) (

) And calculates the idle slot length for the channel assigned to each member node i

). ≪ / RTI > The idle slot length for the channel assigned to each member node i (

) Is defined as the maximum slot interval between the next sensing or next data transmission time. Member node i is the idle slot length (

), It is possible to save energy by switching to a sleep mode.

)는 [수학식 24]에 의해 계산될 수 있다.Referring to Equation (21), a fitness function for the energy saving requirement amount of each member node i

) Can be calculated by Equation (24).

&Quot; (24) "

의 에너지 절약 요구량에 대한 적합도 함수(

)는 실제 에너지 절약 효용비율(

)과 에너지 절약 요구량 비율(

)이

인 경우와

인 경우로 나뉜다.

인 경우 각 멤버 노드의 에너지절약효용은 선형적으로 증가한다.

인 경우에너지 절약 효용함수는 아주 느리게 증가한다. 이러한 방법을 통해 에너지 절약과 관련하여 에너지를 소비하는데 있어서 멤버 노드간 공정성을 확보할 수 있다.Referring to Equation (24), each member node

The fitness function for the energy saving requirement of

) Is the actual energy saving utility ratio (

) And energy saving requirement ratio (

)this

And

.

The energy saving utility of each member node increases linearly.

The energy saving utility function increases very slowly. In this way, fairness among member nodes can be secured in energy consumption related to energy saving.

)의 계산은 [수학식 25]에 의해 계산될 수 있다.Referring to Equation (24), the energy saving requirement amount ratio (

) Can be calculated by the following equation (25).

&Quot; (25) "

는 멤버 노드가 클러스터 헤드에게 전송하는 멤버 노드 i(n _i )의 에너지 절약 요구량을 나타낸다.Referring to Equation (25)

Represents the energy saving requirement amount of the member node i ( n _i ) that the member node transmits to the cluster head.

)은 [수학식 26]에 의해 계산된다.Referring to Equation (24), the actual energy saving utility ratio (

) Is calculated by the following equation (26).

&Quot; (26) "

Referring to the energy conservation fitness functions 561, 12, and 24 shown in FIG. 5, the cluster head has a channel having a small sensing overhead for a member node requiring a high energy saving requirement ) And allocate a data slot with a long sleep mode.

13 is a diagram illustrating a particle structure of a PSO algorithm proposed in a cognitive radio network using multiple channels according to an embodiment of the present invention.

슬롯 파라미터들은 각 채널 k에 대해 정의된다. 각 멤버 노드는 공통으로 가능한 K 개의 채널 중 하나를 할당 받는다.13, 5, and 9, the particle is defined for K channels

Slot parameters are defined for each channel k . Each member node is assigned one of the K possible channels in common.

14 is a diagram illustrating allocation of channels and data slots for member nodes having a high energy saving requirement according to an embodiment of the present invention.

Referring to FIG. 14, a data slot allocation of a member node requiring energy saving consists of a long data slot allocation in a sleep mode.

15 is a diagram illustrating channel and data slot allocation for a member node having a high data transfer requirement according to an embodiment of the present invention.

Referring to FIG. 15, a channel having a high channel gain is allocated to a member node having a high data transmission request amount, and more data slots are allocated.

Hereinafter, a sensing interval and a dynamic resource allocation method based on PSO will be described in a cognitive radio network using multiple channels according to an embodiment of the present invention.

16 is a flowchart illustrating a method of setting a sensing interval and a PSO-based dynamic resource allocation in a cognitive radio network using multiple channels according to an embodiment of the present invention.

Referring to FIG. 16, a PSO-based dynamic resource allocation method according to an exemplary embodiment of the present invention includes: collecting available channel information obtained from member nodes belonging to a cluster, Determining a sensing interval for each channel using the idle time statistics and the priority user protection condition for each channel and constructing a frame structure for each channel 1610, and using a Particle Swarm Optimization (PSO) And dynamically allocating a data slot (step 1620).

The step 1610 of determining a sensing interval for each channel and configuring a frame structure for each channel includes constructing a channel list by grasping channel information through exchange of channel information between the cluster header and the member node in the cluster header part, And a sensing interval determining unit for calculating a sensing interval for each channel.

The step 1620 of dynamically allocating channels and data slots to be used by the member nodes is performed by using a fitness function to use the PSO (Particle Swarm Optimization) in the PSO optimizing unit to calculate a data transfer requirement amount and an energy saving requirement amount And calculate the particle, which is its channel and data slot.

In this case, a cluster head that performs arbitrary communication assigns a channel and a data slot to the cluster member node, a particle position and a velocity memory section that stores velocity particles used in the PSO optimization, It is possible to use the optimal particle memory portion that stores the local optimal particle and the global optimum particle to be used.

When a data amount required for operating a PSO or an energy saving request amount is satisfied by satisfying a transfer request amount or an energy saving request amount of each member node using a fitness function for the energy saving requirement amount, The value can be relaxed to prevent excessive data slot allocation or excessive energy saving.

In order to set the frame structure for reflecting the data transfer requirement amount and the energy saving requirement amount of each member node in the PSO optimization unit, the above-described [Expression 3], [Expression 4], [Expression 5], [Expression 6 ], [Equation 7] and [Equation 8] can be used to calculate the sensing interval.

Then, the fitness function calculation unit can calculate the weighted sum of the transmission capacity fitness function and the energy conservation fitness function using Equation (12) in calculating the total fitness function.

In particular, calculating a transmission capacity fitness function may include calculating a transmission capacity fitness function using Equation (13), calculating an average channel capacity for all available channels using Equation (14) Calculating a transmission capacity fitness function for the member node i using Equation 15, calculating a normalization of the transmission capacity of the member node i for the slots allocated to the frame slot using Equation 16, Calculating an expectation value of a transmission capacity for a channel k and a slot q allocated to a member node i using Equation (17), calculating a transmission capacity requirement ratio using Equation (18) 19] and calculating the average normalized data transmission capacity of the cluster for all the member nodes using Equation (20).

In the meantime, the setting of the sensing interval and the dynamic resource allocation based on the PSO in the multi-channel cognitive radio network according to an embodiment of the present invention are performed in a multi-channel cognitive radio network Sensing interval and a PSO-based dynamic resource allocation system.

17 and 18 are diagrams showing an overall flowchart of an optimal resource allocation process proposed in a cognitive radio network using multiple channels according to an embodiment of the present invention.

Referring to FIG. 17, in step 1610, a sensing interval for each channel is determined and a frame structure for each channel is formed. In step 1611, the member nodes and the cluster head sense a broadband spectrum 1611, After starting the timer 1612, the member nodes acquire the channel information through channel information exchange and transmit the channel information to the cluster head 1613. The cluster head uses the available common channels and the sensing interval for each channel (1615), the cluster head reconstructing a frame structure based on the sensing interval for each channel, and the cluster head may include defining a particle structure based on the domain length (1616) have.

Referring to FIG. 18, a step 1620 of dynamically allocating a channel and a data slot to be used by the member nodes includes a step 1621 of performing a PSO optimization process for the cluster head, and a cluster head is performed based on the derived optimal PSO particle Allocating (1622) channel and data slot locations of each member node and broadcasting the allocated information, the member node performing (1624) communication using the allocated channel and data slot location, (1625) for removing the channel from the common usable channel list and recalculating the available channel and sensing interval when the user is first detected in the operating channels in band spectral sensing, and for the sensing of the broadband spectrum If the timer is complete, re-sensing the broadband spectrum 1626 may be included.

), 데이터 요구량(

)을 포함하는 정보를 클러스터 헤드에게 전송할 수 있다. 이후, 클러스터 헤드는 K 개의 가용한 공통 채널들과 각 채널에 대한 최적 센싱 간격(SI)을 계산할 수 있다. 그리고 클러스터 헤드는 각 채널에 대한 센싱 간격을 기반으로 프레임 구조를 재구성할 수 있다. 이후, 클러스터 헤드는 도메인 길이(

) 기반으로 파티클 구조를 정의할 수 있다. In other words, the member nodes and the cluster head can start the resource allocation optimization process by sensing the broadband spectrum. Then, after starting the timer for the next broadband spectrum sensing, the member nodes are assigned the available channel set (ACS), channel state (G), priority user idle time (I)

), Data requirement (

) To the cluster head. The cluster head may then calculate the K available common channels and the optimal sensing interval (SI) for each channel. The cluster head can reconstruct the frame structure based on the sensing interval for each channel. After that, the cluster head is divided into domain length (

), You can define the particle structure.

And the cluster head can perform the PSO optimization process. Then, the cluster head allocates channel and data slot positions of each member node based on the derived optimal PSO particles, broadcasts this information, and the member node can perform communication using the assigned channel and data slot positions . In the narrowband spectrum sensing, if the user is detected among the operation channels, the corresponding channel is removed from the common usable channel list, and the cluster head can move to the step of calculating the available channel and the sensing interval. When the broadband sensing timer is completed during the entire process, it moves to the broadband spectrum sensing stage.

Hereinafter, a general flow of the PSO optimization process in the cognitive wireless network using multiple channels according to an embodiment will be described.

The proposed PSO optimization process in a multi-channel cognitive wireless network according to an embodiment of the present invention starts with designating the number of particles (Z), the number of particle dimensions (D), and the maximum number of repetitions (max) And then generate the position particle at random by initializing it. Then, it is possible to set the number of iterations of the PSO optimization and perform the PSO optimization process for the number of iterations. Then, the index of the particle can be climbed to 1 and the partial process of the PSO optimization process can be performed by the number of particles. Then, a multi-purpose fitness function can be calculated using Equation (12). Then, if the fitness value of the i- th particle is greater than the local optimal value of the particle, the current position particle can be assigned to the locally optimal particle. If the fitness value of the i- th particle is greater than the global optimal value of the particle, the current position particle can be assigned to the optimal particle. Then, the velocity and position of the i- th particle can be updated and the constraint condition of the position particle can be determined. The iterative process can be performed according to the values of i and t.

The apparatus described above may be implemented as a hardware component, a software component, and / or a combination of hardware components and software components. For example, the apparatus and components described in the embodiments may be implemented within a computer system, such as, for example, a processor, controller, arithmetic logic unit (ALU), digital signal processor, microcomputer, field programmable array (FPA) A programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For ease of understanding, the processing apparatus may be described as being used singly, but those skilled in the art will recognize that the processing apparatus may have a plurality of processing elements and / As shown in FIG. For example, the processing apparatus may comprise a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of the foregoing, and may be configured to configure the processing device to operate as desired or to process it collectively or collectively Device can be commanded. The software and / or data may be in the form of any type of machine, component, physical device, virtual equipment, computer storage media, or device As shown in FIG. The software may be distributed over a networked computer system and stored or executed in a distributed manner. The software and data may be stored on one or more computer readable recording media.

The method according to an embodiment may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions to be recorded on the medium may be those specially designed and configured for the embodiments or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI > or equivalents, even if it is replaced or replaced.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (7)

A cluster header of a cluster of cognitive radio users in a cognitive radio network collects usable channel information obtained from member nodes belonging to the cluster and uses the idle time statistics and the priority user protection condition for each channel, And configuring a channel-specific frame structure; And
Dynamically allocating channels and data slots to be used by each of the member nodes using PSO (Particle Swarm Optimization)
Lt; / RTI >
Determining a sensing interval for each channel and configuring a per-channel frame structure,
Constructing a channel list by grasping channel information through exchange of channel information between the cluster header and the member node in the cluster header; And
Calculating a sensing interval for each channel for the channel list identified in the cluster header
/ RTI >
The sensing interval may be,
The average idle time of the priority user for each channel is determined in advance for each channel to be proportional to the average idle time of the user, and for each of the member nodes, the average idle time of the priority user is calculated for all channels, Weighted moving average is used to determine the latest idle time information by weighting,
Wherein dynamically allocating channels and data slots for use by the member nodes comprises:
A fitness function is used in using the PSO (Particle Swarm Optimization), the transmission capacity fitness function and the energy conservation fitness function are weighted to reflect the data transfer requirement amount and the energy saving requirement amount of each member node, And calculating particles that are data slots
Wherein the PSO-based dynamic resource allocation method comprises: delete delete The method according to claim 1,
Wherein dynamically allocating channels and data slots for use by the member nodes comprises:
When a data amount required for operating the PSO or an energy saving requirement is satisfied to satisfy the transfer requirement amount or the energy saving requirement amount of each member node using the fitness function, Reduce the value to prevent excessive data slot allocation or excessive energy savings
Wherein the PSO-based dynamic resource allocation method comprises: The method according to claim 1,
Determining a sensing interval for each channel and configuring a per-channel frame structure,
The member nodes and the cluster head sensing a broadband spectrum;
After starting a timer for sensing the wideband spectrum, the member nodes grasp the channel information through channel information exchange and transmit the channel information to the cluster head.
Wherein the cluster head comprises: calculating a sensing interval for each channel and available common channels;
Reconstructing a frame structure based on a sensing interval for each channel; And
The cluster head defines a particle structure based on domain length
Based dynamic resource allocation method. 6. The method of claim 5,
Wherein dynamically allocating channels and data slots for use by the member nodes comprises:
The cluster head performing a PSO optimization process;
Allocating channel and data slot positions of each member node based on the derived optimal PSO particles and broadcasting the allocated information;
The member node performing communication using an assigned channel and a data slot location;
Removing the corresponding channel from the common usable channel list and recalculating the available channel and the sensing interval when the user is first detected in the operating channels in the narrowband spectrum sensing; And
When the timer for sensing the wideband spectrum is complete, re-sensing the broadband spectrum
Based dynamic resource allocation method. A cluster header of a cluster of cognitive radio users in a cognitive radio network collects usable channel information obtained from member nodes belonging to the cluster and uses the idle time statistics and the priority user protection condition for each channel, A sensing interval determining unit for determining a frame structure for each channel and configuring a frame structure for each channel; And
A PSO optimizing unit for dynamically allocating channels and data slots to be used by the member nodes by using PSO (Particle Swarm Optimization)
Lt; / RTI >
The sensing interval determination unit may determine,
The method comprising the steps of: constructing a channel list by grasping channel information by exchanging channel information between the cluster header and the member node in the cluster header; calculating a sensing interval for each channel with respect to the channel list identified in the cluster header;
The sensing interval is determined differently for each channel in proportion to the average idle time of the user. The average idle time of the priority user is calculated for all the channel members for each of the member nodes, The average idle time is computed using an exponential weighted moving average to weight the most recent idle time information,
The PSO optimizing unit,
A fitness function is used in using the PSO (Particle Swarm Optimization), the transmission capacity fitness function and the energy conservation fitness function are weighted to reflect the data transfer requirement amount and the energy saving requirement amount of each member node, And calculating particles that are data slots
Wherein the PSO-based dynamic resource allocation system comprises:

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