CN102083101A - Information transmission method for cognitive radio sensor network - Google Patents

Information transmission method for cognitive radio sensor network Download PDF

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CN102083101A
CN102083101A CN2011100263624A CN201110026362A CN102083101A CN 102083101 A CN102083101 A CN 102083101A CN 2011100263624 A CN2011100263624 A CN 2011100263624A CN 201110026362 A CN201110026362 A CN 201110026362A CN 102083101 A CN102083101 A CN 102083101A
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沈连丰
李俊超
夏玮玮
胡静
宋铁成
邓曙光
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Southeast University
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Abstract

The invention relates to an information transmission method for a cognitive radio sensor network by combining a routing protocol and dynamic frequency spectrum allocation, comprising following five steps of: (1) periodically sensing a frequency spectrum to obtain available frequency spectrum information in real time by all sensor nodes in the network; (2) requesting a route to inform adjacent nodes to carry out negotiation on the available frequency spectrum and communication power through broadcasting by a source node when data are required to be forwarded to a sink node by the source node; (3) carrying out negotiation on the available frequency spectrum and the communication power with the node after the request is received by the neighbor node to minimize the use cost of links between two nodes; (4) calculating and saving the use cost of all the links by the source node when multiple links are available, and sequentially forwarding the routing request to the sink node by all the nodes of the available links; and (5) initiating the route to establish the request when the RREQ (Routing Request) from the source node is received by the sink node, and determining a path with the minimum forwarding cost in a distributed way according to the saved cost of all the nodes to obtain maximization of the network throughput and the life cycle.

Description

A kind of cognitive radio sensor network information transmission method
Technical field
The present invention has effectively utilized the usable spectrum of sensor node real-time perception in the network, by the forward-path of dynamic frequency spectrum deployment foundation from data source nodes to aggregation node, to obtain the maximization of network throughput and life cycle, be applied to transmission of Information in the cognitive radio sensor network (CRSN, Cognitive Radio Sensor Network).
Background technology
Cognitive radio (CR, Cognitive Radio) is the radio communication notion and the technology of rising in recent years, it can the present communication environment of perception in all frequency spectrums use chance.Wireless sensor network (WSN, Wireless Sensor Network) is another research focus of message area in recent years, and it has brought a change of information perception with characteristics such as its low-power consumption, low cost, distributed and self-organizings.The superiority that cognitive radio is brought, as improve the availability of frequency spectrum, improve communication quality etc., combine with multi-hop WSN under the resource-constrained situation, can effectively utilize frequency spectrum, have broad application prospects.Therefore, cognitive radio technology can be combined with wireless sensor network very naturally, thereby produce a kind of novel sensor network structure, be i.e. cognitive radio sensor network (CRSN, Cognitive Radio Sensor Network).
Because the frequency spectrum resource that CRSN uses is to obtain by the mode that detects, so CRSN has the frequency spectrum dynamic variation characteristic in essence.Simultaneously, as wireless sensor network, must pay close attention to the maximization of network lifetime, this mainly is reflected in aspects such as balancing energy and minimum energy consumption.Routing Protocol among tradition Ad Hoc network and the traditional WSN can not adapt to the above-mentioned characteristic of CRSN well, and in the existing research, has plenty of the discussion problem that the Routing Protocol design should be noted under the CR environment, but do not provide corresponding solution, what have only is to provide routing algorithm at CRN or WSN, but and not exclusively be fit to the CRSN environment, so design can reflect that CRSN characteristics and the Routing Protocol that is suitable for working seem very urgent in CESN.
Summary of the invention
Technical problem: the objective of the invention is to provide in CRSN a kind of cognitive radio sensor network information transmission method, this method can obtain the maximization of network throughput and life cycle.
Technical scheme: the present invention is a kind of cognitive radio sensor network information transmission method, it comprises five processes: cycle frequency spectrum perception process, broadcasting or forwarding route requests process, usable spectrum and power of communications negotiations process, route is set up process and route maintenance procedure.
Distributed frequency spectrum is distributed for joint route agreement of the present invention and information transferring method and Route Selection combines.At first, when source node need will be broadcasted route requests (RREQ, Routing Request) when aggregation node sends data, its neighbor node is receiving that this request back carries out the negotiation of usable spectrum and power of communications with this node; Then, but arranged the multilink time spent, source node calculates the trace utilization cost of each link and stores, and all nodes in the available link are transmitted route requests successively until aggregation node; At last, receive the RREQ of source node when aggregation node after, initiate route and set up request, each node is according to the cost of storage, distributed earth determines to have minimum path of transmitting cost, to obtain the maximization of network throughput and life cycle.This method comprises following 5 processes and is undertaken by described order:
1) cycle frequency spectrum perception process: each sensor node periodically carries out frequency spectrum perception in the network, and this perception can independently be carried out, and also can cooperate and finish,
2) broadcasting or forwarding route requests process: when source node need will be broadcasted RREQ when aggregation node sends data, its neighbor node is receiving that this request back and this node carry out the negotiation of usable spectrum and power of communications, but there is being the multilink time spent, source node calculates the trace utilization cost of each link and stores, all nodes in the available link are transmitted route requests successively until aggregation node
3) usable spectrum and power of communications negotiations process: this process is a target with maximization network throughput and life cycle, and by linear weighted function formation cost function, after node is received neighbor node RREQ, to minimize point-to-point transmission link trace utilization cost is target, carry out the negotiation of usable spectrum and power of communications with this neighbor node
4) route is set up process: receive the RREQ of source node when aggregation node after, initiate request of route discovery, each node is target according to the cost that stores to minimize cost function described in the step 3), and distributed earth is determined forward-path,
5) route maintenance procedure: adopt the routing error grouping and confirm to divide into groups to carry out route maintenance, when route can not be used because of the change of network topology, the node of chain rupture place is oneself to be data source nodes, again broadcast route requests, consult usable spectrum and power of communications until aggregation node to transmit remaining data.
Two aspects of described forwarding route requests process: on the one hand, and if only if this neighbor node to the distance of aggregation node greater than self to aggregation node apart from the time, node is just accepted this route requests, otherwise abandons request; On the other hand, if consult to show between two nodes there is not available spectrum, promptly under the known inaccessible situation of link constantly, node is not transmitted route requests.The route requests forwarding process as shown in Figure 2.
Communication spectrum and power of communications machinery of consultation are target with maximization network throughput and life cycle, provided the multiple-objection optimization function, with linear weight sum method multiple objective function is converted into the single goal function, is out of shape this single goal function by abbreviation and draws the forward-path cost function.Each node carries out the negotiation of usable spectrum and power of communications to being target to minimize point-to-point transmission link trace utilization cost.
In the described route finding process, receive the RREQ of source node when aggregation node after, initiate route and set up request, each node is according to stored cost, utilize the distributed dijkstra's algorithm in the graph theory, distributed earth is looked for the path with minimal path cost function and is transmitted, and this path is of described multiple-objection optimization function and effectively separates.
Beneficial effect: the CRSN information transferring method that the present invention proposes joint route agreement and dynamic frequency spectrum deployment.Advantage is that cognitive radio is combined with sensor network, the frequency spectrum of improving the occasion inserts and reduces collision and the competition time delay of bringing owing to the sensor node very dense, sensor node distributed earth in the network carries out dynamic frequency spectrum deployment and routing procedure, with the maximization of acquisition network throughput and the maximization of life cycle.
Description of drawings
Fig. 1 is the overall procedure of method.
Fig. 2 is the route requests forwarding process.
Fig. 3 is that communication spectrum and power of communications are consulted flow process.
Fig. 4 is distributed Route Selection flow process.
Embodiment
Distributed frequency spectrum is distributed information transferring method of the present invention and Route Selection combines.At first, when source node need will be broadcasted route requests (RREQ, Routing Request) when aggregation node sends data, its neighbor node is receiving that this request back carries out the negotiation of usable spectrum and power of communications with this node; Then, but arranged the multilink time spent, source node calculates the trace utilization cost of each link and stores, and all nodes in the available link are transmitted route requests successively until aggregation node; At last, receive the RREQ of source node when aggregation node after, initiate route and set up request, each node is according to the cost of storage, distributed earth determines to have minimum path of transmitting cost, to obtain the maximization of network throughput and life cycle.This method comprises following 5 processes and is undertaken by described order:
1) cycle frequency spectrum perception process: each sensor node periodically carries out frequency spectrum perception in the network, and this perception can independently be carried out, and also can cooperate and finish,
2) broadcasting or forwarding route requests process: when source node need will be broadcasted RREQ when aggregation node sends data, its neighbor node is receiving that this request back and this node carry out the negotiation of usable spectrum and power of communications, but there is being the multilink time spent, source node calculates the trace utilization cost of each link and stores, all nodes in the available link are transmitted route requests successively until aggregation node
3) usable spectrum and power of communications negotiations process: this process is a target with maximization network throughput and life cycle, and by linear weighted function formation cost function, after node is received neighbor node RREQ, to minimize point-to-point transmission link trace utilization cost is target, carry out the negotiation of usable spectrum and power of communications with this neighbor node
4) route is set up process: receive the RREQ of source node when aggregation node after, initiate request of route discovery, each node is target according to the cost that stores to minimize cost function described in the step 3), and distributed earth is determined forward-path,
5) route maintenance procedure: adopt the routing error grouping and confirm to divide into groups to carry out route maintenance, when route can not be used because of the change of network topology, the node of chain rupture place is oneself to be data source nodes, again broadcast route requests, consult usable spectrum and power of communications until aggregation node to transmit remaining data.
The transmitting power of node is retrained by two aspects: be the available maximum transmission power of perception user on the one hand, this is mainly determined by perception user hardware condition; Be the activity of other users in the network on the other hand, node one will overcome the interference that self is subjected to and noise guaranteeing proper communication, and two will reduce transmitting power to guarantee the proper communication of user around the influence within reason.Thus, the transmitting power of each node all exists a supremum and an infimum, if the some time is carved infimum less than supremum, then node perceives a frequency spectrum cavity-pocket constantly at this.
Because the dynamic variation characteristic of frequency spectrum and the otherness of the usable spectrum that each node real-time perception arrives need be carried out spectrum allocation may and Route Selection dynamically.According to the target of maximization network throughput and life cycle, the CRSN information transferring method of a kind of joint route agreement and dynamic frequency spectrum deployment has been proposed.This method is a target with maximization network throughput and life cycle, has provided the multiple-objection optimization function, with linear weight sum method multiple objective function is converted into the single goal function, is out of shape this single goal function by abbreviation and draws the forward-path cost function.Sensor node in the network is after receiving route requests RREQ, to minimize point-to-point transmission link trace utilization cost is target, distributed earth carries out the negotiation of usable spectrum and power of communications, and to have the minimum cost forward-path be target to obtain on this basis, carries out routing procedure.Dynamic frequency spectrum deployment can insert chance with effectively utilizing frequency spectrum, carries out Route Selection on this basis to obtain the maximization of network throughput and life cycle.
In conjunction with the accompanying drawings, the present invention program is designed work further concrete analysis and description.
(1) mathematical expression of network throughput and life cycle
The throughput of path P is the data volume of transmitting in the unit interval on this path, is equivalent to the actual average data transmission rate in this path, and under the given situation of data to be transferred amount, the maximization network throughput is equivalent to and minimizes the path delay of time.The path delay of time T PComprise propagation delay time t Tran, processing delay t ProcWith queuing delay t Line, establish data packet transmission, respectively be path delay of time of grouping:
T P = K · ( Σ i = 0 H - 1 N 0 / K R i , i + 1 + Σ i = 0 H - 1 N 0 / K R p + Σ i = 0 H - 1 ( N 0 ( K - 1 ) / 2 K + Q i R p + N 0 ( K - 1 ) / 2 K + Q i R i , i + 1 ) )
≈ K · Σ i = 0 H - 1 ( N 0 / 2 + Q i ) ( 1 R p + 1 R i , i + 1 )
In the following formula, N 0Be the data volume of transmitting, K is a packet count, R I, i+1Be link (i, the i+1) message transmission rate on, R pBe the data processing rate of node, Q iBe the data to be transferred sequence length of node i, H is total jumping figure of path P.
The maximization problems of network lifetime can be converted into the average residual ENERGY E on the selected path P of maximization P, its formulation is the maximization following formula:
E P = 1 H ( Σ i = 0 H - 1 e i - K · ( Σ i = 0 H - 1 P i , i + 1 ( N 0 / K ) 2 R i , i + 1 + HE p N 0 / K ) )
= - 1 H Σ i = 0 H - 1 P i , i + 1 N 0 2 KR i , i + 1 + 1 H Σ i = 0 H - 1 e i - E p N 0
In the following formula, e iBe the dump energy of node i, E pFor the node single-bit is handled energy consumption, P I, i+1(i i+1) goes up the power that sends the required consumption of bit for link.
(2) method of dynamic frequency spectrum deployment
The CRSN information transferring method of joint route agreement of the present invention and dynamic frequency spectrum deployment is a target with maximization network throughput and life cycle, and it is as follows to provide the multiple-objection optimization function:
Look for:
Figure BDA0000045136940000051
P I, i+1, P
Minimize: T P
Maximization: E P
Interval Be link (i, communications band i+1).
Utilize linear weight sum method that multiple objective function is converted into the single goal function, be out of shape this single goal function by abbreviation and draw the forward-path cost function:
Φ = 1 H · Σ i = 0 H - 1 ( 2 ρ i - e i ξ ) + λ 2 E p N 0
And have
λ 2 N 0 2 P i , i + 1 λ 1 ( N 0 / 2 + Q i ) ( 1 + R i , i + 1 / R p ) = η
Parameter ξ and network size among the cost function Φ (comprising monitored area size, leader cluster node number etc.) and data source nodes be to the distance dependent between aggregation node, in addition,
ρ i = λ 1 λ 2 N 0 2 ( N 0 / 2 + Q i ) P i , i + 1 R i , i + 1 ( 1 R i , i + 1 + 1 R p )
Cost 2 ρs of dynamic frequency spectrum deployment method to minimize the point-to-point transmission link i-e i/ ξ is a target.If establishing each node all adopts the BPSK modulation system, be by calculating the optimization result that can obtain earlier on each frequency:
R i , i + 1 ( f ) = min { λ 1 η ( N 0 / 2 + Q i ) λ 2 P i , i + 1 min ( f ) N 0 2 - λ 1 η ( N 0 / 2 + Q i ) / R p , wΔ f B }
P i , i + 1 ( f ) = λ 1 η ( N 0 / 2 + Q i ) ( 1 + R i , i + 1 ( f ) / R p ) λ 2 R i , i + 1 ( f ) N 0 2
Then, node utilizes following target function frequency range that negotiation communication uses on above-mentioned optimization result's basis.Require selected transmission rate, should be the optimization result on certain frequency in the selected frequency range, and the transmitted power on this frequency should not drop on outside the frequency spectrum cavity-pocket, this can finish by simple search.Provide the dynamic frequency spectrum deployment method flow as shown in Figure 3.
(3) method of joint route selection
Route selection method of the present invention adopts the distributed dijkstra's algorithm in the graph theory, receive the RREQ of source node when aggregation node after, initiate route and set up request, each node is according to stored cost, and distributed earth is looked for the path with minimal path cost function and transmitted.In the distributed dijkstra's algorithm, (X Y) is connection charge from X to Y, and (X Y) is the expense of economizing route most from X to Y to Cost_min if establish Cost.Suppose A and Node B, C ..., D has direct connection.Algorithm is followed following principle so:
Cost _ min ( A , Z ) = Cost ( A , B ) + Cost _ min ( B , Z ) Cost ( A , C ) + Cost _ min ( C , Z ) M Cost ( A , D ) + Cost _ min ( D , Z )
According to this principle, as long as node A knows that it arrives the expense of each neighbor node, each neighbour knows the province route of the own Z of arriving simultaneously, and node A just can determine it to arrive the province route of Z.Node A just can carry out aforementioned calculation like this, and determines to have economized route most.
Each node is only known expense and available all information of neighbours that arrive each neighbour.Therefore, in Distributed Calculation, each node is to its information of adjacent office node broadcasts known to it.Each node is all received new information and is correspondingly upgraded its routing table.Because neighbours are broadcast message termly constantly, final network node be connected spread all over whole network for information about.The information that enters node allows the province path that their find new node and lead to other nodes.Algorithm flow as shown in Figure 4.

Claims (4)

1. cognitive radio sensor network information transmission method, it is characterized in that this method is a kind of cognitive radio sensor network information transmission method based on joint route agreement and dynamic frequency spectrum deployment, at first, when source node need will be broadcasted route requests when aggregation node sends data, its neighbor node is receiving that this request back carries out the negotiation of usable spectrum and power of communications with this node; Then, but arranged the multilink time spent, source node calculates the trace utilization cost of each link and stores, and all nodes in the available link are transmitted route requests successively until aggregation node; At last, receive the route requests of source node when aggregation node after, initiate route and set up request, each node is according to the cost of storage, distributed earth determines to have minimum path of transmitting cost, to obtain the maximization of network throughput and life cycle; This method specifically comprises following process:
1). cycle frequency spectrum perception process: each sensor node periodically carries out frequency spectrum perception in the network, this perception is independently to carry out, or cooperation finishes,
2). broadcasting or forwarding route requests process: when source node need will be broadcasted route requests when aggregation node sends data, its neighbor node is receiving that this request back and this node carry out the negotiation of usable spectrum and power of communications, but there is being the multilink time spent, source node calculates the trace utilization cost of each link and stores, all nodes in the available link are transmitted route requests successively until aggregation node
3) usable spectrum and power of communications negotiations process: this process is a target with maximization network throughput and life cycle, and by linear weighted function formation cost function, after node is received the neighbor node route requests, to minimize point-to-point transmission link trace utilization cost is target, carry out the negotiation of usable spectrum and power of communications with this neighbor node
4) route is set up process: receive the route requests of source node when aggregation node after, initiate request of route discovery, each node is target according to the cost that stores to minimize cost function described in the step 3), and distributed earth is determined forward-path,
5) route maintenance procedure: adopt the routing error grouping and confirm to divide into groups to carry out route maintenance, when route can not be used because of the change of network topology, the node of chain rupture place is oneself to be data source nodes, again broadcast route requests, consult usable spectrum and power of communications until aggregation node to transmit remaining data.
2. cognitive radio sensor network information transmission method as claimed in claim 1, it is characterized in that in described broadcasting or the forwarding route requests process, when this neighbor node to the distance of aggregation node greater than self to aggregation node apart from the time, node is just accepted this route requests, otherwise abandons request; If consult to show between two nodes there is not available spectrum, promptly under the known inaccessible situation of link constantly, node is not transmitted route requests.
3. cognitive radio sensor network information transmission method as claimed in claim 1, it is characterized in that in usable spectrum and the power of communications dynamic negotiation method, this method is a target with maximization network throughput and life cycle, provided the multiple-objection optimization function, with linear weight sum method multiple objective function is converted into the single goal function, be out of shape this single goal function by abbreviation and draw the forward-path cost function, each node carries out the negotiation of usable spectrum and power of communications to being target to minimize point-to-point transmission link trace utilization cost.
4. cognitive radio sensor network information transmission method as claimed in claim 1, it is characterized in that described route sets up in the process, receive the route requests of source node when aggregation node after, initiate route and set up request, each node is according to stored cost, utilize the distributed dijkstra's algorithm in the graph theory, distributed earth is looked for the path with minimal path cost function and is transmitted, and this path is of described multiple-objection optimization function and effectively separates.
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Cited By (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102223195A (en) * 2011-07-29 2011-10-19 电子科技大学 Frequency spectrum sensing method
CN102256262A (en) * 2011-07-14 2011-11-23 南京邮电大学 Multi-user dynamic spectrum accessing method based on distributed independent learning
CN102395140A (en) * 2011-10-21 2012-03-28 南京邮电大学 Energy saving frequency spectrum detection method based on cognitive sensor network
CN102571240A (en) * 2012-02-15 2012-07-11 上海大学 Cooperative spectrum sensing parameter optimizing method utilizing improved energy detector
CN102932799A (en) * 2012-11-15 2013-02-13 陈宏滨 Cognition sensor network model and method for optimizing life cycle of cognition sensor network model
CN103036783A (en) * 2011-12-23 2013-04-10 山东黄金集团有限公司 Deep space sensor network multi-path routing method based on delay tolerant network (DTN)
CN103051709A (en) * 2012-12-20 2013-04-17 新浪网技术(中国)有限公司 Data transmission path determination method, network node and content delivery network system
CN103179696A (en) * 2013-03-15 2013-06-26 北京邮电大学 Cognitive radio based communication network system in intelligent power grid and networking method
CN103297160A (en) * 2013-05-27 2013-09-11 东南大学 Spectrum sensing method and spectrum sensing device for goodness-of-fit test based on normalized eigenvalues
CN103686919A (en) * 2014-01-08 2014-03-26 重庆邮电大学 Self-adaptive WSN (wireless sensor network) routing algorithm based on biological inspiring,
CN107005831A (en) * 2014-12-08 2017-08-01 苹果公司 Periphery perceives networking data path
CN107005940A (en) * 2014-12-12 2017-08-01 高通股份有限公司 Service announcement in neighbours' sensing network (NAN) data path
CN108055676A (en) * 2017-11-06 2018-05-18 江苏省邮电规划设计院有限责任公司 4G system D2D route selection methods based on terminal rank and number of nodes
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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2005004416A1 (en) * 2003-06-30 2005-01-13 Mitsubishi Denki Kabushiki Kaisha System for controlling communication between different types of radio communication system
CN101656998A (en) * 2009-09-29 2010-02-24 北京科技大学 Cognitive radio network routing method based on Markov process

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2005004416A1 (en) * 2003-06-30 2005-01-13 Mitsubishi Denki Kabushiki Kaisha System for controlling communication between different types of radio communication system
CN101656998A (en) * 2009-09-29 2010-02-24 北京科技大学 Cognitive radio network routing method based on Markov process

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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CN108055676A (en) * 2017-11-06 2018-05-18 江苏省邮电规划设计院有限责任公司 4G system D2D route selection methods based on terminal rank and number of nodes
CN108055676B (en) * 2017-11-06 2021-04-13 中通服咨询设计研究院有限公司 4G system D2D routing method based on terminal level and node number

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