CN105357649A - PU activity-based broadcasting method of cognitive radio network - Google Patents

Abstract

The invention discloses a PU activity-based broadcasting method of a cognitive radio network. The method comprises the following steps: determining that a neighbor node does not have a receiving node set for receiving a broadcast message under the condition that i is equal to 1, Ti is a null set, A1 is equal to S and B1 is equal to S; judging whether Ai is a null set or not, and if Ai is a null set; judging whether Bi is a null set or not; if Bi is not a null set, judging whether an available channel and a broadcast node can be determined or not; if the available channel and the broadcast node can be determined, adding the broadcast node to Ti, and adding a receiving node corresponding to the available channel to Ri; if the available channel and the broadcast node cannot be determined, ending the broadcasting process of a time period i; updating i+1 into i; judging whether a union set of Ai and Ri is equal to Ai or not; if the union set of Ai and Ri is not equal to Ai, updating the union set of Ai and Ri into Ai, and judging whether Ai is a null set; and if Ai is a null set and Bi is a null set or the union set of Ai and Ri is equal to Ai, ending the overall broadcasting process. According to the method, information redundancy can be avoided; and the time delay is reduced, so that the information transmission loss caused by PU interruption is reduced or avoided.

Description

Based on the broadcasting method of the cognitive radio networks of PU activity

Technical field

The present invention relates to cognition wireless electrical domain, particularly relate to a kind of broadcasting method of the cognitive radio networks based on PU activity.

Background technology

Cognitive radio (CognitiveRadio, CR) concept originates from the founder work of doctor JosephMitola in 1999, its core concept is that CR has learning ability, can with surrounding environment interactive information, the usable spectrum in this space with perception and utilization, and the generation of restriction and reduction conflict.Cognitive radio networks (CognitiveRadioNetworks, CRNs) is the networking of cognitive radio technology, is the study hotspot in active wireless network field.Mainly concentrate in MAC layer and routing layer to the research of cognitive radio networks, the broadcast issue in recent years about cognitive radio networks becomes new study hotspot before.

Current research shows, flooding algorithm in conventional wireless network is not suitable for cognitive radio networks, and its reason is, in traditional wireless network, broadcast message can be transmitted by a public channel, and in cognitive radio networks, lack available common signal channel.People attempt various flooding algorithm to solve the problem that existing flooding algorithm is not suitable for cognitive radio networks.As the selective broadcast algorithm that Kondareddy and Agrawal proposes, this algorithm main thought is the channel set reducing the transmission of broadcast message needs; Experiment proves, selective broadcast algorithm effectively can reduce broadcast time delay and reduce redundancy.The distributed broadcast algorithm that the people such as Song propose, this algorithm has very high reachability and has good delay.

But the existing flooding algorithm be applied in cognitive radio networks is not considered the movable impact on channel of PU or does not carry out quantitative analysis to PU (PrimaryUser, primary user) activity.Due to ununified available channel and the movable impact on channel of PU, cognitive radio networks is made to there is following challenge:

One, concerning traditional adhoc network, due to the uniformity of available channel, all nodes in network can transmit on the same channel or receive information.Wherein, Adhoc net is a kind of multi-hop, acentric, ad hoc deployed wireless networks, is also called multihop network (Multi-hopNetwork), foundation-free facility network (InfrastructurelessNetwork) or self-organization network (Self-organizingNetwork).But, do not exist in CRadhoc network such one to all nodes all can channel.

For further illustrating the problems referred to above, we consider the sight of single-hop broadcast in traditional adhoc network and CRadhoc network.As Fig. 1, its interior joint A is source node, B and C is the neighbor node of A.As Fig. 1 (a), in traditional adhoc network, have unified common signal channel CH1, therefore node A only need send a broadcast message, and when zero defect, its all neighbor nodes just can receive this information.But in CRadhoc network, the available channel of each node is different, as in Fig. 1 (b), the available channel of node A is CH1 and CH3, and the available channel of Node B is CH1 and CH2, and the available channel of node C is CH2 and CH3.Now, node A needs to send broadcast message over multiple channels, could cover its neighbor node.Therefore, in the broadcasting process of cognitive radio networks, the available channel of each node need be considered.

(2) when certain node is transmitting broadcast message on certain channel, PU takies suddenly this channel, thus interrupts the transmission of this node broadcasts information.Particularly, in cognitive radio networks, PU activity has material impact to SU, and PU can interrupt the use of SU to certain channel at any time, now SU must unconditionally abdicate this channel, wherein, and PU (PrimaryUser, primary user), SU (SecondaryUser, cognitive user).Therefore, in the broadcasting process of cognitive radio networks, need consider how to reduce or avoid PU to interrupt the loss caused, thus reduce PU to the impact of SU.

Particularly, if can look-ahead within the next time period, whether certain channel can be used by PU, and at this moment SU will according to the data of prediction reasonably selective channel transmit broadcast message.Adopt single measure to weigh PU activity in prior art, as weighed PU busy channel probability with the value p of some supposition, to simulate the impact of PU on SU, this method has greater difference with actual situation, really can not portray the activity of PU.

And the flooding algorithm of current application in cognitive radio networks has the following disadvantages: as sent broadcast message on all available channels of each node, larger information redundancy can be caused and increase time delay; If when certain node uses certain channel to carry out broadcast message transmission, owing to not considering the movable impact on channel of PU, when PU will use this channel thus interrupt the broadcast message transmission of this node, the efficiency of Information Communication will be affected.

Summary of the invention

The technical problem to be solved in the present invention is, for the deficiency that the existing broadcasting method be applied in cognitive radio networks is not considered the movable impact on channel of PU or do not carried out quantitative analysis to PU activity and cause, provide a kind of broadcasting method of the cognitive radio networks based on PU activity.

The technical solution adopted for the present invention to solve the technical problems is: a kind of broadcasting method of the cognitive radio networks based on PU activity, comprises the steps:

S1: initialization assignment, makes i=1, the receiving node collection of broadcast message is not received in the neighbor node of A1=S, B1=S;

S2: judge that whether Ai is if whole broadcasting process terminates, and returns i for broadcast required time; If then perform step S3;

S3: judge that whether Bi is if whole broadcasting process terminates, and returns i for broadcast required time; If then perform step S4;

S4: all channels of each sending node in traversal Ai, can judgement determine available channel and broadcast node; Wherein, available channel makes PU be in the maximum probability of idle state and expected time the longest channel; Broadcast node is the sending node be connected with available channel in Ai;

S5: if determine available channel and broadcast node, be then added in Ti by broadcast node, to send broadcast message, and is added in Ri, with receiving broadcasting information by the receiving node corresponding to available channel; Until the broadcasting process of time period i terminates, Ai-Ti is updated to Ai, and Bi-Ri is updated to Bi; Renewal i+1 is i; Perform step S7;

S6: if can not determine available channel and broadcast node, then the broadcasting process of time period i terminates; Renewal i+1 is i; Perform step S7;

S7: judge whether the union of Ai and Ri equals Ai; If the union of Ai and Ri equals Ai, then whole broadcasting process terminates, and returns the time of i-1 needed for whole broadcasting process; If the union of Ai and Ri is not equal to Ai, then the union of Ai and Ri is updated to Ai, performs step S2;

Wherein, i is positive integer, represents current slot; A1=S represents initial broadcast set of node; Ai represents at time period i-1 end, has received broadcast message but has not sent the sending node collection of broadcast message; Bi represents the end at time period i-1, does not receive the receiving node collection of broadcast message in the neighbor node of set A i; Ti represents at time period i, sends the sending node collection of broadcast message; Ri represents at time period i, the receiving node collection of receiving broadcasting information.

Preferably, described step S4 comprises:

S401: try to achieve PU according to formula (1) and be in idle shape probability of state at arbitrary channel c

$P_{idle}^c=\frac{{\mathrm{\λ}}_{busy}^c}{{\mathrm{\λ}}_{idle}^c+{\mathrm{\λ}}_{busy}^c}+\frac{{\mathrm{\λ}}_{idle}^c}{{\mathrm{\λ}}_{idle}^c+{\mathrm{\λ}}_{busy}^c}{e}^{-({\mathrm{\λ}}_{busy}^c+{\mathrm{\λ}}_{idle}^c)t}---\left(1\right);$

S402: try to achieve PU to be in idle state expected time u at arbitrary channel c according to formula (2):

$u=\frac{E\[T_{idle}^c\]}{E\[T_{idle}^c\]+E\[T_{busy}^c\]}=\frac{{\mathrm{\λ}}_{busy}^c}{{\mathrm{\λ}}_{idle}^c+{\mathrm{\λ}}_{busy}^c}---\left(2\right);$

S403: travel through all channels, determines to make PU to be in the maximum probability of idle state and expected time the longest channel is available channel, and the sending node be connected with available channel is broadcast node;

Wherein, t is the time period, for in channel c, PU is in the parameter of the probability density function of busy state; for in channel c, PU is in the parameter of the probability density function of idle state.

Preferably, also comprise before described step S401 and S402 and determining with process, specifically comprise: determine that in channel c, PU is in the time of busy state with the time being in idle state if PU changes between busy state and idle state obey Poisson process, and with obeys index distribution, then the probability density function that in channel c, PU is in busy state is in channel c, PU is in the probability density function of idle state $f(t,{\mathrm{\λ}}_{idle}^c)={\mathrm{\λ}}_{idle}^c{e}^{-{\mathrm{\λ}}_{idle}^{c}t};$ According to with determine with

Preferably, described step S4 also comprises step S410: judge whether the broadcast node determined in Ai exists to conflict with the sending node in Ti and send broadcast message, if exist, then get rid of the broadcast node transmission broadcast message that conflict sends in the broadcast node determined from Ai; If do not exist, then the broadcast node by determining in Ai sends broadcast message.

Preferably, whether the broadcast node determined in the described Ai of judgement and the sending node in Ti exist to conflict sends broadcast message and comprises: judge whether to exist in Ti sending node and broadcast node and send broadcast message by available channel to same receiving node in section i at one time.

Preferably, each node of described cognitive radio networks is provided with a transceiver, and section can only receive described broadcast message or send described broadcast message at one time; Described cognitive radio networks comprises signal controller, for determining the available channel of described sending node.

The present invention compared with prior art tool has the following advantages: implement the present invention, in cognitive radio networks broadcasting process, select PU to be in the maximum probability of idle state and expected time the longest channel as available channel, the sending node be connected with available channel in Ai is defined as broadcast node, send broadcast message by available channel, can information redundancy be avoided and reduce time delay.And, in this cognitive radio networks broadcasting process, by being in the quantitative analysis of idle shape probability of state and expected time to PU, whether can be used by PU with prediction channel in subsequent channels, make SU available channel can be selected to send broadcast message according to predicting the outcome, the information transmission loss caused to reduce or avoid PU to interrupt, reduces PU to the impact of SU.

Accompanying drawing explanation

Below in conjunction with drawings and Examples, the invention will be further described, in accompanying drawing:

Fig. 1 is the schematic diagram of single-hop broadcast in traditional adhoc network and CRadhoc network.

Fig. 2 is the schematic diagram of the markoff process of PU activity.

Fig. 3 is the use schematic diagram of PU on channel c.

Fig. 4 is the flow chart based on the broadcasting method of the cognitive radio networks of PU activity in one embodiment of the invention.

Fig. 5 is the broadcast time delay under different SU number.

Fig. 6 is the broadcast time delay under different channels number.

Embodiment

In order to there be understanding clearly to technical characteristic of the present invention, object and effect, now contrast accompanying drawing and describe the specific embodiment of the present invention in detail.

In cognitive radio networks, if every bar channel only has a PU, the markoff process of two states can be adopted to state this PU activity, and this two states is busy state and idle state respectively, and this two states is a continuous print time period respectively.Wherein, busy state refers to channel busy, shared by PU, thus the not spendable state of SU.Idle state refers to channel idle, is not used by PU, and therefore SU can use the state of this channel.As Fig. 2, for channel c, arrow represents the direction of state transitions, and the expression formula on arrow side represents the probability of state transitions.If current state is idle state, then its with probability keep this state constant, with with probability transfer to busy state, wherein, if current state is busy state, then its with probability keep this state constant, with probability transfers to idle state, wherein, wherein,

According to the Marko section husband process of PU activity, PU in channel c can be obtained and use a model, as shown in Figure 3.In Fig. 3, suppose that in channel c, PU is in the desired value of the duration of busy state with the desired value of duration being in idle state if PU changes between busy state and idle state obey Poisson process, and is in the time span of busy state and idle state with obeys index distribution, then the probability density function that in channel c, PU is in busy state is in channel c, PU is in the probability density function of idle state for in channel c, PU is in the parameter of the probability density function of busy state; for in channel c, PU is in the parameter of the probability density function of idle state.Only have satisfied with condition, just can determine with with for channel is in the parameter of parameter busy state and idle state for time service Poisson distribution, determine by Poisson process experiment test or observation.

According to the Marko section husband process of PU activity, PU channel can be obtained and use a model.In PU channel uses a model, following steps S01 and step S02 can be adopted to determine respectively, and PU is in idle shape probability of state and expected time in arbitrary channel c.

S01: when trying to achieve t time period according to formula (1), PU is in idle shape probability of state at arbitrary channel c

$P_{idle}^c=\frac{{\mathrm{\λ}}_{busy}^c}{{\mathrm{\λ}}_{idle}^c+{\mathrm{\λ}}_{busy}^c}+\frac{{\mathrm{\λ}}_{idle}^c}{{\mathrm{\λ}}_{idle}^c+{\mathrm{\λ}}_{busy}^c}{e}^{-({\mathrm{\λ}}_{busy}^c+{\mathrm{\λ}}_{idle}^c)t}---\left(1\right).$

Correspondingly, according to when can try to achieve t time period, PU is in busy shape probability of state at arbitrary channel c

$P_{busy}^c=\frac{{\mathrm{\λ}}_{idle}^c}{{\mathrm{\λ}}_{idle}^c+{\mathrm{\λ}}_{busy}^c}+\frac{{\mathrm{\λ}}_{idle}^c}{{\mathrm{\λ}}_{idle}^c+{\mathrm{\λ}}_{busy}^c}{e}^{-({\mathrm{\λ}}_{busy}^c+{\mathrm{\λ}}_{idle}^c)t}.$

S02: try to achieve PU to be in idle state expected time u at arbitrary channel c according to formula (2):

$u=\frac{E\[T_{idle}^c\]}{E\[T_{idle}^c\]+E\[T_{busy}^c\]}=\frac{{\mathrm{\λ}}_{busy}^c}{{\mathrm{\λ}}_{idle}^c+{\mathrm{\λ}}_{busy}^c}---\left(2\right).$

Wherein, it is the desired value that in channel c, PU is in idle state duration; it is the desired value that in channel c, PU is in busy state duration.

To sum up, a given candidate channel set, SU must find a most suitable channel to carry out transmitting broadcast information.When embody rule, idle shape probability of state can be according to channel c when the t time period or be in busy shape probability of state judge whether subsequent time period channel c can use SU, and namely whether PU uses this channel c.In actual applications, select to be in idle shape probability of state maximum channel, minimum on the impact of SU.Be in the length of the expected time u of idle state again at arbitrary channel c in conjunction with PU to determine most suitable channel, understandably, the expected time u that PU is in idle state at arbitrary channel c is longer, then it is minimum on the impact of SU.Therefore, SU can select probability maximum and the channel that expected time u is the longest is as the channel of transmitting broadcast information, minimum by PU Activity Effects, and can effectively reduce time delay and avoid information redundancy.

According to the characteristic of cognitive radio networks, if each node of cognitive radio networks is provided with a transceiver, at one time section can only receiving broadcasting information or send broadcast message, and can not receive simultaneously and send broadcast channel, and each node is known and oneself can be sent or the channel of receiving broadcasting information.In addition, cognitive radio networks is also provided with signal controller, for determining the channel sent selected by the sending node of broadcast message.

As Fig. 4 and shown in combination algorithm 1 and algorithm 2, the present embodiment provides a kind of broadcasting method of the cognitive radio networks based on PU activity.Be somebody's turn to do in the broadcasting method based on the cognitive radio networks of PU activity, if i is positive integer, represent current slot; A1=S represents initial broadcast set of node; Ai represents at time period i-1 end, has received broadcast message but has not sent the sending node collection of broadcast message; Bi represents the end at time period i-1, does not receive the receiving node collection of broadcast message in the neighbor node of set A i; Ti represents at time period i, sends the sending node collection of broadcast message; Ri represents at time period i, the receiving node collection of receiving broadcasting information.

Should be based on the basic thought of the broadcasting method of the cognitive radio of PU activity, each selection broadcast node and available channel, maximum to guarantee the number of the receiving node be connected with broadcast node by available channel.Particularly, should comprise the steps: based on the broadcasting method of the cognitive radio of PU activity

S1: initialization assignment, makes i=1, the receiving node collection of broadcast message is not received in the neighbor node of A1=S, B1=S.Wherein, all initialization broadcast nodes (i.e. sending node) in S have all received broadcast message and have not sent the sending node of broadcast message.

S2: judge that whether Ai is if then represent at time period i-1 end do not exist and received broadcast message but the sending node not sending broadcast message; Therefore, whole broadcasting process terminates, and returns i for broadcast required time.If namely at time period i-1 end, exist and received broadcast message but the sending node not sending broadcast message, then perform step S3.

S3: judge that whether Bi is if then represent at time period i-1 end, in the neighbor node of set A i, there is not the receiving node not receiving broadcast message; Therefore, whole broadcasting process terminates, and returns i for broadcast required time.If , there is the receiving node not having receiving broadcasting information in i.e. time period i-1 end, then performs step S4 in the neighbor node of set A i.

S4: all channels of each sending node in traversal Ai, can judgement determine available channel and broadcast node; Wherein, available channel makes PU be in the maximum probability of idle state and expected time the longest channel; Broadcast node is the sending node be connected with available channel in Ai.Particularly, step S4 comprises:

S401: try to achieve PU according to formula (1) and be in idle shape probability of state at arbitrary channel c

$P_{idle}^c=\frac{{\mathrm{\λ}}_{busy}^c}{{\mathrm{\λ}}_{idle}^c+{\mathrm{\λ}}_{busy}^c}+\frac{{\mathrm{\λ}}_{idle}^c}{{\mathrm{\λ}}_{idle}^c+{\mathrm{\λ}}_{busy}^c}{e}^{-({\mathrm{\λ}}_{busy}^c+{\mathrm{\λ}}_{idle}^c)t}---\left(1\right).$

S402: try to achieve PU to be in idle state expected time u at arbitrary channel c according to formula (2):

$u=\frac{E\[T_{idle}^c\]}{E\[T_{idle}^c\]+E\[T_{busy}^c\]}=\frac{{\mathrm{\λ}}_{busy}^c}{{\mathrm{\λ}}_{idle}^c+{\mathrm{\λ}}_{busy}^c}---\left(2\right).$

Wherein, t is the time period, for in channel c, PU is in the parameter of the probability density function of busy state; for in channel c, PU is in the parameter of the probability density function of idle state.

S403: travel through all channels, determines to make PU to be in the maximum probability of idle state and expected time the longest channel is available channel, and the sending node be connected with available channel in Ai is broadcast node.Understandably, the number that available channel covers the receiving node in Bi is maximum, and the receiving node number be namely connected with broadcast node by available channel in Bi is maximum; Broadcast node sends broadcast message by available channel, can avoid the movable impact on SU of PU, can be conducive to saving the airtime, reduce time delay and avoid information redundancy.

Described step S4 also comprises step S410: judge whether the broadcast node determined in Ai exists to conflict with the sending node in Ti and send broadcast message, if exist, then gets rid of the broadcast node transmission broadcast message that conflict sends in the broadcast node determined from Ai.Particularly, sending broadcast message by available channel to same receiving node in section i at one time by judging whether to exist in Ti sending node and broadcast node, sending broadcast message to determine whether there is conflict.Understandably, if the broadcast node determined in Ai and the sending node in Ti exist to conflict send broadcast message, section at one time may be caused, two or more sending nodes are had to send broadcast message by selected available information to same receiving node, channel may be caused to block up, information redundancy, thus increase broadcast time delay.Therefore, if there is conflict to send broadcast message, then get rid of corresponding broadcast node and send broadcast message, to ensure that available channel is unimpeded.

S5: if determine available channel and broadcast node, then broadcast node is added in Ti, to send broadcast message; And the receiving node corresponding to available channel is added in Ri, with receiving broadcasting information; Until the broadcasting process of time period i terminates.Now, Ai-Ti is updated to Ai, and Bi-Ri is updated to Bi, get rid of from Ai by the sending node in Ti, receiving node in Ri is got rid of from Bi, to avoid repeating send broadcast message or repeat receiving broadcasting information, thus reduce time delay and avoid information redundancy, to reach the object of saving the airtime.Renewal i+1 is i; Perform step S7.

S6: if can not determine available channel and broadcast node, then the broadcasting process of time period i terminates.Renewal i+1 is i; Perform step S7.

S7: judge whether the union of Ai and Ri equals Ai, namely judges whether the union of the sending node collection in Ai and the receiving node collection in Bi equals the sending node collection of Ai.If the union of Ai and Ri equals Ai, illustrate that the receiving node collection of receiving broadcasting information in current slot i is then whole broadcasting process terminates, and returns the time of i-1 needed for whole broadcasting process.If the union of Ai and Ri is not equal to Ai, illustrate that the receiving node collection of receiving broadcasting information in current slot i is not then the union of Ai and Ri is updated to Ai, is added in Ai by the receiving node in Ri, perform step S2.

Circulation performs above-mentioned steps S2-S7, until whole broadcasting process terminates, its time returned is whole broadcasting process required time.

To sum up, in the broadcasting method of the cognitive radio networks based on PU activity that the present embodiment provides, PU is selected to be in idle shape probability of state the sending node be connected with available channel in Ai, as available channel, is defined as broadcast node, sends broadcast message by available channel, can avoid information redundancy and reduce time delay by the maximum and channel that expected time u is the longest.Further, in this cognitive radio networks broadcasting process, by being in idle shape probability of state to PU carry out quantitative analysis with expected time u, to predict whether channel can be used by PU in subsequent channels, (namely PU is in idle shape probability of state to make SU can select most suitable available channel according to predicting the outcome maximum and the channel that expected time u is the longest) send broadcast message, cause transmission information lose to reduce or avoid PU to interrupt, PU is on the impact of SU in minimizing.

In the present embodiment, Implementation of pseudocode process based on a kind of specific algorithm of the broadcasting method of the cognitive radio networks of PU activity is as follows, understandably, realize including but not limited to based on the broadcasting method of the cognition wireless network of PU activity the algorithm that the present embodiment provides.

By following experiment, to verify the broadcasting method of the cognitive radio networks based on PU activity adopting the present embodiment to provide, can effectively reduce broadcast time delay.

Before testing, need a network topological diagram for shaping cognitive radio networks, the method of stochastic generation can be adopted to produce network topological diagram, detailed process is as follows: first, produce the random point of some, each random point represents a node in cognitive radio networks, and wherein the abscissa value of each node and ordinate value are within 0--1000m.In order to avoid the distance between multiple SU is too near, we can arrange distance threshold values (as 30m) and make the distance between adjacent node be greater than this distance threshold values.Then be added in the distribution map of this random point by limit, the node on behalf having limit to connect can carry out the transmission of broadcast message.Suppose centered by certain node, all nodes in the circle that radius is R have limit to be connected with this Centroid.Owing to needing a connected graph in an experiment, when not finding node can be connected with Centroid in the circle that radius is R, the value that now we should increase R is guaranteed to find node to be connected with Centroid.Through step above, if this figure be not be also communicated with, find out in disconnected partial graph nearest node to and add limit, until this figure is connected graph.

Had the topology diagram of cognitive radio networks, adopted following methods to each peer distribution channel: be at random every bar limit distribution k (k=1,2 ..., M) individual channel.The available channel collection of each node is defined as the set of coupled limit upper signal channel.Suppose that the number of SU changes between 1-100, to each SU Random assignment 0-10 channel, above each channel, have a PU.

Parameter list:

Message transmission rate: 2Kbps

Broadcast data size: 1024bits

	CH1	CH2	CH3	CH4	CH5	CH6	CH7	CH8	CH9	CH10
											E[T idle] (s)	2.0	4.5	5.5	2.0	8.0	3.5	1.5	2.5	0.7	2.5
E[T busy] (s)	1.5	1.0	1.5	1.0	1.5	3.0	2.0	5.5	2.0	3.0
											u	0.57	0.81	0.79	0.67	0.84	0.54	0.43	0.31	0.26	0.45

Fig. 5 shows broadcast time delay to be increased along with the increase of interstitial content.Wherein, SB represents that the broadcast time delay adopting selective broadcast algorithm in cognitive radio networks increases along with the increase of interstitial content.After GWP represents quantitative analysis PU activity, the relation of the broadcast time delay that the flooding algorithm adopting the present embodiment to provide is tried to achieve and interstitial content.Shown in Fig. 5, under same node point number, the broadcast time delay after analyzing PU movable quantitative is lower than the broadcast time delay adopting selective broadcast algorithm; Therefore, the flooding algorithm of the cognitive radio networks based on PU activity adopted in the present embodiment can effectively reduce broadcast time delay.

Fig. 6 shows broadcast time delay to be increased along with the increase of available channel.In Fig. 6, particularly, m_n represents in network m SU user, n available channel.SB represents that the broadcast time delay adopting selective broadcast algorithm in cognitive radio networks increases along with the increase of available channel.After GWP represents quantitative analysis PU activity, the relation of the broadcast time delay that the flooding algorithm adopting the present embodiment to provide is tried to achieve and available channel.In the network topological diagram of identical cognitive radio networks, the broadcast time delay of flooding algorithm in this paper is lower than the broadcast time delay of selective broadcast algorithm; Therefore, the flooding algorithm of the cognitive radio networks based on PU activity adopted in the present embodiment can effectively reduce broadcast time delay.

The present invention is described by several specific embodiment, it will be appreciated by those skilled in the art that, without departing from the present invention, can also carry out various conversion and be equal to substituting to the present invention.In addition, for particular condition or concrete condition, various amendment can be made to the present invention, and not depart from the scope of the present invention.Therefore, the present invention is not limited to disclosed specific embodiment, and should comprise the whole execution modes fallen within the scope of the claims in the present invention.

Claims (6)

1. based on a broadcasting method for the cognitive radio networks of PU activity, it is characterized in that, comprise the steps:

S1: initialization assignment, makes i=1, the receiving node collection of broadcast message is not received in the neighbor node of A1=S, B1=S;

S2: judge that whether Ai is if whole broadcasting process terminates, and returns i for broadcast required time; If then perform step S3;

S3: judge that whether Bi is if whole broadcasting process terminates, and returns i for broadcast required time; If then perform step S4;

S4: all channels of each sending node in traversal Ai, can judgement determine available channel and broadcast node; Wherein, available channel makes PU be in the maximum probability of idle state and expected time the longest channel; Broadcast node is the sending node be connected with available channel in Ai;

S5: if can determine available channel and broadcast node, be then added in Ti by broadcast node, to send broadcast message, and is added in Ri, with receiving broadcasting information by the receiving node corresponding to available channel; Until the broadcasting process of time period i terminates, Ai-Ti is updated to Ai, and Bi-Ri is updated to Bi; Renewal i+1 is i; Perform step S7;

S6: if can not determine available channel and broadcast node, then the broadcasting process of time period i terminates; Renewal i+1 is i; Perform step S7;

S7: judge whether the union of Ai and Ri equals Ai; If the union of Ai and Ri equals Ai, then whole broadcasting process terminates, and returns the time of i-1 needed for whole broadcasting process; If the union of Ai and Ri is not equal to Ai, then the union of Ai and Ri is updated to Ai, performs step S2;

Wherein, i is positive integer, represents current slot; A1=S represents initial broadcast set of node; Ai represents at time period i-1 end, has received broadcast message but has not sent the sending node collection of broadcast message; Bi represents the end at time period i-1, does not receive the receiving node collection of broadcast message in the neighbor node of set A i; Ti represents at time period i, sends the sending node collection of broadcast message; Ri represents at time period i, the receiving node collection of receiving broadcasting information.

2. the broadcasting method of the cognitive radio networks based on PU activity according to claim 1, is characterized in that, described step S4 comprises:

S401: try to achieve PU according to formula (1) and be in idle shape probability of state at arbitrary channel c

$P_{idle}^c=\frac{{\mathrm{\λ}}_{busy}^c}{{\mathrm{\λ}}_{idle}^c+{\mathrm{\λ}}_{busy}^c}+\frac{{\mathrm{\λ}}_{idle}^c}{{\mathrm{\λ}}_{idle}^c+{\mathrm{\λ}}_{busy}^c}{e}^{-({\mathrm{\λ}}_{busy}^c+{\mathrm{\λ}}_{idle}^c)t}---\left(1\right);$

S402: try to achieve PU to be in idle state expected time u at arbitrary channel c according to formula (2):

$u=\frac{E\[T_{idle}^c\]}{E\[T_{idle}^c\]+E\[T_{busy}^c\]}=\frac{{\mathrm{\λ}}_{busy}^c}{{\mathrm{\λ}}_{idle}^c+{\mathrm{\λ}}_{busy}^c}---\left(2\right);$

S403: travel through all channels, determines to make PU to be in the maximum probability of idle state and expected time the longest channel is available channel, and the sending node be connected with available channel is broadcast node;

Wherein, t is the time period, for in channel c, PU is in the parameter of the probability density function of busy state; for in channel c, PU is in the parameter of the probability density function of idle state.

3. the broadcasting method of the cognitive radio networks based on PU activity according to claim 2, is characterized in that, also comprises and determine before described step S401 and S402 with process, specifically comprise: determine that in channel c, PU is in the time of busy state with the time being in idle state if PU changes between busy state and idle state obey Poisson process, and with obeys index distribution, then the probability density function that in channel c, PU is in busy state is in channel c, PU is in the probability density function of idle state according to with determine with

4. the broadcasting method of the cognitive radio networks based on PU activity according to claim 2, it is characterized in that, described step S4 also comprises step S410: judge whether the broadcast node determined in Ai exists to conflict with the sending node in Ti and send broadcast message, if exist, then get rid of the broadcast node transmission broadcast message that conflict sends in the broadcast node determined from Ai; If do not exist, then the broadcast node by determining in Ai sends broadcast message.

5. the broadcasting method of the cognitive radio networks based on PU activity according to claim 4, is characterized in that: whether the broadcast node determined in the described Ai of judgement and the sending node in Ti exist to conflict sends broadcast message and comprise: judge whether to exist in Ti sending node and broadcast node and send broadcast message by available channel to same receiving node in section i at one time.

6. the broadcasting method of the cognitive radio networks based on PU activity according to any one of claim 1-5, it is characterized in that, each node of described cognitive radio networks is provided with a transceiver, and section can only receive described broadcast message or send described broadcast message at one time; Described cognitive radio networks comprises signal controller, for determining the available channel of described sending node.