CN106658523A - Distributed topological method for constructing K channel connectivity in cognitive AdHoc network - Google Patents
Distributed topological method for constructing K channel connectivity in cognitive AdHoc network Download PDFInfo
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Abstract
The invention discloses a distributed topological method for constructing K channel connectivity in a cognitive AdHoc network. The method mainly settles problems of secondary user network disconnection and mutual interference of secondary users when a plurality of main users occupy a channel in prior art. The distributed topological method comprises the realizing steps of 1, broadcasting a HELLO package twice by each node in the network, receiving the HELLO packages of an initial adjacent node, and establishing a local two-hop topological subgraph; 2, constructing a shortest path tree based on the local two-hop topological subgraph, and constructing a local generation subgraph which can ensure sub-user connectivity according to the shortest path tree; 3, adjusting an emission power according to a one-hop adjacent node in the local generation subgraph and determining the logical adjacent node of each node; and 4, forming a full network topology by all nodes in the network and logical adjacent nodes, and performing channel selection. The distributed topological method has advantages of ensuring user network connectivity, eliminating the secondary user interferences and saving channel resource. The distributed topological method can be used for the cognitive AdHoc network.
Description
Technical field
The invention belongs to wireless communication field, more particularly to a kind of network topology structure based on structure K channel-connectivities
Method, can be used for cognitive Ad Hoc networks.
Background technology
The topological structure of network is a highly important factor for affecting cognition Ad Hoc network performances, improves cognition Ad
The robustness of Hoc network, the fault-tolerant ability of enhancing network topology become the primary study direction of Topology Control.Cognitive Ad
There are two kinds of users in Hoc network, one is primary user, another is time user.Primary user enjoys the preferential right of channel.Work as master
During CU channel, secondary user must make a concession the channel in silent status, it is more likely that affect the connectedness of time user.And
When multiple primary users take multiple channels, the right to use of substantial amounts of user's yielding channel is had, this may be such that network
The situation of segmentation will be more serious, therefore, cognitive Ad Hoc networks how are maintained when busy channel resource occur in multiple primary users
Connectedness become a critical problem.In the article that the authors such as Xinjun Wang deliver on IEEE VTC 2014
In the algorithm of " Bi-Channel-Connected Topology Control in Cognitive Radio Networks " etc.
The connection of time user network is can ensure that, the interference between time user can be also eliminated, but the method only has to single primary user
Effect, when multiple primary users occur, it is impossible to ensure the connection of network, can not eliminate the interference of time user, so as to affect cognition
The fault-tolerant ability of Ad Hoc networks.
The content of the invention
Present invention aims to above-mentioned problem of the prior art, proposes to build K in a kind of cognitive Ad Hoc networks
The distributed topology approach of channel-connectivity, to ensure the connectedness of secondary user's network, eliminates the interference between secondary user's, from
And improve the fault-tolerant ability of cognition Ad Hoc networks.
For achieving the above object, technical scheme includes as follows：
(1) it is that k points are connected to initialize network, k >=2, and each node u obtains respectively a jump and double bounce abutment points in network
Sequence number and positional information；
(2) sequence number and positional information in step (1) sets up local double bounce topology subgraphAnd calculateIn
Any two has the node x of annexation, link energy consumption weight w between yp(x, y) and link range weight wd(x,y)；
(3) each node u builds and is locally generated subgraph S in networku：
(3a) initialize each node and be locally generated subgraph SuNode set V (Su) it is local double bounce topology subgraphIn
All nodes, initialize each node and be locally generated subgraph SuLine set E (Su) it is empty set；
(3b) based on local double bounce topology subgraphEach node u is according to link energy consumption weight wp(x, y), structure be with u
Root, the shortest path tree T of all nodes in local double bounce topology subgraphu=(V (Tu),E(Tu)), whereinFor all nodes in local double bounce topology subgraph, E (Tu) it is all sides for constituting shortest path tree, and will
These sides recorded the line set E (S for being locally generated subgraphu) in, i.e. E (Su)<=E (Tu)∪E(Su)；
(3c) each node u in network is according to shortest path tree TuThe node conflicted with oneself is found, conflict section is constituted
Point set CNu, and according to CNuWithBuild conflict subgraph CSu=(V (CSu),E(CSu)), wherein
(3d) conflict subgraph CS is judgeduWhether it is the connection of k-1 points：If so, then by CSuPut into conflict subgraph set { CSu}
In；Otherwise, in local double bounce topology subgraphMiddle structure k-1 points connection conflict subgraphOrderWill
Put into conflict subgraph set { CSuIn；
(3e) judge whether k-1 >=2 set up：If so, then execution step (3f), otherwise, jumps to step (3m)；
(3f) i=2 is initialized, wherein i represents conflict subgraphIn i-th layer；
(3g) j=1 is initialized, wherein j represents conflict subgraph CSuIn j-th conflicting nodes；
(3h) makeWherein { CSu}jRepresent in conflict subgraph CSuJ-th node conflict subgraph,Represent the i-th -1 layer conflict subgraph；
(3i) for all of node In find corresponding conflicting nodes set CNuv, according to CNuv
WithBuild i-th layer of conflict subgraphWhereinSet of nodeSide collection
(3j) judgeWhether it is k-i points connection conflict subgraph：If so, then willIt is incorporated into conflict subgraph set
{CSuIn, otherwise, build k-i points connection conflict subgraphOrderAnd willIt is incorporated into set { CSuIn；
(3k) judge whether j meets j=| { CSu}|：If so, execution step (3l), otherwise, j=j+1 jumps to step
(3h)；
(3l) judge whether i meets i=k-1：If so, execution step (3m), otherwise, i=i+1 jumps to step (3g)；
(3m) to gathering { CSuIn all conflict subgraphs using distributed two channel-connectivities algorithm DBCC build generate son
Tree Su=(V (Su),E(Su)), wherein V (Su) represent SuSet of node, E (Su) represent SuSide collection；
(3n) each node u is locally generated subgraph S according to what the topology information that other nodes are sent updated oneselfuAnd logic
Conflict neighbours collection LCNuv, subgraph S will be locally generateduOn a jump neighbors v as logic neighbors, and constitute logic neighbors
Collection：LCNu={ v ∈ V (Su)|(u,v)∈E(Su)}；
(3p) side collection information E (S)=E (S) ∪ E (S are updatedu), more new logic neighborhood information LCNu=V (Su), wherein E
(S) represent that all nodes generate total side collection for generating figure, LCN in networkuRepresent the logic neighbors set of node u；
(4) each node u determines the transmission power of oneself in network, will transmission power be adjusted to can cover it is all
Minimum power required for logic neighbors：
(5) link combinations between all nodes and each node and the logic neighbors of oneself in network are got up,
Constitute final full mesh topology, i.e. G=(V (G), E (G)), wherein V (G) is all nodes in network, E (G)=(u, v) | u ∈
V(G),v∈LCNu, wherein E (G) represents the side collection in network G；
(6) channel distribution is carried out to each node u in the final full mesh topology that built using greedy coloring algorithm.
The invention has the advantages that：
1) present invention is locally generated subgraph by distributed structure, and combines Power Control and channel distribution causes time user
The independent sets of network do not constitute the cut set of network, when solving multiple multiple channels of primary users' occupancy, the disconnected situation of network,
So as to ensure the connectedness of time user network, the K channel-connectivities of network are realized；
2) joint Power control of the present invention and channel distribution, not only reduce the transmission power of node, and decrease
The required number of channel, so as to save frequency spectrum resource.
3) present invention carries out channel distribution by each node u in the final full mesh topology to having built, eliminates secondary
Interference between user.
Description of the drawings
Fig. 1 is the applicable cognitive Ad Hoc networks schematic diagram of a scenario of the present invention；
Fig. 2 be the present invention realize general flow chart；
Fig. 3 is the peak power topology formed in 50 meshed network scenes in the present invention；
Fig. 4 is that the sub-process figure for being locally generated subgraph is built in the present invention；
Fig. 5 is the exemplary plot that interior joint u of the present invention builds topology；
Fig. 6 is the simulating, verifying figure that topology is generated to the present invention；
Fig. 7 is simulation comparison figure of the average transmission radius obtained to the present invention under different value of K；
Fig. 8 is simulation comparison figure of the average channel number obtained to the present invention under different value of K；
Fig. 9 is simulation comparison figure of the maximum channel number obtained to the present invention under different value of K.
Specific embodiment
Embodiment of the present invention is described in further detail below in conjunction with accompanying drawing.
With reference to Fig. 1, the cognitive Ad Hoc networks that the present invention is used are distributed in the node group in two dimensional surface region by n
Into.Time user of each node on behalf one, and with unique sequence number, it is possible to by GPS or other location technologies come
Obtain the positional information of its own.All of node is affected by multiple primary users, and primary user can be using in C channel
Any one channel.Each node can send data in any one channel in C channel, while in other all channels
Upper interception data, in addition each node do not exist at aspects such as physical arrangement, initial setting up, functional characteristic, parameter indexs
Any difference.In a network, the wireless channel between arbitrary node is additive white Gaussian noise channel.Node by omnidirectional antenna with
Surroundings nodes communicate, and maximum transmission power is Pmax.Transmission power P of arbitrary node uuCan connect between a minimum and a maximum
It is continuous to adjust, i.e. 0≤Pu≤Pmax.Transmission radius r is the transmission range corresponding to node transmitting power, between any two node
The necessary and sufficient condition that there is Radio Link is transmission radius r of the Euclidean distance between them less than or equal to node.
With reference to Fig. 2, the present invention's realizes that step is as follows：
Step 1, each node u sends the first node information HELLO-1 bag of oneself in network, and receives a jump neighbors
The HELLO-1 bags of transmission.
(1a) when each node is using maximum power transfer in network, the topological structure that formed is peak power topology,
As shown in figure 3, peak power topological representation is：Gmax=(V (Gmax),E(Gmax)), wherein V (Gmax) it is node set, represent net
Network node, E (Gmax) it is line set, represent the Radio Link existed between node.
(2b) all nodes in the transmission radius of node u, constitute a jump neighbors collection of node u Wherein secondary user v1Jump for 1 with the distance of secondary user u；
(3c) each node u in network is with maximum transmission power PmaxA HELLO-1 is broadcasted to a jump neighbors of u
Bag, the positional information of sequence number and node u containing node u in HELLO-1 bags；
Each node u in network receives one and jumps neighbors with maximum transmission power PmaxThe HELLO-1 bags of broadcast.
Step 2, the first node information HELLO-1 bag in above-mentioned steps 1, each node u sends oneself in network
Section Point information HELLO-2 bag, and receive a jump neighbors transmission HELLO-2 bags.
(2a) node u is used within double bounce includes all nodes that double bounce can be reached, and constitutes the double bounce neighbors of node u
Collection∪ represents two union of sets ， ＆＆
Represent also, wherein secondary user v2Jump for 2 with the distance of secondary user u；
(2b) each node u in network has received all one and has jumped after the HELLO-1 bags that neighbors sends, with emission maximum
Power PmaxA HELLO-2 bag is broadcasted to a jump neighbors of u, containing u all one jump the sequence of neighbors in HELLO-2 bags
Row number and positional information；
(2c) each node u in network receives one and jumps neighbors with maximum transmission power PmaxThe HELLO-2 bags of broadcast.
Step 3, each node u builds the local double bounce topology subgraph of oneself in network
(3a) first node information HELLO-1 that each node u in network sends according to the jump neighbors for receiving
With Section Point information HELLO-2 package informatin, oneself all double bounce neighbors v is obtained and recorded12Sequence number and positional information,
Wherein
(3b) each node u calculates any two according to the positional information of oneself and the positional information of double bounce neighbors
Node x, the minimum emissive power required for directly transmitting between y：Wherein,β is received signal to noise ratio
Threshold value, according to the sensitivity and bit error rate requirement determination of receiver, α is path-loss factor, and { u } represents node u compositions
Set, dx,yIt is node x, the Euclidean distance between y；
(3c) according to the minimum emissive power for calculating, the annexation between double bounce neighbors is judged, if Px,yLess than node
Maximum transmission power Pmax, it is determined that node x, there is annexation between y；Otherwise, there is no connection between y and close in node x
System；
(3d) each node u sets up local double bounce topology subgraph according to the annexation between double bounce neighborsWhereinNode set beLocal double bounce topology subgraphSide collection
It is combined into:I.e. forIn any two nodeWhenWhen, by sidePut into local double bounce topology subgraphLine setIn；
(3e) each node u calculates any two the node x of annexation, the link energy consumption weight between y：wp(x,
Y)=Px,y, wherein,Px,yFor the node x that any two has annexation, required for directly transmitting between y
Minimum transmit power；
(3f) node u calculates any two the node x of annexation, the link range weight between y：wd(x, y)=
dx,y, wherein,dx,yIt is node x that any two has annexation, the Euclidean distance between y.
Step 4, each node u builds and is locally generated subgraph S in networku=(V (Su),E(Su)), and determine patrolling for oneself
Collect neighbors.
With reference to Fig. 4, this step is implemented as follows：
(4a) initialize each node and be locally generated subgraph SuNode set V (Su) it is local double bounce topology subgraphIn
All nodes, initialize each node and be locally generated subgraph SuLine set E (Su) it is empty set；
(4b) based on local double bounce topology subgraphWith link energy consumption weight wp(x, y) is link weight, and node u passes through
Using dijkstra's algorithm, build with u as root, the shortest path tree T of all nodes in local double bounce topology subgraphu=(V
(Tu),E(Tu)), whereinFor all nodes in local double bounce topology subgraph, E (Tu) it is to constitute shortest path
All sides of tree, so as to acquire the shortest path of the arbitrary node up in local double bounce topology subgraph in subrange, and will
These sides recorded locally connected subgraph SuIn, i.e. E (Su)<=E (Tu)∪E(Su),<=represent assignment；
(4c) each node u in network is according to shortest path tree TuThe node conflicted with oneself is found, conflict section is constituted
Point set CNu, and according to CNuWithBuild conflict subgraph CSu=(V (CSu),E(CSu)), wherein V (CSu)=CNu,
(4d) conflict subgraph CS is judged according to maximum-flow algorithmuWhether it is the connection of k-1 points：
If so, then by CSuPut into conflict subgraph set { CSuIn；
Otherwise, in local double bounce topology subgraphMiddle structure k-1 points connection conflict subgraphOrderI.e.
WillPut into conflict subgraph set { CSuIn, build k-1 point connected subgraphs by following (4d1)-(4d2)：
(4d1) basisConflicting nodes set CNu, the neighbors x and node of addition conflicting nodes v connect to (v, x)
Side E (v, x) for connecing is arrivedIn, formedWhereinv∈CNu。
(4d2) judged according to maximum-flow algorithmWhether k-1 points are connected：If so, orderOtherwise, return
To step (4d1)；
(4e) judge whether k-1 >=2 set up：If so, then execution step (4f), otherwise, jumps to step (4m)；
(4f) i=2 is initialized, wherein i represents conflict subgraphIn i-th layer；
(4g) j=1 is initialized, wherein j represents conflict subgraph CSuIn j-th conflicting nodes；
(4h) makeWherein { CSu}jRepresent in conflict subgraph CSuJ-th node conflict subgraph,Represent the i-th -1 layer conflict subgraph；
(4i) for all of node In find corresponding conflicting nodes set CNuv, according to CNuv
WithBuild i-th layer of conflict subgraphWhereinSet of nodeSide collection
(4j) judged according to maximum-flow algorithmWhether it is a connection conflict subgraph k-i：
If so, then willIt is incorporated into conflict subgraph set { CSuIn；
Otherwise, k-i points connection conflict subgraph is builtOrderAnd willIt is incorporated into set { CSuIn, press
As follows (4j1)-(4j2) builds k-i point connected subgraphs：：
(4j1) basisConflicting nodes set CNuv, the neighbors x and node of addition conflicting nodes w connect to (w, x)
Side E (w, x) for connecing is arrivedIn, formedWhereinw∈CNuv。
(4j2) judged according to maximum-flow algorithmWhether it is the connection of k-1 points：If so, orderOtherwise, return
Return to step (4j1)；
(4k) judge whether j meets j=| { CSu}|：If so, execution step (4l), otherwise, j=j+1 jumps to step
(4h)；
(4l) judge whether i meets i=k-1：If so, execution step (4m), otherwise, i=i+1 jumps to step (4g)；
(4m) to gathering { CSuIn all conflict subgraphs using distributed two channel-connectivities algorithm DBCC build generate son
Tree Su=(V (Su),E(Su)), wherein V (Su) represent SuSet of node, E (Su) represent SuSide collection, comprise the following steps that：
(4m1) for set { CSuIn each conflict subgraphConstruction is locally generated accordingly subgraph T 'u=(V
(T′u),E(T′u))；
(4m2) update and be locally generated subgraph SuSide collection E (Su), i.e. E (Su)<=E (T 'u)∪E(Su), renewal is locally generated
Subgraph SuSide collection V (Su), i.e. V (Su)<=V (T 'u)∪V(Su), and by node V (T 'u) recorded logic conflict neighbours collection
LCNuvIn, i.e. LCNuv=V (T 'u), then node u flooding by way of LCNuvWith E (Su) topology information be sent to Su
In all nodes.
(4n) each node u is locally generated subgraph S according to what the topology information that other nodes are sent updated oneselfuAnd logic
Conflict neighbours collection LCNuv, subgraph S will be locally generateduOn a jump neighbors v as logic neighbors, and constitute logic neighbors
Collection：LCNu={ v ∈ V (Su)|(u,v)∈E(Su)}；
(4p) side collection information E (S)=E (S) ∪ E (S are updatedu), more new logic neighborhood information LCNu=V (Su), wherein E
(S) represent that all nodes generate total side collection for generating figure, LCN in networkuRepresent the logic neighbors set of node u；
By step (4c)-(4m), subgraph S is specifically locally generateduResult as shown in figure 5, wherein ground floor
Represent the k-1 points connection conflict subgraph of node uThe second layer is representedAny node v corresponding k-2 points connection punching
Prominent subgraphThird layer is representedThe corresponding k-2 points connection conflict subgraph of any node vAny node w
Corresponding k-3 points connection conflict subgraphLast layer represents that what is ultimately formed is locally generated subgraph Su。
The author such as dijkstra's algorithm reference Xinjun Wang is in IEEE VTC wherein described in above-mentioned steps (4b)
Article " the Bi-Channel-Connected Topology Control in Cognitive Radio delivered on 2014
Networks”；The maximum-flow algorithm adopted in above-mentioned steps (4d) judges to conflict subgraph whether in the connection of k-1 points and step (4j)
Using maximum-flow algorithm judge the subgraph whether k-i points connection that conflicts, make with reference to Shimon Even and R.Endre Tarjan etc.
" Network Flow and Testing Graph Connectivity " that person delivers.
Step 5, each node u determines the transmission power of oneself in network, will transmission power be adjusted to and can cover
Minimum power required for all logic neighbors：All logic neighbors of wherein u
Required minimum power, refers to the maximum of the transmission power of all logic neighbors of u, pu,vRepresent the logic neighbors of u
The transmission power of v；
Step 6, according to above-mentioned steps 4- step 5 topology control process, each node disjoint in network determines and oneself
Logic neighbors annexation, by the chain between all nodes and each node and the logic neighbors of oneself in network
Road combines, and constitutes final full mesh topology, i.e. G=(V (G), E (G)), wherein V (G) are all nodes in network, E (G)
=(u, v) | u ∈ V (G), v ∈ LCNu}.
Step 7, channel point is carried out using greedy coloring algorithm to each node u in the final full mesh topology that built
Match somebody with somebody.
(7a) node u maximum transmit powers PmaxOn a common control channel broadcast request distributes channel bag RAC, other
Node needs transfer bag again when this bag is received, until logic conflict neighbours collection LCNuIn all nodes all receive
Till RAC bags；
(7b) logic conflict neighbours collection LCNuIn node after RAC bags are received, check oneself the allocated channel, and
Feedback channels distribution bag AC give node u, the allocated channel of the node is contained in wherein channel distribution bag AC, if the section
Point is also unallocated, and bag AC is just designated as empty bag by channel；
(7c) node u collects all LCNuIn node feedback AC bags, and from also unappropriated channel select master
The minimum channel of CU probability, as the available channel of oneself.；
(7d) each node disjoint performs said process, till all nodes all distribute channel.
The effect of the present invention can be further illustrated by emulation：
(1) simulated conditions
In simulating scenes, network node is evenly distributed at random a 1000 × 1000m2Two dimensional surface region in.
The threshold value of received signal to noise ratio SNR is set to -80dBm, and path-loss factor α values are 4.All nodes are using identical in network
Maximum transmission power, wherein maximum transmission power Pmax=256mW, corresponding maximum transmitted radius Rmax=400m.Assume master
User influences whether all of user node.
(2) emulation content and result
Emulation 1, the topologies that the present invention is generated in the scene of 50 nodes are as shown in fig. 6, wherein
Fig. 6 (a) is peak power topology；
Fig. 6 (b) is the topology that the inventive method is generated, and numeral therein represents the channel of node distribution；
The topology of time user network when Fig. 6 (c) represents that primary user takes a channel；
The topology of time user network when Fig. 6 (d) represents that two primary users take two channels；
The topology of time user network when Fig. 6 (e) represents that three primary users take three channels；
By Fig. 6 (a)-(e) as can be seen that the topology that the inventive method is generated arbitrarily takes k-1 channel in primary user
When, the network of secondary user remains connection.
Emulation 2, is entered with peak power topology MaxPower with the inventive method to the different value of K of node average transmission radius
Row emulation, as a result as shown in Figure 7：
From fig.7, it can be seen that with network time user node number increase, the average transmission of peak power topology MaxPower
Radius keeps constant, is 400m, and the average transmission radius of the present invention is continuous with the increase of in network user node number
Reduce, and with the increase of k, average transmission radius is continuously increased, therefore the inventive method can be very good to reduce the energy of node
Consumption, increases the life cycle of network.
Emulation 3, is carried out with peak power topology MaxPower with the inventive method to the different value of K of required average channel number
Emulation, as a result as shown in Figure 8：
As seen from Figure 8, with network time user node number increase, the average channel of peak power topology MaxPower
Number is linear to be increased, and average channel number is less needed for the inventive method, and increasing with network user node number, averagely
The number of channel slowly increases, and with the increase of k, average channel number also slowly increases.
Emulation 4, is carried out with peak power topology MaxPower with the inventive method to the different value of K of required maximum channel number
Emulation, as a result as shown in Figure 9：
As seen from Figure 9, with network time user node number increase, peak power topology MaxPower's is maximum required
The number of channel linearly increases, and the number of channel needed for the inventive method is maximum is less, and increasing with network user node number,
The number of channel needed for maximum slowly increases, and with the increase of k, average channel number also slowly increases, and can draw from Fig. 8 and Fig. 9
The present invention not only greatlys save channel resource, and maintains the connectedness of network, so that network has good Shandong
Rod.
Claims (10)
1. the distributed topology approach of K channel-connectivities is built in cognition Ad Hoc networks, is comprised the steps：
(1) initialize network to connect for k points, k >=2, each node u obtains respectively the sequence of a jump and double bounce abutment points in network
Number and positional information；
(2) sequence number and positional information in step (1) sets up local double bounce topology subgraphAnd calculateIn any two
The individual node x for having an annexation, link energy consumption weight w between yp(x, y) and link range weight wd(x,y)；
(3) each node u builds and is locally generated subgraph S in networku：
(3a) initialize each node and be locally generated subgraph SuNode set V (Su) it is local double bounce topology subgraphIn institute
There is node, initialize each node and be locally generated subgraph SuLine set E (Su) it is empty set；
(3b) based on local double bounce topology subgraphEach node u is according to link energy consumption weight wp(x, y), builds with u as root,
The shortest path tree T of all nodes in local double bounce topology subgraphu=(V (Tu),E(Tu)), wherein
For all nodes in local double bounce topology subgraph, E (Tu) it is to constitute all sides of shortest path tree, and these sides recorded
It is locally generated the line set E (S of subgraphu) in, i.e. E (Su)<=E (Tu)∪E(Su)；
(3c) each node u in network is according to shortest path tree TuThe node conflicted with oneself is found, conflicting nodes set is constituted
CNu, and according to CNuWithBuild conflict subgraph CSu=(V (CSu),E(CSu)), wherein V (CSu)=CNu,
(3d) conflict subgraph CS is judgeduWhether it is the connection of k-1 points：If so, then by CSuPut into conflict subgraph set { CSuIn；
Otherwise, in local double bounce topology subgraphMiddle structure k-1 points connection conflict subgraphOrderWillPut
Enter to conflict subgraph set { CSuIn；
(3e) judge whether k-1 >=2 set up：If so, then execution step (3f), otherwise, jumps to step (3m)；
(3f) i=2 is initialized, wherein i represents conflict subgraphIn i-th layer；
(3g) j=1 is initialized, wherein j represents conflict subgraph CSuIn j-th conflicting nodes；
(3h) makeWherein { CSu}jRepresent in conflict subgraph CSuJ-th node conflict subgraph,Table
Show the i-th -1 layer conflict subgraph；
(3i) for all of node In find corresponding conflicting nodes set CNuv, according to CNuvWithBuild i-th layer of conflict subgraphWhereinSet of nodeSide collection
(3j) judgeWhether it is k-i points connection conflict subgraph：If so, then willIt is incorporated into conflict subgraph set { CSu}
In, otherwise, build k-i points connection conflict subgraphOrderAnd willIt is incorporated into set { CSuIn；
(3k) judge whether j meets j=| { CSu}|：If so, execution step (3l), otherwise, j=j+1 jumps to step (3h)；
(3l) judge whether i meets i=k-1：If so, execution step (3m), otherwise, i=i+1 jumps to step (3g)；
(3m) to gathering { CSuIn all conflict subgraphs using distributed two channel-connectivities algorithm DBCC build generate subtree Su
=(V (Su),E(Su)), wherein V (Su) represent SuSet of node, E (Su) represent SuSide collection；
(3n) each node u is locally generated subgraph S according to what the topology information that other nodes are sent updated oneselfuWith logic conflict
Neighbours collect LCNuv, subgraph S will be locally generateduOn a jump neighbors v as logic neighbors, and constitute logic neighbors collection：
LCNu={ v ∈ V (Su)|(u,v)∈E(Su)}；
(3p) side collection information E (S)=E (S) ∪ E (S are updatedu), more new logic neighborhood information LCNu=V (Su), wherein E (S) table
Show the side collection of the total generation figure of all nodes generations in network, LCNuRepresent the logic neighbors set of node u；
(4) each node u determines the transmission power of oneself in network, will transmission power be adjusted to and can cover all logics
Minimum power required for neighbors：
(5) link combinations between all nodes and each node and the logic neighbors of oneself in network are got up, is constituted
Final full mesh topology, i.e. G=(V (G), E (G)), wherein V (G) be network in all nodes, E (G)=(u, v) | u ∈ V
(G),v∈LCNu, wherein E (G) represents the side collection in network G；
(6) channel distribution is carried out to each node u in the final full mesh topology that built using greedy coloring algorithm.
2. the distributed topology approach of K channel-connectivities is built in cognitive Ad Hoc networks according to claim 1, wherein walking
Suddenly the sequence number and positional information of a jump and double bounce abutment points are obtained in (1) respectively, refers to that each node u is sent out with maximum in network
Penetrate power PmaxFirst node information HELLO- is broadcasted respectively to positioned at all nodes in oneself transmission radius
1 bag and Section Point information HELLO-2 bag, and the HELLO-1 bags and HELLO-2 bags of jump neighbors transmission are received, wherein should
HELLO-1 bags include the sequence number and positional information of u node, and containing u all one jump the sequence of neighbors in HELLO-2 bags
Number and positional information.
3. the distributed topology approach of K channel-connectivities is built in cognitive Ad Hoc networks according to claim 1, wherein walking
Suddenly local double bounce topology subgraph is set up in (2)Carry out as follows：
(2a) first node information HELLO-1 bags and Section Point information of each node u according to the jump neighbors for receiving
HELLO-2 bags, obtain and record the sequence number and positional information of the HELLO-1 bags and HELLO-2 bag interior joints, these neighbors
Constitute double bounce neighbors collectionWherein described HELLO-1 bags include the sequence number and positional information of u node, described
Containing u all one jump the sequence number and positional information of neighbors in HELLO-2 bags；
(2b) each node u calculates any two node according to the positional information of oneself and the positional information of double bounce neighbors
Minimum emissive power required for directly transmitting between x, yWherein,β is received signal to noise ratio thresholding
Value, determines according to the sensitivity of receiver and bit error rate requirement, and α is path-loss factor, dx,yIt is node x, it is European between y
Distance, if Px,yLess than the maximum transmission power P of nodemax, it is determined that node x, there is annexation between y；Otherwise, node x,
There is no annexation between y；
(2c) each node u sets up local double bounce topology subgraph according to the annexation between double bounce neighborsWherein local topology subgraphNode set beLocal topology subgraphLine set be:I.e. forIn any two nodeWhenWhen, side
4. the distributed topology approach of K channel-connectivities is built in cognitive Ad Hoc networks according to claim 1, wherein walking
Suddenly calculate in (2)Middle any two has the node x of annexation, link energy consumption weight w between yp(x, y), is according to office
Portion's double bounce topology subgraph, calculating any two in each node u has the node x of annexation, the link energy consumption weight between y：
wp(x, y)=Px,y, wherein,Px,yFor the node x that any two has annexation, directly transmit between y required
The minimum transmit power wanted.
5. the distributed topology approach of K channel-connectivities is built in cognitive Ad Hoc networks according to claim 1, wherein walking
Suddenly calculate in (2)Middle any two has the node x of annexation, link range weight w between yd(x, y), is according to Europe
Formula distance, any two has the distance between the node x of annexation, y weight in calculate node u：wd(x, y)=dx,y, its
In,dx,yIt is node x that any two has annexation, the Euclidean distance between y.
6. the distributed topology approach of K channel-connectivities is built in cognitive Ad Hoc networks according to claim 1, wherein walking
Suddenly the shortest path tree T in (3b)uBuilt using dijkstra's algorithm or bellman-ford algorithm.
7. the distributed topology approach of K channel-connectivities is built in cognitive Ad Hoc networks according to claim 1, wherein walking
Suddenly it is by FLSS that k-1 points connection conflict subgraph is built in (3d)kAlgorithm builds, and comprises the following steps that：
(3d1) basisConflicting nodes set CNu, the neighbors x and node for adding conflicting nodes v connected to (v, x)
Side E (v, x) is arrivedIn, formedWhereinv∈CNu。
(3d2) judgeWhether k-1 points are connected：If so, orderOtherwise, step (3d1) is returned to.
8. the distributed topology approach of K channel-connectivities is built in cognitive Ad Hoc networks according to claim 1, wherein walking
Suddenly it is by FLSS that k-i points connection conflict subgraph is built in (3j)kAlgorithm builds, and comprises the following steps that：
(3j1) basisConflicting nodes set CNuv, the neighbors x and node of addition conflicting nodes w are connected to (w, x)
Side E (w, x) arriveIn, formedWhereinw∈CNuv。
(3j2) judgeWhether k-i points are connected：If so, then makeOtherwise return to step (3j1).
9. the distributed topology approach of K channel-connectivities is built in cognitive Ad Hoc networks according to claim 1, wherein walking
Suddenly built using distributed two channel-connectivities algorithm DBCC in (3m) and generate subtree, carried out as follows：
(3m1) for set { CSuIn each conflict subgraphConstruction is locally generated accordingly subgraph T 'u=(V (T 'u),E
(T′u))；
(3m2) update and be locally generated subgraph SuSide collection E (Su), i.e. E (Su)<=E (T 'u)∪E(Su), renewal is locally generated subgraph
SuSide collection V (Su), i.e. V (Su)<=V (T 'u)∪V(Su), and by node V (T 'u) recorded logic conflict neighbours collection LCNuvIn,
That is LCNuv=V (T 'u), then node u flooding by way of LCNuvWith E (Su) topology information be sent to SuIn it is all
Node.
10. the distributed topology approach of K channel-connectivities is built in cognitive Ad Hoc networks according to claim 1, wherein
Greedy coloring algorithm carries out channel distribution to each node u in the final full mesh topology that built used in step (6), by such as
Lower step is carried out：
(6a) node u collects LCN to logic conflict neighboursuIn all nodes with maximum transmit power by way of flooding in public affairs
Send request distribution channel bag RAC in control channel altogether；
(6b) logic conflict neighbours collection LCNuIn node after RAC bags are received, with maximum transmit power by way of unicast handle
Feedback channels distribution bag AC issues node u, informs and has been chosen by channel；
(6c) node u collects all LCNuIn node feedback AC bags, and from also unappropriated channel select primary user account for
With the channel that probability is minimum, as the available channel of oneself.
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| CN107197425A (en) * | 2017-06-16 | 2017-09-22 | 韩冰青 | Isomery Energy-aware topology control method in wireless self-networking |
| CN107197425B (en) * | 2017-06-16 | 2019-08-06 | 韩冰青 | Isomery Energy-aware topology control method in wireless self-networking |
| CN109121098A (en) * | 2018-08-24 | 2019-01-01 | 京东方科技集团股份有限公司 | A kind of method and system for distributing channel |
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| CN110022562B (en) * | 2019-04-11 | 2022-04-01 | 池州学院 | Distributed channel allocation control method for mobile ad hoc network |
| CN111683413A (en) * | 2020-08-12 | 2020-09-18 | 成都极米科技股份有限公司 | Method, terminal, network access device and storage medium for establishing multilink connection |
| CN111683413B (en) * | 2020-08-12 | 2020-11-10 | 成都极米科技股份有限公司 | Method, terminal, network access device and storage medium for establishing multilink connection |
| CN112468996A (en) * | 2020-12-14 | 2021-03-09 | 华东交通大学 | Network topology control method in cognitive Internet of vehicles |
| CN112468996B (en) * | 2020-12-14 | 2022-07-26 | 华东交通大学 | Network topology control method in cognitive Internet of vehicles |
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