CN103179632A - Cross-layer routing method utilized in cognitive radio cellular network and based on energy optimization and network lifetime - Google Patents

Cross-layer routing method utilized in cognitive radio cellular network and based on energy optimization and network lifetime Download PDF

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CN103179632A
CN103179632A CN201310023802XA CN201310023802A CN103179632A CN 103179632 A CN103179632 A CN 103179632A CN 201310023802X A CN201310023802X A CN 201310023802XA CN 201310023802 A CN201310023802 A CN 201310023802A CN 103179632 A CN103179632 A CN 103179632A
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cognitive
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base station
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CN103179632B (en
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吴启晖
宋绯
张尧然
徐煜华
程云鹏
郑学强
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COMMUNICATION ENGINEERING COLLEGE SCIENCE & ENGINEEIRNG UNIV PLA
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention discloses a cross-layer routing method utilized in a cognitive radio cellular network and based on energy optimization and network lifetime, and relates to the cognitive radio field in wireless communication technology. The cross-layer routing method has the advantages that new routing metrics are provided specific to characteristics that various cognitive users in the cognitive radio cellular networks have different dynamic spectrum resources and energy of wireless cognitive nodes is limited, route selection and channel assignment in the cognitive network are considered in a combined manner by the aid of a cross-layer technology, a priority algorithm for the shortest path is modified, the problem that load on individual nodes is excessively high, energy is used up in advance and the individual nodes fail are solved, death time of each node is delayed, the lifetime of the network is prolonged, large quantities of relay nodes can be selected as cognitive nodes owing to large quantities of available effective nodes, accordingly, the average energy consumption is reduced integrally, and a communication access success rate is increased.

Description

In the cognitive radio cellular network network based on the cross-layer routing method of energy-optimised and network life
Technical field
The present invention relates to the cognition wireless electrical domain in wireless communication technology, is specifically a kind of in conjunction with the cross-layer technology, the link-state routing algorithm of application enhancements and new dynamic routing module, the new method of carrying out routing in cognitive radio networks.
Background technology
At present, along with improving constantly and the rapid growth of radio communication service kind wireless communication needs, people also are exponential increase to the demand of radio spectrum resources, and this makes " frequency spectrum deficient " problem in radio communication and the contradiction between existing fixed frequency spectrum allocative decision ineffective assignment.Cognitive radio technology is as a kind of emerging technology that is intended to improve spectrum utilization efficiency, authorized user (primary user can guaranteed, abbreviation PU) under the condition of service quality, allow cognitive user or secondary user's (secondaryuser, abbreviation SU) utilize the idle frequency range of authorized user in the mode of dynamic access, can effectively solve the effective ways of the problem of " frequency spectrum is deficient ", have important practical significance and wide application prospect.
In based on the cognitive radio cellular network network, by adopting multi-hop transmission, can significantly enlarge the coverage of single cognition network base station, but because the geographical position of PU is different with working frequency range, cause frequency spectrum resource that each SU can use can be in time, place and changing, thereby cognitive radio networks and general multi-channel wireless network are distinguished.This also makes us must consider the frequency spectrum resource isomerism of each SU when selecting the multi-hop relay node, should improve spectrum utilization efficiency, avoids again disturbing mutually between the interference of PU and SU.
In wireless network, the base station generally has stronger electric power support, but radio node mostly adopts powered battery, yet under current technical conditions, the energy that battery can provide is limited and valuable, in case the running down of battery of one or more nodes will cause the inefficacy of node, the decline of network performance, the inefficacy of even whole network.Therefore, how when communicating, the node resources such as reasonable distribution frequency spectrum, link, energy, thus when satisfying the telex network demand, lowering as much as possible energy consumption, prolong network lifetime is a problem demanding prompt solution.
In traditional network model, between each layer, function distinguishing is clear and definite, all information only flow between adjacent layer, but in cognitive radio, due to the variation of frequency spectrum resource and the use of dynamic access technology, when selecting route, the user's request that must unite power control, channel allocation and the top layer of considering bottom, this necessity of making use of momentum is broken the information flow obstacle between each layer, introduce rather popular in recent years cross-layer technology, the information of each layer is converged to come together to carry out complex optimum, just can obtain gratifying performance.
Summary of the invention
The objective of the invention is to propose a kind of cross-layer routing algorithm that is applied to the cognitive radio cellular network network, its objective is and will reduce the energy consumption of radio node under the prerequisite that satisfies the telex network rate requirement, prolong network lifetime improves network performance.
Technical scheme of the present invention is:
In a kind of cognitive radio cellular network network, based on the cross-layer routing method of energy-optimised and network life, it comprises: network status initialization, obtain the common signal channel collection C of each node ijStep; By calculating every energy consumption metric that can lead to link, choose the step of route that cognitive user nodes arrives the energy consumption minimum of cognitive base station; Carry out the step of channel allocation for each section link.
The present invention specifically comprises the following steps:
Step (1) network status initialization, complete following work:
1.1 each cognitive user i in network, i ∈ 1 ..., N} obtains the node status information of self, comprises geographical location information, available communication channel collection and current energy content of battery value, the maximum lifetime TTL=Hop of each Node configuration aforementioned nodes state information max, Hop maxBe the i.e. maximum hop count at the Zhongdao cognitive base of all nodes station of the max-forwards number of times of the information that arranges according to network size; Each node carries out broadcast transmission with the node status information of this node and the maximum lifetime TTL of this node status information on control channel;
After 1.2 each node is received and is not surpassed the node status information of maximum lifetime, be that the information hop count adds 1 with its life span, and forward this node status information, if the life span of the node status information of receiving has equaled maximum lifetime, directly abandon;
1.3 cognitive base station receives from the node status information of each node and storage, obtains phase mutual edge distance and the common signal channel collection that can be used to communicate by letter between each node, and builds network topological diagram; Wherein, the following public affairs of common signal channel centralized procurement between each node
Formula is calculated:
C ij=C i∩C j,i∈(1,...,N,B),j∈(1,...,N,B)
Wherein, C ijCommon signal channel collection between representation node i and node j, each channel wherein can both be used for direct communication by node i, j, is called link; I, j are nodal scheme, C iAnd C jThe available communication channel collection of difference representation node i and node j, N is that cognitive user is number of nodes, B represents cognitive base station;
During initialization, the routing table of cognitive base station is empty;
Arbitraryly in step (2) network want the cognitive user of access base station communication to initiate access request by control channel to the base station, request comprises data length L that needs send and the communications speed R of needs;
After user's access request was received in the cognitive base station of step (3), this user of iterative computation arrived the best route of cognitive base station, realized by carrying out following steps:
3.1 initiate the maximum transmission power of each node on communications speed R in request and network according to cognitive user, calculate the led to link of each node, if the power demand P that communicates by letter between any two node i, j ijSatisfy following formula, the link that forms between node i, j is for can lead to link;
P ij = ( 2 R W - 1 ) N 0 Wd ij &alpha; < P max , i &Element; ( 1 , . . . , N , B ) , j &Element; ( 1 , . . . N , B )
Wherein, W is communication channel bandwidth, the communications speed of R for needing, N 0Be known Background Noise Power spectrum density, d ijBe the phase mutual edge distance between each node that obtains in step 1.3 to the air line distance between node j for node i, α is the radio transmission fading coefficients,
Figure BDA00002763782800032
The expression radio signal is in the decline gain of free-space propagation;
If the power demand P that calculates ijLess than the node maximum power P that initiates requesting node max, think that link i → j can lead to link, one jumps and can reach;
3.2 measure as every in step 2.1 weights that can lead to link energy consumption metric COST with dynamic energy consumption ijAdopt following formula to calculate:
COST ij=P ij*T*(E max/(E i-P ij*T)),i∈(1,...,N,B),j∈(1,...,N,B)
Wherein, P ijBe the power demand of communication, T is once the transmission time of communication, T=L/R, and the data length of L for needing to send, R is communications speed; E maxBe energy content of battery maximum, Ei is the current energy content of battery value of node i;
3.3 take cognitive base station as source point, be the energy consumption tolerance initialize of each cognitive nodes: the energy consumption of the node i that wherein directly is connected with the base station is the COST of its direct link iB, its next-hop node NEXT i=B; All and cognitive base station do not have the node of direct link, and its energy consumption tolerance initial value that arrives cognitive base station is ∞;
3.4 standing in all, cognitive base directly is connected with own, perhaps by in the node that in routing table, other node relaying can arrive, and selection energy consumption metric COST ijMinimum node i adds in routing table entry, and upgrades the energy consumption metric of all node j that directly are connected with node i; Update method is, is ∞ if originally arrive the energy consumption tolerance of node j, and its energy consumption tolerance is set to COST j=COST i+ COST ij, its next-hop node NEXT j=i; Be not ∞ if originally arrive the energy consumption tolerance of node j, and COST i+ COST ij＜COST j, be set to COST j=COST i+ COST ij, its next-hop node is made as i, otherwise will not change;
If be added to routing table 3.5 initiate the cognitive user of access request, ending step 3; Otherwise, return to step 3.4;
Step (4) is according to the routing table that obtains in step 3, for the cognitive user of initiating access request provides access path, and be the suitable channel of each section link selection, route and channel selection result are returned to cognitive user by control channel, the method for the distribution of aforementioned suitable channel is:
4.1 with the channel number that each section link is concentrated according to common signal channel, namely the number of available channel sorts;
4.2 be at first the minimum link assignment channel of available channel, select a channel as communication channel at random in its all available channels, this channel is left out having the available channel of all links of public point to concentrate with this link simultaneously;
If obtain channel 4.3. all links all have been assigned with, continue step 4.4; Otherwise, return to step 4.1
4.4 cognitive base station returns to cognitive user by control channel with route and channel allocation result.
After step (5) was determined a route, cognitive base station was all allocated channels on this route, concentrated deletion from the available channel of the adjacent node of place both link ends node;
Step (6) routing update, complete following work:
6.1 cognitive user is to cognitive base station sending node state updating information.Cognitive user before each sign off, in the end in packet to cognitive base station sending node energy state lastest imformation; When perceiving self available channel collection and change, utilize control channel, to cognitive base station sending node available channel collection lastest imformation.
6.2 after the node usable spectrum state updating information or node energy lastest imformation that cognitive user sends received in cognitive base station, the state information of the respective nodes of updated stored was upgraded network topology according to step 1.3.
Step of the present invention (1) 1.1 in, each node by control channel, adopts the mode of CSMA to carry out broadcast transmission the maximum lifetime TTL of the node status information of this node and this node status information.
In step 3.1 of the present invention, α is the radio transmission fading coefficients, gets α=3 or α=4.
Beneficial effect of the present invention:
This algorithm of the present invention improves based on link-state routing algorithm, link-state routing algorithm claims again OSPF, it is based on the shortest-path first algorithm of Dijkstra, between each node, neighbours' Link State is led in exchange each other, each node is according to the Link State generating network topology of collecting, carry out operation independent in this locality, find the shortest path that leads to other node or network.This algorithm makes improvements, the topology that whole honeycomb is responsible for collecting in the cognitive base station powerful by computing capability, that energy is lasting, for each cognitive nodes of sending access request is distributed best route, configuration is simple, has fast convergence rate, the characteristics such as routing overhead is little can find source node to arrive the best route of cognitive base station fast.
The dynamic change that the present invention can conform.Routing table can in time be adjusted in cognitive base station when the cognitive user nodes state changes, can make in real time optimized route-frequency spectrum co-allocation.
The present invention has considered the variation of node frequency spectrum state, energy state in routing decision, can promote internodal justice when selecting the least energy route, has avoided reducing the situation that the heavy node of indivedual loads exhausts energy too early.
Routing algorithm implementation complexity of the present invention is low.The radio node of each finite energy does not need independent collecting network information, carries out Route Selection.And the base station unification lasting by energy, that computing capability is powerful is carried out, and has avoided the double counting of each node, and the local decision-making improper decision-making that may cause.
Routing update easy maintenance of the present invention, the update package load is little.This method only just sends the state update package to the base station when node state changes, and its energy state incidentally upgrades in the access communications bag, thereby has reduced routing overhead, has significantly reduced the transmission pressure of common signal channel.
Description of drawings
Fig. 1 is the algorithm flow chart of being suggested plans in the present invention.
Fig. 2 is instantiation artificial network model in the present invention.
Fig. 3 be suggest plans and shortest path and least energy route in the present invention energy consumption relatively.
Fig. 4 be suggest plans and shortest path and least energy route in the present invention the access success rate relatively.
Fig. 5 be suggest plans and shortest path and least energy route in the present invention network life relatively.
Embodiment
The present invention is further illustrated below in conjunction with drawings and Examples.
As shown in Figure 1, a kind of cross-layer routing method based on energy-optimised and network life provided by the invention, as shown in Figure 1 and Figure 2, embodiment is as follows:
The present invention is applied to network configuration as shown in Figure 2.Wherein cognitive base station provides access service for all cognitive user in the residential quarter.Each cognitive user accesses by the mode of single-hop or multi-hop.Cognitive base station and each cognitive user have a cognitive antenna and a traditional antenna.Cognitive antenna is used for cognitive user to the dynamic spectrum access communication of cognitive base station, traditional antenna uses a common signal channel, each user mode by CSMA on this common signal channel is transmitted, report node frequency spectrum state to cognitive base station, carry out route requests, cognitive base station is also assigned the decision-making of route frequency spectrum co-allocation by common signal channel to cognitive user.
The present invention adopts algorithm flow as shown in Figure 1.This algorithm flow mainly is comprised of following six steps:
Step (1) network status initialization;
Arbitraryly in step (2) network want the cognitive user of access base station communication to initiate access request by control channel to the base station, request comprises data length L that needs send and the communications speed R of needs;
After user's access request is received in the cognitive base station of step (3), calculate the best route that this user arrives cognitive base station;
Step (4) according to the routing table that obtains in step 3, for the cognitive user of initiating access request provides access path, and is the suitable channel of each section link selection, and route and channel selection result are returned to cognitive user by control channel;
After step (5) was determined a route, cognitive base station was all allocated channels on this route, concentrated deletion from the available channel of the adjacent node of place both link ends node;
Following work is completed in step (6) routing update.
Embodiment:A following description of specific embodiment of the present invention, the discrete event simulation network system that system emulation adopts the C language to build, setting parameter does not affect generality.In the present embodiment, within 49 cognitive nodes and 1 cognitive base station are randomly dispersed in the scope of 400m*400m, the maximum transmission power of each node is 1w, primary power is 10J, channel width W=1MHz, each node has random several available channels in whole 10 channels, Background Noise Power N at random 0=9.76*10 -11W/Hz, radio transmission fading coefficients α=3.In emulation, select at random a cognitive nodes each second, send the stream that length is 1Mbit to cognitive base station, the traffic rate demand is 1Mbit/s.Under this network scenarios, we have adopted respectively minimum hop count route, least energy route and us to propose new method for routing to carry out Route Selection.Simulation time is 500s.
In emulation, the coordinate of each node is respectively:
Table 1: all node coordinates
Node serial number Abscissa (m) Ordinate (m)
0 285 301
1 166 11
2 194 399
3 99 289
4 335 30
5 43 152
6 184 155
7 94 273
8 56 265
9 32 324
10 203 289
11 359 217
12 164 333
13 288 14
14 55 318
15 41 326
16 381 152
17 230 342
18 117 275
19 15 24
20 303 106
21 270 59
22 161 205
23 371 47
24 244 81
25 225 314
26 374 45
27 241 56
28 359 205
29 316 4
30 14 385
31 275 3
32 4 45
33 345 232
34 294 248
35 310 238
36 150 351
37 20 20
38 40 258
39 307 346
40 71 227
41 310 39
42 143 236
43 53 181
44 370 232
45 332 321
46 310 55
47 345 109
48 195 284
49 272 192
Wherein, being numbered 0 node is cognitive base station, and all the other are cognitive access node.The usable spectrum collection of each node is respectively:
Table 2: all node usable spectrum collection
Node serial number Abscissa (m)
0 1,2,3,4,7
1 0,1,2,3,4,6,7,9
2 1,2,4,6,7,8,9
3 0,2,5,7,8
4 0,1,2,4,6,7,9
5 1,2,3,4,7,8,9
6 0,1,2,3,5,6,7,8
7 0,2,4,6,7
8 2,3,4,6,7
9 2,4,7,8,9
10 0,1,3,4,7,8,9
11 0,7,9
12 0,3,5
13 0,1,4,5,6,8,9
14 1,2,4,6,7
15 1,2,3,5,7,8
16 3,4,7,9
17 1,6,7,9
18 0,3,5,6,7,8
19 1,7
20 1,2,5,6,8,9
21 0,1,3,4,5,6,7,8
22 0,4,5,8
23 0,1,3,5,6,8
24 3,4,5,6,7
25 0,2,3,4,5,7,9
26 0,5,6,7,8,9
27 2,3,4,7,8
28 0,1,2,3,4,5,6,7,8
29 5,9
30 0,3,5,7
31 0,1,2,4,5
32 1,3,6,8
33 4,6,8,9
34 0,1,3,4,5,9
35 0,1,4,6,7
36 1,2,4,5,8
37 0,1,3,5,6
38 4,5,8,9
39 0,8
40 0,2,3,4,6,8
41 0,1,2,4,5,8
42 0,1,2,6,9
43 1,2,3,5,6,8,9
44 0,1,3,4,7,8,9
45 2,4,6,7,8,9
46 3
47 0,1,2,3,5,6
48 3,6,7,9
49 2,6,7,8,9
Fig. 2 has provided the network topological diagram of this emulation case.
Fig. 3 has provided and has adopted three kinds of different method for routing, accesses the average energy loss-rate of session at every turn.
Fig. 4 has provided the success rate that adopts three kinds of different method for routing, all cognitive nodes to access cognitive base station and has compared.
Fig. 5 has provided and has adopted three kinds of different method for routing, passing in time, and the number of nodes that lost efficacy because of depleted of energy compares.
As can be seen from Figure 5, new method for routing, significantly postponed node because of the energy decline Post-dead duration, it is fair that this has not only promoted between node, also for follow-up route provides more trunk node selection, to such an extent as to although the each route of selecting of new method for routing is not the least energy route, as can see from Figure 3, it accesses the average energy consumption of session still less than the least energy method for routing at every turn in whole simulation process.Simultaneously as can see from Figure 4, because new method for routing makes more node life, make available via node relatively increase, thereby improved the access success rate of cognitive nodes.And in emulation, for the ease of several method for routing are compared, we only are chosen in emulation before at every turn, the node that does not all have to lose efficacy under three kinds of method for routing is as access node, there is obvious postponement the node failure time of considering new route, and it can more be better than other two kinds of methods for all nodes provide the practical capacity of access service.
The part that the present invention does not relate to all prior art that maybe can adopt same as the prior art is realized.

Claims (4)

  1. In a cognitive radio cellular network network based on the cross-layer routing method of energy-optimised and network life, it is characterized in that it comprises: network status initialization, obtain the common signal channel collection C of each node ijStep; By calculating every energy consumption metric that can lead to link, choose the step of route that cognitive user nodes arrives the energy consumption minimum of cognitive base station; Carry out the step of channel allocation for each section link.
  2. In cognitive radio cellular network network according to claim 1 based on the cross-layer routing method of energy-optimised and network life, it specifically comprises the following steps its feature:
    Step (1) network status initialization, complete following work:
    1.1 each cognitive user i in network, i ∈ 1 ..., N} obtains the node status information of self, comprises geographical location information, available communication channel collection and current energy content of battery value, the maximum lifetime TTL=Hop of each Node configuration aforementioned nodes state information max, Hop maxBe the i.e. maximum hop count at the Zhongdao cognitive base of all nodes station of the max-forwards number of times of the information that arranges according to network size; Each node carries out broadcast transmission with the node status information of this node and the maximum lifetime TTL of this node status information on control channel;
    After 1.2 each node is received and is not surpassed the node status information of maximum lifetime, be that the information hop count adds 1 with its life span, and forward this node status information, if the life span of the node status information of receiving has equaled maximum lifetime, directly abandon;
    1.3 cognitive base station receives from the node status information of each node and storage, obtains phase mutual edge distance and the common signal channel collection that can be used to communicate by letter between each node, and builds network topological diagram; Wherein, the common signal channel centralized procurement between each node is calculated with following formula:
    C ij=C i∩C j,i∈(1,...,N,B),j∈(1,...,N,B)
    Wherein, C ijCommon signal channel collection between representation node i and node j, each channel wherein can both be used for direct communication by node i, j, is called link; I, j are nodal scheme, C iAnd C jThe available communication channel collection of difference representation node i and node j, N is that cognitive user is number of nodes, B represents cognitive base station;
    During initialization, the routing table of cognitive base station is empty;
    Arbitraryly in step (2) network want the cognitive user of access base station communication to initiate access request by control channel to the base station, request comprises data length L that needs send and the communications speed R of needs;
    After user's access request was received in the cognitive base station of step (3), this user of iterative computation arrived the best route of cognitive base station, realized by carrying out following steps:
    3.1 initiate the maximum transmission power of each node on communications speed R in request and network according to cognitive user, calculate the led to link of each node, if the power demand P that communicates by letter between any two node i, j ijSatisfy following formula, the link that forms between node i, j is for can lead to link;
    P ij = ( 2 R W - 1 ) N 0 Wd ij &alpha; < P max , i &Element; ( 1 , . . . , N , B ) , j &Element; ( 1 , . . . N , B )
    Wherein, W is communication channel bandwidth, the communications speed of R for needing, N 0Be known Background Noise Power spectrum density, d ijBe the phase mutual edge distance between each node that obtains in step 1.3 to the air line distance between node j for node i, α is the radio transmission fading coefficients,
    Figure FDA00002763782700022
    The expression radio signal is in the decline gain of free-space propagation;
    If the power demand P that calculates ijLess than the node maximum power P that initiates requesting node max, think that link i → j can lead to link, one jumps and can reach;
    3.2 measure as every in step 2.1 weights that can lead to link energy consumption metric COST with dynamic energy consumption ijAdopt following formula to calculate:
    COST ij=P ij*T*(E max/(E i-P ij*T)),i∈(1,...,N,B),j∈(1,...,N,B)
    Wherein, P ijBe the power demand of communication, T is once the transmission time of communication, T=L/R, and the data length of L for needing to send, R is communications speed; E maxBe energy content of battery maximum, E iIt is the current energy content of battery value of node i;
    3.3 take cognitive base station as source point, be the energy consumption tolerance initialize of each cognitive nodes: the energy consumption of the node i that wherein directly is connected with the base station is the COST of its direct link iB, its next-hop node NEXT i=B; All and cognitive base station do not have the node of direct link, and its energy consumption tolerance initial value that arrives cognitive base station is ∞;
    3.4 standing in all, cognitive base directly is connected with own, perhaps by in the node that in routing table, other node relaying can arrive, and selection energy consumption metric COST ijMinimum node i adds in routing table entry, and upgrades the energy consumption metric of all node j that directly are connected with node i; Update method is, is ∞ if originally arrive the energy consumption tolerance of node j, and its energy consumption tolerance is set to COST j=COST i+ COST ij, its next-hop node NEXT j=i; Be not ∞ if originally arrive the energy consumption tolerance of node j, and COST i+ COST ij＜COST j, be set to COST j=COST i+ COST ij, its next-hop node is made as i, otherwise will not change;
    If be added to routing table 3.5 initiate the cognitive user of access request, ending step 3; Otherwise, return to step 3.4;
    Step (4) is according to the routing table that obtains in step 3, for the cognitive user of initiating access request provides access path, and be the suitable channel of each section link selection, route and channel selection result are returned to cognitive user by control channel, the method for the distribution of aforementioned suitable channel is:
    4.1 with the channel number that each section link is concentrated according to common signal channel, namely the number of available channel sorts;
    4.2 be at first the minimum link assignment channel of available channel, select a channel as communication channel at random in its all available channels, this channel is left out having the available channel of all links of public point to concentrate with this link simultaneously;
    If obtain channel 4.3. all links all have been assigned with, continue step 4.4; Otherwise, return to step 4.1
    4.4 cognitive base station returns to cognitive user by control channel with route and channel allocation result.
    After step (5) was determined a route, cognitive base station was all allocated channels on this route, concentrated deletion from the available channel of the adjacent node of place both link ends node;
    Step (6) routing update, complete following work:
    6.1 cognitive user is to cognitive base station sending node state updating information.Cognitive user before each sign off, in the end in packet to cognitive base station sending node energy state lastest imformation; When perceiving self available channel collection and change, utilize control channel, to cognitive base station sending node available channel collection lastest imformation.
    6.2 after the node usable spectrum state updating information or node energy lastest imformation that cognitive user sends received in cognitive base station, the state information of the respective nodes of updated stored was upgraded network topology according to step 1.3.
  3. In cognitive radio cellular network network according to claim 2 based on the cross-layer routing method of energy-optimised and network life, it is characterized in that described step (1) 1.1 in, each node passes through control channel with the node status information of this node and the maximum lifetime TTL of this node status information, adopts the mode of CSMA to carry out broadcast transmission.
  4. In cognitive radio cellular network network according to claim 2 based on the cross-layer routing method of energy-optimised and network life, it is characterized in that in described step 3.1, α is the radio transmission fading coefficients, gets α=3 or α=4.
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CN105376153A (en) * 2015-09-14 2016-03-02 江西师范大学 Energy saving-oriented SACK path selection mechanism ecSACK
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