CN105979528B - A kind of Cognitive-Cooperation network association resource allocation methods based on efficiency optimization - Google Patents
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Abstract
A kind of Cognitive-Cooperation network association resource allocation methods based on efficiency optimization are claimed in the present invention.Specifically include: the master and slave user sharing frequency spectrum resource of cognitive radio networks carries out information transmission, and each primary user occupies corresponding authorized frequency bands and communicates, respectively from user in the case where not interfering primary user to communicate, using direct transferring or cooperation transmission mode is communicated.Resource management entity reception is respectively requested from customer service, and federated resource distribution and route selection algorithm are executed, and is source-destination node to the optimal routing of selection, and send power and subchannel for source/relay node distribution.The present invention can effectively realize that the optimization of cognition network efficiency and QoS of customer (Quality of Service, QoS) ensure.
Description
Technical field
The present invention relates to wireless communication technology fields, especially Cognitive-Cooperation network association resource allocation and Route Selection skill
Art.
Background technique
With the fast development of wireless communication technique, wireless device rapid proliferation, wireless network is in the economic development of the country
Increasingly important role is played, and has been penetrated into the every field of society.The rapid development of wireless technology is so that nothing
Gauze network shows the features such as high speed, broadband, isomerization, while also bringing a series of stern challenges, wherein the most
Urgent is continuous growth of the user to frequency spectrum resource demand, and the authorized frequency bands of existing static allocation is caused to be unable to satisfy use
Family communication requirement.But then, part has been distributed authorized frequency bands and has not been used sufficiently in some times or area,
Cause the availability of frequency spectrum low.To effectively improve frequency spectrum resource utilization rate, alleviate frequency spectrum resource scarcity problem, using dynamic spectrum
The cognitive radio technology of access mechanism receives significant attention in recent years.
Cognitive radio system uses the cognition wireless electric terminals based on software and radio technique, can dynamic sensing it is available
Frequency spectrum differentiates current network state, is planned according to these states, decision and response, not influencing, authorized user is (primary
Family) dynamic, intelligence access frequency spectrum carry out data transmission in the case of normal communication, so as to effectively realize sharing frequency spectrum resource, mention
High spectrum utilization alleviates the rare problem of frequency spectrum resource.
Relay cooperative communication technology can effectively improve network capacity and data transmission matter by the cooperative transmission between user
Amount, and reduce I terminal transmission power.Each user can be made in network in shared frequency spectrum using cooperative communication technology in cognition network
In the case where resource, network performance enhancing and the raising of the availability of frequency spectrum are realized.
Resource allocation methods design in existing cognitive radio system at present, such as document [Feng Zhiyong, Zhang Ping, He Chun, base
In the cognitive radio system and its resource allocation methods of relay cooperative transmission, 101895991 B of publication number CN, publication date
On November 6th, 2013] propose a kind of Cognitive-Cooperation system optimization frequency spectrum based on relay cooperative transmission, transmission rate allocation and in
After, path selection mechanism, to realize that system effective throughput maximizes and user QoS is ensured.
Document [A.A.El-Sherif, A.Mohamed, Joint Routing and Resource Allocation
for Delay Minimization in Cognitive Radio Based Mesh Networks,IEEE
Transactions on Wireless Communications, Vol.13, Issue.1, January 2013] in propose one
Kind of joint route and resource allocation methods, optimization design relay selection and power distribution strategies are to realize the poly- of data flow in network
End-to-end time delay is closed to minimize.
Existing research is mainly maximized using throughput of system or minimizing delay is optimization aim, does not consider user's energy consumption,
It is lower to may cause user's efficiency, for a large number of users, especially with the user of energy-sensitive terminal, business experience will be by
It seriously affects；In addition, existing research more considers Route Selection, subchannel distribution or power distribution in cognition network in isolation
Problem does not comprehensively consider multifactor combined optimization, cannot achieve overall performance of network optimization.
Summary of the invention
Present invention seek to address that the above problem of the prior art.Propose it is a kind of effectively realize the optimization of cognition network efficiency and
The Cognitive-Cooperation network association resource allocation methods based on efficiency optimization of QoS of customer guarantee.Technical solution of the present invention
It is as follows:
A kind of Cognitive-Cooperation network association resource allocation methods based on efficiency optimization comprising following steps:
Step 1: in Cognitive-Cooperation network, if source node will be communicated with its destination node, source node is sent first
Communication requirement is to resource management entity；
Step 2: after resource management entity receives the communication request of source node, determine that source node and destination node cover model
Candidate route set Ψ in enclosing obtains each candidate hop count and selects the least candidate routing of hop count, is stored in set Ψ0,
That is Ψ0The least candidate route set of hop count is indicated, with NminIndicate Ψ0Middle element number；
Step 3: if 1) Nmin=1, it is determined that candidate routing is optimal routing, and the resource based on efficiency Optimality Criteria
Allocation algorithm executes optimal power and sub-channel allocation scheme；
If 2) Nmin> 1, then each fewest number of hops candidate is routed and execute the resource allocation algorithm based on efficiency Optimality Criteria, really
The optimal power and subchannel distribution strategy of fixed each routing；Relatively more each routing can valid value, the optimal routing of selection efficiency and optimal road
It is complete according to optimization allocation strategy by corresponding power, the corresponding sub-channel allocation scheme of optimal routing as optimization allocation strategy
At Cognitive-Cooperation network association resource allocation.
Further, determination source described in step 2 and the candidate route set Ψ method in destination node coverage area
Are as follows: with R(i)Indicate the transmission rate of i-th routing, wherein i=1,2 ... Ntot, NtotFor the sum of all possible routings, Rl (i)Indicate i-th article routing l hop link transmission rate, l=1,2 ... L(i), thenEnable R(s,min)
Indicate the minimum transmission rate demand from user couple, then only when i-th routing meetsRl (i)≥R(s,min),
It is routed as candidate.
Further, the method for the least candidate routing of selection hop count described in step 2 are as follows: indicate Ψ in set with N
First prime number, then fewest number of hops routing is in all candidate routingsL(i)Indicate the hop count number of i-th routing
Candidate hop count is L by amountminRouting be stored in set Ψ0, use ψ(i)Indicate that i-th of candidate routing is in Ψ in Ψ0In, then have
Ψ0={ ψ(i)|L(i)=Lmin,ψ(i)∈Ψ,1≤i≤N}。
Further, the calculation method of the transmission rate of i-th routing are as follows: withIndicate that i-th article of routing l is jumped
The subchannel distribution variable of link, wherein 1≤k≤K, K indicate system sub-channels sum, ifIt indicates k-th
Subchannel distribution gives the l hop link of i-th article of routing, does not distribute thenWithIndicate i-th article of routing l hop link
Transmission rate when using k-th of subchannel, then Rl (i)It is represented byIfHaveAccording to shannon formula, haveWherein W is subchannel bandwidth,
WithRespectively indicate source/relaying cognitive user transimission power of i-th article of routing l hop link using k-th of subchannel when and
Channel gain, Pk (p)Indicate the transimission power of k-th of primary user,It indicates to jump chain from k-th of primary user to i-th article of routing l
Road destination uses link gain when k-th of subchannel, σ2Indicate channel noise power.
Further, it is specifically included described in step 3 based on the resource optimization algorithm of efficiency criterion: meeting optimization limit
Under conditions of system, optimize power and subchannel distribution as realization of goal to maximize link efficiency, with η(i)It indicates i-th most short
The efficiency of candidate's routing, can obtainWhereinThe efficiency of l hop link is routed for i-th article,WhereinIt indicates to obtain using the efficiency of i-th article of routing l hop link when subchannel kPcirFor i-th article of routing l hop link transmitting terminal circuit power loss；WithIt indicatesIt is optimal
Value,Indicate the optimal subchannel selection variable of i-th article of routing l hop link,Indicate i-th article of routing l hop link
Optimal power allocation variable, enableBased on link efficiency Optimality Criteria, can obtain
It enablesIt can obtainWhereinIndicate i-th article of routing l hop link
Optimal energy valid value, the then optimal efficiency that i-th fewest number of hops candidate routes areCompare all minimum
The maximum of hop count candidate routing can valid value η(i,*), determine that the maximum candidate routing of efficiency is optimal routing, i.e.,Wherein i*For the routing of efficiency maximum, power is corresponded to, sub-channel allocation scheme is optimized allocation of resources
Strategy.
Further, the optimization restrictive condition specifically includes:
1) cognitive user maximum transmission power limits:
2) primary user's minimum transmission rate limits:WhereinIndicate the most brief biography of k-th of primary user
Defeated rate requirement,The transmission rate for indicating k-th of primary user can be obtained according to shannon formula
WhereinIndicate the channel gain of k-th of primary user,It indicates from i-th article of routing l hop link source to primary user base station
Channel gain.Then cognitive user transimission power limits are as follows:
3) cognitive user limits minimum transmission rate: since i-th routing need to meet minimum transmission rate limitation R(i)≥
R(s,min), then the all-links of the routing are both needed to meet minimum transmission rate limitation:Then cognitive user transimission power limits:
4) subchannel distribution binary limits: subchannel distribution markIt is a binary variable, it may be assumed that
5) transmission end subchannel distribution limits: assuming that i-th article of routing l hop link at most distributes a sub-channels, it may be assumed that
It advantages of the present invention and has the beneficial effect that:
The present invention effectively realizes the cognition based on efficiency optimization of the optimization of cognition network efficiency and QoS of customer guarantee
Collaborative network federated resource distribution method.
Detailed description of the invention
Fig. 1 is that the present invention provides preferred embodiment Cognitive-Cooperation network system illustraton of model；
Fig. 2 is the Cognitive-Cooperation network association resource allocation optimized based on efficiency and route selection algorithm flow chart.
Specific embodiment
Below in conjunction with attached drawing, a preferred embodiment of the present invention will be described in detail.
Fig. 1 is Cognitive-Cooperation network system illustraton of model, as shown, there are multiple primary users and from the cognition wireless of user
In electric network, master and slave user sharing frequency spectrum resource carries out information transmission, and each primary user occupies corresponding authorized frequency bands and communicates,
Respectively from user in the case where not interfering primary user to communicate, using direct transferring or cooperation transmission mode is communicated.If source-mesh
Node communicated to quasi-, service request need to be sent to resource management entity, be executed by resource management entity and be based on efficiency
The joint route and resource allocation algorithm of Optimality Criteria are source-destination node to the optimal routing of selection, and are source/relay node
Distribution sends power and subchannel.
Fig. 2 is the algorithm flow of the Cognitive-Cooperation network association resource allocation and route selection method that are optimized based on efficiency
Figure, specifically includes:
Step 1: if cognition source node (abbreviation source node) is quasi- destination node (abbreviation destination node) is recognized with it is led to
Letter, then send communication requirement to resource management entity.
Step 2: resource management entity receives source node communication request, determines the time in source and destination node coverage area
Route set Ψ is selected, each candidate hop count is assessed and selects the least candidate routing of hop count, is stored in set Ψ0, with NminIt indicates
Ψ0Middle element number.
Determine the candidate route set Ψ method in source and destination node coverage area are as follows: with R(i)Indicate i-th routing
Transmission rate, wherein i=1,2 ... Ntot, NtotFor the sum of all possible routings, Rl (i)Indicate that the l of i-th article of routing jumps chain
The transmission rate on road, l=1,2 ... L(i), thenEnable R(s,min)Indicate the minimum transfer speed from user couple
Rate demand, then only when i-th routing meetsRl (i)≥R(s,min), just can be used as candidate routing.The transmission speed
Rate, withThe subchannel distribution variable of i-th article of routing l hop link is indicated, wherein 1≤k≤K, K indicate system sub-channels
Sum,Indicate the l hop link by k-th of subchannel distribution to i-th article of routing, otherwiseWithTable
Show transmission rate of i-th article of routing l hop link using k-th of subchannel when, then Rl (i)It is represented by
Restrictive condition can be obtained: ifHaveAccording to shannon formula, haveWherein W is subchannel bandwidth,WithIt respectively indicates i-th article of routing l and jumps chain
Road uses source/relaying cognitive user transimission power and channel gain when k-th of subchannel, Pk (p)Indicate k-th of primary user
Transimission power,When indicating to use k-th of subchannel from k-th of primary user to i-th article of routing l hop link destination
Link gain, σ2Indicate channel noise power.
The least candidate route computing method of hop count: indicating first prime number of Ψ in set with N, then in all candidate routings most
Few hop count, which routes, isL(i)Indicate the hop count quantity of i-th routing.It is L by candidate hop countminRoad
By being stored in set Ψ0, use ψ(i)Indicate that i-th of candidate routing is in Ψ in Ψ0In, then there is Ψ0={ ψ(i)|L(i)=Lmin,ψ(i)∈
Ψ,1≤i≤N}。
Step 3: according to NminValue executes federated resource distribution and route selection algorithm:
If 1) Nmin=1, it is determined that candidate routing is optimal routing, and is based on efficiency Optimality Criteria, executes optimal power
And sub-channel allocation scheme；
If 2) Nmin> 1, then each fewest number of hops candidate is routed and execute the resource allocation algorithm based on efficiency Optimality Criteria, really
The optimal power and subchannel distribution strategy of fixed each routing；Relatively each routing can valid value, select the optimal routing of corresponding efficiency and its
Power, sub-channel allocation scheme are joint route and resources configuration optimization strategy.
Resource optimization algorithm based on efficiency criterion, specifically includes: under conditions of meeting optimization limitation, to maximize chain
Road efficiency is that realization of goal optimizes power and subchannel distribution, with η(i)The efficiency for indicating i-th most short candidate routing, can obtainWhereinThe efficiency of l hop link is routed for i-th article,WhereinTable
Show using the efficiency of i-th article of routing l hop link when subchannel k, can obtainPcirFor i-th article of routing l
Hop link transmitting terminal circuit power loss.
Optimization restrictive condition specifically includes:
1) cognitive user maximum transmission power limits:
2) primary user's minimum transmission rate limits:WhereinIndicate the most brief biography of k-th of primary user
Defeated rate requirement,The transmission rate for indicating k-th of primary user can be obtained according to shannon formula
WhereinIndicate the channel gain of k-th of primary user,It indicates from i-th article of routing l hop link source to primary user base station
Channel gain.Then cognitive user transimission power limits are as follows:
3) cognitive user limits minimum transmission rate: since i-th routing need to meet minimum transmission rate limitation R(i)≥
R(s,min), then the all-links of the routing are both needed to meet minimum transmission rate limitation:Then cognitive user transimission power limits:
4) subchannel distribution binary limits: subchannel distribution markIt is a binary variable, it may be assumed that
5) transmission end subchannel distribution limits: assuming that i-th article of routing l hop link at most distributes a sub-channels, it may be assumed that
WithIt indicatesOptimal value,Indicate that the optimal subchannel selection of i-th article of routing l hop link becomes
Amount,Indicate the optimal power allocation variable of i-th article of routing l hop link.It enablesOptimized based on link efficiency quasi-
Then, it can obtainIt enablesIt can obtainWhereinIndicate the optimal energy valid value of i-th article of routing l hop link, then i-th fewest number of hops
Candidate routing optimal efficiency beComparing all the maximum of fewest number of hops candidate routing can valid value
η(i,*), determine that the maximum candidate routing of efficiency is optimal routing,Wherein i*It is routed for efficiency maximum,
It corresponds to power, sub-channel allocation scheme is optimized allocation of resources strategy.
The above embodiment is interpreted as being merely to illustrate the present invention rather than limit the scope of the invention.?
After the content for having read record of the invention, technical staff can be made various changes or modifications the present invention, these equivalent changes
Change and modification equally falls into the scope of the claims in the present invention.
Claims (4)
1. a kind of Cognitive-Cooperation network association resource allocation methods based on efficiency optimization, it is characterised in that: the following steps are included:
Step 1: in Cognitive-Cooperation network, if source node will be communicated with its destination node, source node sends communication first
Demand is to resource management entity；
Step 2: it after resource management entity receives the communication request of source node, determines in source node and destination node coverage area
Candidate route set Ψ, obtain each candidate hop count and simultaneously select the least candidate routing of hop count, be stored in set Ψ0, i.e. Ψ0
The least candidate route set of hop count is indicated, with NminIndicate Ψ0Middle element number；
Step 3: if Nmin=1, it is determined that candidate routing is optimal routing, and is calculated based on the resource allocation of efficiency Optimality Criteria
Method executes optimal power and sub-channel allocation scheme；If Nmin> 1, then it is excellent based on efficiency execution to be routed to each fewest number of hops candidate
The resource allocation algorithm for changing criterion, determines the optimal power and subchannel distribution strategy of each routing；Relatively more each routing energy valid value, choosing
The optimal routing of efficiency and the corresponding power of optimal routing, the corresponding sub-channel allocation scheme of optimal routing are selected as optimization distribution plan
Slightly, Cognitive-Cooperation network association resource allocation is completed according to optimization allocation strategy；
Based on the resource optimization algorithm of efficiency criterion described in step 3, specifically include: under conditions of meeting optimization limitation, with
Maximizing link efficiency is that realization of goal optimizes power and subchannel distribution, with η(i)Indicate the energy of i-th most short candidate routing
Effect, can obtainWhereinThe efficiency of l hop link is routed for i-th article,
Indicate the subchannel distribution variable of i-th article of routing l hop link, wherein 1≤k≤K, K indicate system sub-channels sum, whereinIt indicates to obtain using the efficiency of i-th article of routing l hop link when subchannel k Indicate i-th
Transmission rate of the l hop link using k-th of subchannel when is routed,Indicate that i-th article of routing l hop link uses k-th of son
Source/relaying cognitive user transimission power when channel, PcirFor i-th article of routing l hop link transmitting terminal circuit power loss；
WithIt indicatesOptimal value,Indicate the optimal subchannel selection variable of i-th article of routing l hop link,
The optimal power allocation variable for indicating i-th article of routing l hop link, enablesOptimized based on link efficiency quasi-
Then, it can obtainIt enablesIt can obtainWhereinIndicate the optimal energy valid value of i-th article of routing l hop link, then i-th fewest number of hops
Candidate routing optimal efficiency beComparing all the maximum of fewest number of hops candidate routing can valid value
η(i,*), determine that the maximum candidate routing of efficiency is optimal routing, i.e.,Wherein i*For efficiency most main road
By corresponding to power, sub-channel allocation scheme is optimized allocation of resources strategy；
The optimization restrictive condition specifically includes:
1) cognitive user maximum transmission power limits:Pl (i,max)Indicate that i-th article of routing l hop link uses kth
The maximum value of source/relaying cognitive user transimission power when sub-channels, 1≤l≤Lmin, 1≤k≤K；LminIndicate least
Hop count；
2) primary user's minimum transmission rate limits:WhereinIndicate the minimum transfer speed of k-th of primary user
Rate requirement,The transmission rate for indicating k-th of primary user can be obtained according to shannon formulaWhereinIndicate that the channel gain of k-th of primary user, W are subchannel bandwidth, σ2
Indicate channel noise power,Indicate the transimission power of k-th of primary user,It indicates from i-th article of routing l hop link source
Hold the channel gain of primary user base station；Then cognitive user transimission power limits are as follows:
3) cognitive user limits minimum transmission rate: since i-th routing need to meet minimum transmission rate limitation R(i)≥R(s ,min), R(i)Indicate the transmission rate of i-th routing, then the all-links of the routing are both needed to meet minimum transmission rate limitation:R(s,min)Indicate the minimum transmission rate demand from user couple；
Then cognitive user transimission power limits:
4) subchannel distribution binary limits: subchannel distribution markIt is a binary variable, it may be assumed that
5) transmission end subchannel distribution limits: assuming that i-th article of routing l hop link at most distributes a sub-channels, it may be assumed that
2. the Cognitive-Cooperation network association resource allocation methods according to claim 1 based on efficiency optimization, feature exist
In: determination source described in step 2 and the candidate route set Ψ method in destination node coverage area are as follows: with R(i)Indicate i-th
The transmission rate of item routing, wherein i=1,2 ... Ntot, NtotFor the sums of all possible routings,Indicate i-th routing
The transmission rate of l hop link, l=1,2 ... L(i), thenThen only when i-th routing meetsJust as candidate routing.
3. the Cognitive-Cooperation network association resource allocation methods according to claim 2 based on efficiency optimization, feature exist
In: the method for the least candidate routing of selection hop count described in step 2 are as follows: first prime number that Ψ in set is indicated with N then owns
Fewest number of hops, which routes, in candidate's routing isL(i)The hop count quantity for indicating i-th routing routes candidate
Hop count is LminRouting be stored in set Ψ0, use ψ(i)Indicate that i-th of candidate routing is in Ψ in Ψ0In, then there is Ψ0={ ψ(i)|L(i)
=Lmin,ψ(i)∈Ψ,1≤i≤N}。
4. the Cognitive-Cooperation network association resource allocation methods according to claim 2 based on efficiency optimization, feature exist
In: the calculation method of the transmission rate of i-th routing are as follows: withIndicate the subchannel point of i-th article of routing l hop link
With variable, wherein 1≤k≤K, K indicate system sub-channels sum, ifIt indicates k-th of subchannel distribution to i-th
Article routing l hop link, do not distribute thenWithIndicate that i-th article of routing l hop link uses k-th of subchannel
When transmission rate, thenIt is represented byIfHaveAccording to Shannon
Formula hasWherein W is subchannel bandwidth,WithRespectively indicate i-th routing
L hop link uses source/relaying cognitive user transimission power and channel gain when k-th of subchannel,It indicates k-th
The transimission power of primary user,It indicates from k-th of primary user to i-th article of routing l hop link destination using k-th of son letter
Link gain when road, σ2Indicate channel noise power.
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| CN107949056A (en) * | 2016-10-13 | 2018-04-20 | 中兴通讯股份有限公司 | A kind of channel resource allocation method and device |
| CN106656297A (en) * | 2016-10-14 | 2017-05-10 | 西安电子科技大学 | Cognitive orthogonal cooperative transmission method in the presence of primary user interference |
| CN106912059B (en) * | 2017-03-09 | 2020-01-17 | 重庆邮电大学 | Cognitive relay network joint relay selection and resource allocation method supporting mutual information accumulation |
| CN108271241B (en) * | 2017-12-12 | 2019-10-22 | 广东电网有限责任公司电力调度控制中心 | A kind of information rate access control optimization method and system based on resource allocation |
| CN108513334B (en) * | 2018-03-13 | 2021-11-16 | 重庆邮电大学 | Relay selection method applied to cognitive hybrid duplex network |
| CN113347727B (en) * | 2021-05-08 | 2022-04-15 | 华中科技大学 | Base station and wireless information and energy cooperative transmission system |
| CN115843081B (en) * | 2022-06-20 | 2024-06-28 | 西安电子科技大学 | Sidelink standard-oriented joint routing and resource allocation method |
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| CN101562861A (en) * | 2009-05-15 | 2009-10-21 | 重庆邮电大学 | Cross-layer and bi-directional routing method based on hop number and energy in wireless sensor network |
| CN102497641A (en) * | 2011-12-20 | 2012-06-13 | 山东大学 | Method for improving communication quality of wireless sensor network |
| CN103874162A (en) * | 2014-03-21 | 2014-06-18 | 徐州工业职业技术学院 | Downhole wireless sensor network on-demand routing algorithm |
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