CN105979528A - Cognitive cooperative network united resource allocation method based on energy efficiency optimization - Google Patents
Cognitive cooperative network united resource allocation method based on energy efficiency optimization Download PDFInfo
- Publication number
- CN105979528A CN105979528A CN201610465406.6A CN201610465406A CN105979528A CN 105979528 A CN105979528 A CN 105979528A CN 201610465406 A CN201610465406 A CN 201610465406A CN 105979528 A CN105979528 A CN 105979528A
- Authority
- CN
- China
- Prior art keywords
- route
- represent
- efficiency
- candidate
- cognitive
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/14—Spectrum sharing arrangements between different networks
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
- H04W40/08—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on transmission power
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/50—Allocation or scheduling criteria for wireless resources
- H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Quality & Reliability (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The invention discloses a cognitive cooperative network united resource allocation method based on energy efficiency optimization. Specifically, master and slave users in a cognitive radio network transmit information by sharing spectrum resources; each master user carries out communication by occupying a corresponding licensed band; each slave user carries out communication by use of a direct transmission or cooperative transmission mode under the condition of not interfering the communication of the master users; a resource management entity receives the service request of each slave user, performs a united resource allocation and route selection algorithm, selects optimum routes for source-destination node pairs and allocates sending powers and sub-channels to source/relay nodes. According to the method, the energy efficiency of the cognitive network can be optimized and the quality of service Qos of the users can be guaranteed.
Description
Technical field
The present invention relates to wireless communication technology field, particularly the distribution of Cognitive-Cooperation network association resource and Route Selection skill
Art.
Background technology
Along with the fast development of wireless communication technology, wireless device is popularized rapidly, and wireless network is in national economic development
Play the most important effect, and penetrated in the every field of society.Developing rapidly so that nothing of wireless technology
Gauze network presents the feature such as high speed, broadband, isomerization, also brings a series of stern challenge, the most simultaneously
Urgent is i.e. the user's continuous growth to frequency spectrum resource demand, causes the authorized frequency bands of existing static allocation cannot meet use
Family communication requirement.But then, part has been distributed authorized frequency bands and has the most fully been used in some times or area,
Cause the availability of frequency spectrum low.For being effectively improved frequency spectrum resource utilization rate, alleviate frequency spectrum resource scarcity problem, use dynamic spectrum
The cognitive radio technology of access mechanism receives significant attention in recent years.
Cognitive radio system uses cognition wireless electric terminals based on software and radio technique, it is possible to dynamic sensing can be used
Frequency spectrum, differentiates current network state, carries out planning according to these states, decision-making and response, and not affecting, authorized user is (primary
Family) in the case of proper communication dynamically, intelligence access frequency spectrum and carry out data transmission, thus can effectively realize sharing frequency spectrum resource, carry
High spectrum utilization, alleviates the problem that frequency spectrum resource is rare.
Relay cooperative communication technology, by the cooperative transmission between user, can be effectively improved network capacity and data transmission matter
Amount, and reduce I terminal transmission power.Cognition network use cooperative communication technology each user can be made in network at shared frequency spectrum
In the case of resource, it is achieved network performance strengthens and the raising of the availability of frequency spectrum.
Have the resource allocation methods design in cognitive radio system at present, such as document [Feng Zhiyong, Zhang Ping, He Chun, base
In cognitive radio system and the resource allocation methods thereof of relay cooperative transmission, publication number CN 101895991 B, 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
Continue, path selection mechanism, with realize system effective throughput maximize and user QoS ensure.
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] middle proposition one
Kind of joint route and resource allocation methods, optimize design relay selection and power distribution strategies to realize the poly-of data stream in network
Conjunction end-to-end time delay minimizes.
Existing research mainly maximizes with throughput of system or minimizing delay is as optimization aim, does not considers user's energy consumption,
User's efficiency may be caused relatively low, and for a large number of users, especially with the user of energy-sensitive terminal, business experience will be subject to
Have a strong impact on；It addition, existing research considers the distribution of the Route Selection in cognition network, subchannel or power distribution the most in isolation
Problem, does not considers multifactorial combined optimization, it is impossible to realize overall performance of network optimization.
Summary of the invention
Present invention seek to address that above problem of the prior art.Propose one effectively realize cognition network efficiency optimize and
The Cognitive-Cooperation network association resource allocation methods optimized based on efficiency that QoS of customer ensures.Technical scheme
As follows:
A kind of Cognitive-Cooperation network association resource allocation methods optimized based on efficiency, it comprises the following steps:
Step one: in Cognitive-Cooperation network, if source node to communicate with its destination node, first source node sends
Communication requirement is to resource management entity；
Step 2: after resource management entity receives the communication request of source node, determines that source node covers model with destination node
Candidate route set Ψ in enclosing, obtain each candidate's hop count and select jumping figure minimum candidate route, be stored in set Ψ0,
I.e. Ψ0Represent candidate's route set that jumping figure is minimum, with NminRepresent Ψ0Middle element number；
Step 3: 1) if Nmin=1, it is determined that this candidate route is optimum route, and resource based on efficiency Optimality Criteria
Allocation algorithm, performs optimal power and sub-channel allocation scheme；
2) if Nmin> 1, then each fewest number of hops candidate is route execution resource allocation algorithm based on efficiency Optimality Criteria, really
The optimal power of fixed each route and subchannel allocation strategy；Relatively more each route energy valid value, selects efficiency optimum route and optimum road
By corresponding power, the optimum sub-channel allocation scheme of correspondence that route as optimized distribution strategy, complete according to optimized distribution strategy
Become the distribution of Cognitive-Cooperation network association resource.
Further, the determination source described in step 2 and the candidate's route set Ψ method in destination node coverage
For: with R(i)Represent i-th transfer rate routeing, wherein i=1,2 ... Ntot, NtotFor the sum likely routeing, Rl (i)Represent the transfer rate of i-th article of l hop link routeing, l=1,2 ... L(i), thenMake R(s,min)
Represent the minimum transmission rate demand from user couple, the most only meet when i-th routeRl (i)≥R(s,min), just make
It route for candidate.
Further, the method that the candidate selecting jumping figure minimum described in step 2 route is: represent Ψ in set with N
Unit's prime number, in the most all candidates route, fewest number of hops route isL(i)Represent i-th jumping figure number routeing
Amount, is L by candidate's hop countminRoute be stored in set Ψ0, use ψ(i)Represent that in Ψ, i-th candidate route at Ψ0In, then have
Ψ0={ ψ(i)|L(i)=Lmin,ψ(i)∈Ψ,1≤i≤N}。
Further, the computational methods of the transfer rate of described i-th route are: withRepresent that i-th article of route l jumps
Subchannel distribution variable, the wherein 1≤k≤K of link, K represents system sub-channels sum, ifRepresent kth
Subchannel distributes to the l hop link of i-th article of route, does not distribute thenWithRepresent i-th article of route l hop link
Use transfer rate during kth subchannel, then Rl (i)It is represented byIfHaveAccording to shannon formula, haveWherein W is subchannel bandwidth,
WithRespectively represent i-th article route l hop link use kth subchannel time source/relaying cognitive user through-put power and
Channel gain, Pk (p)Represent the through-put power of kth primary user,Represent and jump chain from kth primary user to i-th article route l
Road destination uses link gain during kth subchannel, σ2Represent channel noise power.
Further, the resource optimization algorithm based on efficiency criterion described in step 3, specifically include: optimize limit satisfied
Under conditions of system, with maximize link efficiency for realization of goal optimize power and subchannel distribution, with η(i)Represent i-th the shortest
The efficiency of candidate's route, can obtainWhereinIt is the efficiency of i-th article of route l hop link,WhereinRepresent the efficiency of i-th article of route l hop link when using subchannel k, can obtainPcirIt is i-th article of route l hop link transmitting terminal circuit power loss；WithRepresentOptimal value,Represent that the optimum subchannel of i-th article of route l hop link selects variable,Represent the optimum of i-th article of route l hop link
Power distribution variable, orderBased on link efficiency Optimality Criteria, can obtain
OrderCan obtainWhereinRepresent i-th article of route l hop link
Optimum energy valid value, then the optimum efficiency of i-th fewest number of hops candidate route isAll minimum
Maximum energy valid value η of jumping figure candidate route(i,*), determine that candidate's route of efficiency maximum is optimum route, i.e.Wherein i*Routeing for efficiency maximum, its corresponding power, sub-channel allocation scheme are optimized allocation of resources
Strategy.
Further, described optimization restrictive condition specifically includes:
1) cognitive user maximum transmission power limits:
2) primary user's minimum transmission rate limits:WhereinRepresent the minimum transfer speed of kth primary user
Rate requirement,Represent the transfer rate of kth primary user, can obtain according to shannon formula
WhereinRepresent the channel gain of kth primary user,Represent from i-th article of route l hop link source to primary user base station
Channel gain.Then cognitive user through-put power is limited to:
3) minimum transmission rate is limited by cognitive user: limit R owing to i-th route need to meet minimum transmission rate(i)≥R(s ,min), then the all-links of this route is both needed to meet minimum transmission rate and limits:
Then cognitive user through-put power limits:
4) subchannel distribution binary limits: subchannel allocation identificationIt is a binary variable, it may be assumed that
5) transmission end subchannel assignment constraint: assume that i-th article of route l hop link at most distributes a sub-channels, it may be assumed that
Advantages of the present invention and having the beneficial effect that:
The present invention effectively realizes cognition network efficiency optimization and the cognition optimized based on efficiency of QoS of customer guarantee
Collaborative network federated resource distribution method.
Accompanying drawing explanation
Fig. 1 is that the present invention provides preferred embodiment Cognitive-Cooperation network system illustraton of model；
Fig. 2 is the distribution of Cognitive-Cooperation network association resource and route selection algorithm flow chart optimized based on efficiency.
Detailed description of the invention
Below in conjunction with accompanying drawing, the preferred embodiments of the present invention are described in detail.
Fig. 1 is Cognitive-Cooperation network system illustraton of model, as it can be seen, there is multiple primary user and the cognition wireless from user
In electric network, master and slave user's share spectrum resources carries out information transmission, and each primary user takies corresponding authorized frequency bands and communicates,
Respectively from user in the case of not disturbing primary user to communicate, employing direct transfers or cooperation transmission mode communicates.If source mesh
Node to intending communicating, service request need to be sent to resource management entity, resource management entity perform based on efficiency
The joint route of Optimality Criteria and resource allocation algorithm, for source destination node to selecting optimum route, and be source/via node
Distribution transmit power and subchannel.
Fig. 2 is the distribution of Cognitive-Cooperation network association resource and the algorithm flow of route selection method optimized based on efficiency
Figure, specifically includes:
Step one: if cognitive source node (abbreviation source node) intends leading to its cognitive destination node (abbreviation destination node)
Letter, then send communication requirement to resource management entity.
Step 2: resource management entity receives source node communication request, determines source and the time in destination node coverage
Select route set Ψ, assess each candidate's hop count and select jumping figure minimum candidate route, be stored in set Ψ0, with NminRepresent
Ψ0Middle element number.
Determine that source with the candidate's route set Ψ method in destination node coverage is: with R(i)Represent that i-th route
Transfer rate, wherein i=1,2 ... Ntot, NtotFor the sum likely routeing, Rl (i)Represent that i-th article of l routeing jumps chain
The transfer rate on road, l=1,2 ... L(i), thenMake R(s,min)Represent the minimum transfer speed from user couple
Rate demand, the most only meets when i-th routeRl (i)≥R(s,min), just can route as candidate.Described transmission speed
Rate, withRepresenting subchannel distribution variable, the wherein 1≤k≤K of i-th article of route l hop link, K represents that system sub-channels is total
Number,Represent the l hop link that kth subchannel is distributed to i-th article of route, otherwiseWithRepresent the
The i article of transfer rate routeing during l hop link use kth subchannel, then Rl (i)It is represented byCan limit
Condition processed: ifHaveAccording to shannon formula, haveWherein W
For subchannel bandwidth,WithRepresent that i-th article of route l hop link uses source/relaying during kth subchannel cognitive respectively
The through-put power of user and channel gain, Pk (p)Represent the through-put power of kth primary user,Represent from kth primary user to
Article i-th, link gain during route l hop link destination use kth subchannel, σ2Represent channel noise power.
Candidate's route computing method that jumping figure is minimum: represent first prime number of Ψ in set with N, in the most all candidates route
Few jumping figure route isL(i)Represent i-th the jumping figure quantity routeing.It is L by candidate's hop countminRoad
By being stored in set Ψ0, use ψ(i)Represent that in Ψ, i-th candidate route at Ψ0In, then there is Ψ0={ ψ(i)|L(i)=Lmin,ψ(i)∈
Ψ,1≤i≤N}。
Step 3: according to NminValue performs federated resource and distributes and route selection algorithm:
1) if Nmin=1, it is determined that this candidate route is optimum route, and based on efficiency Optimality Criteria, performs optimal power
And sub-channel allocation scheme；
2) if Nmin> 1, then each fewest number of hops candidate is route execution resource allocation algorithm based on efficiency Optimality Criteria, really
The optimal power of fixed each route and subchannel allocation strategy；Relatively each route can valid value, select corresponding efficiency optimum route and
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 satisfied optimization limits, to maximize chain
Road efficiency is that realization of goal optimizes power and subchannel distribution, with η(i)Represent the efficiency of i-th the shortest candidate route, can obtainWhereinIt is the efficiency of i-th article of route l hop link,WhereinTable
Show the efficiency of i-th article of route l hop link when using subchannel k, can obtainPcirIt is i-th article of route l
Hop link transmitting terminal circuit power loss.
Optimize restrictive condition to specifically include:
1) cognitive user maximum transmission power limits:
2) primary user's minimum transmission rate limits:WhereinRepresent the minimum transfer speed of kth primary user
Rate requirement,Represent the transfer rate of kth primary user, can obtain according to shannon formula
WhereinRepresent the channel gain of kth primary user,Represent the letter from i-th article of route l hop link source to primary user base station
Road gain.Then cognitive user through-put power is limited to:
3) minimum transmission rate is limited by cognitive user: limit R owing to i-th route need to meet minimum transmission rate(i)≥R(s ,min), then the all-links of this route is both needed to meet minimum transmission rate and limits:
Then cognitive user through-put power limits:
4) subchannel distribution binary limits: subchannel allocation identificationIt is a binary variable, it may be assumed that
5) transmission end subchannel assignment constraint: assume that i-th article of route l hop link at most distributes a sub-channels, it may be assumed that
WithRepresentOptimal value,Represent that the optimum subchannel of i-th article of route l hop link selects variable,Represent the optimal power allocation variable of i-th article of route l hop link.OrderBased on link efficiency Optimality Criteria, can obtainOrderCan obtain
WhereinRepresent the optimum energy valid value of i-th article of route l hop link, the then optimum efficiency of i-th fewest number of hops candidate route
ForRelatively maximum energy valid value η of all fewest number of hops candidates route(i,*), determine efficiency maximum
Candidate's route is optimum route,Wherein i*Routeing for efficiency maximum, its corresponding power, subchannel are divided
Formula case is optimized allocation of resources strategy.
The above embodiment is interpreted as being merely to illustrate the present invention rather than limiting the scope of the invention.?
After the content of the record having read the present invention, the present invention can be made various changes or modifications by technical staff, and these equivalences become
Change and modify and fall into the scope of the claims in the present invention equally.
Claims (6)
1. the Cognitive-Cooperation network association resource allocation methods optimized based on efficiency, it is characterised in that: comprise the following steps:
Step one: in Cognitive-Cooperation network, if source node to communicate with its destination node, first source node sends communication
Demand is to resource management entity；
Step 2: after resource management entity receives the communication request of source node, determines in source node and destination node coverage
Candidate route set Ψ, obtain each candidate's hop count and select jumping figure minimum candidate route, be stored in set Ψ0, i.e. Ψ0
Represent candidate's route set that jumping figure is minimum, with NminRepresent Ψ0Middle element number；
Step 3: 1) if Nmin=1, it is determined that this candidate route is optimum route, and resource based on efficiency Optimality Criteria distribution
Algorithm, performs optimal power and sub-channel allocation scheme；
2) if Nmin> 1, then each fewest number of hops candidate is route execution resource allocation algorithm based on efficiency Optimality Criteria, determines each
The optimal power of route and subchannel allocation strategy；Relatively more each route energy valid value, selects efficiency optimum route and optimum route right
The power answered, the optimum sub-channel allocation scheme of correspondence that route, as optimized distribution strategy, complete to recognize according to optimized distribution strategy
Know that collaborative network federated resource distributes.
The Cognitive-Cooperation network association resource allocation methods optimized based on efficiency the most according to claim 1, its feature exists
In: the determination source described in step 2 with the candidate's route set Ψ method in destination node coverage is: with R(i)Represent i-th
The transfer rate of bar route, wherein i=1,2 ... Ntot, NtotFor the sum likely routeing,Represent that i-th route
The transfer rate of l hop link, l=1,2 ... L(i), thenMake R(s,min)Represent from user couple
Little transmission rate requirements, the most only meets when i-th routeJust it route as candidate.
The Cognitive-Cooperation network association resource allocation methods optimized based on efficiency the most according to claim 2, its feature exists
In: the method that the candidate selecting jumping figure minimum described in step 2 route is: represents first prime number of Ψ in set with N, then owns
In candidate's route, fewest number of hops route isL(i)Represent i-th the jumping figure quantity routeing, candidate is route
Jumping figure is LminRoute be stored in set Ψ0, use ψ(i)Represent that in Ψ, i-th candidate route at Ψ0In, then there is Ψ0={ ψ(i)|L(i)
=Lmin,ψ(i)∈Ψ,1≤i≤N}。
The Cognitive-Cooperation network association resource allocation methods optimized based on efficiency the most according to claim 2, its feature exists
In: the computational methods of the transfer rate of described i-th route are: withRepresent that the subchannel of i-th article of route l hop link is divided
Distribution transforming amount, wherein 1≤k≤K, K represents system sub-channels sum, ifRepresent and kth subchannel is distributed to i-th
Article route l hop link, do not distribute thenWithRepresent that i-th article of route l hop link uses kth subchannel
Time transfer rate, thenIt is represented byIfHaveAccording to Shannon
Formula, hasWherein W is subchannel bandwidth,WithRepresent i-th route respectively
The through-put power of source/relaying cognitive user during l hop link use kth subchannel and channel gain,Represent kth
The through-put power of primary user,Represent and use kth letter from kth primary user to i-th article route l hop link destination
Link gain during road, σ2Represent channel noise power.
The Cognitive-Cooperation network association resource allocation methods optimized based on efficiency the most according to claim 1, its feature exists
In: the resource optimization algorithm based on efficiency criterion described in step 3, specifically include: under conditions of satisfied optimization limits, with
Maximizing link efficiency is that realization of goal optimizes power and subchannel distribution, with η(i)Represent the energy of i-th the shortest candidate route
Effect, can obtainWhereinIt is the efficiency of i-th article of route l hop link,WhereinRepresent the efficiency of i-th article of route l hop link when using subchannel k, can obtainPcirIt is i-th route
L hop link transmitting terminal circuit power loss；WithRepresentOptimal value,Represent i-th article of route l hop link
Optimum subchannel selects variable,Represent the optimal power allocation variable of i-th article of route l hop link, orderBased on
Link efficiency Optimality Criteria, can obtainOrder
Can obtainWhereinRepresent i-th article route l hop link optimum energy valid value, then i-th minimum
The optimum efficiency of jumping figure candidate route isThe relatively maximum efficiency of all fewest number of hops candidates route
Value η(i,*), determine that candidate's route of efficiency maximum is optimum route, i.e.Wherein i*Maximum for efficiency
Route, its corresponding power, sub-channel allocation scheme are optimized allocation of resources strategy.
The Cognitive-Cooperation network association resource allocation methods optimized based on efficiency the most according to claim 5, its feature exists
In: described optimization restrictive condition specifically includes:
1) cognitive user maximum transmission power limits:1≤l≤Lmin, 1≤k≤K；
2) primary user's minimum transmission rate limits:WhereinRepresent the minimum transmission rate of kth primary user
Requirement,Represent the transfer rate of kth primary user, can obtain according to shannon formula
WhereinRepresent the channel gain of kth primary user,Represent from i-th article of route l hop link source to primary user base station
Channel gain.Then cognitive user through-put power is limited to:1≤l≤Lmin, 1≤k
≤K；
3) minimum transmission rate is limited by cognitive user: limit R owing to i-th route need to meet minimum transmission rate(i)≥R(s ,min), then the all-links of this route is both needed to meet minimum transmission rate and limits:1≤l≤Lmin,
Then cognitive user through-put power limits:
4) subchannel distribution binary limits: subchannel allocation identificationIt is a binary variable, it may be assumed that1≤l≤
Lmin, 1≤k≤K；
5) transmission end subchannel assignment constraint: assume that i-th article of route l hop link at most distributes a sub-channels, it may be assumed that1≤l≤Lmin。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610465406.6A CN105979528B (en) | 2016-06-23 | 2016-06-23 | A kind of Cognitive-Cooperation network association resource allocation methods based on efficiency optimization |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610465406.6A CN105979528B (en) | 2016-06-23 | 2016-06-23 | A kind of Cognitive-Cooperation network association resource allocation methods based on efficiency optimization |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105979528A true CN105979528A (en) | 2016-09-28 |
| CN105979528B CN105979528B (en) | 2019-04-09 |
Family
ID=57019029
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610465406.6A Active CN105979528B (en) | 2016-06-23 | 2016-06-23 | A kind of Cognitive-Cooperation network association resource allocation methods based on efficiency optimization |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105979528B (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
| CN106912059A (en) * | 2017-03-09 | 2017-06-30 | 重庆邮电大学 | Support the cognitive junction network joint relay selection and resource allocation methods of mutual information accumulation |
| 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 |
| CN108271241A (en) * | 2017-12-12 | 2018-07-10 | 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 |
| CN108513334A (en) * | 2018-03-13 | 2018-09-07 | 重庆邮电大学 | A kind of relay selection method being applied to cognition mixing duplex network |
| CN113347727A (en) * | 2021-05-08 | 2021-09-03 | 华中科技大学 | Base station and wireless information and energy cooperative transmission system |
| CN115843081A (en) * | 2022-06-20 | 2023-03-24 | 西安电子科技大学 | Combined routing and resource allocation method facing Sidelink standard |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101364918A (en) * | 2008-09-25 | 2009-02-11 | 东南大学 | Efficiency reliable routing method based on link quality for multi-hop wireless sensor network |
| CN101364945A (en) * | 2008-10-06 | 2009-02-11 | 天津大学 | Method for realizing unicast energy-saving routing protocol based on cross-layer mechanism on Ad Hoc network |
| 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 |
-
2016
- 2016-06-23 CN CN201610465406.6A patent/CN105979528B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101364918A (en) * | 2008-09-25 | 2009-02-11 | 东南大学 | Efficiency reliable routing method based on link quality for multi-hop wireless sensor network |
| CN101364945A (en) * | 2008-10-06 | 2009-02-11 | 天津大学 | Method for realizing unicast energy-saving routing protocol based on cross-layer mechanism on Ad Hoc network |
| 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 |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
| CN106912059A (en) * | 2017-03-09 | 2017-06-30 | 重庆邮电大学 | Support the cognitive junction network joint relay selection and resource allocation methods of mutual information accumulation |
| 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 |
| CN108271241A (en) * | 2017-12-12 | 2018-07-10 | 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 |
| 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 |
| CN108513334A (en) * | 2018-03-13 | 2018-09-07 | 重庆邮电大学 | A kind of relay selection method being applied to cognition mixing duplex network |
| CN108513334B (en) * | 2018-03-13 | 2021-11-16 | 重庆邮电大学 | Relay selection method applied to cognitive hybrid duplex network |
| CN113347727A (en) * | 2021-05-08 | 2021-09-03 | 华中科技大学 | Base station and wireless information and energy cooperative transmission system |
| CN113347727B (en) * | 2021-05-08 | 2022-04-15 | 华中科技大学 | Base station and wireless information and energy cooperative transmission system |
| CN115843081A (en) * | 2022-06-20 | 2023-03-24 | 西安电子科技大学 | Combined routing and resource allocation method facing Sidelink standard |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105979528B (en) | 2019-04-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105979528A (en) | Cognitive cooperative network united resource allocation method based on energy efficiency optimization | |
| Wang et al. | Energy-efficient power allocation and Q-learning-based relay selection for relay-aided D2D communication | |
| Deng et al. | Cooperative channel allocation and scheduling in multi-interface wireless mesh networks | |
| CN105813129B (en) | A kind of resource allocation methods based on D2D sub-clustering | |
| CN103997740B (en) | Cognitive-Cooperation network association resource allocation methods based on optimization utility | |
| CN103607750A (en) | Relay selection method based on terminal straight-through communication in next-generation cellular system | |
| JP4976858B2 (en) | Resource allocation method and apparatus in relay-based cellular configuration | |
| CN102196587B (en) | Wireless-resource-dispatching method during multi-cell cooperation in relay-aided communication system | |
| Alzubir et al. | State of the art, channel assignment multi-radio multi-channel in wireless mesh network | |
| Raziah et al. | An adaptive best relay selection for energy efficient cooperative D2D communications | |
| CN106912059B (en) | Cognitive relay network joint relay selection and resource allocation method supporting mutual information accumulation | |
| Avallone et al. | A traffic-aware channel re-assignment algorithm for wireless mesh networks | |
| Kumbhkar et al. | Rate optimal design of a wireless backhaul network using TV white space | |
| Tang et al. | Dynamic resource allocation with threshold in OFDMA-based relay networks | |
| CN108055667B (en) | Cognitive vehicle network combined routing and resource allocation method | |
| Kompella et al. | Revisiting the optimal scheduling problem | |
| CN104066122A (en) | Congestion control and transmission scheduling method for cellular and D2D hybrid network | |
| Zhang et al. | End-to-end outage minimization in OFDM based linear relay networks | |
| CN110958304B (en) | Time division-oriented wireless energy-carrying transmission relay Internet of things low-power-consumption transmission method | |
| CN103298060A (en) | Relay node distribution method of content-centered wireless mesh network | |
| Xin et al. | Gateway selection scheme for throughput optimization in multi-radio multi-channel wireless mesh networks | |
| KR20120063744A (en) | Method and apparatus for distributed transmission power control in wireless networks | |
| Liu et al. | On the improvement of scaling laws for wireless ad hoc networks with physical layer caching | |
| Salameh et al. | Effective peer-to-peer routing in heterogeneous half-duplex and full-duplex multi-hop cognitive radio networks | |
| Le et al. | Joint rate control and resource allocation in OFDMA wireless mesh networks |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |