Improved Utility-Based Cooperative CognitiveRadio Networks
by Team10Haobing Wang
Ren MaoFei YeLi Li
June 9, 2009
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
CRNCCRN
Part I
Introduction
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
CRNCCRN
Cognitive Radio Network
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
CRNCCRN
Cognitive Radio Network
In Cognitive Radio Network, two kinds of users exists:
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
CRNCCRN
Cognitive Radio Network
In Cognitive Radio Network, two kinds of users exists:
Primary Users(PU): PU has a higher priority to access thechannel, and they have the right to improve their ownperformance.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
CRNCCRN
Cognitive Radio Network
In Cognitive Radio Network, two kinds of users exists:
Primary Users(PU): PU has a higher priority to access thechannel, and they have the right to improve their ownperformance.
Secondary Users(SU): SU has no license to access theband, so they should pay to the PU for proportional accesstime.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
CRNCCRN
Cognitive Radio Network
In Cognitive Radio Network, two kinds of users exists:
Primary Users(PU): PU has a higher priority to access thechannel, and they have the right to improve their ownperformance.
Secondary Users(SU): SU has no license to access theband, so they should pay to the PU for proportional accesstime.
Problem: In previous research, there is no inter-cooperationbetween PU and SUs. So we wonder if we introduce acooperative pattern, the performance of the whole networkmay be improved.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
CRNCCRN
Cooperative Cognitive Radio Network
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
CRNCCRN
Cooperative Cognitive Radio Network
Cooperative Pattern:
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
CRNCCRN
Cooperative Cognitive Radio Network
Cooperative Pattern:
Leveraging SUs as the cooperative relays for the PU’stransmission, the rate can be dramatically increased.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
CRNCCRN
Cooperative Cognitive Radio Network
Cooperative Pattern:
Leveraging SUs as the cooperative relays for the PU’stransmission, the rate can be dramatically increased.
Similarly, PU can serve as SU’s relay, which can improvethe rate of SU’s transmission.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
CRNCCRN
Cooperative Cognitive Radio Network
Cooperative Pattern:
Leveraging SUs as the cooperative relays for the PU’stransmission, the rate can be dramatically increased.
Similarly, PU can serve as SU’s relay, which can improvethe rate of SU’s transmission.
If we can select a subset of the SUs as relays properly, PU’sdata can be transferred in a shorter interval of time, whichcorrespondingly lead to more spare time for SU’s datatransferring, and also PU may get more pay from the SUs. So,we can see that it is a win-win situation.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Part II
Model
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
System Model
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
System Model
In our system Model, a slot is separated into three parts:
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
System Model
In our system Model, a slot is separated into three parts:
Step 1: In the first (αβ) fraction of slot, PU trasmit data toselected SUs.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
System Model
In our system Model, a slot is separated into three parts:
Step 1: In the first (αβ) fraction of slot, PU trasmit data toselected SUs.
Step 2: In the second (α(1 − β)) fraction of slot, both PUand SUs transmit data cooperatively.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
System Model
In our system Model, a slot is separated into three parts:
Step 1: In the first (αβ) fraction of slot, PU trasmit data toselected SUs.
Step 2: In the second (α(1 − β)) fraction of slot, both PUand SUs transmit data cooperatively.
Step 3: In the third (1 − α) fraction of slot, each SUi isprovided an interval of time for transmitting with respect toits payment ci . And for each SUi, PU is used as a relayand the fraction of time for PU is γi .
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
System Model
In our system Model, a slot is separated into three parts:
Step 1: In the first (αβ) fraction of slot, PU trasmit data toselected SUs.
Step 2: In the second (α(1 − β)) fraction of slot, both PUand SUs transmit data cooperatively.
Step 3: In the third (1 − α) fraction of slot, each SUi isprovided an interval of time for transmitting with respect toits payment ci . And for each SUi, PU is used as a relayand the fraction of time for PU is γi .
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Transmission Rate
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Transmission Rate
We calculate several transmission rate in all three steps:Step 1:
RPTST (S) = log2 (1 +mini∈S |hPTST ,i |2Pp
No) (1)
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Transmission Rate
We calculate several transmission rate in all three steps:Step 1:
RPTST (S) = log2 (1 +mini∈S |hPTST ,i |2Pp
No) (1)
Step 2:
RPSPR(S) = log2 (1 +|hp|2Pp
No+
∑
i∈S
|hSTPR,i |2Ps
No) (2)
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Transmission Rate
We calculate several transmission rate in all three steps:Step 1:
RPTST (S) = log2 (1 +mini∈S |hPTST ,i |2Pp
No) (1)
Step 2:
RPSPR(S) = log2 (1 +|hp|2Pp
No+
∑
i∈S
|hSTPR,i |2Ps
No) (2)
Step 3:
RSTPT ,i(S) = log2 (1 +|hSTPT ,i |2Pp
No) (3)
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Transmission Rate
We calculate several transmission rate in all three steps:Step 1:
RPTST (S) = log2 (1 +mini∈S |hPTST ,i |2Pp
No) (1)
Step 2:
RPSPR(S) = log2 (1 +|hp|2Pp
No+
∑
i∈S
|hSTPR,i |2Ps
No) (2)
Step 3:
RSTPT ,i(S) = log2 (1 +|hSTPT ,i |2Pp
No) (3)
RSPSR,i(S) = log2 (1 +|hPTSR,i |2Pp
No+
|hSTSR,i |2Ps
No) (4)
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Transmission Rate
We calculate several transmission rate in all three steps:Step 1:
RPTST (S) = log2 (1 +mini∈S |hPTST ,i |2Pp
No) (1)
Step 2:
RPSPR(S) = log2 (1 +|hp|2Pp
No+
∑
i∈S
|hSTPR,i |2Ps
No) (2)
Step 3:
RSTPT ,i(S) = log2 (1 +|hSTPT ,i |2Pp
No) (3)
RSPSR,i(S) = log2 (1 +|hPTSR,i |2Pp
No+
|hSTSR,i |2Ps
No) (4)
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Transmission Rate
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Transmission Rate
Note: S is the set of chosen relay SUs.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Transmission Rate
Note: S is the set of chosen relay SUs.Thus, for PU,
RP(α, β, S) = min (αβRPTST (S), α(1 − β)RPSPR(S)) (5)
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Transmission Rate
Note: S is the set of chosen relay SUs.Thus, for PU,
RP(α, β, S) = min (αβRPTST (S), α(1 − β)RPSPR(S)) (5)
For SUi,
Ri = min ((1 − α)γiRSTPT ,i(S), (1 − α)(1 − γi)RSPSR,i(S)) (6)
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Transmission Rate
Note: S is the set of chosen relay SUs.Thus, for PU,
RP(α, β, S) = min (αβRPTST (S), α(1 − β)RPSPR(S)) (5)
For SUi,
Ri = min ((1 − α)γiRSTPT ,i(S), (1 − α)(1 − γi)RSPSR,i(S)) (6)
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Utility Function
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Utility Function
The utility function of PU is
UP = wPUR(RP(α, β, S)) +∑
i∈S
ci (7)
where wP is a predefined equiavalent revenue per unit data rateutility contributes to the overall utility and
UR(RP(α, β, S)) =1
1 + e−a(RP(α,β,S)−Ro)(8)
a measure of PU’s degree of satisfaction and Ro is PU’s trafficrequirement.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Utility Function
The utility function of PU is
UP = wPUR(RP(α, β, S)) +∑
i∈S
ci (7)
where wP is a predefined equiavalent revenue per unit data rateutility contributes to the overall utility and
UR(RP(α, β, S)) =1
1 + e−a(RP(α,β,S)−Ro)(8)
a measure of PU’s degree of satisfaction and Ro is PU’s trafficrequirement.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Utility Function
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Utility Function
The utility function of SU is
ui = wsRi(|hSTPR,i |2Ps
∑
i∈S |hSTPR,i |2Pswx +
ci∑
i∈S ci) · 1
1 + wx− ci (9)
where ws is the equivalent revenue per unit transmission ratecontributes to the overall utility and wx is the weighted constantbetween price and transmission contribution.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Utility Function
The utility function of SU is
ui = wsRi(|hSTPR,i |2Ps
∑
i∈S |hSTPR,i |2Pswx +
ci∑
i∈S ci) · 1
1 + wx− ci (9)
where ws is the equivalent revenue per unit transmission ratecontributes to the overall utility and wx is the weighted constantbetween price and transmission contribution.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Implementation Protocol
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Implementation Protocol
1 PU collects the information of all existing channels.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Implementation Protocol
1 PU collects the information of all existing channels.2 By predicting the performance of SUs and in purpose of
maximizing its own utility, PU make a decision of α, β andthe set of SUs for relaying.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Implementation Protocol
1 PU collects the information of all existing channels.2 By predicting the performance of SUs and in purpose of
maximizing its own utility, PU make a decision of α, β andthe set of SUs for relaying.
3 Depending on the strategies PU sets, the chosen SUsmake a decision of ci and γi to maximize its utility.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Implementation Protocol
1 PU collects the information of all existing channels.2 By predicting the performance of SUs and in purpose of
maximizing its own utility, PU make a decision of α, β andthe set of SUs for relaying.
3 Depending on the strategies PU sets, the chosen SUsmake a decision of ci and γi to maximize its utility.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
SU’s Strategy Selection Game
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
SU’s Strategy Selection Game
It can be inferred from the definition of SU’s utility function thatui is an increasing function of Ri .
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
SU’s Strategy Selection Game
It can be inferred from the definition of SU’s utility function thatui is an increasing function of Ri .Moreover, Ri is the minimum of (1 − α)γiRSTPT ,i and(1 − α)(1 − γi)RSPSR,i , one of which is an increasing function ofγi and another is a decreasing function of γi , so RS,i canachieve its maximization when
(1 − α)γi RSTPT ,i = (1 − α)(1 − γi)RSPSR,i (10)
.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
SU’s Strategy Selection Game
It can be inferred from the definition of SU’s utility function thatui is an increasing function of Ri .Moreover, Ri is the minimum of (1 − α)γiRSTPT ,i and(1 − α)(1 − γi)RSPSR,i , one of which is an increasing function ofγi and another is a decreasing function of γi , so RS,i canachieve its maximization when
(1 − α)γi RSTPT ,i = (1 − α)(1 − γi)RSPSR,i (10)
.Then we have
γ∗i =
RSPSR,i
RSPSR,i + RSTPT ,i(11)
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
SU’s Strategy Selection Game
It can be inferred from the definition of SU’s utility function thatui is an increasing function of Ri .Moreover, Ri is the minimum of (1 − α)γiRSTPT ,i and(1 − α)(1 − γi)RSPSR,i , one of which is an increasing function ofγi and another is a decreasing function of γi , so RS,i canachieve its maximization when
(1 − α)γi RSTPT ,i = (1 − α)(1 − γi)RSPSR,i (10)
.Then we have
γ∗i =
RSPSR,i
RSPSR,i + RSTPT ,i(11)
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
SU’s Strategy Selection Game
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
SU’s Strategy Selection Game
For ci ,
∂ui
∂ci=
wsbRi∑j 6=i
j∈S cj
(∑
j∈S cj)2 (12)
where b denotes 11+wx
.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
SU’s Strategy Selection Game
For ci ,
∂ui
∂ci=
wsbRi∑j 6=i
j∈S cj
(∑
j∈S cj)2 (12)
where b denotes 11+wx
.And
∂2ui
∂2ci= −
2wsbRi∑j 6=i
j∈S cj∑
j∈S cj
3
< 0 (13)
which indicates that the first order is an decreasing function ofci .
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
SU’s Strategy Selection Game
For ci ,
∂ui
∂ci=
wsbRi∑j 6=i
j∈S cj
(∑
j∈S cj)2 (12)
where b denotes 11+wx
.And
∂2ui
∂2ci= −
2wsbRi∑j 6=i
j∈S cj∑
j∈S cj
3
< 0 (13)
which indicates that the first order is an decreasing function ofci .
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
SU’s Strategy Selection Game
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
SU’s Strategy Selection Game
So, if we let ∂ui∂ci
= 0, and suppose k SUs are chosen, we canget the optimal
c∗i = wsb(k − 1)(
∑
j∈S
1Rj
− k − 1Ri
)/(∑
j∈S
1Rj
)2 (14)
under conditionsj 6=i∑
j∈S
cj < bwsRi (15)
and√
bwsRisumj 6=ij∈Scj − sumj 6=i
j∈Scj < c̄ (16)
where
c̄ > wsb(k − 1)(∑
j∈S
1Rj
− k − 1maxi∈S Ri
)/(∑
j∈S
1Rj
)2 (17)
.by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
SU’s Strategy Selection Game
So, if we let ∂ui∂ci
= 0, and suppose k SUs are chosen, we canget the optimal
c∗i = wsb(k − 1)(
∑
j∈S
1Rj
− k − 1Ri
)/(∑
j∈S
1Rj
)2 (14)
under conditionsj 6=i∑
j∈S
cj < bwsRi (15)
and√
bwsRisumj 6=ij∈Scj − sumj 6=i
j∈Scj < c̄ (16)
where
c̄ > wsb(k − 1)(∑
j∈S
1Rj
− k − 1maxi∈S Ri
)/(∑
j∈S
1Rj
)2 (17)
.by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Maximizing PU’s Utility
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Maximizing PU’s Utility
By substituting the value of c∗i into the function of PU’s utility,
we can get
UP =wP
1 + e−a(RP(α,β,S)−Ro)+
bws(k − 1)∑
i∈S1Ri
(18)
.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Maximizing PU’s Utility
By substituting the value of c∗i into the function of PU’s utility,
we can get
UP =wP
1 + e−a(RP(α,β,S)−Ro)+
bws(k − 1)∑
i∈S1Ri
(18)
.UP is an increasing function of RP(α, β, S), and similar to themethod of finding γ∗
i and c∗i , we can get that
β∗ =RPSPR(S)
RPSPR(S) + RPTST (S)(19)
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Maximizing PU’s Utility
By substituting the value of c∗i into the function of PU’s utility,
we can get
UP =wP
1 + e−a(RP(α,β,S)−Ro)+
bws(k − 1)∑
i∈S1Ri
(18)
.UP is an increasing function of RP(α, β, S), and similar to themethod of finding γ∗
i and c∗i , we can get that
β∗ =RPSPR(S)
RPSPR(S) + RPTST (S)(19)
α∗ = [aRo − ln (A − 2B +
√A2 − 4AB
2B)]/A (20)
where A = awpRSTPT ,i(S)RSPSR,i (S)/(RSTPT ,i(S) + RSPSR,i(S))
and B = bws(k − 1)/∑
( 1RSTPT ,i (S) + 1
RSPSR,i (S)), and B should be
less than A/4.by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Maximizing PU’s Utility
By substituting the value of c∗i into the function of PU’s utility,
we can get
UP =wP
1 + e−a(RP(α,β,S)−Ro)+
bws(k − 1)∑
i∈S1Ri
(18)
.UP is an increasing function of RP(α, β, S), and similar to themethod of finding γ∗
i and c∗i , we can get that
β∗ =RPSPR(S)
RPSPR(S) + RPTST (S)(19)
α∗ = [aRo − ln (A − 2B +
√A2 − 4AB
2B)]/A (20)
where A = awpRSTPT ,i(S)RSPSR,i (S)/(RSTPT ,i(S) + RSPSR,i(S))
and B = bws(k − 1)/∑
( 1RSTPT ,i (S) + 1
RSPSR,i (S)), and B should be
less than A/4.by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Selection of SUs
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Selection of SUs
1 α∗ = α∗(S), β∗ = β∗(S)
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Selection of SUs
1 α∗ = α∗(S), β∗ = β∗(S)
2 We should select proper S to make UP as large aspossible.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Selection of SUs
1 α∗ = α∗(S), β∗ = β∗(S)
2 We should select proper S to make UP as large aspossible.
3 Thus, S∗ = arg maxS U∗P(S)
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Selection of SUs
1 α∗ = α∗(S), β∗ = β∗(S)
2 We should select proper S to make UP as large aspossible.
3 Thus, S∗ = arg maxS U∗P(S)
In our report, we use two kinds of selecting methods: traversaland greedy algorithm.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Selection of SUs
1 α∗ = α∗(S), β∗ = β∗(S)
2 We should select proper S to make UP as large aspossible.
3 Thus, S∗ = arg maxS U∗P(S)
In our report, we use two kinds of selecting methods: traversaland greedy algorithm.And the complexity of each method is: O(t) = 2k andO(g) = k2.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Selection of SUs
1 α∗ = α∗(S), β∗ = β∗(S)
2 We should select proper S to make UP as large aspossible.
3 Thus, S∗ = arg maxS U∗P(S)
In our report, we use two kinds of selecting methods: traversaland greedy algorithm.And the complexity of each method is: O(t) = 2k andO(g) = k2.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Selection of SUs
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ModelProtocol
Selection of SUs
The flow chart of greedy algorithm is as below:
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ScenarioResults
Part III
Simulation
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ScenarioResults
Scenario
In simulation, we consider one pair of PU with six groups ofSUs.
Gain: All the channel gain h are set as GaussianDistribution.
Power: No = 0.1, PP = 1 and 0 < PsPP
< 1
Rate-weight: ws = 0.15, wP = 0.3, wx = 1.2
PU’s required data rate Ro = 3.6
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ScenarioResults
Select Method Compare
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
0.31
0.32
0.33
0.34
0.35
0.36
0.37
0.38
0.39
0.4
Ps/Pp
Up
Sub−optimalOptimal
Figure: Comparison of selecting method
The Comparison between two selecting methods.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ScenarioResults
Alpha-Beta
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Ps/Pp
alph
a,be
ta
alphabeta
Figure: Optimal Alpha Beta
While Ps changes from 0 to Pp, the choosing of parameteralpha and beta also changes.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ScenarioResults
Utility
Figure: Utility over Ps/Pp
When we increase the ratio of Ps over Pp, the utility of both PUand SUs become greater.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks
ScenarioResults
Optimal Gamma
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1−4
−3
−2
−1
0
1
2
3
4
5
6x 10
−3
gama
Util
ity
Ui
Figure: Ui over gamma
Use different values of gamma, observe how Ui changes.
by Team10 Haobing Wang Ren Mao Fei Ye Li Li Improved Utility-Based Cooperative Cognitive Radio Networks