Cooperative Communication-Aware Spectrum Leasing in Cognitive Radio Networks

Y. Yi†, J. Zhang†, Q. Zhang†, T. Jiang‡, J. Zhang╫ †Hong Kong University of Science and Technology ‡ Huazhong University of Science and Technology ╫ Huawei Technologies Co., Ltd.

Presenter: Yi Youwen ([email protected]) April 5, 2010

Outline 

Introduction  



Game Theory Analysis  

 

Background System Model Utility Functions Stackelberg Game

Simulation Results Conclusions

Outline 

Introduction  



Game Theory Analysis  

 

Background System Model Utility Functions Stackelberg Game

Simulation Results Conclusions

Cognitive Radio 

Fixed spectrum allocation is inefficient  



Spectrum scarcity: most of the spectrum band is allocated Spectrum hole: spectrum is not fully utilized

One solution: cognitive radio (CR)  

Primary users (PU): own the spectrum Secondary users (SU): opportunistically access without interference

1

CCRN 

Cooperative cognitive radio networks (CCRN)  

PU leverages SU as cooperative relay Data rate of PU will increase, and results in more access opportunities Secondary Network

Payment

Access Opportunity Primary Network

2

Network Cooperation 

Challenges: 





How much opportunity the secondary network can obtain, and the according payment? What is the optimal relay selection?

Cooperative Communication-Aware Spectrum Leasing Framework: 



Design a negotiation mechanism for each network to maximize its utility with regards to data rate and revenue. Both have motivation to cooperate, and relay selection can be done within polynomial time. 3

Outline 

Introduction  



Game Theory Analysis  

 

Background System Model Utility Functions Stackelberg Game

Simulation Results Conclusions

System Model 

Transmission Mode  Primary transmission 



Cooperative transmission 



SU -> PAP

Secondary transmission 



PU -> SU, PU->PAP

SU ->SAP

Access Mode  TDMA 4

Outline 

Introduction  



Game Theory Analysis  

 

Background System Model Utility Functions Stackelberg Game

Simulation Results Conclusions

Game Theory Analysis Utility Functions 

1 0.9

a=2 a=6

0.8

Primary network

0.7

U

d

0.6 0.5 0.4 0.3 0.2 0.1 0

0

0.5

1

1.5

2



7 b=0.4 b=0.8

6



5

Secondary network

4

us



3 2 1 0 0

2

4

6

8

Rs

5

10

Outline 

Introduction  



Game Theory Analysis  

 

Background System Model Utility Functions Stackelberg Game

Simulation Results Conclusions

Game Theory Analysis 

Spectrum Leasing Framework



Backward Induction 



Given primary network’s strategy, find the optimal reaction of secondary network’s Assuming the secondary network will act as its optimal reaction, the primary network selects its strategy to maximize its utility 6

Game Theory Analysis 

The best strategy of the secondary network  



Given price c, the SN determines A convex optimal problem

The best response function:

7

Game Theory Analysis 

The Best Strategy of Primary Network 

Given the best response function of the SN , the PN determines the relay selection and the price per unit access time c Total access time constrain

Relay selection constrain

Primary transmission mode

8

Game Theory Analysis 

Relay Selection User

……

……

Virtual node

……

……

Min-cost Problem & Hungarian Method 9

Game Theory Analysis 

Price Determination



A convex problem, and unique solution exist

10

Outline 

Introduction  



Game Theory Analysis  

 

Background System Model Utility Functions Stackelberg Game

Simulation Results Conclusions

Simulation Results 

Setup 

Assumptions  



PU

Fading channel No power control

SU

Some key parameters     

Kp = 10 Ks = 5 ~ 20 rp = 100m rs = 70m d = 20m

d PU

rp

PAP

SU

SAP

rs

PU

SU

PU

11

Simulation Results 

Both PN and SN have motivation to share the spectrum, and involve cooperative transmission. 200

14 CSL NCSL NSL

190

12 10

170

8

Us

Up

180

CSL NCSL NSL

160

6

150

4

140

2

130

5

10

15 Ks

20

0 5

10

15

20

Ks

Fig. 1 The utility of PN and SN versus the number of secondary users

12

Simulation Results

15

210

CSL NCSL NSL

CSL NCSL NSL

200 190

10

180 170

Us



With heavier traffic load, the PN gain less from spectrum leasing, while gain more from cooperative transmission. Cooperative transmission still benefits both networks

Up



160

5

150 140 130 120 0.2

0.4

0.6

0.8

1 

1.2

1.4

1.6

0 0.2

0.4

0.6

0.8



1

1.2

1.4

1.6

Fig. 2 The utility of PN and SN versus the traffic demand of the primary users

13

Outline 

Introduction  



Game Theory Analysis  

 

Background System Model Utility Functions Backward Induction

Simulation Results Conclusions

Conclusions 

Cooperative Communication-Aware Spectrum Leasing Framework 



Game Theory Analysis  



Two collocated infrastructure-based primary and secondary networks can share the spectrum

The spectrum leasing problem is modeled as a stackelberg game. An unique Nash Equilibrium exists which gives the optimal strategies for both networks.

Cooperation Benefits 

Simulation results show that both primary and secondary networks achieve higher utility when leveraging cooperative transmission.

14

Thank you! Q&A Email: [email protected]

Simulation Results (cont.) Different number of secondary users 0.7

100 CSL NCSL

0.65

CSL NCSL

95

0.6

90

The spectrum price c

The spectrum leased to secondary network s



0.55 0.5 0.45

85 80 75

0.4

70

0.35

65 5

10 15 The number of secondary uers Ks

20

60

5

10 15 The number of secondary uers Ks

20

Simulation Results (cont.) 

Different traffic loads of primary network 1

The spectrum leased to secondary network s

90 CSL NCSL

The spectrum price c

85

80

75

70 0.2

0.4

0.6 0.8 1 1.2 The traffic demand coefficient 

1.4

1.6

CSL NCSL

0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.2

0.4

0.6 0.8 1 1.2 The traffic demand coefficient 

1.4

1.6

Cooperative Communication-Aware Spectrum Leasing ...

Apr 5, 2010 - Cooperative Communication-Aware Spectrum. Leasing in Cognitive Radio Networks. Y. Yi. †. , J. Zhang. †. , Q. Zhang. †. , T. Jiang. ‡. , J. Zhang. ╫. †. Hong Kong University of Science and Technology. ‡. Huazhong University of Science and Technology. ╫. Huawei Technologies Co., Ltd. Presenter: Yi ...

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