Abstract
| Original language | English |
|---|---|
| Article number | 44 |
| Number of pages | 14 |
| Journal | EURASIP Journal on Wireless Communications and Networking |
| Volume | 2014 |
| Issue number | 1 |
| Early online date | 24 Mar 2014 |
| DOIs | |
| Publication status | Published - Dec 2014 |
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Keywords
- adaptive mechanism design
- cognitive radio networks
- Nash Equilibrium
- wireless networks
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Adaptive mechanism design and game theoretic analysis of auction-driven dynamic spectrum access in cognitive radio networks. / Zhong, Wei; Xu, Youyun; Wang, Jiaheng; Li, Dapeng; Tianfield, Huaglory.
In: EURASIP Journal on Wireless Communications and Networking , Vol. 2014, No. 1, 44, 12.2014.Research output: Contribution to journal › Article
TY - JOUR
T1 - Adaptive mechanism design and game theoretic analysis of auction-driven dynamic spectrum access in cognitive radio networks
AU - Zhong, Wei
AU - Xu, Youyun
AU - Wang, Jiaheng
AU - Li, Dapeng
AU - Tianfield, Huaglory
PY - 2014/12
Y1 - 2014/12
N2 - This paper studies the auction-driven dynamic spectrum access in cognitive radio networks with heterogeneous secondary users, who have different risk attitudes. First, a game theoretic framework is established for auction-driven dynamic spectrum access in cognitive radio networks. The utility functions and bidding strategies of heterogeneous secondary users are defined, and the parameterized auction mechanisms of primary user are also introduced. Then, we formulate the auction-driven dynamic spectrum access problem as a finite discrete game with a mixed- or pure-strategy Nash equilibrium solution. We study the existence and uniqueness properties of the pure-strategy Nash equilibrium in the defined game. Next, we propose a distributed learning automata algorithm (DLA) to attain the Nash equilibrium of the defined game with limited feedback. The adaptive mechanism design is realized in the updating procedure of our DLA algorithm. We further prove that our DLA algorithm converges to a Nash equilibrium of the defined game. Finally, simulation results show that our DLA algorithm is efficient and outperforms the dynamic spectrum access schemes with fixed auction mechanism.
AB - This paper studies the auction-driven dynamic spectrum access in cognitive radio networks with heterogeneous secondary users, who have different risk attitudes. First, a game theoretic framework is established for auction-driven dynamic spectrum access in cognitive radio networks. The utility functions and bidding strategies of heterogeneous secondary users are defined, and the parameterized auction mechanisms of primary user are also introduced. Then, we formulate the auction-driven dynamic spectrum access problem as a finite discrete game with a mixed- or pure-strategy Nash equilibrium solution. We study the existence and uniqueness properties of the pure-strategy Nash equilibrium in the defined game. Next, we propose a distributed learning automata algorithm (DLA) to attain the Nash equilibrium of the defined game with limited feedback. The adaptive mechanism design is realized in the updating procedure of our DLA algorithm. We further prove that our DLA algorithm converges to a Nash equilibrium of the defined game. Finally, simulation results show that our DLA algorithm is efficient and outperforms the dynamic spectrum access schemes with fixed auction mechanism.
KW - adaptive mechanism design
KW - cognitive radio networks
KW - Nash Equilibrium
KW - wireless networks
U2 - 10.1186/1687-1499-2014-44
DO - 10.1186/1687-1499-2014-44
M3 - Article
VL - 2014
JO - EURASIP Journal on Wireless Communications and Networking
JF - EURASIP Journal on Wireless Communications and Networking
SN - 1687-1472
IS - 1
M1 - 44
ER -