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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Guangen Wu Pinyi Ren Chao Zhang |
| Copyright Year | 2011 |
| Abstract | Auction based dynamic spectrum access is an efficient approach to solve the spectrum shortage problem. However, conventional spectrum auction algorithms mainly concentrated on maximizing the revenue, under which the dynamic spectrum access (DSA) users with poorer cognitive abilities are usually hard to win the auction for spectrum access. In this paper, we propose a novel waiting-time auction (WTA) algorithm to improve the winning probabilities for the DSA users with poorer cognitive abilities. Specifically, we formulate the spectrum allocation as an auction game. In the auction, all game users bid with waiting time to obtain the spectrum access opportunities, unlike the conventional approaches where users bid by using money. Correspondingly, users with poorer cognitive ability, usually having the lower time cost, can win the auction with higher probabilities through bidding longer waiting time. We prove that there exists a unique Nash equilibrium (NE) in the WTA based spectrum-allocation game and the NE is desirable for all game users. Both theoretical and simulation analyses show that our proposed WTA algorithm can effective improve the winning probabilities of users with lower cognitive abilities. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 158007 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424492664 |
| ISSN | 1930529X |
| e-ISBN | 9781424492688 |
| e-ISBN | 9781424492671 |
| DOI | 10.1109/GLOCOM.2011.6133796 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-12-05 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Servers Heuristic algorithms Cognitive radio Resource management Games Dynamic scheduling Signal processing algorithms |
| Content Type | Text |
| Resource Type | Article |
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