Enabling opportunistic and dynamic spectrum access through learning techniques

被引:4
|
作者
Alsaleh, Omar [1 ]
Venkatraman, Pavithra [1 ]
Hamdaoui, Bechir [1 ]
Fern, Alan [1 ]
机构
[1] Oregon State Univ, Sch EECS, Corvallis, OR 97331 USA
来源
关键词
dynamic spectrum access; adaptive techniques; learning schemes;
D O I
10.1002/wcm.1221
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The expected shortage in spectrum supply is well understood to be primarily due to the inefficient, static nature of current spectrum allocation policies. In order to address this problem, Federal Communications Commission promotes the so called opportunistic spectrum access (OSA) to be applied on cognitive radio networks (CRNs). In short, the idea behind OSA is allowing unlicensed users to use unused licensed spectra as long as they do not cause interference to licensed users. In this paper, we present and evaluate learning schemes that allow unlicensed users to locate and use spectrum opportunities effectively, thus improving efficiency of CRNs. We separately consider two models: single and multiple unlicensed user(s). For the latter model, we present two schemes: noncooperative and cooperative Q-learning. All proposed schemes do not require prior knowledge or prediction models of the environment's dynamics and behaviors, yet can still achieve high performance by learning from interaction with the environment. Using simulations, we show that the proposed schemes achieve good performances in terms of throughput and fairness. Copyright (C) 2011 John Wiley & Sons, Ltd.
引用
收藏
页码:1497 / 1506
页数:10
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