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Classification of DSA channel selection for estimation of secondary user behavior
Many applications of cognitive engines in wireless environments require the system to dynamically select a channel on which to operate. While the different selection strategies are targeted at a very wide range of different networks, they can be organized into a smaller set of simple strategies. Thi...
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creator | Rebhol, M. J. Bose, T. Kadambe, S. L. |
description | Many applications of cognitive engines in wireless environments require the system to dynamically select a channel on which to operate. While the different selection strategies are targeted at a very wide range of different networks, they can be organized into a smaller set of simple strategies. This paper will begin by briefly introducing a simulator called the Universal DSA Network Simulator, which will be used to model the actions of a DSA network using these simplified strategies. The remainder of the paper will then cover the current progress in classification of channel selection in order to estimate the behavior of the secondary users; specifically, which secondary user has begun transmitting on a known channel, as is determined by a passive observer. This paper will serve as a strong starting point for low-cost channel selection estimation, since the methods that are used only require features and monitoring equipment that would already be a part of a DSA secondary user. |
doi_str_mv | 10.1109/MWSCAS.2011.6026498 |
format | conference_proceeding |
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J. ; Bose, T. ; Kadambe, S. L.</creator><creatorcontrib>Rebhol, M. J. ; Bose, T. ; Kadambe, S. L.</creatorcontrib><description>Many applications of cognitive engines in wireless environments require the system to dynamically select a channel on which to operate. While the different selection strategies are targeted at a very wide range of different networks, they can be organized into a smaller set of simple strategies. This paper will begin by briefly introducing a simulator called the Universal DSA Network Simulator, which will be used to model the actions of a DSA network using these simplified strategies. The remainder of the paper will then cover the current progress in classification of channel selection in order to estimate the behavior of the secondary users; specifically, which secondary user has begun transmitting on a known channel, as is determined by a passive observer. 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The remainder of the paper will then cover the current progress in classification of channel selection in order to estimate the behavior of the secondary users; specifically, which secondary user has begun transmitting on a known channel, as is determined by a passive observer. 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subjects | Additives Monitoring Switches |
title | Classification of DSA channel selection for estimation of secondary user behavior |
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