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Record Nr. |
UNINA9910254218203321 |
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Autore |
Liao Yun |
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Titolo |
Listen and Talk : Full-duplex Cognitive Radio Networks / / by Yun Liao, Lingyang Song, Zhu Han |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (VIII, 100 p. 35 illus., 25 illus. in color.) |
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Collana |
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SpringerBriefs in Electrical and Computer Engineering, , 2191-8112 |
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Disciplina |
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Soggetti |
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Electrical engineering |
Computer communication systems |
Communications Engineering, Networks |
Computer Communication Networks |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Introduction -- Full-duplex Cognitive Radio Networks -- Extensions of the LAT Protocol -- Full-duplex WiFi -- Conclusions and Future Works. . |
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Sommario/riassunto |
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This brief focuses on the use of full-duplex radio in cognitive radio networks, presenting a novel spectrum sharing protocol that allows the secondary users to simultaneously sense and access the vacant spectrum. This protocol, called “Listen-and-talk” (LAT), is evaluated by both mathematical analysis and computer simulations in comparison with other existing protocols, including the listen-before-talk protocol. In addition to LAT-based signal processing and resource allocation, the brief discusses techniques such as spectrum sensing and dynamic spectrum access. The brief proposes LAT as a suitable access scheme for cognitive radio networks, which can support the quality-of-service requirements of these high priority applications. Fundamental theories and key techniques of cognitive radio networks are also covered. Listen and Talk: Full-duplex Cognitive Radio Networks is designed for researchers, developers, and professionals involved in cognitive radio networks. Advanced-level students studying signal processing or simulations will also find the content helpful since it moves beyond traditional cognitive radio networks into future applications for the |
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