Yan Zhang, Jun Zheng, Hsiao-Hwa Chen's Cognitive Radio Networks: Architectures, Protocols, and PDF

By Yan Zhang, Jun Zheng, Hsiao-Hwa Chen

ISBN-10: 1420077759

ISBN-13: 9781420077759

ISBN-10: 1420077767

ISBN-13: 9781420077766

Whereas nonetheless within the early levels of analysis and improvement, cognitive radio is a hugely promising communications paradigm having the ability to successfully deal with the spectrum insufficiency challenge. Written through these pioneering the sector, Cognitive Radio Networks: Architectures, Protocols, and criteria bargains a whole view of cognitive radio—including introductory techniques, basic recommendations, rules, criteria, process implementations, and up to date advancements. From the actual layer to protocol layer, world-class editors offer accomplished technical and regulatory advice throughout cognitive radio, dynamic spectrum entry, and cognitive instant networks. The e-book examines routing, Medium entry keep an eye on (MAC), cooperation schemes, source administration, mobility, and online game concept procedure. prepared into 3 sections for ease of reference: Introduces and addresses the problems within the actual layer, together with sensing, potential, and tool keep watch over Examines matters within the protocol layers and provides useful options Explores functions, together with cognitive radio structures whole with illustrative figures that permit for entire cross-referencing, this authoritative reference presents readers with the knowledge of the elemental techniques, rules, and framework of cognitive instant structures had to begin the advance of future-generation instant structures and networks.

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Additional resources for Cognitive Radio Networks: Architectures, Protocols, and Standards (Wireless Networks and Mobile Communications)

Example text

In the remainder of this section, we explore some of the state-of-the-art cooperative sensing techniques. 1 that, in the low-SNR regime, the ED is highly vulnerable to fading and fluctuations in the level of the noise power. What if, instead of employing ∗ This would also apply to the case where RX is shadowed or is in a deep multipath fading. 1 18 ■ Cognitive Radio Networks the ED at one location, we could do the same thing in other locations as well? It is expected that among several secondary receivers, even though some will suffer from fading or imprecisions due to the choice of the threshold, some will be able to correctly sense the medium.

Let us, for simplicity sake, suppose that all secondary receivers {RX 1 , RX 2 , RX3 , . . 3 are within the range of a certain primary transmitter. Then, considering a flat-faded environment, we have yi (k) = ni (k): hi (k)s(k) + ni (k): H0 , H1 where the subscript i means that each value is to be taken for each user i. We can see that for the H0 hypothesis, all yi (k) are independent because they are only composed of AWGN noise. On the other hand, in the H1 hypothesis, all yi (k) are composed of not only the noise but also the signal component s(k) modulated by the channel hi (k).

In IEEE Wireless Communications and Networking Conference 2007 (WCNC’07 ), Hong Kong, China, 2007, pp. 1–5. C. Sun, W. B. Letaief. Cluster-based cooperative spectrum sensing in cognitive radio systems. , 2007, pp. 2511–2515. S. Cardoso, M. Debbah, P. Bianchi, and J. Najim. Cooperative spectrum sensing using random matrix theory. In International Symposium on Wireless Pervasive Computing (ISWPC’08 ), Santorini, Greece, 2008. Spectrum Sensing in Cognitive Radio Networks ■ 27 29. Y. C. Liang. Eigenvalue base spectrum sensing algorithms for cognitive radio.

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Cognitive Radio Networks: Architectures, Protocols, and Standards (Wireless Networks and Mobile Communications) by Yan Zhang, Jun Zheng, Hsiao-Hwa Chen


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