By Yan Zhang, Jun Zheng, Hsiao-Hwa Chen
Whereas nonetheless within the early levels of study and improvement, cognitive radio is a hugely promising communications paradigm being able to successfully handle the spectrum insufficiency challenge. Written via these pioneering the sphere, Cognitive Radio Networks: Architectures, Protocols, and criteria deals an entire view of cognitive radio—including introductory thoughts, basic options, rules, criteria, method implementations, and up to date advancements. From the actual layer to protocol layer, world-class editors offer accomplished technical and regulatory counsel throughout cognitive radio, dynamic spectrum entry, and cognitive instant networks. The publication examines routing, Medium entry keep watch over (MAC), cooperation schemes, source administration, mobility, and video game conception method. equipped into 3 sections for ease of reference: Introduces and addresses the problems within the actual layer, together with sensing, means, and tool keep watch over Examines matters within the protocol layers and provides functional suggestions Explores purposes, together with cognitive radio platforms whole with illustrative figures that permit for entire cross-referencing, this authoritative reference offers readers with the certainty of the basic recommendations, ideas, and framework of cognitive instant platforms had to begin the improvement of future-generation instant platforms and networks.
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Additional resources for Cognitive Radio Networks: Architectures, Protocols, and Standards (Wireless Networks and Mobile Communications)
The cyclostationary feature detector relies on the fact that most signals exhibit periodic features, present in pilots, cyclic preﬁxes, modulations, carriers, and other repetitive characteristics [6,33–37]. Because the noise is not periodic, the signal can be successfully detected. The works by Gardner  in 1991 and Enserink et al.  in 1995 have studied this signal detection scheme in detail. The work of Enserink et al. 11) which goes into the decision statistic, given by decide for H0 , H1 , ˆ <ν if M ˆ ≥ ν, if M A recent work focuses on a cyclostationary feature detector for cognitive radio networks , called multi-cycles detector.
The cooperative spectrum sensing can be  ■ ■ Centralized, in which a central entity gathers all information from all secondary receivers to make a decision about the medium status, which is then transmitted back to the receivers Distributed, in which the receivers share their information to make their own decision In both these situations, the cooperative spectrum sensing is plagued with one problem: how to report or distribute the measures in a resource-constrained network. In fact, if these measurements are the basis for deciding whether a transmission can be made or not, then it does not make any sense to propagate the measurements before the decision is made.
Secondary systems can exploit pilot signals to detect the presence of transmissions of primary systems in their vicinity. If a pilot signal is known, then the MF signal detector achieves the optimal detection performance in AWGN channel, since it maximizes the SNR, as shown by Tandra and Sahai in . Let us assume that ■ ■ ■ The signal detector knows the pilot sequence x(k), the bandwidth, and the center frequency in which it will be transmitted. The pilot sequence is always appended to the transmission of each primary system (uplink or downlink).
Cognitive Radio Networks: Architectures, Protocols, and Standards (Wireless Networks and Mobile Communications) by Yan Zhang, Jun Zheng, Hsiao-Hwa Chen