Download Cognitive Radio Networking and Security A Game Theoretic by K. J. Ray Liu PDF

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By K. J. Ray Liu

With the fast progress of latest instant units and purposes over the last decade, the call for for instant radio spectrum is expanding relentlessly. the advance of cognitive radio networking offers a framework for making the absolute best use of restricted spectrum assets, and it's revolutionising the telecommunications undefined. This booklet offers the basics of designing, enforcing, and deploying cognitive radio conversation and networking structures. Uniquely, it specializes in video game idea and its functions to numerous elements of cognitive networking. It covers intimately the middle facets of cognitive radio, together with cooperation, situational wisdom, studying, and safety mechanisms and methods. additionally, it offers novel, state of the art options and up to date effects. this can be a fantastic reference for researchers, scholars and execs in who have to study the functions of online game conception to cognitive networking. providing the basics of designing, imposing, and deploying cognitive radio networks, this publication presents a special specialise in video game conception and its purposes. Cooperation, situational knowledge, studying, and safety are all lined intimately, as well as novel, state of the art options and up to date effects.

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Example text

However, the required number of signal samples also grows as the received SNR decreases, so there exists an SNR wall [424] for a matched filter. In addition, its implementation complexity and power consumption are too high [71], because the matched filter needs receivers for all types of signals and corresponding receiver algorithms have to be executed. Matched filtering requires perfect knowledge of the primary user’s signal, such as the operating frequency, bandwidth, modulation type and order, pulse shape, packet format, etc.

12 Introduction to cognitive radios a certain QoS. The interference-temperature dynamics in a CR network were investigated in [400] using a hidden Markov model (HMM). The HMM is trained with the observed interference-temperature values using the Baum–Welch procedure. The trained HMM is shown to be statistically stable, and can be used as a sequence generator for secondary nodes to predict the interference temperature of the channel in the future. Secondary users can further utilize the prediction to aid their channel selection for transmission.

A primary-prioritized Markov approach for dynamic spectrum access is proposed in [449], which models the interactions between the primary users and the secondary users as continuous-time Markov chains. By designing appropriate access probabilities for the secondary users, a good tradeoff between spectrum efficiency and fairness, and a higher throughput than with CSMA-based random access, can be achieved. A cognitive MAC (C-MAC) protocol for distributed multi-channel wireless networks is introduced in [48].

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