Journal ArticleDOI
Cognitive Radio Networks: The Spectrum Supply Chain Paradigm
Simon Haykin,Peyman Setoodeh +1 more
TLDR
Two classes of spectrum-supply chain networks based on two regimes, one allows open-access to the spectrum, and the other is a market-driven regime are discussed, which allow for analysis of both equilibrium and transient behaviors.Abstract:
Cognitive radio provides a basis for addressing the practical issue of spectrum scarcity. This issue has been raised due to the continuing advances in wireless technology, which has led to ever-increasing demand for larger bandwidth. The issue of spectrum scarcity has been exacerbated due to inefficient use of the electromagnetic spectrum. Adopting the novel idea of cognitive radio for secondary usage of underutilized spectrum results in the existence of two worlds of wireless communications going on side by side: the legacy wireless world and the cognitive wireless world. Spectrum holes (i.e., the unused spectrum subbands) are the medium, through which these two worlds dynamically interact. Releasing subbands by primary users allows the cognitive radio users to sustain communication and perform their normal tasks. Combination of the two wireless worlds can be viewed as a spectrum-supply chain network, in which the legacy owners and their customers (primary users) play the role of the suppliers and cognitive radios (secondary users) play the role of consumers. This paper discusses two classes of spectrum-supply chain networks based on two regimes, one allows open-access to the spectrum, and the other is a market-driven regime. Each one of them has its own merits and suitability for a different environment; therefore, they have complementary roles. Analytic models are developed for these two classes of networks, which allow for analysis of both equilibrium and transient behaviors.read more
Citations
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Posted Content
Stigmergic epistemology, stigmergic cognition
Leslie Marsh,Christian Onof +1 more
TL;DR: A stigmergic framework for social epistemology is recommended to account for the supposed tension between individual action, wants and beliefs and the social corpora and it is proposed that the so-called ‘‘extended mind’’ thesis offers the requisite stighergic cognitive analog to stigMERgic knowledge.
Journal ArticleDOI
Fusion Methods for CNN-Based Automatic Modulation Classification
TL;DR: Three fusion methods are proposed to solve the problem of automatic modulation classification in wireless communications, such as voting-based fusion, confidence- based fusion, and feature-based Fusion, and the results show that the three fusion methods perform better than the non-fusion method.
Journal ArticleDOI
Cooperative Coevolutionary Bare-Bones Particle Swarm Optimization With Function Independent Decomposition for Large-Scale Supply Chain Network Design With Uncertainties
TL;DR: A cooperative coevolutionary bare-bones particle swarm optimization (CCBBPSO) with function independent decomposition (FID) for a multiperiod three-echelon LUSCND problem is proposed, which has an evident superiority over contestant algorithms.
Journal ArticleDOI
Big Data Processing Architecture for Radio Signals Empowered by Deep Learning: Concept, Experiment, Applications and Challenges
TL;DR: A big data processing architecture for radio signals is presented and a new approach of end-to-end signal processing based on deep learning is discussed in detail, and challenges are discussed, such as unified representation of radio signal features, distortionless compression of wideband sampled data, and deep neural networks forRadio signals.
Posted Content
Spectrum Sensing Based on Deep Learning Classification for Cognitive Radios
TL;DR: In this article, the authors proposed a deep learning-based spectrum sensing method based on deep learning classification, which normalizes the received signal power to overcome the effects of noise power uncertainty.
References
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Cognitive radio: brain-empowered wireless communications
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Journal ArticleDOI
Cognitive radio: making software radios more personal
TL;DR: With RKRL, cognitive radio agents may actively manipulate the protocol stack to adapt known etiquettes to better satisfy the user's needs and transforms radio nodes from blind executors of predefined protocols to radio-domain-aware intelligent agents that search out ways to deliver the services the user wants even if that user does not know how to obtain them.