4.8 Article

A framework for spectrum harvesting in heterogeneous wireless networks integration

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DOI: 10.1016/j.jksuci.2019.01.009

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Heterogeneous networks; Cognitive radio networks; Spectrum harvesting; Networks integration; Cross correlated sequences

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This paper proposes a cognitive-radio-inspired framework for integrating idle spectrum resources of different wireless networks into a single mobile heterogeneous wireless network. The framework combines a generic and cooperative spectrum-harvesting scheme to keep the network supplied with vital spectrum resources. By using cross-correlated sequences (CCSs) for context-aware event signaling, a reporting and detection scheme is presented in the context of OFDMA systems.
Today's, and near future, communication networks rely heavily on capacity expansion to keep pace with the massive number of mobile devices and ever-increasing mobile traffic. This expansion can be achieved through three major ingredients, namely, adding more wireless-spectrum, efficient usage of this spectrum, and adequate networks' architectures. In this paper, a proposition for integrating these three ingredients in a cognitive-radio-inspired framework is presented. The focus is on the integration of the idle spectrum resources of different wireless networks into a single mobile heterogeneous wireless network. This framework is based on a conceptual network-architecture articulated with a generic and cooperative spectrum-harvesting scheme. The former brings the necessary agility for such heterogeneous environments, the latter keeps the network supplied with the vital spectrum resources. In our proposal, we make use of cross-correlated sequences (CCSs) for context-aware events' signaling purposes. This choice is motivated by the particularly interesting characteristics of CCSs, namely, duration shortness, robustness to bad radio conditions, detection rather than decoding, and low probability of collision. As an illustration, we propose a reporting and detection scheme, in the context of OFDMA systems, and provide performance results from simulations to validate our proposal. (c) 2019 Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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