Neural Networks and SDR Modulation schemes for wireless mobile nodes: a synergic approach

Abstract : In this paper, we envisage the possibility to exploit, in a synergic way, the Software Defined Radio (SDR) capability and the mobility support for wireless devices to dynamically compute the most suitable modulation scheme and the best position in order to improve both the coverage and connectivity in a specific area. The combined approach is based on a Neural/Genetic technique and wireless nodes are able to self-organize in a totally distributed way by using only local information. The extreme adaptability to the network conditions and application level constraints makes the proposed approach well suited for different communication scenarios such as standard monitoring or disaster recovery. The system performance has been evaluated by dealing a suite of simulation tests to show as the controlled mobility paradigm, coupled with the intrinsic re-configuring SDR capabilities of such wireless devices, allows to increase the network performances both in terms of coverage and connectivity by dynamically adapting the modulation schemes to the specific communication scenario.
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Article dans une revue
Ad Hoc Networks, Elsevier, 2017, 〈10.1016/j.adhoc.2016.09.016〉
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Soumis le : lundi 24 octobre 2016 - 15:31:04
Dernière modification le : mercredi 18 avril 2018 - 14:24:05


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Francesca Guerriero, Valeria Loscrí, Pasquale Pace, Rosario Surace. Neural Networks and SDR Modulation schemes for wireless mobile nodes: a synergic approach. Ad Hoc Networks, Elsevier, 2017, 〈10.1016/j.adhoc.2016.09.016〉. 〈hal-01386749〉



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