Event Detection in Molecular Communication Networks with Anomalous Diffusion

Trang Mai 1 Malcolm Egan 2 Trung Duong 1 Marco Renzo 3
2 SOCRATE - Software and Cognitive radio for telecommunications
Inria Grenoble - Rhône-Alpes, UCBL - Université Claude Bernard Lyon 1, CITI - CITI Centre of Innovation in Telecommunications and Integration of services
Abstract : A key problem in nanomachine networks is how information from sensors is to be transmitted to a fusion center. In this paper, we propose a molecular communication-based event detection network. In particular, we develop a detection framework that can cope with scenarios where the molecules propagate according to anomalous diffusion instead of the conventional Brownian motion. We propose an algorithm for optimizing the network throughput by exploiting tools from reinforcement learning. Our algorithms are evaluated with the aid of numerical simulations, which demonstrate the tradeoffs between performance and complexity.
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IEEE Communications Letters, Institute of Electrical and Electronics Engineers, 2017
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Dernière modification le : mardi 16 janvier 2018 - 16:34:50

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Trang Mai, Malcolm Egan, Trung Duong, Marco Renzo. Event Detection in Molecular Communication Networks with Anomalous Diffusion. IEEE Communications Letters, Institute of Electrical and Electronics Engineers, 2017. 〈hal-01671181〉

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