Abstract
The feasibility of obtaining an integrated model of a nanonetwork node on a Graphene Composite Substrate (GCS) exploring the same mechanical, electrical and self-sustainable characteristics, contributes to the proposal of this work consisting of an integrated node model applying the same concepts of TCNet to nanodevice networks, where the nodes are cooperatively interconnected with a low-complexity Mealy Machine (MM) topology, integrating in the same electronic system the modules necessary for independent operation in wireless sensor networks (WSNs), compound of Rectennas (RF to DC power converters), Code Generators based on Finite State Machine (FSM) & Trellis Decoder and On-chip Transmit/Receive with autonomy in terms of energy sources applying the Energy Harvesting technique. One of the most critical and ubiquitous problems for nodes in a network is battery life. The battery supply for thousands of wireless sensors used in IoT networks and the logistics of replacement and disposal with consequences for the environment are the main objectives of this research project, with the use of harvesting of energy. In addition, graphene consists of a layer of carbon atoms with the configuration of a honeycomb crystal lattice, which has attracted the attention of the scientific community due to its unique Electrical Characteristics.
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Lima Filho, D.F., Amazonas, J.R. (2023). An Approach of Node Model TCnNet: Trellis Coded Nanonetworks on Graphene Composite Substrate. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2022, Volume 1. FTC 2022 2022. Lecture Notes in Networks and Systems, vol 559. Springer, Cham. https://doi.org/10.1007/978-3-031-18461-1_56
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