Literature Database Entry

angjo2022optimal


Joana Angjo, Ali E. Pusane, H. Birkan Yilmaz, Ertugrul Basar and Tuna Tugcu, "Optimal relaying in molecular communications," Elsevier Nano Communication Networks, vol. 32-33, pp. 100404, June 2022.


Abstract

Molecular communication via diffusion (MCvD) schemes are limited to short distances between the nanomachines due to the transmitted signal becoming rapidly weaker as the distance increases. Additionally, these schemes are very often affected by high inter-symbol interference, which makes them prone to errors, thus leading to unreliability. In this paper, a novel system is proposed, which aims to enhance the received signal shape and the overall performance of MCvD schemes over longer distances. A relay nanomachine is introduced between the transmitter–receiver pair, which collects the first portion of the molecules emitted from the transmitter and keeps them for some delay time , then releases them towards the receiver, such that the delayed and non-delayed portions of the molecules arrive almost at the same time. In this way, the signal’s strength is enhanced by pointing more molecules towards the intended direction, that is, the receiver node. An analytical model for the optimal relaying scheme is proposed, alongside with an optimization problem to find the most advantageous value. Comparison between the proposed scheme and the conventional single-input single-output scenario is provided by means of analytical and computer simulation results, showing a promising improvement in error rates when the relay is introduced.

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Joana Angjo
Ali E. Pusane
H. Birkan Yilmaz
Ertugrul Basar
Tuna Tugcu

BibTeX reference

@article{angjo2022optimal,
    author = {Angjo, Joana and Pusane, Ali E. and Yilmaz, H. Birkan and Basar, Ertugrul and Tugcu, Tuna},
    doi = {10.1016/j.nancom.2022.100404},
    title = {{Optimal relaying in molecular communications}},
    pages = {100404},
    journal = {Elsevier Nano Communication Networks},
    issn = {1878-7789},
    publisher = {Elsevier},
    month = {6},
    volume = {32-33},
    year = {2022},
   }
   
   

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