Receiver Techniques for Diffusion-Based Molecular Nano Communications Using an Adaptive Neuro-Fuzzy-Based Multivariate Polynomial Approximation

Molecular communication (MC) nanonetworks, the interconnection of biological nanomachines (Bio-NMs), are envisaged to significantly expand the applications of nano-technology in the areas of the biomedical, material science, and electrical engineering. In this paper, we consider the scenario of a di...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on molecular, biological, and multi-scale communications biological, and multi-scale communications, 2018-09, Vol.4 (3), p.140-159
Hauptverfasser: Alshammri, Ghalib H., Ahmed, Walid K. M., Lawrence, Victor B.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Molecular communication (MC) nanonetworks, the interconnection of biological nanomachines (Bio-NMs), are envisaged to significantly expand the applications of nano-technology in the areas of the biomedical, material science, and electrical engineering. In this paper, we consider the scenario of a diffusion-based molecular communication (DMC) system that is a promising bio-inspired approach to implementing nanonetwork systems. Considering the limited computation capability, ultra-low energy assumption, and expensive information exchange cost among Bio-NMs, this paper proposes a pulse-based demodulation scheme in three biologically inspired techniques for the detection of the molecular pulses: 1) a multivariate polynomial approximation (MPA) scheme; 2) an adaptive fuzzy threshold-based detection (AFTD) scheme; and 3) an adaptive neuro-fuzzy-based MPA (ANF-MPA) scheme. These methods are suitable for binary ON- OFF keying (BOOK signaling), where the Rx Bio-NM adapts the 1/0-bit detection threshold based on the previously received bits that help to alleviate the inter-symbol interference (ISI) problem resulting from residual (tail) diffusion molecules arriving at the receiver due to past bit transmissions and reception noise. To evaluate the performance of DMC systems, the essential communication metrics in each detection scheme are identified, and the numerical results are obtained and validated by MATLAB simulation. Moreover, the complexity of the proposed schemes is calculated, and the performance evaluation in various noisy channel sources shows a promising improvement in the un-coded bit error rate (BER) performance compared with the threshold detection schemes in the literature. These results provide insights that may guide the implementation of future DMC nanonetworks.
ISSN:2372-2061
2332-7804
2372-2061
DOI:10.1109/TMBMC.2019.2923907