Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/5617
Title: Iterative Signal Detection for Diffusion-Based Molecular Communications
Authors: Thakur, Mahendra Singh
Bhatia, Vimal
Keywords: Diffusion;Impulse response;Intersymbol interference;Iterative methods;Spurious signal noise;Data symbols;Diffusion channels;Frame durations;Iterative signal detection;Molecular communication;Received signals;Slow-moving molecules;Transmitter and receiver;Signal detection
Issue Date: 2020
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Thakur, M. S., Sharma, S., & Bhatia, V. (2020). Iterative signal detection for diffusion-based molecular communications. IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, 6(1), 36-49. doi:10.1109/TMBMC.2020.3003876
Abstract: Inter-symbol interference (ISI) due to slow-moving molecules is one of the key limitations affecting throughput of a diffusion based molecular communication (MC). In this paper, we propose novel ISI mitigation approaches for diffusion based MC systems. The first approach uses weighted sum (WS) to enhance the received signal-to-ISI plus noise ratio (SINR) by exploiting the apriori characteristics of the diffusion channel impulse response. In the second approach, an iterative method estimates the ISI in a frame using the block-wise data symbol detection and subtracts this estimated ISI before the signal detection. Both the proposed methods improve the MC system's performance as compared to the conventional signal detection method. Further, we have analyzed the combined WS and iterative method, resulting in further improvement in the performance. Furthermore, the effect of various system parameters such as frame duration, diffusion coefficient, and the distance between transmitter and receiver is analyzed. © 2015 IEEE.
URI: https://doi.org/10.1109/TMBMC.2020.3003876
https://dspace.iiti.ac.in/handle/123456789/5617
ISSN: 2332-7804
Type of Material: Journal Article
Appears in Collections:Department of Electrical Engineering

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