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K-Means Clustering-Aided Non-Coherent Detection for Molecular Communications.

Authors :
Qian, Xuewen
Di Renzo, Marco
Eckford, Andrew
Source :
IEEE Transactions on Communications. Aug2021, Vol. 69 Issue 8, p5456-5470. 15p.
Publication Year :
2021

Abstract

In this paper, we consider non-coherent detection schemes for molecular communication systems in the presence of inter-symbol-interference. In particular, we study non-coherent detectors based on memory-bits-based thresholds in order to achieve low bit-error-ratio (BER) transmission. The main challenge of realizing detectors based on memory-bits-based thresholds is to obtain the channel state information based only on the received signals. We tackle this issue by reformulating the thresholds through intermediate variables, which can be obtained by clustering multi-dimensional data from the received signals, and by using the K-means clustering algorithm. In addition to estimating the thresholds, we show that the transmitted bits can be retrieved from the clustered data. To reduce clustering errors, we propose iterative clustering methods from one-dimensional to multi-dimensional data, which are shown to reduce the BER. Simulation results are presented to verify the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00906778
Volume :
69
Issue :
8
Database :
Academic Search Index
Journal :
IEEE Transactions on Communications
Publication Type :
Academic Journal
Accession number :
153154538
Full Text :
https://doi.org/10.1109/TCOMM.2021.3075523