4.5 Article

Efficient Nanosystem for Nanomedicine Applications Based on Molecular Communications

期刊

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s13369-023-07909-3

关键词

Molecular communication via diffusion (MCvD); Savitzky-Golay (SG) filter; I-filter; Wavelet denoising; BER

向作者/读者索取更多资源

The authors propose an efficient nanosystem based on molecular communication technology, which uses molecular diffusion for exchanging biochemical signals in aqueous media. The nanosystem-based MCvD has applications in targeted drug delivery and healthcare monitoring. The proposed SG filter significantly improves the performance of the nanosystem-based molecular communication by reducing counting noise.
The authors propose an efficient nanosystem based on molecular communication technology. Molecular communication via diffusion (MCvD) is a promising trend for exchanging biochemical signals between a nanotransmitter (NT) and a nanoreceiver (NR) in aqueous media over short distances. Nanosystem-based MCvD has recently received a lot of attention in advanced targeted nanomedicine applications such as targeted drug delivery and healthcare monitoring (disease/diagnosis/analysis). However, the random nature of molecular diffusion causes counting noise, which significantly degrades the performance of the nanosystem-based molecular communication. In this paper, a reliable and simple denoising technique, namely Savitzky-Golay (SG) filter, is developed in the nanosystem-based MCvD to provide high accuracy of molecular information reception. The performance of the proposed nanosystem is evaluated in terms of bit error rate (BER) and correlation efficiency. The results reveal that the nanosystem-based MCvD using the proposed SG filter outperforms the MCvD using current denoising techniques such as moving average filter, wavelet denoising and I-filter. Actually, it was found that the SG filter increases the gain efficiency in terms of the correlation coefficient by more than 60% in comparison to the I-filter at low and high signal-to-noise ratios (SNRs), whereas in comparison to wavelet denoising, the SG filter achieves more than 10% enhancement in gain efficiency at low SNRs.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据