Maximum Likelihood Estimation of SNR for Diffusion-Based Molecular Communication

Satish K. Tiwari; Prabhat K. Upadhyay

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Maximum Likelihood Estimation of SNR for Diffusion-Based Molecular Communication

机译：基于扩散的分子通信的SNR最大似然估计

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摘要

We investigate the problem of estimation of a signal-to-noise ratio (SNR) measure for diffusion-based molecular communication (DMC) systems. Considering molecular concentration-encoded signal with residual noise, we present the SNR estimation using maximum likelihood principle with sampled observations. Moreover, we derive the Cramer–Rao lower bound and assess the performance of our proposed estimator in terms of its mean square error. Our analysis helps in designing a reliable DMC system with a memoryless receiver nanomachine.

机译：我们研究基于扩散的分子通讯（DMC）系统的信噪比（SNR）度量估计问题。考虑到带有残留噪声的分子浓度编码信号，我们使用采样观测值的最大似然原理给出了SNR估计。此外，我们推导了Cramer-Rao下界，并根据均方误差评估了我们提出的估计器的性能。我们的分析有助于设计具有无记忆接收器纳米机的可靠DMC系统。

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来源
《Wireless Communications Letters, IEEE》 |2016年第3期|320-323|共4页
作者
Satish K. Tiwari; Prabhat K. Upadhyay;
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作者单位

Discipline of Electrical Engineering, Indian Institute of Technology Indore, Indore, India;

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正文语种 eng
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关键词
Cramer-Rao lower bound; Nanomachine; diffusion; maximum likelihood estimation; molecular communication;

机译：Cramer-Rao下界;纳米机械;扩散;最大似然估计;分子通信;

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Maximum Likelihood Estimation of SNR for Diffusion-Based Molecular Communication

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