Please use this identifier to cite or link to this item:
https://dspace.iiti.ac.in/handle/123456789/6030
| Title: | Maximum Likelihood Estimation of SNR for Diffusion-Based Molecular Communication |
| Authors: | Upadhyay, Prabhat Kumar |
| Keywords: | Cramer-Rao bounds;Diffusion;Maximum likelihood;Mean square error;Nanotechnology;Signal to noise ratio;Cramer Rao lower bound;Encoded signals;Maximum likelihood Principle;Molecular communication;Molecular concentration;Nanomachines;Sampled observations;SNR estimation;Maximum likelihood estimation |
| Issue Date: | 2016 |
| Publisher: | Institute of Electrical and Electronics Engineers Inc. |
| Citation: | Tiwari, S. K., & Upadhyay, P. K. (2016). Maximum likelihood estimation of SNR for diffusion-based molecular communication. IEEE Wireless Communications Letters, 5(3), 320-323. doi:10.1109/LWC.2016.2553034 |
| Abstract: | 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. © 2016 IEEE. |
| URI: | https://doi.org/10.1109/LWC.2016.2553034 https://dspace.iiti.ac.in/handle/123456789/6030 |
| ISSN: | 2162-2337 |
| Type of Material: | Journal Article |
| Appears in Collections: | Department of Electrical Engineering |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
Altmetric Badge: