@inproceedings{c249f27390cc4b048e7133488562cf2f,
title = "Bit Error Rate Performance of In-vivo Radio Channel Using Maximum Likelihood Sequence Estimation",
abstract = "In this paper we present the Bit Error Rate (BER) performance of equalizers using in-vivo channel response measured using Vector Network Analyzer (VNA). Including the use of a Bandwidth (BW) of 50 MHz in the simulations, the results are compared with multiple equalizers and it is shown that Maximum Likelihood Sequence Estimation (MLSE) equalizer outperformed the rest of the equalizers including linear equalizers Least Mean Square (LMS) and Recursive least sequence (RLS) and non-linear equalizer Decision Feedback Equalizer (DFE). The BER performance using MLSE showed significant improvement by improving the BER and outperforming the linear equalizer from 10-2 to 10-6 and DFE from 10-4 to 10-6 at text\{Eb\}/ text\{No\}= 14 dB for in vivo radio communication channel at ultra wideband (UWB) frequencies. Furthermore, the un-equalized and equalized channel frequency response spectrum is also part of this article which presents the overall improvement between the two spectrums.",
keywords = "Bit Error Rate (BER), Body Area Networks (WBANs), Equalization, Ultra wideband, in vivo Communication",
author = "Mohanad Mezher and Muhammad Ilyas and Oguz Bayat and Abbasi, \{Qammer H.\}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020 ; Conference date: 12-06-2020 Through 13-06-2020",
year = "2020",
month = jun,
doi = "10.1109/ICECCE49384.2020.9179248",
language = "English",
series = "2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020",
address = "United States",
}