Evaluation of ultra‐wideband in vivo radio channel and its effects on system performance

Abstract

This paper presents bit‐error‐rate (BER) performance analysis and improvement using equalizers for an in vivo radio channel at ultra‐wideband frequencies (3.1 GHz to 10.6 GHz). By conducting simulations using a bandwidth of 50 MHz, we observed that the in vivo radio channel is affected by small‐scale fading. This fading results in intersymbol interference affecting upcoming symbol transmission, causing delayed versions of the symbols to arrive at the receiver side and causes increase in BER. A 29‐taps channel was observed from the experimentally measured data using a human cadaver, and BER was calculated for the measured in vivo channel response along with the ideal additive white Gaussian noise and Rayleigh channel models. Linear and nonlinear adaptive equalizers, ie, decision feedback equalizer (DFE) and least mean square (LMS), were used to improve the BER performance of the in vivo radio channel. It is noticed that both the equalizers improve the BER but DFE has better BER compared to LMS and shows the 2‐dB and 4‐dB performance gains of DFE over the LMS at Eb/No = 12 dB and at Eb/No = 14 dB, respectively. The current findings will help guide future researchers and designers in enhancing systems performance of an ultra‐wideband in vivo wireless systems.

Bit Error Rate Performance of In-vivo Radio Channel Using Maximum Likelihood Sequence Estimation

“…Hence by taking the comparison between the power spectrums, we can notice that the (DFE) and the linearly equalized will be able to be noticed that the Maximum variation is gained in un equalized frequency response and it is with the range of 0 dB to -40 dB. Where the linear equalizer can make it less within this range 0 dB to -30 dB [4]. Meanwhile, the (DFE) decision feedback equalizer outperformed the linear equalizer and by applying the Ideal MLSE we can obviously notice that it outperformed both of the linear equalizer and the decision feedback equalizer as presented in Fig.…”

“…The system performance of the in-vivo channel is discussed in details in [4] initially worst BER performance were observed due to the multipath effect a multi tap channel was observed. In order to compensate the effect of ISI different equalizers were used including linear equalizer and nonlinear equalizers.…”

“…One of the design for these kind of antennas is shown in [3] for a better communication system with the wireless functionality to communicate with the external world, this scheme will help the researchers to make the size of implantable device smaller. In [4] another major issue of battery changing and charging the implants are addressed in detail as once the implant is placed, it is hard to charge it on daily basis or change the battery. Although with the advancement of fifth Generation (5G) technology, theoretically it is expected to have the battery life of those devices for up to 10 years, which will have a positive impact on those devices.…”

Data Transmission Enhancement Using Optimal Coding Technique Over In Vivo Channel for Interbody Communication

“…The very difficult requirements related to the transceivers of WBAN, like power efficiency, forced IEEE Task Group6 (TG-6) to use 3 physical layer types for satisfying various application types [4]. Also, such physical layers might be reported in the following way [5]:…”

Location Dependent Channel Characteristics for Implantable Devices

“…The results show a reasonable Root Mean Square Error (RMSE) for both the modeled channel and the blind testing. Furthermore, the Bit Error Rate (BER) performance is evaluated in [7]. Equalizers are used to improve the performance of the in-vivo BER.…”