A Splitting-Detection Joint-Decision Receiver for Ultrasonic Intra-Body Communications

TL;DR

This paper introduces a novel joint-decision splitting receiver for ultrasonic intra-body communication, significantly improving bit-error rate and channel capacity over traditional methods by combining multiple detection strategies.

Contribution

It proposes the SDJD receiver that enhances performance and reduces complexity in ultrasonic intra-body communication systems, with theoretical analysis and simulation validation.

Findings

SDJD achieves lower BER than traditional receivers.

Both SDSD and SDJD outperform CD and ED in capacity and error rate.

SDJD performs best under imperfect channel estimation.

Abstract

Ultrasonic intra-body communication (IBC) is a promising enabling technology for future healthcare applications, due to low attenuation and medical safety of ultrasonic waves for the human body. A splitting receiver, referred to as the splitting-detection separate-decision (SDSD) receiver, is introduced for ultrasonic pulse-based IBCs, and SDSD can significantly improve bit-error rate (BER) performance over the traditional coherent-detection (CD) and energy detection (ED) receivers. To overcome the high complexity and improve the BER performance of SDSD, a splitting-detection joint-decision (SDJD) receiver is proposed. The core idea of SDJD is to split the received signal into two steams that can be separately processed by CD and ED, and then summed up as joint decision variables to achieve diversity combining. The theoretical channel capacity and BER of the SDSD and SDJD are derived for M-ary pulse position modulation (M-PPM) and PPM with spreading codes. The derivation takes into account the channel noise, intra-body channel fading, and channel estimation error. Simulation results verify the theoretical analysis and show that both SDSD and SDJD can achieve higher channel capacity and lower BER than the CD and ED receivers with perfect channel estimation, while SDJD can achieve the lowest BER with imperfect channel estimation.