Practical Distributed Reception for Wireless Body Area Networks Using Supervised Learning

Medical applications have driven many areas of engineering to optimize diagnostic capabilities and convenience. In the near future, wireless body area networks (WBANs) are expected widespread impact in medicine. To achieve this impact, however, significant advances research needed cope with changes human body’s state, which make coherent communications difficult or even impossible. paper, we consider a realistic noncoherent WBAN system model where transmissions receptions conducted without any channel state information due fast-varying channels body. Using distributed reception, propose several symbol detection approaches on-off keying (OOK) modulation is exploited, among supervised-learning-based approach developed overcome issue. Through simulation results, compare verify performance proposed techniques for WBANs OOK transmissions. We show that well-defined enable robust systems.