  We investigate the existence of 'long-memory' or long-range dependence (LRD)
of the wireless body-centric channels, e.g., on-body, body-to-body (B2B), with
real-life experimental dataset collected from 10 co-located wireless body area
networks or BANs (people fitted with wearable sensors). We examine two
different factors on that purpose such as: the pattern of the decaying
autocorrelation function (ACF) and the Hurst exponent. From the experimental
outcome, we show that, the ACF decay of the body-centric channels follows a
power-like decay and the channels have a Hurst exponent much greater than 0.5
on average. These results indicate that the body-centric channels can possess
long-memory or LRD characteristic which can be used for predictive analysis and
intelligent decision making to build futuristic wireless human-centered
networks that can sense and act autonomously. We also clarify whether the
presence of the LRD property is sufficient for reliable prediction of the
body-centric channels.
