2019/02/01 by Samiya M. Shimly, David B. Smith, Shimly, Samiya M. +1
Computer Science · Engineering · #Energy Efficient Wireless Sensor Networks #FOS: Electrical engineering #Molecular Communication and Nanonetworks #Signal Processing (eess.SP) #Wireless Body Area Networks #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1902.00149
openalex publication_date 2019/02/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.