Mixed Generalized Fractional Brownian Motion

To extend several known centered Gaussian processes, we introduce a new centered mixed self-similar Gaussian process called the mixed generalized fractional Brownian motion, which could serve as a good model for a larger class of natural phenomena. This process generalizes both the well known mixed fractional Brownian motion introduced by Cheridito [10] and the generalized fractional Brownian motion introduced by Zili [31]. We study its main stochastic properties, its non-Markovian and non-stationarity characteristics and the conditions under which it is not a semimartingale. We prove the long range dependence properties of this process

Adaptive parameters adjustment in WBAN to mitigate Wi-Fi interferences

Wireless Body Area Network (WBAN), called also Wireless Body Sensor Network (WBSN), is composed of a set of tiny wireless devices (sensors) attached, implanted or ingested into the body. It offers real time and ubiquitous applications thanks to the small form, the lightness, and the wireless interface of sensors. WBAN performance is expected to be considerably degraded in the presence of Wi-Fi networks. Their operating channels overlap in the 2.4 GHz Industrial Scientific and Medical (ISM) band which produces interference when they transmit data, accompanied by data losses and quick battery exhaustion. Therefore, it is crucial to mitigate the interference between WBAN and Wi-Fi networks in order to maintain the efficiency and the reliability of the WBAN system. Proposals in the literature use an added complex hardware in WBAN system, or perform the exchange of additional information, or establish expensive communications, or affect the quality of service of the WBAN. Unlike previous researches, we proposed simple, low cost and dynamic method that adaptively adjusts specific parameters in the Medium Access Control (MAC) layer. We have proved the effectiveness of our approach based on theoretical analysis and simulation using MiXiM framework of OMNet++ simulato