Distributed Adaptive Filtering on Wireless Sensor Networks with Shared Medium Competition

Abstract

Wireless Sensor Networks (WSN) are of significant importance with increasingly diverse and viable applications. They gained even more traction after the IEEE 802.15.4 standard was defined. Distributed adaptive filtering algorithms have added statistical inference to WSN applications, employing techniques that extract data from distributed devices. In contrast, most adaptive filtering contributions do not consider realistic features of the subjacent telecommunications network protocols. Similarly, the telecommunications area typically does not take into account interesting abilities of adaptive filtering algorithms. In this paper, we explore this gap between the two study areas, allowing the development of network-protocol-aware distributed adaptive filtering techniques. In order to explore network realistic behaviors, this paper focuses on distributed inference problems. More specifically, we propose two new diffuse adaptive algorithms, aware of the characteristics of the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol, namely: (i) Variant Reuse of Coefficients Least Mean Squares (VRCLMS) algorithm; and the (ii) Reuse of Coefficients Least Mean Squares (RC-LMS) algorithm in the Adapt-Then-Combine (ATC) modality. These two new algorithms will bring some advantages, specifically when information is delayed because of too much packet loss. Another advantage will be the addition of the spatial information diversity contribution in the VRC-LMS algorithm.