Exploiting causes and effects of wireless link correlation for better performance

Contradicting the widely believed assumption of link independence, recently the phenomenon of reception correlation among nearby receivers has been revealed and exploited for varieties of protocols [3], [8], [17], [21], [23], [24]. However, despite the diversified correlation-aware designs proposed up to date, they commonly suffer from a shortcoming where link correlation is inaccurately measured, which leads them to sub-optimal performance. In this work we propose a general framework for accurate capturing of link correlation, enabling better utilization of the phenomenon for protocols lying on top of it. Our framework uses SINR (Signal to Interference plus Noise Ratio) to detect correlations, followed by modeling the correlations for in-network use. We show that our design is light-weight, both computation and storage-wise. We apply our model to opportunistic routing and network coding on a physical 802.15.4 test-bed for energy savings of 25% and 15%.