Exploiting Interference Fingerprints for Predictable Wireless Concurrency

Operating in unlicensed ISM bands, ZigBee devices often yield poor performance due to the interference from ever increasing wireless devices in the 2.4 GHz band. Our empirical results show that, a specific interference is likely to have different influence on different outbound links of a ZigBee sender, which indicates the chance of concurrent transmissions . Based on this insight, we propose Smoggy-Link, a practical protocol to exploit the potential concurrency for adaptive ZigBee transmissions under harsh interference. Smoggy-Link maintains an accurate link model to quantify and trace the relationship between interference and link qualities of the sender’s outbound links. With such a link model, Smoggy-Link can translate low-cost interference information to the fine-grained spatiotemporal link state. The link information is further utilized for adaptive link selection and intelligent transmission schedule. We implement and evaluate a prototype of our approach with TinyOS and TelosB motes. The evaluation results show that Smoggy-Link has consistent improvements in both throughput and packet reception ratio under interference from various interferers.