2020 NSDI NSDI 2020

Comb Decoding towards Collision-Free WiFi

Abstract

Packet collisions happen every day in WiFi networks. RTS/CTS is a widely-used approach to reduce the cost of collisions of long data packets as well as combat the hidden terminal problem. In this paper, we present a new design called comb decoding (CombDec) to efficiently resolve RTS collisions without changing the 802.11 standard. We observe that an RTS payload, when treated as a vector in a vector space, exhibits a comb-like distribution; i.e., a limited number of vectors are much more likely to be used than the others due to RTS payload construction and firmware design. This enables us to reformulate RTS collision resolution as a sparse recovery problem. We create algorithms that carefully construct the search range for sparse recovery, making the complexity feasible for system design and implementation. Experimental results show that CombDec boosts the WiFi throughput by 33.6%–46.2% in various evaluation scenarios.

🧭 Keyword Pioneer — rts ct
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization
🌉 Interdisciplinary Bridge — Computer Science and Mathematics & Optimization