@misc{ChatharajupalliRottaKarnapkeetal., author = {Chatharajupalli, Navya Sneha and Rotta, Randolf and Karnapke, Reinhardt and Nolte, J{\"o}rg}, title = {Probing considered harmful : leveraging RSSI for link quality prediction}, series = {Proceedings of the IEEE 50th Conference on Local Computer Networks : LCN 2025 : October 14-16, 2025, Sydney, Australia}, journal = {Proceedings of the IEEE 50th Conference on Local Computer Networks : LCN 2025 : October 14-16, 2025, Sydney, Australia}, publisher = {IEEE}, address = {New York, NY}, isbn = {979-8-3315-3704-3}, issn = {2831-7742}, doi = {10.1109/LCN65610.2025.11146347}, pages = {1 -- 9}, abstract = {Wireless mesh protocols that use a routing metric based on throughput or airtime require predictions about future throughput for all mesh neighbors. Typically, the Wi-Fi rate controller provides this information, and state-of-the-art rate control algorithms estimate it based on statistics from past unicast transmissions. This introduces an adverse cross-layer dependency because meaningful statistics are only available for the links that were used by the routing layer. Existing implementations either ignore this, or use other routing metrics, such as distance, or generate artificial periodic probe traffic to all neighbors. Unfortunately, probing reacts slowly to changing conditions, increases the medium contention, and can lead to overly optimistic predictions. To overcome this, we introduce an RSSI-based link quality prediction for the routing layer. Benchmarks in a B.A.T.M.A.N. version V mesh show a decrease of round-trip time by three orders of magnitude and an increase of the end-to-end packet delivery ratio. TCP connections became possible over long routes that were previously unusable. Although highly imprecise, the easy to acquire RSSI provided sufficiently good predictions for our mesh network.}, language = {en} }