Energy Efficient Channel State Classification for Lifetime Enhancement of LPWA Networks

Abstract

Current Low Power Wide Area Network (LPWAN) wireless transceivers are designed, or configured at deployment time, to function assuming a worse-case application scenario. Most of the time, they waste a significant amount of energy when operated under favourable channel conditions. Energy efficient and accurate channel state classification is imperative for selecting the optimum trade-off between transceiver performance and amount of saved energy, without impacting transmission quality. This work presents a novel, low complexity channel state indicator and a simple mono-feature classifier for channel state recognition. The classifier is trained using a set of experimental data acquisitions and has a 96% accuracy when tested with a new collected data set. Specially designed for LPWA applications, the classifier is capable of distinguishing undisturbed channels from those suffering from both mobility-induced fading and interference, while operating at low to medium SNR.