RSSI Estimation for Constrained Indoor Wireless Networks using ANN

arXiv:2404.15337v1 Announce Type: cross
Abstract: In the expanding field of the Internet of Things (IoT), wireless channel estimation is a significant challenge. This is specifically true for low-power IoT (LP-IoT) communication, where efficiency and accuracy are extremely important. This research establishes two distinct LP-IoT wireless channel estimation models using Artificial Neural Networks (ANN): a Feature-based ANN model and a Sequence-based ANN model. Both models have been constructed to enhance LP-IoT communication by lowering the estimation error in the LP-IoT wireless …

abstract accuracy ann artificial arxiv challenge communication cs.lg cs.ni eess.sp efficiency internet internet of things iot low networks power research true type wireless