Chirp-Based Over-the-Air Computation for Power-Efficient Distributed Localization

In this study, we propose an over-the-air computation (OAC) approach for power-efficient localization in a sensor network. The proposed approach relies on a voting-based distributed localization and the computation of the majority votes (MVs) with OAC. In this method, the anchor node (AN)'s votes encoding the potential location of a server node (SN) are mapped to a circularly-shifted chirp (CSC) signal and all ANs simultaneously transmit their CSC signals. The aggregated signal is received at the SN and the MV votes are detected non-coherently without requiring an ideal time-synchronization or channel state information (CSI). We further propose an iterative refinement procedure to increase the localization performance. We demonstrate that the CSCs result in spectral-efficient and power-efficient transmission. We also demonstrate that the proposed iterative refinements and repetitions decrease the gap between the root-mean-square error (RMSE) error and the quantization bound.