# WiFi-Based Indoor Localization via Multi-Band Splicing and Phase Retrieval

## TL;DR

This paper introduces a WiFi-based indoor localization method that combines multi-band splicing and phase retrieval to achieve centimeter-level accuracy, overcoming hardware distortions and bandwidth limitations.

## Contribution

It proposes a novel multi-band CSI splicing and phase retrieval approach with sparse CIR recovery, significantly improving indoor localization accuracy over existing methods.

## Key findings

- Achieves cm-level localization accuracy in simulations
- Outperforms state-of-the-art methods by an order of magnitude
- Effective across various SNR regimes

## Abstract

We study the problem of indoor localization using commodity WiFi channel state information (CSI) measurements. The accuracy of methods developed to address this problem is limited by the overall bandwidth used by the WiFi device as well as various types of signal distortions imposed by the underlying hardware. In this paper, we propose a localization method that performs channel impulse response (CIR) estimation by splicing measured CSI over multiple WiFi bands. In order to overcome hardware-induced phase distortions, we propose a phase retrieval (PR) scheme that only uses CSI magnitude values to estimate the CIR. To achieve high localization accuracy, the PR scheme involves a sparse recovery step, which exploits the fact that the CIR is sparse over the delay domain, due to the small number of contributing signal paths in an indoor environment. Simulation results indicate that our approach outperforms the state of the art by an order of magnitude (cm-level localization accuracy) for more than 90% of the trials and for various SNR regimes.