Significance of Mobility on Received Signal Strength: An Experimental Investigation

TL;DR

This study presents a cost-effective, hardware-free method to estimate mobility using Wi-Fi signal strength, achieving reasonable accuracy across various environments and scalable to multiple devices.

Contribution

The paper introduces a novel approach to infer speed from Wi-Fi signal features without additional sensors, with low computational complexity and scalability.

Findings

Average speed estimation error of 12%

Method works across different environments

Scalable to multiple smartphones

Abstract

In this paper, estimation of mobility using received signal strength is presented. In contrast to standard methods, speed can be inferred without the use of any additional hardware like accelerometer, gyroscope or position estimator. The strength of Wi-Fi signal is considered herein to compute the time-domain features such as mean, minimum, maximum, and autocorrelation. The experiments are carried out in different environments like academic area, residential area and in open space. The complexity of the algorithm in training and testing phase are quadratic and linear with the number of Wi-Fi samples respectively. The experimental results indicate that the average error in the estimated speed is 12 % when the maximum signal strength features are taken into account. The proposed method is cost-effective and having a low complexity with reasonable accuracy in a Wi-Fi or cellular environment. Additionally, the proposed method is scalable that is the performance is not affected in a multi-smartphones scenario.