Enhancing Location Awareness: A Perspective on Age of Information and Localization Precision

In the realm of industrial Internet of Things (IIoT), the concept of location awareness plays a crucial role in the integrated sensing and communication (ISAC) framework. This paper introduces an innovative methodology for assessing the location awareness of a mobile entity by combining the precision of the positioning algorithm and the timeliness of location estimations based on the age of information (AoI). The assessment employs a novel metric termed as the aging error of localization (AEoL), which encapsulates both the accuracy of localization and its evolution over the data packet lifecycle. This metric bridges a gap in existing research, which predominantly emphasizes geographical precision while neglecting the dynamic spatial attributes of a mobile entity, thereby offering valuable insights into both the precision and temporal aspects of location awareness. The study delves into the evaluation of AEoL under scenarios of perfect and imperfect localization algorithm precision. By considering a scenario where an automated guided vehicle (AGV) adheres to the uniform rectilinear motion (URM) and transmits radio signals via specific queuing models, analytical expressions for the time-average AEoL are derived across varying update rates. These expressions are subsequently validated through numerical simulations. Furthermore, for specific root mean square error (RMSE) scenarios, optimal update rates are recommended, through which the performance of location awareness can be enhanced by reducing the AEoL metric by 10% to 68% compared to the worst-case scenario.