How Well Sensing Integrates with Communications in MmWave Wi-Fi?

The development of integrated sensing and communication (ISAC) systems has recently gained interest for its ability to offer a variety of services including resources sharing and new applications, for example, localization, tracking, and health care related. While the sensing capabilities are offered through many technologies, rending to their wide deployments and the high frequency spectrum they provide and high range resolution, its accessibility through the Wi-Fi networks IEEE 802.11ad and 802.11ay has been getting the interest of research and industry. Even though there is a dedicated standardization body, namely the 802.11bf task group, working on enhancing the Wi-Fi sensing performance, investigations are needed to evaluate the effectiveness of various sensing techniques. In this project, we, in addition to surveying related literature, we evaluate the sensing performance of the millimeter wave (mmWave) Wi-Fi systems by simulating a scenario of a human target using Matlab simulation tools. In this analysis, we processed channel estimation data using the short time Fourier transform (STFT). Furthermore, using a channel variation threshold method, we evaluated the performance while reducing feedback. Our findings indicate that using STFT window overlap can provide good tracking results, and that the reduction in feedback measurements using 0.05 and 0.1 threshold levels reduces feedback measurements by 48% and 77%, respectively, without significantly degrading performance.Comment: arXiv admin note: substantial text overlap with arXiv:2207.04859 by other author

Evaluation of Multi-Sensor Fusion Methods for Ultrasonic Indoor Positioning

Indoor positioning systems have become a feasible solution for the current development of multiple location-based services and applications. They often consist of deploying a certain set of beacons in the environment to create a coverage volume, wherein some receivers, such as robots, drones or smart devices, can move while estimating their own position. Their final accuracy and performance mainly depend on several factors: the workspace size and its nature, the technologies involved (Wi-Fi, ultrasound, light, RF), etc. This work evaluates a 3D ultrasonic local positioning system (3D-ULPS) based on three independent ULPSs installed at specific positions to cover almost all the workspace and position mobile ultrasonic receivers in the environment. Because the proposal deals with numerous ultrasonic emitters, it is possible to determine different time differences of arrival (TDOA) between them and the receiver. In that context, the selection of a suitable fusion method to merge all this information into a final position estimate is a key aspect of the proposal. A linear Kalman filter (LKF) and an adaptive Kalman filter (AKF) are proposed in that regard for a loosely coupled approach, where the positions obtained from each ULPS are merged together. On the other hand, as a tightly coupled method, an extended Kalman filter (EKF) is also applied to merge the raw measurements from all the ULPSs into a final position estimate. Simulations and experimental tests were carried out and validated both approaches, thus providing average errors in the centimetre range for the EKF version, in contrast to errors up to the meter range from the independent (not merged) ULPSs.Agencia Estatal de InvestigaciónUniversidad de Alcal