Angle-of-Arrival Estimation With Practical Phone Antenna Configurations

Abstract

With the advances in Internet of Things (IoT) and mobile connectivity, location-based services (LBSs) are increasingly popular and continue to enhance our experience. Multiple antennas have been pivotal for the provision of reliable wireless communications and high-resolution localization. However, in the real world, mobile handsets tend to have very limited space and the incorporation of multiple antennas hardly obeys the rule of half-wavelength separation between antenna elements, resulting in complex mutual coupling. More often than not, antennas are placed not to affect negatively the artistic design and handling of the device. The irregular 3D radiation pattern of each antenna element further impairs the capability of the antenna array for localization. In this paper, we propose a generic parametric model that can incorporate the actual antenna responses into the angleof-arrival (AoA) estimation. As a result, we present an efficient algorithm to enable 3D AoA estimation on mobile phones based on the proposed model, and test it on a 5G phone at a midband spectrum with 100MHz channel bandwidth. Our results reveal promising performance with over 90% scenarios where the AoA estimation errors are lower than 10 • on a mobile phone.

Vehicular Localization Framework with UWB and DAG-Based Distributed Ledger for Ensuring Positioning Accuracy and Security

“…UWB localization is a technology that performs precise location estimation using ultra-wideband. UWB localization generally uses the Time of Arrival (ToA) [23][24][25] and Angle of Arrival (AoA) [26][27][28] to perform distance and angle-based positioning, so the positioning principle is the same as other wireless communication positioning systems. However, UWB technology has the characteristic of enabling more-accurate positioning by utilizing a highly wide bandwidth and transmitting pulse signals with a fairly short width [16,29].…”

“…Designing and implementing a positioning system can be more expensive and complex compared to RFID, Bluetooth, and other sensor-based networks [34,35]. Additionally, technical regulations and standardization are different in many countries, which can cause problems with frequency spectrum management [28,36]. In terms of security, it shows weaknesses like other wireless-communication-based positioning systems [37,38].…”