Abstract

Direction-of-arrival (DoA) estimation is essential in many industrial internet of things (IIoT) applications where IoT users may require a high-resolution estimation algorithm for features limited to positioning and device localization. The conventional DoA estimation is challenging as the number of antenna arrays increases leading to an increase in design complexity and cost in RF circuitry. As a result, the conventional DoA estimation algorithms may not be suited for IIoT applications. In this work, a joint DOA and carrier frequency offset (CFO) schemes is introduced for typical uplink IIoT systems by equipping the receiver with a leaky-wave antenna (LWA). By considering that the LWA can simultaneously steer its beam direction towards the active user. As a result, each user is estimated independently. The joint algorithm is developed based on the high-resolution MUSIC scheme, which utilizes the LWA properties to compute the DoA spectrum. Furthermore, we develop an iterative CFO estimation approach as the desired solution to a multi-dimensional search. Subsequently, we further formulate the Cramer–Rao lower bounds (CRLB) to serve as a performance benchmark for the accuracy of the proposed scheme. The SDR platform is provided to validate the proposed algorithm in real-time. Finally, the simulation results and the SDR experiments justify that the proposed scheme offers more robustness than conventional counterparts with linear array antenna, which achieves a root mean square error (RMSE) approach to the derived CLRB, especially at a medium signal-to-noise ratio (SNR) range which suited for IIoT applications.

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