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Document Type

Original Study

Keywords

Communication Engineering

Abstract

Over the past four decades, the communication sector has experienced significant economic growth and widespread adoption. Some emerging applications require high data rates, low latency, and must operate efficiently in environments where wireless devices are moving at high speeds. Noise and high device mobility have a considerable impact on received signal frequency, ultimately affecting system performance. So, accurate frequency estimation for received signals is therefore crucial, prompting extensive research. In this paper, we propose a three-step frequency estimation technique. The first stage, termed the coarse stage, employs a few sampling sizes to perform a fast Fourier transform. The second stage utilizes the Candan algorithm to refine the coarse output, while the third stage applies the Generalized Goertzel algorithm for further accuracy. The proposed method offers more precise frequency estimation compared to several wellknown techniques, while significantly reducing latency and computational power requirements. Our proposed result enhances the real-time transfer of vital data, such as telemedical information collected by wearable devices, as well as remote surgeries that require extremely low latency. It offers a viable solution for enhancing the performance of the telecommunications sector, particularly in applications like autonomous vehicles and 5G and beyond, which demand stringent latency requirements

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