Blind carrier frequency offset estimation techniques for next-generation multicarrier communication systems: challenges, comparative analysis, and future prospects

Abstract

Frequency synchronization is essential to achieving the intended performance for single and multicarrier wireless systems. Blind techniques, which don't require prior channel knowledge or pilot symbols, are crucial for dynamic environments where self-adaptive synchronization is needed. A key objective of this paper is to provide the readers as well as the industry's professionals with a comprehensive understanding of the carrier frequency offset (CFO) problem in multicarrier communication systems like orthogonal frequency division multiplexing (OFDM), single carrier-frequency division multiple access (SC-FDMA), multiple input multiple output (MIMO)-OFDM, and MIMO-SC-FDMA. These waveforms are used in today's and future wireless communication systems such as wireless-fidelity (Wi-Fi), fifth-generation, and sixth-generation. Moreover, this paper also develops a taxonomy of the available solutions to address the CFO issue. We study blind techniques for CFO estimation presented in the recent literature and give potential future directions. We summarize various statistical methods and deep learning algorithms for CFO estimation and emphasize their advantages and limitations. We also incorporate the CFO impact on next-generation wireless systems such as orthogonal time frequency space and reconfigurable intelligent surface-assisted communication systems and provide a broader and deeper knowledge of the area. We provide simulation results of some existing estimators and their performance comparison in terms of mean square error for better understanding. Therefore, this paper is perfectly adapted to provide a comprehensive information source on blind CFO estimation techniques.