Performance Evaluation of CFO and Channel Estimation in Hybrid Tone OFDM Signals

Abstract

Introduction: There is a growing need for high-accuracy signal processing in 5G and future 6G networks. Reconfigurable Intelligent Surface (RIS)-assisted OFDM is a promising solution to enhance channel quality. Hybrid tone OFDM (HT-OFDM) introduces a new approach to improve carrier frequency offset (CFO) and channel estimation.

Objectives: This paper aims to develop an efficient method for joint CFO and channel estimation in HT-OFDM. The goal is to minimize the mean square error (MSE) and improve estimation accuracy.

Methods: The method starts with correlation and least-squares techniques to get initial CFO and channel estimates. A hybrid tone is then inserted into OFDM symbols. This step reduces noise and enhances accuracy by lowering MSE. Simulations and theoretical analysis validate the approach.

Results: At 20 dB SNR, the method reduces MSE to 0.02 when 100 RIS elements are used. The CFO estimation error drops to 0.005 for a CFO value of 0.5. Increasing pilot subcarriers to 32 at 30 dB SNR further lowers MSE to 0.01. Additional hybrid tone symbols show significant improvements in high-SNR conditions.

Conclusions: The proposed method effectively enhances CFO and channel estimation. It achieves significant MSE reduction and improves accuracy in RIS-assisted HT-OFDM systems. This makes it suitable for advanced 5G and 6G networks.