A Novel Integer Frequency Offset Estimation Method for OFDM Based on Preamble

Orthogonal frequency division multiplexing (OFDM) is very sensitive to frequency offset. Although the existence of integer frequency offset in OFDM will not destroy the orthogonality between subcarriers, it will cause a cyclic shift of the frequency domain data after FFT transformation at the receiving end, which will affect the demodulation of data. In this paper, we propose a novel integer frequency offset estimation method based on the similarity property of adjacent subcarriers of the preamble. This method not only guarantees the original accuracy and performance of the conventional method but also achieves less resource consumption and lower computational complexity.

1 Introduction

Orthogonal frequency division multiplexing (OFDM) technology has important applications in many wireless communication fields, with high spectrum utilization and robust fading resistance [1]. However, the receiver synchronization errors, especially frequency offset has a huge influence on the performance of OFDM system. For example, oscillator instabilities frequency mismatch of transceiver system, Doppler shift and complex channel environment will introduce carrier frequency offset (CFO) to an OFDM system, which will lead to frequency offset of subcarrier frequency. The OFDM system performance will have a sharp decline because frequency offset of subcarrier frequency can destroy the orthogonality between subcarriers [2]. The carrier frequency offset is composed by two parts of fractional frequency offset (FFO) and integer frequency offset (IFO). The FFO can cause intercarrier interference (ICI), while IFO will not cause ICI. IFO results in a circular shift of the subcarrier in the frequency domain [3], which influence demodulation of data. The realization of OFDM receiver and transceiver requires a large number of hardware resources. If the IFO estimation module can use fewer resources, it will improve the resource use efficiency of the whole system. To reduce the use of resources while ensuring the performance of the algorithm, new research is carried out in this paper.