A low-complexity null space-based method for blind CFO and DCO estimator in OFDM systems

Although orthogonal frequency division multiplexing (OFDM) holds great potentials for the next generation wireless communication demands, the carrier frequency offset (CFO) and the DC Offset (DCO) in many practical systems can cause the loss of subcarrier orthogonality and hence severe performance degradation. So far, in the absence of DCO, one most successful CFO estimation approach makes use of the signal null space. However, with DCO, the same kind of easy to-implement null space to both the CFO and DCO terms have not been discovered. A compromise solution has been proposed to first project the signal onto the null space of the DCO term, then carry out the singular value decomposition (SVD) to find out the null space of the resulting CFO term. Although very accurate CFO estimation results can be obtained this way, the involved high computational complexity may pose a major hindrance to its practical deployment. In this paper, we show that it is possible to construct a null space to both the CFO and DCO terms. Our particular construction makes use of the Householder transform. As a consequence, the null space approach to CFO estimation in the presence of DCO can be done just as easily as in the absence of DCO, without having to resort to SVD. Experimental results show that the proposed method can obtain the same estimation accuracy as the state of the art methods, yet with much lower complexity and more than 10 times the speedup gain.