Time-domain preamble-based SNR estimation for OFDM systems in doubly selective channels

In wireless orthogonal frequency division multiplexing (OFDM) systems, the knowledge of signal-to-noise ratio (SNR) plays an important role for system optimization. Most of the exiting literatures have studied the SNR estimation for perfect synchronization in additive white Gaussian noise (AWGN) channels, or in frequency selective channels. However, the realistic channels are always doubly selective, and there may exist some residual symbol timing offset (STO) and carrier frequency offset (CFO) after coarse synchronization in the time domain. In this paper, we take these into account and propose a time-domain average SNR estimation scheme using one OFDM training symbol (preamble) which has been divided into multiple parts with equal length. Compared with the timedomain low-complexity SNR estimator (TLSE), our proposed time-domain preamble-based SNR estimator (TPSE) can not only be implemented in the presence of STO and CFO, but also generate more accurate SNR estimation for the channels with large Doppler shift. The estimated SNR value based on our scheme in the time-domain can be further reused to improve the ensuing CFO estimation and fine synchronization efficiently.