A Blind ML-SNR Estimation Method for OFDM Systems in Dispersive Fading Channels

Orthogonal Frequency Division Multiplexing (OFDM) is a common used technology for communication systems nowadays. Besides the synchronization of OFDM based receivers, the estimation of the noise variance as well as the corresponding signal-to-noise ratio (SNR) is a challenging issue, especially under dispersive fading channel conditions. In this paper the principle of blind OFDM synchronization via Maximum Likelihood functions is picked up and extended in such a way, that the signal-to-noise ratio can be determined under realistic multipath fading channels. Furthermore the symbol timing offset and the channel length are estimated in advance, to overcome the problem of previous proposed SNR estimation techniques. Besides all existing blind SNR estimation procedures, no computationally inefficient sub procedures are required to find the Inter-Symbol-Interference (ISI) free region to determine the correct SNR value. All extracted parameters can be used to evaluate the signal quality within the receiver and to build up applications such as minimum mean-square error (MMSE) channel estimation. The algorithm is applied to the OFDM based Digital Audio Broadcasting (DAB/DAB+) system and shows excellent performance with less computational effort.