Dynamic channel-order estimation algorithm

This correspondence develops a robust method to estimate channel order in a single-input multiple-output (SIMO) or an oversampled single-input single-output (SISO) system. Current methods based on the use of information theoretic criteria for blind channel-order estimation suffer from estimation errors at high signal-to-noise ratio (SNR) and when a large number of samples is used or when subchannels are correlated. The new algorithm exploits (spatial) oversampling and the fact that the linear prediction approach to channel estimation is robust to the overdetermination of channel order. A distinct advantage is that channel estimates are also available after the channel-order estimate is made. The method is robust over a wide SNR range and is independent of correlation in the received channels. Simulation results are presented showing performance and behavior for various SNRs and channel conditions.