Channel Order Estimation Using Gerschgorin Disks in SIMO Systems

So far the majority of blind channel estimation methods mainly utilize the second-order statistics. The performances of these methods are seriously affected by the results of channel order estimation. Under the condition of low signal-to-noise ratio (SNR) and the channel with significant head-tail coefficients, the performances of most channel order estimation methods are not ideal. In this paper, we analyze the relationship between the rank of the sample covariance matrix and the channel order. As the Gerschgorin Disks theory can be used to estimate the rank effectively, we propose a method of channel order estimation based on Gerschgorin Disks. This method constructs an improved adaptive decision threshold, which makes the method more robust under various channel conditions. Simulation results show that this method performs better on channel order estimation when SNR is low and the channel has head-tail coefficients.