Robust Estimation of Channel Statistics from Narrowband Reference Signals

Estimating second-order channel statistics (specifically, frequency-domain covariance matrices) from narrowband reference signals is crucial for channel estimation in 5 G cellular systems. The problem is challenging because of the limited number of available pilot subcarriers. In this work, we reparametrize the problem using a delay-domain characterization. Three algorithms are proposed for estimating the power delay profile (PDP) using least squared error and maximum likelihood estimation frameworks. The algorithms demonstrate a tradeoff between the computational complexity and model insights used to estimate the underlying PDP. The performance of the proposed algorithms is numerically analyzed under different channel conditions and pilot density. The proposed algorithms demonstrate significant gains (up to 3 dB in signal-to-noise ratio), and are robust to noisy delay spread information.