Instrumental variable identification of fading channel models from irregularly sampled noisy data

A continuous-time stochastic model is considered for describing fading channels from irregularly sampled data affected by measurement noise. The model parameters are estimated using an instrumental variable approach that gives consistent estimates as the number of data tends to infinity and the upper bound on the irregular sampling interval tends to zero. The proposed estimator is robust to measurement noise, computationally efficient, and easy to implement. Once the model parameters are estimated, the design of efficient algorithms for power control is possible.