We study a linear discrete-time partially observed system perturbed by white noises. The observations are transmitted to the controller via communication channels with irregular transmission times. Various measurement signals may incur independent delays, arrive at the estimator out of order, and be lost or corrupted. The estimator is given a dynamic control over the sensors data by selecting signals to be used from those arrived at the current time. The minimum variance state estimate and the optimal sensor control strategy are obtained. Ideas of model predictive control are employed to derive a non-optimal but implementable in real time method for sensor control.