AR(1) processes are one of the most popular models in signal processing. Also, stable distributions are good candidates to model sparsity which is in the center of attention of the signal processing community. Knowing the performance of the best possible estimation of a process embedded in AWGN is one of the basic theoretical questions about it. In this project we are going to find bounds on this quantity for stable AR(1) processes.