Joint time and frequency synchronization for distributed beamforming in decode-and-forward relaying systems using importance sampling

In this paper, we tackle the problem of joint time and frequency synchronization for decode-and-forward (DF) systems. We devise a new maximum likelihood (ML) algorithm for the joint estimation of these synchronization parameters based on the importance sampling (IS) technique. Unlike the traditional iterative estimation techniques, the proposed IS-based ML approach enjoys guaranteed global optimality. Moreover, it transforms the original multi-dimensional optimization problem into multiple two-dimensional ones, thereby entailing low computational burden. Simulation results show the advantage of the IS-based ML estimator over state-of-the-art estimation techniques.