Supporting spontaneous low-latency machine type communications requires fast synchronization and channel estimation at the receiver. The problems of synchronizing the received frame and estimating the channel coefficients are often addressed separately with the later one relying on accurate timing acquisition. While these conventional approaches can be adequate in flat fading environments, time dispersive channels can have a negative impact on both tasks and severely degrade the performance of the receiver. To circumvent this large degradation, in this paper we consider the use of a sparse based reconstruction approach for joint timing synchronization and channel estimation by formulating the problem in a form that is closely related to Compressive Sensing(CS) framework. Using modified versions of well-known sparse reconstruction techniques, which can take into account the additional signal structure in addition to sparsity, it is shown through numerical simulations that, even with short training sequences, excellent timing synchronization and channel estimation performance can be achieved, both in single user and multiuser scenarios.

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Channel estimation,Compressive sensing,Sparse signal recovery,Time synchronization

• Mathematics - Natural Sciences
• Electrical Engineering, Electronic Engineering, Information Engineering - Engineering and Technology