Compressed sensing based estimation of doubly selective channels using a sparsity-optimized basis expansion

We propose a technique for estimating doubly selective channels within multicarrier communication systems. The new channel estimation technique uses the methodology of compressed sensing for a reduction of the number of pilots, and it employs a basis expansion that is optimized with a criterion of maximum sparsity. Simulation results demonstrate that the optimized basis yields significant performance gains relative to a previously proposed technique.