Compressed Sensing Based Channel Estimation for GFDM Systems in High Mobility Scenario

In this paper a channel estimation method using compressed sensing is proposed for generalized frequency division multiplexing (GFDM) systems in high mobility scenarios. The sparsity of the channel model in the delay-Doppler domain makes it possible to employ the subspace pursuit (SP) algorithm to ease the channel estimation process. Besides, the spectral efficiency is improved through superimposing pilot symbols on the data symbols without requiring any guard between pilot and data symbols. To separate data from pilot symbols for the channel estimation in the delay-Doppler domain, an unknown data-dependent sequence is added to the time-frequency data symbols. Our simulation results show that the proposed algorithm provides accurate channel estimation with low pilot overhead.