Iterative channel estimation algorithm based on compressive sensing for GFDM

Abstract

Generalized Frequency Division Multiplexing (GFDM) is a promising solution for the cellular system of the fifth generation (5G) PHY layer because its flexibility can address the different application requirements. However, due to the pulse shaping, there is inherent interference existing in the received signal, which has a negative impact on pilot-based channel estimation. Although the interference on the pilot symbols can be eliminated at the transmitter by using precoding matrices, the accompanied transmitting power penalty increases with the non-orthogonality of subcarriers and subsymbols. In our work, we propose an iterative method for interference cancellation at the receiver, which can efficiently mitigate the effect of neighboring symbols on pilots without transmitting power penalty. In addition, to improve the accuracy of channel estimation, we adopt the compressive sensing (CS) technology. Simulation results show that our proposed channel estimation algorithm is efficient even when the interference is severe, and by using orthogonal match pursuit (OMP) recovery algorithm, the performance of our algorithm can be close to the Cramer-Rao bound (CRB).