Compressive sensing-based channel estimation for high mobile systems with delay Doppler effects

In this paper, channel overhead is reduced by exploiting sparsity for multiple input output-orthogonal frequency division multiplexing (MIMO-OFDM) system. Where, compressive sensing (CS) based dictionary design algorithms has been adopted as a estimation technique in high mobile systems with minimal number of pilots, such high-speed train (HST) systems. A novel framework the dictionary-based CS was proposed considering both delay and Doppler effects order to correctly recover response. The under consideration 2 space-time block code (STBC) MIMO channel. Simulation tests according international telecommunication union (ITU) model demonstrated suitability estimating impulse response (CIR) liner time varying (LTV) mobility approaches 675 Km/h related 1500 Hz 2.4 GHz carrier frequency. Two recovery were applied; orthogonal matching pursuit (OMP) basis (BP), where about 7 dB gain signal noise ratio (SNR) achieved using OMP compared BP at bit error rate (BER) 128 OFDM subcarriers.