OTFS Channel Estimation With Superimposed Pilots Based on Compressed Sensing.

Orthogonal time frequency space (OTFS) modulation has shown better performance in high-mobility communication scenarios compared to orthogonal frequency division multiplexing (OFDM) systems in recent years. Conventional OTFS channel estimation scheme requires guard symbols around pilot symbols to prevent pilot-data interference, which results in a loss of spectral efficiency and high peak-to-average power ratio (PAPR). Hence, in this paper, we propose a partially superimposed pilot scheme, where data symbols are distributed in all the delay-Doppler (DD) bins and pilot symbols are superimposed on them partially. In our scheme, we only need part of the OTFS frame for channel estimation rather than the entire frame in existing superimposed pilot scheme, which reduces complexity significantly. We utilize the sparsity of the DD channel, establish the compressed sensing (CS) model through the double block-cyclic characteristics of sensing matrix and transform the channel estimation problem into a sparse signal recovery problem. We also propose an iterative algorithm to alleviate the pilot interference at the receiver. Moreover, we obtain the optimum pilot-to-data ratio (PDR) through simulations. Simulation results show that the proposed scheme achieves better performance compared to the existing superimposed pilot scheme.