OTFS Channel Estimation and Data Detection Designs With Superimposed Pilots

2022 
We propose a superimposed pilot (SP)-based channel estimation and data detection framework for orthogonal time-frequency space (OTFS) systems, which superimposes low-powered pilots on to data symbols in the delay-Doppler domain. We propose two channel estimation and data detection designs for SP-OTFS systems which, unlike the existing OTFS designs, do not designate any slots for pilots, and consequently have higher spectral efficiency (SE). The first SP design estimates channel by treating data as interference, which degrades its performance at high signal to noise ratio. The second SP design alleviates this problem by iterating between channel estimation and data detection. Both these designs detect data using message passing algorithm which exploits OTFS channel sparsity, and consequently has low computational complexity. We also derive a lower bound on the signal-to-interference-plus-noise ratio of the proposed designs and maximize it by optimally allocating power between data and pilot symbols. We numerically validate the derived analytical results, and show that the proposed designs have superior SE than the existing OTFS channel estimation and data detection designs.
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