Channel Estimation and Equalization for CP-OFDM-based OTFS in Fractional Doppler Channels

Optimal Zak-OTFS Receiver and its Relation to the Radar Matched Filter

“…These challenges have been considered before, for the case of integer sampling on transmission grid. For channel estimation, sparse Bayesian learning based models were proposed to estimate the Doppler shifts from the received OTFS pilot symbols [17]- [19]. For OTFS ML detection, message passing based detectors have been proposed [4], [20]- [24].…”

Low pilot overhead channel estimation for CP‐OFDM‐based massive MIMO OTFS system

“…Considering the same situation as in references [23] and [25], we assume a ray‐based quasi‐static propagation channel, $$h(\tau ,\nu )$$ is described as $$\begin{equation} \begin{aligned} h(\tau ,\nu ) = \sum \limits _{p = 1}^P {{h_p}} \delta {\left({\tau - {\tau _p}} \right)}\delta {\left({\nu - {\nu _p}} \right)}, \end{aligned} \end{equation}$$where $$P$$ is the number of propagation paths, $${h_p}$$, $${\tau _p}$$, $${\nu _p}$$ represents the complex Gaussian channel gain, delay, and Doppler shift associated with the $$p$$ propagation path, respectively. Assume $${h_p}$$ is an independent and equally distributed random variable $${h_p} \sim CN({0,\frac{1}{{P}}} )$$, which satisfies $$\sum \nolimits _{p = 1}^{P} \mathcal {E} \lbrace {{{| {{h_p}} |}^2}} \rbrace = 1$$, and …”

“…Considering the same situation as in references [23] and [25], we assume a ray-based quasi-static propagation channel, h(𝜏, 𝜈) is described as…”

A New Micro-Subcarrier OFDM-Based Waveform for Delay Doppler Domain Communication

“…However, the Doppler resolution level is limited since the symbol time has to be small, due to latency constraints and a need to stay within the coherence period of the DD domain channel. As a result, non-integer fractional Doppler shifts need to be considered for practical implementations [5], [19], [20], [21], [22].…”

“…The approach was not applicable to non-integer channels, however a number of related approaches have since been developed based on [5], which address fractional Doppler to an extent, either at a significant increase in complexity or under special assumptions. In [19] and [21] sparse Bayesian learning based models were proposed to estimate the Doppler shifts from the received pilot symbols. In [20] a non-integer channel was approximated by an integer channel by treating each received pilot symbol as an individual path.…”