Sai Pradeep Muppaneni

In this paper, we present a novel low-complexity receiver that performs detection and channel estimation tasks in Zak-OTFS modulation using over-sampling in the delay-Doppler (DD) domain. Towards this, we partition the over-sampled signal into multiple two-dimensional (2D) blocks, which is equivalent to parallel branch conventional sampling of delay- and Doppler-shifted signals. This partitioning along with processing only a subset of the partitioned 2D blocks aids in reducing complexity. Specifically, in terms of detection, we propose a symbol-wise selection-based detection (SSD) algorithm which makes symbol-wise decisions based on selection among parallel branch outputs. While the partition based processing reduces complexity, the selection-based symbol decisions offer good performance. We also exploit the proposed partitioning for low-complexity path-wise estimation of the DD channel taps based on maximum energy across blocks. Simulation results with fractional DDs show that the proposed detection and channel estimation algorithms for Zak-OTFS achieve good performance at low complexity.

In this paper, we consider the problem of estimating the delay-Doppler (DD) domain inputoutput (I/O) relation in Zak-OTFS modulation, which is needed for signal detection. Two approaches, namely, model-dependent and model-free approaches, can be employed for this purpose. The modeldependent approach requires explicit estimation of the physical channel parameters (path delays, Dopplers, and gains) to obtain the I/O relation. Such an explicit estimation is not required in the model-free approach, where the I/O relation can be estimated by reading off the samples in the fundamental DD period of the received pilot frame. Model-free approach has the advantage of acquiring fractional DD channels with simplicity. However, the read-off in the model-free approach provides an estimate of the effective channel only over a limited region in the DD plane but it does not provide an estimate for the region outside, and this can affect the estimation performance depending on the pulse shaping characteristics of the DD pulse shaping filter used. A poorly localized DD pulse shape leads to an increased degradation in performance. Motivated by this, in this paper, we propose a novel, yet simple, I/O relation estimation scheme that alleviates the above issue in the model-free approach. We achieve this by obtaining a coarse estimate of the effective channel outside the model-free estimation region using a novel model-dependent scheme and using this estimate along with the model-free estimate to obtain an improved estimate of the overall I/O relation. We devise the proposed estimation scheme for both exclusive and embedded pilot frames. Our simulation results using Vehicular-A, TDL-A and TDL-C channel models with fractional DDs show that the proposed hybrid estimation approach achieves superior performance compared to the pure model-free approach. For example, at a bit error rate (BER) of 1.5 W 10-3, the proposed scheme achieves an SNR gain of about 3.5 dB compared to the model-free approach for sinc filter in Veh-A channel, and this performance gain is achieved with a moderate increase in complexity (e.g., about 2.95W108 and 8.1W108 real operations for model-free approach and the proposed scheme, respectively). Also, the proposed scheme performs close to that of the sparse Bayesian learning (SBL) based estimation but at a significantly lesser complexity (e.g., about 8.3W1012 and 8.1W108 real operations for the SBL based method and the proposed scheme, respectively).

Orthogonal time frequency space (OTFS) waveform is suited for both communication as well as radar sensing. In this paper, we propose an algorithm for efficient channel estimation at the receiver and range/velocity estimation at the transmitter using OTFS. The algorithm processes received pilot frames for channel estimation at the receiver and data frames echoed from the target/user for range and velocity estimation at the transmitter. A key component in the proposed algorithm is the cancellation of inter-path interference (IPI) in the DD domain. The algorithm works for fractional delay-Doppler which is a source of IPI. The proposed algorithm outperforms other channel estimation schemes and also achieves good root mean square error performance of range and velocity estimation.