1.
Mehrotra, Anand; Srivastava, Suraj; Reddy, N. Shanmughanadha; Jagannatham, Aditya; Hanzo, Lajos
Sparse Channel Estimation for MIMO OTFS/OTSM Systems Using Finite-Resolution ADCs Journal Article
In: IEEE Transactions on Communications, vol. 73, no. 6, pp. 3971–3987, 2025, ISSN: 1558-0857.
Abstract | Links | BibTeX | Tags: Bayes methods, Channel estimation, delay-Doppler, delay-sequency, Estimation, finite-resolution ADCs, Modulation, OFDM, OTFS, OTSM, Quantization (signal), Receivers, Signal processing algorithms, Signal resolution, sparsity, Time-domain analysis
@article{mehrotra_sparse_2025,
title = {Sparse Channel Estimation for MIMO OTFS/OTSM Systems Using Finite-Resolution ADCs},
author = {Anand Mehrotra and Suraj Srivastava and N. Shanmughanadha Reddy and Aditya Jagannatham and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10758799},
doi = {10.1109/TCOMM.2024.3502682},
issn = {1558-0857},
year = {2025},
date = {2025-06-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Communications},
volume = {73},
number = {6},
pages = {3971–3987},
abstract = {Variational Bayesian learning (VBL)-based sparse channel state information (CSI) estimation is conceived for multiple input multiple output (MIMO) orthogonal time frequency space (OTFS) and for orthogonal time sequence multiplexing (OTSM)-based systems relying on low-resolution analog-to-digital convertors (ADCs). First, the CSI estimation model is developed for MIMO-OTFS systems considering quantized outputs. Then a novel VBL technique is developed for exploiting the inherent DD domain sparsity. Subsequently, an end-to-end system model is derived for MIMO-OTSM systems, once again, using only finite-resolution ADCs. Similar to OTFS systems, it is demonstrated that the channel is sparse in the delay-sequency (DS)-domain. Thus the sparse CSI estimation problem of the MIMO-OTSM system can also be solved using the VBL technique developed for its OTFS counterpart. A bespoke minimum mean square error (MMSE) receiver is developed for data detection, which unlike the conventional MMSE receiver also accounts for the quantization error. Finally, finite-resolution ADCs emerge as a solution, offering reduced costs and energy consumption amid the growing challenge posed by energy-intensive high-resolution ADCs in Next-Generation (NG) systems. The efficacy of the proposed techniques is validated by simulation results, surpassing the state-of-the-art and signalling a transition towards more sustainable communication technologies.},
keywords = {Bayes methods, Channel estimation, delay-Doppler, delay-sequency, Estimation, finite-resolution ADCs, Modulation, OFDM, OTFS, OTSM, Quantization (signal), Receivers, Signal processing algorithms, Signal resolution, sparsity, Time-domain analysis},
pubstate = {published},
tppubtype = {article}
}
Variational Bayesian learning (VBL)-based sparse channel state information (CSI) estimation is conceived for multiple input multiple output (MIMO) orthogonal time frequency space (OTFS) and for orthogonal time sequence multiplexing (OTSM)-based systems relying on low-resolution analog-to-digital convertors (ADCs). First, the CSI estimation model is developed for MIMO-OTFS systems considering quantized outputs. Then a novel VBL technique is developed for exploiting the inherent DD domain sparsity. Subsequently, an end-to-end system model is derived for MIMO-OTSM systems, once again, using only finite-resolution ADCs. Similar to OTFS systems, it is demonstrated that the channel is sparse in the delay-sequency (DS)-domain. Thus the sparse CSI estimation problem of the MIMO-OTSM system can also be solved using the VBL technique developed for its OTFS counterpart. A bespoke minimum mean square error (MMSE) receiver is developed for data detection, which unlike the conventional MMSE receiver also accounts for the quantization error. Finally, finite-resolution ADCs emerge as a solution, offering reduced costs and energy consumption amid the growing challenge posed by energy-intensive high-resolution ADCs in Next-Generation (NG) systems. The efficacy of the proposed techniques is validated by simulation results, surpassing the state-of-the-art and signalling a transition towards more sustainable communication technologies.