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}
}
Lu, Zhou; El-Hajjar, Mohammed; Yang, Lie-Liang
Wavelet Transform Aided Single-Carrier FDMA With Index Modulation Journal Article
In: IEEE Open Journal of Vehicular Technology, vol. 6, pp. 1524–1538, 2025, ISSN: 2644-1330.
Abstract | Links | BibTeX | Tags: detection, Frequency division multiaccess, Frequency-domain analysis, index modulation, Indexes, Maximum likelihood detection, Modulation, OFDM, Peak to average power ratio, peak-to-average power ratio, single carrier-frequency division multiple access (SC-FDMA), spatial modulation, Symbols, Time-domain analysis, Vectors, Wavelet, Wireless communication
@article{lu_wavelet_2025,
title = {Wavelet Transform Aided Single-Carrier FDMA With Index Modulation},
author = {Zhou Lu and Mohammed El-Hajjar and Lie-Liang Yang},
url = {https://ieeexplore.ieee.org/document/11021437},
doi = {10.1109/OJVT.2025.3576062},
issn = {2644-1330},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Open Journal of Vehicular Technology},
volume = {6},
pages = {1524–1538},
abstract = {Single-carrier frequency-division multiple access (SC-FDMA) is a well-known multiuser transmission method for uplink communications owing to its low peak-to-average power ratio (PAPR) characteristics. Simultaneously, index modulation (IM) has been widely studied owing to its flexibility for spectral-efficiency versus energy-efficiency trade-off. However, applying conventional IM schemes with SC-FDMA may affect the desirable characteristics of SC-FDMA signals, resulting in the increase of PAPR, for example. On the other side, Wavelet Transform (WT) has been shown to provide an improved performance over the fast Fourier transform (FFT)-based SC-FDMA, owing to WT's local focusing capability in both time and frequency domains. In this paper, we propose three IM schemes, namely Symbol Position Index Modulation (SPIM), Spreading Matrix Index Modulation (SMIM) and Joint Matrix-Symbol Index Modulation (JMSIM) schemes, which perform IM at the symbol vector level, spreading matrix level, or a combination of both. These IM schemes are implemented with the WT-based SC-FDMA for data transmission. We consider two spreading matrix design schemes, namely random dispersion matrix design and Gram-Schmidt (GS) orthogonalization matrix design. Correspondingly, we propose different detection schemes, including Maximum Likelihood Detection (MLD), Simplified Maximum Likelihood Detection (SMLD), and the Two Stage Index-QAM Detection (TSD). The performance of the proposed schemes is evaluated by simulations. Our studies and results show that all the three schemes can effectively reduce the PAPR encountered by the conventional IM-assisted SC-FDMA signals. Moreover, the method of GS matrices can provide a gain upto 20 dB compared with the method of random dispersion matrices. Furthermore, the GS-based system can employ the proposed low-complexity TSD, allowing to achieve a similar bit error rate (BER) performance as MLD, while requiring significantly low complexity.},
keywords = {detection, Frequency division multiaccess, Frequency-domain analysis, index modulation, Indexes, Maximum likelihood detection, Modulation, OFDM, Peak to average power ratio, peak-to-average power ratio, single carrier-frequency division multiple access (SC-FDMA), spatial modulation, Symbols, Time-domain analysis, Vectors, Wavelet, Wireless communication},
pubstate = {published},
tppubtype = {article}
}