Optimization on OTFS Modulation Channel Estimation Path Employing CNN-based Self-Adjustment Model

The orthogonal time frequency space (OTFS) modulation has emerged as a promising modulation scheme for high mobility wireless communications. To enable efficient OTFS detection in the delay-Doppler (DD) domain, the DD domain channels need to be acquired accurately. To achieve the low latency requirement in future wireless communications, the time duration of the OTFS block should be small, therefore fractional Doppler shifts have to be considered to avoid significant modelling errors due to the assumption of integer Doppler shifts. However there lack investigations on the estimation of OTFS channels with fractional Doppler shifts in the literature. In this work, we develop a channel estimator for OTFS with particular attention to fractional Doppler shifts, and both bi-orthogonal waveform and rectangular waveform are considered. Instead of estimating the DD domain channel directly, we estimate the channel gains and (fractional) Doppler shifts that parameterize the DD domain channel. The estimation is formulated as a structured sparse signal recovery problem with a Bayesian treatment. Based on a factor graph representation of the problem, an efficient message passing algorithm is developed to recover the structured sparse signal (thereby the OTFS channel). The Cramer-Rao Lower Bound (CRLB) for the estimation is developed and the effectiveness of the algorithm is demonstrated through simulations.

In this paper, a near-optimal Karhunen-Loeve basis expansion modeling (KL-BEM) orthogonal time frequency space (OTFS) receiver with superimposed pilots has been proposed for high-mobility communications over time-varying channels with Doppler and delay spread. First, an initial KL-BEM channel estimation is conducted using superimposed pilots, followed by the removal of superimposed pilots from the received OTFS signal and equalization based on message passing (MP) algorithm. After that, the detected data symbols are utilized as pseudo pilots together with the superimposed pilots to refine both KL-BEM channel estimation and equalization in an iterative manner. Simulation results confirm the superior performance of the proposed KL-BEM OTFS receiver over prior art in terms of bit error rate (BER). The resulting BER performance is close to the lower bound obtained by assuming perfect channel estimation. Besides, the proposed scheme provides high spectral efficiency, while featuring fast convergence and affordable complexity.

In this study, the Peak-to-Average Power Ratio (PAPR) and Bit Error Rate (BER) performance in Orthogonal Time Frequency Space (OTFS) modulation with Non-Orthogonal Multiple Access (NOMA) over Rayleigh fading channels were investigated. Simulations with 256-QAM and 512-QAM modulation schemes on 256 subcarriers evaluated several PAPR reduction techniques, including the Vandermonde matrix-based Partial Transmit Sequence with Companding (Vm-PTS+Companding), Vm-SLM+Companding, conventional PTS, Selective Mapping (SLM), Companding, and Clipping & Filtering (C&F). The proposed Vm-PTS+Companding achieves up to 9dB PAPR reduction for 256-QAM and 8.9dB for 512-QAM at a Complementary Cumulative Distribution Function (CCDF) of [Formula: see text], outperforming existing methods. Under a [Formula: see text] channel estimation error, the PAPR performance degrades, yet the proposed scheme maintains a 2.9-9.9dB gain over conventional approaches. BER analysis showed Signal-to-Noise Ratio (SNR) improvements of 3.5-13.7dB in ideal channels and up to 16dB under error conditions. Power Spectral Density (PSD) evaluation further confirmed the reduced spectral leakage, with the method achieving a level of [Formula: see text]dB. These results demonstrate that Vm-PTS+Companding effectively optimizes both the PAPR and BER in OTFS-NOMA systems, supporting high data rates in error-prone wireless environments.

Known as a new promising waveform modulation technique, the orthogonal time-frequency space (OTFS) technique is considered a very important waveform modulation technique that modulates data in the delay-Doppler (DD) domain. The key difference between OTFS and the traditional multiplexing techniques is that it is two-dimensional modulation that converts between the time-frequency (TF) domain and delay-Doppler domain, these features enable dealing with the Doppler shift generated from high mobility objects which were ignored in the traditional modulation techniques such as orthogonal frequency division multiplexing (OFDM). The main objective of this survey is to provide an overview of this novel subject indicating its system model. Also, we review the main topics related to OTFS modulation as data detection techniques, channel estimation, MIMO, and multiuser systems. Then, the main research direction of OTFS on future wireless generation systems is given.

A doppler delay-time frequency (DD-TF) cross-domain high-security transmission scheme based on orthogonal time frequency space (OTFS) is proposed, which is compatible with high-speed and large-capacity optical transmission systems. In this scheme, 36 sets of chaotic sequences are mapped out through a two-dimensional chaotic system with variable control parameters and variable initial values for optical physical layer encryption. The data modulated based on OTFS is encrypted by multiple sets of chaotic sequences, achieving cross-domain joint encryption in the DD domains and TF domains. This method improves security performance of the optical transmission system. An experiment is conducted, in which the encrypted 16-quadrature amplitude modulation (QAM) OTFS signals over 25km standard single-mode fiber (SSMF) is achieved, and the key space is 101140 to effectively prevent malicious attacks from illegal Optical Network Units (ONUs). This key space is the reported maximum key space of the physical layer of two-dimensional chaotic systems. Compared with orthogonal frequency division multiplexing (OFDM) encryption scheme, this scheme obtains better transmission performance. It is shown that OTFS system with cyclic prefix (CP) of 1/16 obtains 2.1dB gain than the OTFS system with CP of 1/32 in terms of receiver sensitivity when the bit error rate (BER) is 10-3. Due to its comprehensive advantages in error rate and security performance, this chaotic encryption based on OTFS has a high application prospect in low-cost and reliable optical access system.

PAPR analysis in OTFS using the centre phase sequence matrix based PTS method

Orthogonal time frequency space (OTFS) modulation scheme is based on a novel 2-dimensional modulation technique designed to transform the time-varying multi-path channel into a time invariant Delay- Doppler channel. In general, the Message Passing (MP) algorithm works well for data detection in OTFS, but its complexity is quite large. In this paper, a low complexity MP algorithm for data detection in OTFS is presented based on a Doppler compensation precoder and a modified stopping criterion. Besides, an improved Approximate Message Passing (AMP) algorithm based on covariance processing, having almost the same complexity as that of conventional AMP algorithm, but exhibiting better bit error rate(BER) performance is presented, as demonstrated by simulation results.

This paper proposes a novel joint channel and data estimation (JCDE) algorithm via parametric bilinear Gaussian belief propagation (PBiGaBP) for orthogonal time frequency space (OTFS) demodulation. In doubly-selective fading channels, since the Doppler shift breaks the orthogonality between subcarriers, the signal demodulation process requires estimating the path gains and data symbols from the high-dimensional signals that are multiplexed in the frequency-time (FT) domain. To obtain highly accurate channel state information (CSI) using a typical channel estimation scheme based only on reference signals, an increase in pilot overhead to suppress inter-symbol interference (ISI) is unavoidable. In addition, large-scale matrix operations based on the size of OTFS-equivalent channels also pose problems in terms of computational cost. To address these issues, we focus on the fact that OTFS demodulation can be formulated as a large-scale parametric bilinear inference (PBI) problem, and solve it using the Gaussian belief propagation (GaBP) approach, which enables an approximate implementation of the sum-product algorithm (SPA), based on the central limit theorem (CLT), to design a low-complexity and high-accuracy JCDE algorithm using short pilots. Simulation results show that the proposed PBiGaBP-based JCDE algorithm outperforms the state-of-the-art (SotA) schemes and approaches the performance of idealized (genie-aided) scheme in terms of mean square error (MSE) and bit error rate (BER) performances.

Orthogonal time frequency space (OTFS) is a new emerging modulation scheme that performs better than orthogonal frequency division multiplexing (OFDM) in high mobility scenarios. In this paper, we consider the delay-Doppler (DD) channel estimation problem in an OTFS system. By exploiting the inherent sparse nature of the DD channel, the channel estimation problem is modeled as a sparse signal recovery problem. Next, we build a two-layer graphical model with the Laplacian scale mixture (LSM) prior utilized to model the sparse channel. Then, a variational Bayesian inference (VBI) based algorithm is proposed to solve this problem. Simulation results are presented to show that the proposed algorithm can achieve better performance than other existing channel estimation algorithms.

Orthogonal time frequency space (OTFS) modulation is a recently introduced modulation which has been shown to perform better than OFDM in RF wireless communications. In this paper, we investigate OTFS in multi-LED indoor visible light wireless communications. We propose two multi-LED OTFS schemes, namely, quadrature spatial modulation OTFS (QSMOTFS) scheme and dual mode index modulation OTFS (DMIMOTFS) scheme. The proposed schemes use dual-LED complex modulation as the basic building block and offer enhanced rates compared to conventional index modulation schemes. The schemes also have the advantage of not requiring Hermitian symmetry and DC bias operations to obtain real, positive-valued signals suited for intensity modulation of LEDs. We obtain upper bounds on the bit error rate performance of the proposed schemes, which are tight at high signal-to-noise ratios. The proposed OTFS schemes are shown to perform better than their OFDM counterparts known in the literature. In addition, the spatial distribution of the performance gap between OTFS and OFDM across the room is captured using the ratio of the minimum distance of normalized received signal sets of the considered schemes as a metric.

Orthogonal time frequency space (OTFS) modulation is an emerging technique for next-generation communication due to its robustness to the doubly dispersive channels under high mobility scenarios. We have designed and analyzed a deep learning (DL)-based OTFS system (DL-OTFS) in the presence of hardware impairments (HI) such as in-phase and quadrature-phase (IQ) component mismatch and DC offset. Further, data augmentation is also considered for the proposed DL-OTFS to enhance the system performance. Numerical results show that the DL-OTFS model can efficiently learn the input and output relation and leads to improved bit error rate (BER) performance than the conventional message passing and minimum mean square error (MMSE)-based receiver with and without HI.

Design of simple transceiver architectures is inevitable in order to provide low computational complexity, low power consumption and affordable cost in beyond 5G (B5G) wireless systems, but it results in hardware impairments that significantly degrade the performance reliability of transmission. In this paper, among these hardware impairments, we discuss in-phase and quadrature (IQ) imbalance in orthogonal time frequency space (OTFS), which is a recent waveform considered as a potential candidate for B5G systems to relax the vulnerability against time-variant wireless channels. To mitigate the effect of IQ imbalance for OTFS, we propose an energy and spectral efficient IQ imbalance compensation scheme with the aid of index modulation (IM), which provides an attractive flexibility in the system design. In contrast to conventional solutions used in classical wireless technologies, such as iterative and pilot-based techniques, the proposed scheme avoids additional energy consumption and significant spectral efficient loss during the estimation and compensation of the IQ imbalance effect. The obtained bit error rate (BER) results validate the accuracy of the proposed compensator for different OTFS system configurations considering perfect/imperfect channel state information in practical scenarios.

Orthogonal time frequency space (OTFS) modulation exhibits excellent performance in time-varying channels with severe Doppler shifts. Diversity analysis is an effective method in predicting error performance of an OTFS system. Recent works have studied OTFS diversity in a time-varying channel assuming constant delay-Doppler (DD) channel realization per frame. However, in practice, DD channel realizations may vary in a frame due to the rapid changes in channel geometry relative to a frame duration, leading to a block time-varying (BTV) channel. This paper analyzes the OTFS diversity in such BTV channels. Specifically, we derive the pairwise error probability of the system and analyze its diversity by finding the minimum rank of the pairwise error matrix and its associated multiplicity. We also compare it with other known schemes and demonstrate its improved diversity. Finally, simulations are performed to validate the analytical results.

By selecting various active-silent combinations, classical frequency-domain index modulation (IM) generates numerous energy-free subcarriers dispersed across subblocks, which we refer to as the fragmented spectra. This letter proposes a novel IM approach aimed at collecting the fragmented spectra in subblocks to form a completely unused frequency band, called the IM-aided fragmented spectra centralization (IM-FSC). Specifically, within each subblock, if the last subcarrier is to be activated, we transfer this active position to the first unactivated subcarrier and employ a distinguishable constellation to modulate the symbol on this subcarrier. Through this approach, each subblock contributes one energy-free subcarrier, and the unused frequency band can be obtained accordingly by combining these fragmented spectra from multiple subblocks. We designate this unoccupied frequency band as zero padding (ZP) and guard interval for interference cancellation and channel estimation in orthogonal time frequency space (OTFS) system. The closed-form expressions of bit error rate (BER) and generalization guidelines are also derived. Simulation results demonstrate the promising communication capability and channel estimation accuracy of the proposed scheme.

This work proposes a superimposed pilot (SP)-based channel estimation and data detection framework for orthogonal time-frequency space (OTFS) scheme, wherein low-powered pilots are superimposed on to data symbols in the delay-Doppler domain. We propose an iterative channel estimation and data detection design for SP-OTFS systems which, unlike the existing OTFS designs, does not designate any slots for pilots, which improves its spectral efficiency (SE). The proposed design iterates between message-passing-aided data detection and data-aided channel estimation. The data-detection and channel-estimation steps of the proposed design exploit the OTFS channel sparsity, which reduces its computational complexity. We numerically show that the proposed design has superior SE than the two state-of-the-art OTFS channel estimation and data detection designs.