Orthogonal Time Frequency Space Modulation Research Articles

Cross-Water–Air Optical Wireless Communication Using Orthogonal Time–Frequency Space Modulation

This paper examines the communication difficulties encountered in cross-media wireless optical transmission through simulated research on the utilization of orthogonal time and frequency space (OTFS) modulation technology. Our analysis and comparison demonstrate that OTFS significantly improves the reliability and throughput of data transmission in intricate multipath channel settings. In contrast to conventional orthogonal frequency division multiplexing (OFDM) technology, OTFS displays better resilience and transmission effectiveness. We foresee additional enhancements and progress in OTFS technology to present a sturdier and more efficient resolution for wireless communication, thereby providing valuable perspectives and encouragement for associated research initiatives. Our results underscore the capability of OTFS technology to transform wireless communication systems in demanding multipath channel conditions.

A hybrid detection algorithm for 5G OTFS waveform for 64 and 256 QAM with Rayleigh and Rician channels

Abstract Signal detection in orthogonal time frequency space modulation is one of the critical aspects for enhancing the throughput of the beyond fifth-generation framework, especially in challenging environments characterized by high mobility and multipath propagation. In this work, we proposed a hybrid detection algorithm by combining zero-forcing equalization (ZFE) and minimum square error equalization (MMSE), also known as ZFE–MMSE, with Rician and Rayleigh channels for 64 and 256 quadrature amplitude modulation. The combination of ZFE and MMSE allows for a more comprehensive approach to equalization. ZFE addresses channel-induced distortions, while MMSE tackles the impact of noise. Together, they enhance the overall performance of the equalization process, resulting in improved signal detection accuracy. The analysis and comparison of the simulation parameters with traditional detection systems include bit error rate, power spectral density (PSD), and complexity. The projected algorithms achieve a signal-to-noise ratio and a PSD gain of 2 dB and −800, respectively, outperforming the traditional detection techniques.

Spatial‐Doppler domain precoding for orthogonal time frequency space modulation with rake detector

Spatial‐Doppler domain precoding for orthogonal time frequency space modulation with rake detector

Low Complexity Turbo SIC-MMSE Detection for Orthogonal Time Frequency Space Modulation

Low Complexity Turbo SIC-MMSE Detection for Orthogonal Time Frequency Space Modulation

Integrated Sensing and Communication via Orthogonal Time Frequency Space Signaling with Hybrid Message Passing Detection and Fractional Parameter Estimation.

For the orthogonal time frequency space (OTFS) modulation, we generally multiplex symbols on a new type of carrier waveform in the delay-Doppler (DD) domain. These two parameters can be used to infer the range (R) and velocity (V) of the communication user and sensing target; thus, it is natural for the OTFS to be implemented in integrated sensing and communication (ISAC). A framework for ISAC based on OTFS modulation is proposed in this paper, in which the matched filter scheme with fractional parameter estimation is implemented for radar sensing. In addition, the hybrid message passing (MP) detection algorithm is developed for OTFS symbol demodulation. According to the simulation results, fractional DD shifts associated with multiple targets can be accurately obtained through the proposed framework. Meanwhile, the bit error rate under the proposed detector is less than 10-4 when the signal-to-noise ratio is high enough.

Beam-Space MIMO Radar for Joint Communication and Sensing With OTFS Modulation

Motivated by automotive applications, we consider joint radar sensing and data communication for a system operating at millimeter wave (mmWave) frequency bands, where a Base Station (BS) is equipped with a co-located radar receiver and sends data using the Orthogonal Time Frequency Space (OTFS) modulation format. We consider two distinct modes of operation. In <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Discovery</i> mode, a single common data stream is broadcast over a wide angular sector. The radar receiver must detect the presence of not yet acquired targets and perform coarse estimation of their parameters (angle of arrival, range, and velocity). In <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Tracking</i> mode, the BS transmits multiple individual data streams to already acquired users via beamforming, while the radar receiver performs accurate estimation of the aforementioned parameters. Due to hardware complexity and power consumption constraints, we consider a hybrid digital-analog architecture where the number of RF chains and A/D converters is significantly smaller than the number of antenna array elements. In this case, a direct application of the conventional MIMO radar approach is not possible. Consequently, we advocate a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">beam-space approach</i> where the vector observation at the radar receiver is obtained through a RF-domain beamforming matrix operating the dimensionality reduction from antennas to RF chains. Under this setup, we propose a likelihood function-based scheme to perform joint target detection and parameter estimation in Discovery, and high-resolution parameter estimation in Tracking mode, respectively. Our numerical results demonstrate that the proposed approach is able to reliably detect multiple targets while closely approaching the Cramér-Rao Lower Bound (CRLB) of the corresponding parameter estimation problem.

Secure precoding design for high-mobility systems with OTFS modulation

This paper investigates a downlink high-mobility secure communication system with orthogonal time–frequency space (OTFS) modulation. In order to achieve secure transmission, a secure precoding scheme based on a privacy-preserving method is proposed, in which a projection matrix with artificial noise (AN) is introduced to disturb eavesdropper. Specifically, the normalized projection matrix of AN, the normalized precoding matrix of desired signals, and the power allocation coefficients are alternatively optimized. The projection matrix and precoding matrix are first derived in closed-form with the normalization constraints and fixed power allocation. Then, the power allocation coefficients are obtained by solving a secure rate maximization problem. Simulation results show that the proposed privacy-preserving projection matrix can effectively interfere with eavesdropping from the illegitimate user, and the proposed secure precoding scheme has significant performance gains over the existing schemes.

Cell-Free Massive MIMO With OTFS Modulation: Statistical CSI-Based Detection

We study the downlink spectral efficiency (SE) of a cell-free massive multiple-input multiple-output (CF-mMIMO) system with orthogonal time frequency space (OTFS) modulation. Each user equipment (UE) uses the minimum mean-squared error-based successive interference cancellation (MMSE-SIC) scheme to detect the received signal. Given the statistical channel information at the UEs, an analytical closed-form expression for the downlink SE is derived. To improve the per-user SE, a max-min fairness resource allocation is proposed and developed. Numerical results show that the proposed resource allocation strategies for superimposed pilot-based (SP-CHE) and embedded pilot-based channel estimation (EP-CHE) achieve up to 43% and 65% performance gain over the baseline system without power allocation.

A Structured Sparse Bayesian Channel Estimation Approach for Orthogonal Time-Frequency Space Modulation.

Orthogonal time-frequency space (OTFS) modulation has been advocated as a promising waveform for achieving integrated sensing and communication (ISAC) due to its superiority in high-mobility adaptability and spectral efficiency. In OTFS modulation-based ISAC systems, accurate channel acquisition is critical for both communication reception and sensing parameter estimation. However, the existence of the fractional Doppler frequency shift spreads the effective channels of the OTFS signal significantly, making efficient channel acquisition very challenging. In this paper, we first derive the sparse structure of the channel in the delay Doppler (DD) domain according to the input and output relationship of OTFS signals. On this basis, a new structured Bayesian learning approach is proposed for accurate channel estimation, which includes a novel structured prior model for the delay-Doppler channel and a successive majorization-minimization (SMM) algorithm for efficient posterior channel estimate computation. Simulation results show that the proposed approach significantly outperforms the reference schemes, especially in the low signal-to-noise ratio (SNR) region.

Generalized Index Modulation for MIMO-OTFS Transmission

Recently, the combination of multiple-input multiple-output technology with orthogonal time frequency space modulation (MIMO-OTFS) has drawn extensive attention with the advantage of exploring the additional transmit diversity or spatial multiplexing of the MIMO scheme. Motivated by the potential spectral efficiency of multi-domain index modulation, in this paper, we propose a generalized index modulation based MIMO-OTFS (GIM-MIMO-OTFS) to convey extra information with the aid of the spatial and delay-Doppler indices. To reduce the supreme complexity of maximum likelihood (ML) detection with a large size of look-up table in GIM-MIMO-OTFS, a two stage index detector based on power information is presented. Furthermore, the analytical expression of average bit error probability (ABEP) is derived to evaluate the performance of the proposed scheme. Simulation results demonstrate the enhanced performance of the proposed scheme in high-mobility scenarios, and highlight the complexity and outperformance of the proposed detector compared to ML detector.

A Novel Cyclic Prefix Configuration for Enhanced Reliability and Spectral Efficiency in OTFS Systems

In practical transmission, orthogonal time-frequency-space (OTFS) is implemented using different prefix configurations including reduced-cyclic prefix (RCP) and full-CP (FCP). This letter presents a novel OTFS structure, which is a modification of the FCP structure in OTFS modulation. The proposed approach leverages the FCP structure in the delay-Doppler domain to decode the information in the CP block rather than discarding it at the receiver to enhance the system performance. This is validated via simulations in terms of the reduction in channel estimation overhead as well as the improved signal-to-noise ratio (SNR) of the received signal.

Performance analysis for orthogonal time frequency space modulation systems with generalized waveform

Orthogonal time-frequency space (OTFS), which exhibits beneficial advantages in high-mobility scenarios, has been considered as a promising technology in future wireless communication systems. In this paper, a universal model for OTFS systems with generalized waveform has been developed. Furthermore, the average bit error probability (ABEP) upper bounds of the optimal maximum likelihood (ML) detector are first derived for OTFS systems with generalized waveforms. Specifically, for OTFS systems with the ideal waveform, we elicit the ABEP bound by recombining the transmitted signal and the received signal. For OTFS systems with practical waveforms, a universal ABEP upper bound expression is derived using moment-generating function (MGF), which is further extended to MIMO-OTFS systems. Numerical results validate that our theoretical ABEP upper bounds are concur with the simulation performance achieved by ML detectors.

Doubly-Iterative Sparsified MMSE Turbo Equalization for OTFS Modulation

Currently, orthogonal time frequency space (OTFS) modulation has drawn much attention to reliable communications in high-mobility scenarios. This paper proposes a doubly-iterative sparsified minimum mean square error (DI-S-MMSE) turbo equalizer, which iteratively exchanges the extrinsic information between a soft-input-soft-input (SISO) MMSE estimator and a SISO decoder. Our proposed equalizer does not suffer from short loops and approaches the performance of the near-optimal symbol-wise maximum a posteriori (MAP) algorithm. To exploit the inherent sparsity of OTFS system, we resort to graph theory to investigate the sparsity pattern of the channel matrix, and propose two sparsification guidelines to reduce the complexity of calculating the matrix inverse at the MMSE estimator. Then, we apply two iterative algorithms to MMSE estimation, i.e., the Generalized Minimal Residual (GMRES) and Factorized Sparse Approximate Inverse (FSPAI) algorithms. The former is used at the initial turbo iteration, whose global convergence is proven in our equalizer, while the latter is used at the subsequent turbo iterations with the help of our proposed guidelines. Simulation results demonstrate that our equalizer can achieve a good bit-error-rate (BER) performance regardless of the fractional Doppler, and only has a linear order of complexity.

OTFS modulation and PAPR reduction for IoT-railways

The internet of things (IoT) has been widely considered to be integrated with high-speed railways to improve safety and service. It is important to achieve reliable communication in IoT for railways (IoT-R) under high mobility scenarios and strict energy constraints. Orthogonal time frequency space (OTFS) modulation is a two-dimensional modulation technique that has the potential to overcome the challenges in high Doppler environments. In addition, OTFS can have lower peak-to-average power ratio (PAPR) compared to orthogonal frequency division multiplexing, which is especially important for the application of IoT-R. Therefore, OTFS modulation for IoT-R is investigated in this paper. In order to decrease PAPR of OTFS and promote the application of OTFS modulation in IoT-R, the peak windowing technique is used in this paper. This technique can reduce the PAPR of OTFS by reducing the peak power and does not require multiple iterations. The impacts of different window functions, window sizes and clipping levels on PAPR and bit error rate of OTFS are simulated and discussed. The simulation results show that the peak windowing technique can efficiently reduce the PAPR of OTFS for IoT-R.

Orthogonal Time Frequency Space Modulation—Part I: Fundamentals and Challenges Ahead

This letter is the first part of a three-part tutorial on orthogonal time frequency space (OTFS) modulation, which is a promising candidate waveform for future wireless networks. This letter introduces and compares two popular implementations of OTFS modulation, namely the symplectic finite Fourier transform (SFFT)- and discrete Zak transform (DZT)-based architectures. Based on these transceiver architectures, fundamental concepts of OTFS modulation, including the delay-Doppler (DD) domain, DD domain information multiplexing, and its potential benefits, are discussed. Finally, the challenges ahead for OTFS modulation are highlighted.

Guest editorial: Orthogonal time frequency space modulation in 6G era

Over the past decades, wireless technologies with reliable data transmissions and precise sensing ability in hostile environments are much less understood and significantly under-developed. The DD domain waveform, e.g., orthogonal time frequency space (OTFS), has been recognized globally for its great potential to achieve high-reliable communications and robust sensing performance under various channel conditions in 6G era.

Auto-Encoder Based Orthogonal Time Frequency Space Modulation and Detection With Meta-Learning

To tackle a Doppler sensitivity problem of orthogonal frequency division multiplexing (OFDM), orthogonal time frequency space (OTFS) has been investigated, where information is carried over delay-Doppler domain. In this paper, to improve communication reliability in doubly dispersive channel, an auto-encoder (AE)-based OTFS modulation and detection scheme is developed, where the transmit OTFS waveform and its associated detection scheme at the receiver are jointly optimized in a deep learning framework. However, the conventional AE architecture which takes one-hot encoded input vector is hard to be reused in OTFS due to its enormous input dimensionality that increases exponentially on the number of grid points in delay-Doppler domain. To overcome it, we divide the delay-Doppler grid into multiple subblocks and associate the one-hot encoded vector with each subblock. Then, by concatenating them, one multi-hot vector is formed and exploited as the input vector for the proposed AE-based OTFS modulation and detection. We also develop a meta-learning scheme to effectively train the AE-based OTFS transceiver for newly updated channel profile.

Orthogonal Time Frequency Space Modulation—Part III: ISAC and Potential Applications

The first two parts of this tutorial on orthogonal time frequency space (OTFS) modulation have discussed the fundamentals of delay-Doppler (DD) domain communications as well as some advanced technologies for transceiver design. In this letter, we will present an OTFS-based integrated sensing and communications (ISAC) system, which is regarded as an enabling technology in next generation wireless communications. In particular, we illustrate the sensing as well as the communication models for OTFS-ISAC systems. Next, we show that benefiting from time-invariant DD channels, the sensing parameters can be used for inferring the communication channels, leading to an efficient transmission scheme. As both functionalities are realized in the same DD domain, we briefly discuss several promising benefits of OTFS-based ISAC systems, which have not been completely unveiled yet. Finally, a range of potential applications of OTFS for the future wireless networks will be highlighted.

Orthogonal Time Frequency Space Modulation—Part II: Transceiver Designs

The fundamental concepts and challenges of orthogonal time frequency space (OTFS) modulation have been reviewed in Part I of this three-part tutorial. In this second part, we provide an overview of the state-of-the-art transceiver designs for OTFS systems, with a particular focus on the cyclic prefix (CP) design, window design, pulse shaping, channel estimation, and signal detection. Furthermore, we analyze the performance of OTFS modulation, including the diversity gain and the achievable rate. Specifically, comparative simulations are presented to evaluate the error performance of different OTFS detection schemes, and the advantages of coded OTFS systems over coded orthogonal frequency-division multiplexing (OFDM) systems are investigated.

Bayesian Neural Network Detector for an Orthogonal Time Frequency Space Modulation

The orthogonal time frequency space (OTFS) modulation is proposed for beyond 5G wireless systems to deal with high mobility communications. The existing low complexity OTFS detectors’ performance is suboptimal in rich scattering environments where there are a large number of moving reflectors that reflect the transmitted signal towards the receiver. In this letter, we propose an OTFS detector, referred to as the BPICNet OTFS detector that integrates NN, Bayesian inference, and parallel interference cancellation concepts. Simulation results show that the proposed detector outperforms the state-of-the-art.