arXiv subjects

Xuehan Wang

Publications and source records attributed to Xuehan Wang.

14 recordsLinked to original sources

arXiv2026

Prior-Aided Iterative Channel Reconstruction with Optimized Frame Structure for DSE Mitigation in CP-OTFS-Based LEO Satellite Systems

Orthogonal time frequency space (OTFS) modulation has emerged as a promising solution to mitigate the severe Doppler shift in low Earth orbit (LEO) satellite communications. However, the frequency-dependent Doppler shift induced by the high mobility of LEO satellites leads to the Doppler squint effect (DSE). This effect compromises the channel sparsity in the delay-Doppler (DD) domain, rendering existing channel estimation methods ineffective. To overcome this challenge, this paper proposes a DSE-resilient transmission scheme for cyclic prefix OTFS (CP-OTFS)-based LEO satellite systems. Specifically, we analyze the input-output relationship of the CPOTFS- based LEO satellite communication system and derive a DSE-aware representation of the satellite-terrestrial channel in the DD domain. To efficiently capture DSE-aware channel characteristics, we propose a novel OTFS frame structure that allows the energy distribution of the received signal to serve as prior information for channel estimation. Meanwhile, this frame structure strategically allocates pilot symbols to achieve uniform energy distribution and reduce the peak-to-average power ratio (PAPR), while imposing a time-domain waveform continuity constraint to suppress out-of-band emission (OOBE) caused by rectangular pulses. Based on the frame structure, we propose a prior-aided iterative channel reconstruction (PAICR) algorithm to mitigate the severe power leakage induced by DSE. The proposed algorithm iteratively extracts and removes dominant channel components using Doppler-domain received signal energy observations, with a convergence criterion ensuring reliable termination. Furthermore, a Cramer-Rao lower bound is derived to provide a theoretical benchmark for evaluating the algorithm's performance.

eess.SP↗

arXiv2026

Hyperbolic Frequency Multicarrier Modulation for Wideband Linear Time-Varying Channels

Numerous multicarrier modulation schemes have been proposed recently to enhance the performance in narrowband doubly dispersive channels for emerging high-mobility applications. However, the ultra-reliable modulation framework in wideband linear time-varying (LTV) channels remains an open problem, where the time dilations and contractions brought by the high mobility cannot be ignored for the baseband signal to obtain the constant Doppler shift across the whole transmission band. To solve this problem, we propose the hyperbolic frequency multicarrier (HFMC) waveform in this paper based on the inspiration from affine frequency division multiplexing (AFDM) modulation, where the delay and Doppler shift are absorbed into a 1D shift in the affine domain to provide a compact characterization of doubly dispersive discrete-time channels. By adopting the passband representation of wideband LTV channels and hyperbolic frequency modulated (HFM) signals, we reveal that the Doppler scaling factor brought by the relative mobility can be absorbed into an equivalent delay. The basic principle of HFMC modulation is established by investigating the approximate orthogonality among HFMC subcarriers, which are generated from a basic HFM signal by utilizing uniformly spaced equivalent delay. The spectrum of HFMC subcarriers is also analyzed to evaluate the system capacity, where the overlapping nature in the frequency domain can be observed. The input-output characterization in wideband LTV channels is then executed to confirm the 1D integration of time delay and Doppler scaling factor for each path, which demonstrates the ability to exploit potential multipath diversity. The parameter optimization based on the input-output relation and spectrum analysis is finally developed to balance the efficiency and reliability.

eess.SP↗

arXiv2026

Doppler Shift Keying Modulation for Uplink Multiple Access over Doubly-Dispersive Channels

The delay-Doppler (DD) domain modulation has been regarded as one of the most competitive candidates to support wireless communications for emerging high-mobility applications in the sixth-generation mobile networks. Unfortunately, most of the existing designs for DD domain modulation suffer from high peak-to-average power ratio (PAPR) and unbearable detection complexity under uplink transmission since large time duration and bandwidth are required to guarantee high DD resolutions. To address these issues, the Doppler shift keying (DSK) modulation based on the orthogonal delay Doppler division multiplexing modulator is proposed in this paper, where the input-output characterization in the DD domain is fully exploited. The principle of the DSK transceiver is first established with the one-hot mapper and low-complexity iterative successive interference cancellation-maximum ratio combining detector for point-to-point scenarios. The proposed scheme is then generalized to the zero auto-correlation sequence-based implementation, which benefits the extension of multi-user (MU) uplink DSK frameworks. For uplink DSK transmission, Zadoff-Chu (ZC) sequences are adopted as the basis sequences. We optimize the assignment of ZC roots to different user equipments (UEs) by minimizing the maximum inter-user interference. This optimization process, which analyzes the root allocation, directly assigns a specific ZC sequence to each UE. The PAPR and bit error rate performance of the proposed DSK modulation with the low-complexity detector is finally verified by extensive simulation results under doubly-dispersive channels, which demonstrates the superiority of DSK modulation especially for uplink multiple access over doubly dispersive channels.

eess.SP↗

arXiv2026

Channel Estimation with Hierarchical Sparse Bayesian Learning for ODDM Systems

Orthogonal delay-Doppler division multiplexing (ODDM) is a promising modulation technique for reliable communications in high-mobility scenarios. However, the existing channel estimation frameworks for ODDM systems cannot achieve both high accuracy and low complexity simultaneously, due to the inherent coupling of delay and Doppler parameters. To address this problem, a two-dimensional (2D) hierarchical sparse Bayesian learning (HSBL) based channel estimation framework is proposed in this paper. Specifically, we address the inherent coupling between delay and Doppler dimensions in ODDM by developing a partially-decoupled 2D sparse signal recovery (SSR) formulation on a virtual sampling grid defined in the delay-Doppler (DD) domain. With the help of the partially-decoupled formulation, the proposed 2D HSBL framework first performs low-complexity coarse on-grid 2D sparse Bayesian learning (SBL) estimation to identify potential channel paths. Then, high-resolution fine grids are constructed around these regions, where an off-grid 2D SBL estimation is applied to achieve accurate channel estimation. Simulation results demonstrate that the proposed framework achieves performance superior to conventional off-grid 2D SBL with significantly reduced computational complexity.

econ.EM↗

arXiv2026

Achieving Full Multipath Diversity by Random Constellation Rotation: a Theoretical Perspective

Diversity is an essential concept associated with communication reliability in multipath channels since it determines the slope of bit error rate performance in the medium to high signal-to-noise ratio regions. However, most of the existing analytical frameworks were developed for specific modulation schemes while the efficient validation of full multipath diversity for general modulation schemes remains an open problem. To fill this research gap, we propose to utilize random constellation rotation to ease the conditions for full-diversity modulation designs. For linearly precoded cyclic-prefix orthogonal frequency division multiplexing (OFDM) systems, we prove that maximum multipath diversity can be attained as long as the spread matrix does not have zero entries, which is a sufficient but easily satisfied condition. Furthermore, we derive the sufficient and necessary condition for general modulation schemes, whose verification can be divided into validation tasks for each column of the modulation matrix. Based on the proposed conditions, maximum diversity order can be attained with the probability of 1 by enabling a randomly generated rotation pattern for both time and doubly dispersive channels. The theoretical analysis in this paper also demonstrates that the diversity evaluation can be concentrated on the pairwise error probability when the number of error symbols is one, which reduces the complexity of diversity-driven design and performance analysis for novel modulation schemes significantly in both time and doubly dispersive channels. Finally, numerical results for various modulation schemes confirm that the theoretical analysis holds in both time and doubly dispersive channels. Furthermore, when employing practical detectors, the random constellation rotation technique consistently enhance the transmission reliability for both coded and uncoded systems.

eess.SP↗

arXiv2025

RSMA-Assited and Transceiver-Coordinated ICI Management for MIMO-OFDM System

High-mobility scenarios are becoming increasingly critical in next-generation communication systems. While multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) stands as a prominent technology, its performance in such scenarios is fundamentally limited by Doppler-induced inter-carrier interference (ICI). Rate splitting multiple access (RSMA), recognized as a key multiple access technique for future communications, demonstrates superior interference management capabilities that we leverage to address this challenge. In specific, we propose a novel RSMA-assisted and transceiver-coordinated transmission scheme for ICI management in MIMO-OFDM system: (1) At the receiver side, we develop a hybrid successive interference cancellation (SIC) architecture with dynamic subcarrier clustering, which enables parallel intra-cluster and serial inter-cluster processing to balance complexity and performance. (2) At the transmitter~side, we design a matched hybrid precoding through formulated sum-rate maximization, solved via our proposed augmented boundary-compressed particle swarm optimization (ABC-PSO) algorithm for analog phase optimization and weighted minimum mean-square error (WMMSE)-based digital precoding iteration. Simulation results show that our scheme brings effective ICI suppression and enhanced system capacity with controlled complexity.

eess.SP↗

arXiv2025

On the Characterization and Evaluation of Doppler Squint in Wideband ODDM Systems

The recently proposed orthogonal delay-Doppler division multiplexing (ODDM) modulation has been demonstrated to enjoy excellent reliability over doubly-dispersive channels. However, most of the prior analysis tends to ignore the interactive dispersion caused by the wideband property of ODDM signal, which possibly leads to performance degradation. To solve this problem, we investigate the input-output relation of ODDM systems considering the wideband effect, which is also known as the Doppler squint effect (DSE) in the literature. The extra delay-Doppler (DD) dispersion caused by the DSE is first explicitly explained by employing the time-variant frequency response of multipath channels. Its characterization is then derived for both reduced cyclic prefix (RCP) and zero padded (ZP)-based wideband ODDM systems, where the extra DD spread and more complicated power leakage outside the peak region are presented theoretically. Numerical results are finally provided to confirm the significance of DSE. The derivations in this paper are beneficial for developing accurate signal processing techniques in ODDM-based integrated sensing and communication systems.

eess.SP↗

arXiv2025

Dynamic SINR-Guided Iterative Interference Cancellation for ODDM Systems in Doubly Dispersive Channels

Orthogonal delay-Doppler division multiplexing (ODDM) modulation has recently gained significant attention as a promising candidate to promote the communication reliability in high-mobility environments. Low complexity signal detection is one of the most significant challenges for ODDM over general physical channels, due to the large channel spreading caused by the fractional delay and Doppler shifts. In this paper, we investigate the low-complexity data detection for ODDM system by utilizing iterative interference cancellation. Based on the theoretical analysis of signal to interference plus noise ratio (SINR) during the iteration, a dynamic SINR-guided approach is proposed to provide a better initialization result. Specifically, we analyze the SINR of each time domain sample before initial estimate with consideration of off-grid delay and Doppler shifts. The iteration is then started from the multi-carrier symbol index which has the best SINR. The corresponding interference is then eliminated for other time domain samples while the SINR for symbol awaiting detection is also updated. Based on the updated SINR, the next multi-carrier symbol index is selected for the same processing until all data symbols have been initialized. Finally, we update the SINR synchronously until the end of the initialization. Simulation experiments indicate that our proposed algorithms demonstrate satisfying convergence and error performance while avoiding the huge complexity introduced by full linear minimum mean squared error (LMMSE) initialization.

econ.TH↗

arXiv2025

Data-Driven Modulation Optimization with LMMSE Equalization for Reliability Enhancement in Underwater Acoustic Communications

Ultra-reliable underwater acoustic (UWA) communications serve as one of the key enabling technologies for future space-air-ground-underwater integrated networks. However, the reliability of current UWA transmission is still insufficient since severe performance degradation occurs for conventional multicarrier systems in UWA channels with severe delay-scale spread. To solve this problem, we exploit learning-inspired approaches to optimize the modulation scheme under the assumption of linear minimum mean square error (LMMSE) equalization, where the discrete representation of waveforms is adopted by utilizing Nyquist filters. The optimization problem is first transferred into maximizing the fairness of estimation mean square error (MSE) for each data symbol since the total MSE is invariant considering the property of orthogonal modulation. The Siamese architecture is then adopted to obtain consistent optimization results across various channel conditions, which avoids the overhead of online feedback, cooperation, and deployment of neural networks and guarantees generalization. The overall scheme including the loss function, neural network structure, and training process is also investigated in depth in this paper. The excellent performance and robustness of the proposed modulation scheme are verified by carrying out the bit error rate test over various UWA channels with severe delay-scale spread.

eess.SP↗

arXiv2024

Universal Modem Generation with Inherent Adaptability to Variant Underwater Acoustic Channels: a Data-Driven Perspective

In underwater acoustic (UWA) communication, orthogonal frequency division multiplexing (OFDM) is commonly employed to mitigate the inter-symbol interference (ISI) caused by delay spread. However, path-specific Doppler effects in UWA channels could result in significant inter-carrier interference (ICI) in the OFDM system. To address this problem, we introduce a multi-resolution convolutional neural network (CNN) named UWAModNet in this paper, designed to optimize the modem structure, specifically modulation and demodulation matrices. Based on a trade-off between the minimum and the average equivalent sub-channel rate, we propose an optimization criterion suitable to evaluate the performance of our learned modem. Additionally, a two-stage training strategy is developed to achieve quasi-optimal results. Simulations indicate that the learned modem outperforms zero-padded OFDM (ZP-OFDM) in terms of equivalent sub-channel rate and bit error rate, even under more severe Doppler effects during testing compared to training.

eess.SP↗

arXiv2024

Modem Optimization of High-Mobility Scenarios: A Deep-Learning-Inspired Approach

The next generation wireless communication networks are required to support high-mobility scenarios, such as reliable data transmission for high-speed railways. Nevertheless, widely utilized multi-carrier modulation, the orthogonal frequency division multiplex (OFDM), cannot deal with the severe Doppler spread brought by high mobility. To address this problem, some new modulation schemes, e.g. orthogonal time frequency space and affine frequency division multiplexing, have been proposed with different design criteria from OFDM, which promote reliability with the cost of extremely high implementation complexity. On the other hand, end-to-end systems achieve excellent gains by exploiting neural networks to replace traditional transmitters and receivers, but have to retrain and update continually with channel varying. In this paper, we propose the Modem Network (ModNet) to design a novel modem scheme. Compared with end-to-end systems, channels are directly fed into the network and we can directly get a modem scheme through ModNet. Then, the Tri-Phase training strategy is proposed, which mainly utilizes the siamese structure to unify the learned modem scheme without retraining frequently faced up with time-varying channels. Simulation results show the proposed modem scheme outperforms OFDM systems under different highmobility channel statistics.

eess.SP↗

arXiv2024

Sparse Estimation for XL-MIMO with Unified LoS/NLoS Representation

Extremely large-scale antenna array (ELAA) is promising as one of the key ingredients for the sixth generation (6G) of wireless communications. The electromagnetic propagation of spherical wavefronts introduces an additional distance-dependent dimension beyond conventional beamspace. In this paper, we first present one concise closed-form channel formulation for extremely large-scale multiple-input multiple-output (XL-MIMO). All line-of-sight (LoS) and non-line-of-sight (NLoS) paths, far-field and near-field scenarios, and XL-MIMO and XL-MISO channels are unified under the framework, where additional Vandermonde windowing matrix is exclusively considered for LoS path. Under this framework, we further propose one low-complexity unified LoS/NLoS orthogonal matching pursuit (XL-UOMP) algorithm for XL-MIMO channel estimation. The simulation results demonstrate the superiority of the proposed algorithm on both estimation accuracy and pilot consumption.

cs.IT↗

arXiv2023

Input-Output Relation and Low-Complexity Receiver Design for CP-OTFS Systems with Doppler Squint

In orthogonal time frequency space (OTFS) systems, the impact of frequency-dependent Doppler which is referred to as the Doppler squint effect (DSE) is accumulated through longer duration, whose negligence has prevented OTFS systems from exploiting the performance superiority. In this paper, practical OFDM system using cyclic prefix time guard interval (CP-OFDM)-based OTFS systems with DSE are adopted. Cyclic prefix (CP) length is analyzed while the input-output relation considering DSE is derived. By deploying two prefix OFDM symbols, the channel estimation can be easily divided into three parts as delay detection, Doppler extraction and gain estimation. The linear equalization scheme is adopted taking the block diagonal property of the channel matrix into account, which completes the low-complexity receiver design. Simulation results confirm the significance of DSE and the considerable performance of the proposed low-complexity receiver scheme considering DSE.

cs.IT↗

arXiv2023

On the Doppler Squint Effect in OTFS Systems over Doubly-Dispersive Channels: Modeling and Evaluation

Extensive work has demonstrated the excellent performance of orthogonal time frequency space (OTFS) modulation in high-mobility scenarios. Time-variant wideband channel estimation serves as one of the key compositions of OTFS receivers since the data detection requires accurate channel state information (CSI). In practical wideband OTFS systems, the Doppler shift brought by the high mobility is frequency-dependent, which is referred to as the Doppler Squint Effect (DSE). Unfortunately, DSE was ignored in overall prior estimation schemes employed in OTFS systems, which leads to severe performance loss in channel estimation and the consequent data detection. In this paper, we investigate DSE of wideband time-variant channel in delay-Doppler domain and concentrate on the characterization of OTFS channel coefficients considering DSE. The formulation and evaluation of OTFS input-output relationship are provided for both ideal and rectangular waveforms considering DSE. The channel estimation is therefore formulated as a sparse signal recovery problem and an orthogonal matching pursuit (OMP)-based scheme is adopted to solve it. Simulation results confirm the significance of DSE and the performance superiority compared with traditional channel estimation approaches ignoring DSE.

cs.IT↗