Papers

We submitted a paper on geometry-aware deep-unfolded MIMO-OTFS detection to IEEE WCL.

We submitted a paper on multi-functional diversity via flexible spatial partitioning for massive MIMO ISAC to IEEE TWC.

We submitted two papers to ICUAS 2026: one on semantically-informed UAV path planning for mmWave connectivity in urban environments, and one on …

A novel time series approach is developed to accurately model and predict optical links between Low Earth Orbit (LEO) satellites.

Researchers develop an integrated sensing and communication technology to enhance safety and efficiency in advanced air mobility vehicles.

A novel simulation framework is developed to model and evaluate Frequency Modulated Continuous Wave (FMCW) radar sensors integrated with Unmanned …

The paper improves massive MIMO channel estimation by leveraging UAV state-space information to mitigate the effects of beam squint and enhance …

The paper presents a unified time-domain framework for estimating MIMO channel matrices in extremely large THz systems under dual-wideband fading …

This research develops a biconvex optimization approach to estimate time-domain MIMO channel matrices under dual-wideband fading conditions, …

A novel channel estimation protocol enables autonomous configuration of semi-passive Reconfigurable Intelligent Surfaces for receiving pilot signals …

Researchers propose flexible hybrid precoding schemes to optimize joint sensing and communication performance in resource-constrained wireless …

The study optimizes 5G network performance to support seamless and immersive extended reality experiences on-the-go.

This study introduces velocity-aided channel estimation for spatially selective mmWave massive MIMO communications, significantly improving channel …

This paper develops a novel channel estimation method for lens-based hybrid MIMO systems using low-resolution ADCs, significantly improving …

This research proposes a novel flexible hybrid beamforming scheme for spectrally efficient 6G joint radar-communications, enabling interference …

This paper develops a covariance-based hybrid beamformer for spectrally efficient joint radar-communications systems, enhancing interference …

This research introduces a novel subset selection-based RIS-aided beamforming approach that maximizes spectral efficiency in joint …

This research develops quantum computing-assisted channel estimation techniques to significantly improve computational efficiency in massive MIMO …

The paper develops a novel channel estimation method for UAV-based mmWave massive MIMO systems with beam squint, improving accuracy by accounting for …

Researchers develop a distributed model predictive control approach to stabilize coupled motion and hybrid beam alignment in UAV networks.

This research presents a novel optimal sensor selection technique for mmwave-based bearing-only localization in smart environments, improving accuracy …

Researchers develop game-theoretic algorithms to optimize power and rate control in vehicular networks, improving reliability and efficiency of IEEE …

This paper introduces a novel RF chain and DAC bit selection approach for sub-arrayed hybrid MIMO joint radar-communications systems, optimizing …

This research develops a novel ADMM-based cooperative control framework for platooning of connected autonomous vehicles, enabling efficient and …

This research contributes to 6G by developing a spectrally efficient joint radar-communication system that selects optimal radio frequencies, …

The paper jointly optimizes digital-to-analog converter bit resolutions and hybrid beamforming matrices to achieve energy-efficient millimeter wave …

This research introduces a novel hybrid massive MIMO precoding architecture using random-resolution DACs and RF selection to maximize …

Researchers develop an algorithm to optimize radio-frequency chain selection for efficient wireless transmission while minimizing hardware …

This study develops a fast adaptive method for completing correlation matrices in industrial IoT networks, preserving privacy by adding noise that …

This research develops a novel joint localization and channel estimation framework for UAV-assisted mmWave communications, enabling accurate …

A novel energy-efficient beamformer maximizes millimeter wave hybrid MIMO system performance by optimizing DAC resolution and RF chain selection using …

A novel matrix-completion-based approach enables efficient wideband channel tracking in millimeter wave massive MIMO systems with hybrid beamforming …

A novel hardware architecture for reconfigurable intelligent surfaces minimizes active elements while enabling explicit channel estimation, a crucial …

This research optimizes ADC bit allocation and hybrid combining in millimeter wave MIMO systems, achieving highly energy-efficient solutions through a …

This paper introduces a novel dynamic RF chain selection framework that maximizes energy efficiency and minimizes complexity in millimeter wave MIMO …

A novel random spatial sampling approach enables reliable wideband MIMO channel estimation in hybrid beamforming millimeter wave systems, overcoming …

The paper presents novel signal processing techniques for static and dynamic 3D meshes, introducing sparse representations that enable efficient data …

This paper presents a robust estimator for lens-based hybrid MIMO systems using low-resolution ADCs, improving symbol estimation accuracy and enabling …

This research develops a novel approach to efficiently preserve privacy in Industrial IoT systems by leveraging correlation completion and tracking, …

A novel hybrid beamforming technique combining random analog sampling and matrix completion enables accurate wideband channel estimation in millimeter …

This research proposes an energy-efficient transmission scheme for 3D meshes over mmWave-based massive MIMO systems, achieving up to 30% reduction in …

A novel energy-efficient millimeter wave hybrid MIMO beamformer is proposed, maximizing energy efficiency by optimizing DAC resolution and selecting …

A novel distributed consolidation approach uses rank minimization to reconstruct highly incomplete dynamic point clouds, enabling reliable generation …

This research introduces adaptive windowing for intercarrier interference mitigation in vehicular communications, improving receiver performance by …

This work develops a matrix completion-based approach to massive MIMO channel estimation in millimeter wave systems, achieving reliable recovery with …

The proposed algorithm efficiently estimates mmWave MIMO channels using compressed sensing and SURE-based parametric denoising, effectively leveraging …

This research optimizes the energy efficiency of millimeter wave massive MIMO systems by designing a transmitter that leverages low-resolution DACs …

The authors propose dithered beamforming to combat staircase quantization effects in mmWave-based massive MIMO channel estimation, introducing …

Researchers develop an efficient graph-based approach to complete missing data in animated models, leveraging structural relationships between frames.

This study develops novel interference mitigation techniques for OFDM-based vehicular communications in 5G networks, enhancing the reliability of …

This research develops a model-based Bayesian learning approach to efficiently encode dense 3D meshes using compressed sensing, achieving higher …

A novel supervised energy disaggregation method uses dictionary-based modelling of appliance states to accurately identify and quantify energy …

This research develops an adaptive completion algorithm for wireless sensor networks, preserving privacy while accurately estimating the full-rank …

This paper presents a low-complexity OSIC equalization algorithm for OFDM-based vehicular communications, significantly reducing computational …

This paper introduces a novel matrix completion-based approach to distributed beamforming, enabling efficient maximization of receiver SNR while …

This research develops a novel regularized receiver windowing technique that adapts to non-stationary V2V channel conditions, significantly improving …

Researchers develop novel transmitter techniques to mitigate interference and fading effects in wireless communication systems, enhancing reliability …

This paper proposes a regularized MMSE ICI equalization scheme for OFDM systems over doubly selective channels, achieving linear complexity and …

This paper presents a decentralized approach to generalized power system state estimation, enabling efficient and scalable joint estimation of network …

This novel scheme leverages sparse representations to denoise X-ray medical images by decomposing noisy images into dictionaries, offering superior …

A distributed, adaptive beamforming approach is developed to maximize fairness in multi-cell relay networks with multiple receive antennas, achieving …

This study proposes two low-complexity iterative successive interference cancellation schemes for OFDM systems with doubly selective channels, …

A novel stochastic gradient pursuit algorithm adaptively equalizes sparse multipath channels by exploiting their inherent sparsity and outperforms …

A novel application of compressed sensing techniques significantly improves decision feedback equalization of sparse wireless channels by exploiting …

This research proposes two novel adaptive decision feedback equalization schemes that exploit sparsity in both channel impulse responses and equalizer …