2 citations · 2 across the 16 of their papers we have counts for
9 papers · 1 filter
Compressed LLM Reprogramming for Vision-Aided Beam Prediction in Vehicular Networks
Kai Dong, Lei Wang, Changyi Li +2
Large Language Model (LLM) reprogramming-based beam prediction demonstrates strong data efficiency by adapting pretrained language models for vehicle-to-infrastructure (V2I) beam p…
A Majorization-Minimization Framework for Activity Detection in Mixed Near-and-Far-Field Random Access
Xinjue Wang, Zhi-Yong Wang, Sergiy A. Vorobyov +3
Grant-free random access in massive machine-type communications requires detecting a small active set from length-L uplink pilots received at an M-antenna base station. Classical c…
Covariance-Aware MM-PGD for Mixed Near-/Far-Field Activity Detection
Xinjue Wang, Zhi-Yong Wang, Sergiy A. Vorobyov +3
Grant-free activity detection with mixed near-field (NF) and far-field (FF) devices is an important problem that can be addressed via covariance-based detectors. The difficulty is…
Tensor Train Decomposition Based Noise Reduction and Enhanced Parameter Estimation for FMCW MIMO Radar Systems
Luoyan Zhu, Sergiy A. Vorobyov, Jie Wang +2
Frequency modulated continuous wave (FMCW) radar is widely used in autonomous driving and industrial inspection due to its high-resolution target location and velocity estimation c…
Computationally Efficient Neural Receiver via Axial Self-Attention
SaiKrishna Saketh Yellapragada, Atchutaram K. Kocharlakota, Mário Costa +2
Deep learning-based neural receivers offer promising physical-layer solutions for next-generation wireless systems. We propose an axial self-attention transformer neural receiver t…
Generalized Nonnegative Structured Kruskal Tensor Regression
Xinjue Wang, Esa Ollila, Sergiy A. Vorobyov +1
This paper introduces Generalized Nonnegative Structured Kruskal Tensor Regression (NS-KTR), a novel tensor regression framework that enhances interpretability and performance thro…
Wasserstein Distributionally Robust Adaptive Beamforming
Kiarash Hassas Irani, Sergiy A. Vorobyov, Yongwei Huang
Distributionally robust optimization (DRO)-based robust adaptive beamforming (RAB) enables enhanced robustness against model uncertainties, such as steering vector mismatches and i…
SINR Maximizing Distributionally Robust Adaptive Beamforming
Kiarash Hassas Irani, Yongwei Huang, Sergiy A. Vorobyov
This paper addresses the robust adaptive beamforming (RAB) problem via the worst-case signal-to-interference-plus-noise ratio (SINR) maximization over distributional uncertainty se…
Robust Activity Detection for Massive Random Access
Xinjue Wang, Esa Ollila, Sergiy A. Vorobyov
Massive machine-type communications (mMTC) are fundamental to the Internet of Things (IoT) framework in future wireless networks, involving the connection of a vast number of devic…