From the 1 of 14 linked papers with an AI index.
6 papers · 1 filter
Computationally Efficient Neural Receivers via Axial Self-Attention
SaiKrishna Saketh Yellapragada, Atchutaram K. Kocharlakota, Mário Costa +2
The paper introduces an axial self‑attention transformer neural receiver that reduces computational complexity while achieving state‑of‑the‑art block error rate performance for wir…
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…
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…
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…