Energy efficient beamforming for small cell systems: A distributed learning and multicell coordination approach

H Zhou, X Wang, M Umehira, B Han… - ACM Transactions on …, 2023 - dl.acm.org
The integration of small cell architecture and edge intelligence is expected to make high-
grade mobile connectivity accessible and thus provide smart and efficient services for …

Localization with reconfigurable intelligent surface: An active sensing approach

Z Zhang, T Jiang, W Yu - IEEE Transactions on Wireless …, 2023 - ieeexplore.ieee.org
This paper addresses an uplink localization problem in which a base station (BS) aims to
locate a remote user with the help of reconfigurable intelligent surfaces (RISs). We propose …

Active sensing for localization with reconfigurable intelligent surface

Z Zhang, T Jiang, W Yu - ICC 2023-IEEE International …, 2023 - ieeexplore.ieee.org
This paper addresses an uplink localization problem in which the base station (BS) aims to
locate a remote user with the aid of reconfigurable intelligent surface (RIS). This paper …

Active sensing for two-sided beam alignment and reflection design using ping-pong pilots

T Jiang, F Sohrabi, W Yu - IEEE Journal on Selected Areas in …, 2023 - ieeexplore.ieee.org
Beam alignment is an important task for millimeter-wave (mmWave) communication,
because constructing aligned narrow beams both at the transmitter (Tx) and the receiver …

Optimized Resource Allocation for Distributed Joint Radar-Communication System

A Ahmed, YD Zhang - IEEE Transactions on Vehicular …, 2023 - ieeexplore.ieee.org
In this article, we consider a distributed joint radar-communication (JRC) multiple-input
multiple-output (MIMO) system that performs both radar and communication objectives …

Deep learning-based compressive sampling optimization in massive MIMO systems

SR Pavel, YD Zhang, MS Greco… - ICASSP 2023-2023 IEEE …, 2023 - ieeexplore.ieee.org
In this paper, we develop a deep learning framework to optimize the compressive sampling
matrix in a massive multiple-input multiple-output (MIMO) system. The optimized …

Deep-learning-based accurate beamforming prediction using LiDAR-assisted network

O Rinchi, A Alsharoa, I Shatnawi - 2023 IEEE 34th Annual …, 2023 - ieeexplore.ieee.org
Beamforming optimization can enhance the next-generation wireless networks. However,
finding the optimal beamforming in real-time is hard due to the need for large beam training …

Integrated beam tracking and communication for (Sub-) mmWave links with stochastic mobility

N Ronquillo, CS Gau, T Javidi - IEEE Journal on Selected …, 2023 - ieeexplore.ieee.org
We consider the problem of active sensing and sequential beam tracking at mmWave
frequencies and above. We focus on the setting of aerial communications between a quasi …

Deep Active Learning for Multi-Source AoA Tracking in mmWave-Based ISAC Systems

X Cheng, X Yuan, W Jiang, L Zhu… - 2023 IEEE Globecom …, 2023 - ieeexplore.ieee.org
In this paper, we investigate the problem of tracking the angle of arrivals (AoAs) of multi-
source in millimeter wave (mmWave)-based integrated sensing and communication (ISAC) …

Regularized Neural Detection for One-Bit Massive MIMO Communication Systems

A Sant, BD Rao - arXiv preprint arXiv:2305.15543, 2023 - arxiv.org
Detection for one-bit massive MIMO systems presents several challenges especially for
higher order constellations. Recent advances in both model-based analysis and deep …