1 code implementation • 2 Apr 2024 • Haichao Zhang, Yi Xu, HongSheng Lu, Takayuki Shimizu, Yun Fu
By enhancing trajectory prediction accuracy and addressing the challenges of out-of-sight objects, our work significantly contributes to improving the safety and reliability of autonomous driving in complex environments.
no code implementations • 9 Oct 2023 • Haichao Zhang, Yi Xu, HongSheng Lu, Takayuki Shimizu, Yun Fu
In summary, our approach offers a promising solution to the challenges faced by layout sequence and trajectory prediction models in real-world settings, paving the way for utilizing sensor data from mobile phones to accurately predict pedestrian bounding box trajectories.
no code implementations • 26 Aug 2023 • Yun Chen, Nuria González-Prelcic, Takayuki Shimizu, Hongshen Lu, Chinmay Mahabal
In this paper, we propose first a mmWave channel tracking algorithm based on multidimensional orthogonal matching pursuit algorithm (MOMP) using reduced sparsifying dictionaries, which exploits information from channel estimates in previous frames.
no code implementations • 30 Jun 2023 • Yun Chen, Nuria González-Prelcic, Takayuki Shimizu, HongSheng Lu
One strategy to obtain user location information in a wireless network operating at millimeter wave (mmWave) is based on the exploitation of the geometric relationships between the channel parameters and the user position.
no code implementations • 31 May 2022 • Xiaowen Tian, Nuria Gonzalez-Prelcic, Takayuki Shimizu
In this paper, we propose to enable LEO SatCom in non-line-of-sight (NLoS) channels, as those corresponding to links to users in urban canyons, with the aid of reconfigurable intelligent surfaces (RISs).
no code implementations • 4 Apr 2022 • Yun Chen, Joan Palacios, Nuria González-Prelcic, Takayuki Shimizu, HongSheng Lu
High resolution compressive channel estimation provides information for vehicle localization when a hybrid mmWave MIMO system is considered.
no code implementations • 12 Jan 2022 • Andrew Graff, Yun Chen, Nuria González-Prelcic, Takayuki Shimizu
Then, a deep network is used to translate features of these radar spatial covariances into features of the communication spatial covariances, by learning the intricate mapping between radar and communication channels, in both line-of-sight and non-line-of-sight settings.
no code implementations • 16 Nov 2021 • Yun Chen, Andrew Graff, Nuria González-Prelcic, Takayuki Shimizu
In this paper, we obtain prior information to speed up the beam training process by implementing two deep neural networks (DNNs) that realize radar-to-communication (R2C) channel information translation in a vehicle-to-infrastructure (V2I) system.
no code implementations • 16 Nov 2021 • Joan Palacios, Nuria González-Prelcic, Carlos Mosquera, Takayuki Shimizu
Beamforming gain is a key ingredient in the performance of LEO satellite communication systems to be integrated into cellular networks.
no code implementations • 22 Apr 2021 • Joan Palacios, Nuria Gonzalez-Prelcic, Carlos Mosquera, Takayuki Shimizu, Chang-Heng Wang
5G and future cellular networks intend to incorporate low earth orbit (LEO) satellite communication systems (SatCom) to solve the coverage and availability problems that cannot be addressed by satellite-based or ground-based infrastructure alone.
no code implementations • 12 Mar 2020 • Monowar Hasan, Sibin Mohan, Takayuki Shimizu, HongSheng Lu
Modern vehicular wireless technology enables vehicles to exchange information at any time, from any place, to any network -- forms the vehicle-to-everything (V2X) communication platforms.
Networking and Internet Architecture Cryptography and Security