no code implementations • 10 Oct 2023 • Jingzhi Hu, Zhe Chen, Tianyue Zheng, Robert Schober, Jun Luo
Our simulation results confirm that HoloFed achieves a 57% lower positioning error variance compared to a beam-scanning baseline and can effectively adapt to diverse environments.
1 code implementation • ICCV 2023 • Shujie Zhang, Tianyue Zheng, Zhe Chen, Jingzhi Hu, Abdelwahed Khamis, Jiajun Liu, Jun Luo
To overcome the challenge in labeling RF imaging given its human incomprehensible nature, OCHID-Fi employs a cross-modality and cross-domain training process.
no code implementations • 28 Mar 2023 • Jingzhi Hu, Zhe Chen, Jun Luo
Metamaterial-based reconfigurable holographic surfaces (RHSs) have been proposed as novel cost-efficient antenna arrays, which are promising for improving the positioning and communication performance of integrated sensing and communications (ISAC) systems.
no code implementations • 26 Jun 2022 • Jingzhi Hu, Hongliang Zhang, Boya Di, Zhu Han, H. Vincent Poor, Lingyang Song
However, to maximize the sensing accuracy, the structures of meta-IoT sensors need to be optimized considering their joint influence on sensing and transmission, which is challenging due to the high computational complexity in evaluating the influence, especially given a large number of sensors.
no code implementations • 14 Aug 2021 • Jingzhi Hu, Hongliang Zhang, Kaigui Bian, Zhu Han, H. Vincent Poor, Lingyang Song
Semantic segmentation is a process of partitioning an image into multiple segments for recognizing humans and objects, which can be widely applied in scenarios such as healthcare and safety monitoring.
no code implementations • 3 Jul 2021 • Xu Liu, Jingzhi Hu, Hongliang Zhang, Boya Di, Lingyang Song
It is a challenge to optimize the positions of the Meta-IoT devices to ensure sensing accuracy of 3D environmental conditions.
no code implementations • 3 Jul 2021 • Jingzhi Hu, Hongliang Zhang, Boya Di, Kaigui Bian, Lingyang Song
In the coming 6G communications, the internet of things (IoT) serves as a key enabler to collect environmental information and is expected to achieve ubiquitous deployment.
no code implementations • 25 Nov 2020 • Jingzhi Hu, Hongliang Zhang, Kaigui Bian, Marco Di Renzo, Zhu Han, Lingyang Song
To tackle this challenge, we formulate an optimization problem for minimizing the cross-entropy loss of the sensing outcome, and propose a deep reinforcement learning algorithm to jointly compute the optimal beamformer patterns and the mapping of the received signals.
no code implementations • 6 Aug 2020 • Haobo Zhang, Jingzhi Hu, Hongliang Zhang, Boya Di, Kaigui Bian, Zhu Han, Lingyang Song
However, in MetaRadar, it is challenging to build radio maps for all the radio environments generated by metamaterial units and select suitable maps from all the possible maps to realize a high accuracy localization.
no code implementations • 28 Jul 2020 • Jingzhi Hu, Hongliang Zhang, Lingyang Song, Robert Schober, H. Vincent Poor
In this paper, we consider a cellular Internet of UAVs, where the UAVs execute sensing tasks through cooperative sensing and transmission to minimize the age of information (AoI).