Search Results for author: Jingzhi Hu

Found 10 papers, 1 papers with code

HoloFed: Environment-Adaptive Positioning via Multi-band Reconfigurable Holographic Surfaces and Federated Learning

no code implementations10 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.

Federated Learning Position +2

OCHID-Fi: Occlusion-Robust Hand Pose Estimation in 3D via RF-Vision

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.

3D Pose Estimation Hand Pose Estimation

Multi-band Reconfigurable Holographic Surface Based ISAC Systems: Design and Optimization

no code implementations28 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.

Meta-material Sensor Based Internet of Things: Design, Optimization, and Implementation

no code implementations26 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.

MetaSketch: Wireless Semantic Segmentation by Metamaterial Surfaces

no code implementations14 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.

Compressive Sensing Object Recognition +1

Deployment Optimization for Meta-material Based Internet of Things

no code implementations3 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.

Meta-material Sensors based Internet of Things for 6G Communications

no code implementations3 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.

MetaSensing: Intelligent Metasurface Assisted RF 3D Sensing by Deep Reinforcement Learning

no code implementations25 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.

reinforcement-learning Reinforcement Learning (RL)

MetaRadar: Indoor Localization by Reconfigurable Metamaterials

no code implementations6 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.

Indoor Localization

Cooperative Internet of UAVs: Distributed Trajectory Design by Multi-agent Deep Reinforcement Learning

no code implementations28 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).

reinforcement-learning Reinforcement Learning (RL)

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