publications | Qinpei (Sheldon) Luo's Homepage

2024

Meta-Critic Reinforcement Learning for Intelligent Omnidirectional Surface Assisted Multi-User Communications

Qinpei Luo, Zhu Han, and Boya Di

IEEE Transactions on Wireless Communications, 2024

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Horus: Enhancing Safe Corners via Integrated Sensing and Communication Enabled by Reconfigurable Intelligent Surface

Qinpei Luo, Jiahao Gao, and Boya Di

In Proceedings of the 30th Annual International Conference on Mobile Computing and Networking, 2024

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As a key feature that has the potential to enable many advanced applications, the integration of sensing functionality is considered essential in the 6G network, which motivates the design of integrated sensing and communication (ISAC) systems. However, traditional ISAC systems based on non-overlapped resource allocation face the challenge of poor energy and spectral efficiency. In this paper, we implement an ISAC system named Horus based on reconfigurable intelligent surfaces, which provides an energy-efficient solution to sense objects in a wide range of blind areas. With a carefully designed ISAC protocol, Horus can transmit sensing information to the receiver with high spectral efficiency. We have verified the ability of the proposed system in two case studies of multi-modal sensing and around-corner radar early warning, respectively. Our demonstration video can be found in [11].

2023

Meta Learning for Meta-Surface: A Fast Beamforming Method for RIS-Assisted Communications Adapting to Dynamic Environments

Qinpei Luo, and Boya Di

In IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), May 2023

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Meta-Critic Reinforcement Learning for IOS-Assisted Multi-User Communications in Dynamic Environments

Qinpei Luo, Boya Di, and Zhu Han

In 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring), Jun 2023

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Demo: Meta2Locate: Meta Surface Enabled Indoor Localization in Dynamic Environments

Qinpei Luo, Ziang Yang, Boya Di, and 1 more author

In Proceedings of the Twenty-Fourth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, Oct 2023

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Received signal strength (RSS) fingerprint map is one of the most widely-used indoor localization approaches, but it often relies on multiple access points (AP) for data collection and suffers from frequent data updates due to dynamic wireless environments. In this work, we implement a reconfigurable-intelligent-surface (RIS) assisted indoor localization system named Meta2Locate to tackle the above issues using only one AP. In the proposed system, we deploy our self-designed RIS at 5.5GHz in an indoor environment, which can customize the propagation channels between the AP and the target. For the changing propagation environment, we design a mean maximum discrepancy weighted meta-learning approach to train a model that maps the RSS fingerprint to the location of the user, and it only needs a few data for the model update.
An Overview of 3GPP Standardization for Extended Reality (XR) in 5G and Beyond

Qinpei Luo, Hongliang Zhang, Minrui Xu, and 5 more authors

GetMobile: Mobile Comp. and Comm., Nov 2023

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In recent years, aiming to enhance and extend user experiences beyond the real world, Extended Reality (XR) has emerged to become a new paradigm that enables a plethora of applications [1], e.g., online gaming, online conferencing, social media, etc. XR refers to the human-machine interactions that combine real and virtual environments with the support of computing/communications technologies and wearable devices. The XR content is generated by providers or other users, including audio, video and other metadata. In general, the generated XR content is transmitted to XR devices and rendered into XR scenes (i.e., to generate an image from a 2D or 3D model by means of a computer program), where users can experience a hybrid experience of the real and virtual worlds.