Ruiqi Wang

Ruiqi Wang

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Pages

Posts

portfolio

Embedded-AI-Based Intelligent Payload Delivery UAV

  • Description: This project developed an intelligent UAV system for target-aware payload delivery based on embedded AI. The system integrates onboard target detection, embedded inference deployment, flight-control experiments, and a payload delivery workflow, enabling the UAV to recognize target regions and support autonomous or assisted delivery tasks.
  • Role: Team leader, responsible for training the target detection model, deploying the embedded AI on the STM32 MCU, and conducting UAV flight-control experiments.
  • Keywords: Embedded AI, UAV, target detection, object detection model training, edge deployment, flight control.
Target detection demo.

Efficient Resource Allocation for LoRaWAN via Online Learning

  • Description: This project studies efficient resource allocation for LoRaWAN networks under energy-constrained IoT scenarios. It formulates the joint optimization of carrier frequency, spreading factor, and transmission power as a combinatorial multi-armed bandit problem, and designs both distributed and hybrid online learning frameworks for non-stationary wireless environments.
  • Role: Independent researcher, algorithm designer, system developer.
  • Keywords: LoRaWAN, wireless resource allocation, online learning, combinatorial multi-armed bandit, energy-constrained IoT, distributed optimization.

Joint Optimization of Multi-UAV Beamforming and Path Planning

  • Description: This project develops a learning-based framework for multi-UAV downlink communications. It decouples short-term beamforming and long-term cooperative trajectory planning, combines topology-aware GNN beamforming with MAPPO-based path planning, and follows the centralized-training decentralized-execution paradigm.
  • Role: Independent researcher, algorithm designer.
  • Keywords: GNN, MAPPO, Dec-POMDP, multi-agent reinforcement learning, wireless communications.

Privacy Leakage from Radio Frequency Energy Harvesting Signals

  • Description: This project investigates a newly identified side channel in radio frequency energy harvesting (RFEH) systems, where harvested voltage signals from ambient RF energy may reveal users’ mobile app activities and fine-grained in-app actions. The project aims to understand the relationship between mobile-device activities, wireless traffic, indoor propagation, and harvested energy signals, and to build a systematic framework for evaluating RFEH-based privacy leakage.
  • Role: Research assistant; responsible for theoretical modeling, simulator development, and side-channel attack framework design.
  • Keywords: Radio frequency energy harvesting, side-channel attack, mobile privacy, wireless sensing, indoor propagation modeling, blind source separation.

Smart Robot Design and Demonstration

  • Description: This team design project built an autonomous smart robot car for navigation, recognition and transportation tasks, integrating mechanical chassis construction, motor control, visual perception, ultrasonic sensing, and a mechanical arm/claw. The robot combined an mbed-based control system with OpenMV vision to recognize visual cues, navigate the task field, and execute object-handling actions during field demonstrations.
  • Role: Team member, responsible for robot car frame construction, PID/control tuning, and field experiments.
  • Keywords: Smart robot, autonomous navigation, PID control, STM32 MCU, OpenMV, ultrasonic sensing, motor control.

Robot Path Planning Based on Visual SLAM

  • Description: This project extends ORB-SLAM3 with dense point-cloud mapping based on RGB-D data, converts dense maps into Octomap and lightweight 2D occupancy grids, and evaluates reinforcement-learning-based planners for autonomous navigation.
  • Role: Independent researcher, algorithm designer, system developer.
  • Keywords: Visual SLAM, robot path planning, dense mapping, occupancy grid mapping, reinforcement learning, autonomous navigation.

publications

D-LoRa: a Distributed Parameter Adaptation Scheme for LoRa Network

Published in IEEE Global Communications Conference (GLOBECOM), 2025

A distributed parameter adaptation scheme for LoRa networks.

Recommended citation: R. Wang, T. Song, J. Ren, et al. (2025). "D-LoRa: a Distributed Parameter Adaptation Scheme for LoRa Network." In Proc. IEEE Global Communications Conference (GLOBECOM), Taipei, Taiwan. Accepted.
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Code

Two-Layer Reinforcement Learning-Assisted Joint Beamforming and Trajectory Optimization for Multi-UAV Downlink Communications

Published in Submitted to IEEE Transactions on Wireless Communications, 2026

A two-layer learning framework for joint beamforming and trajectory optimization in multi-UAV downlink communications.

Recommended citation: R. Wang, E. M. A. Ghoura, O. A. M. Alhussein, et al. (2026). "Two-Layer Reinforcement Learning-Assisted Joint Beamforming and Trajectory Optimization for Multi-UAV Downlink Communications." Submitted to IEEE Transactions on Wireless Communications.
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Code

talks

teaching