Ruiqi Wang

Ruiqi Wang

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.
Distributed resource allocation framwork for LoRaWAN based on online learning
Distributed resource allocation framwork for LoRaWAN based on online learning.