8 citations · 31 across the 10 of their papers we have counts for
6 papers · 1 filter
A Self-Configurable Grouping Method for Integrated Wi-SUN FAN and TSCH-based Networks
Xinyu Ni, Michael Baddeley, Nan Jiang +1
Recent applications in large-scale wireless mesh networks (WSN), e.g., Advanced Metering Infrastructure (AMI) scenarios, expect to support an extended number of nodes with higher t…
A Decoupled Learning Strategy for Massive Access Optimization in Cellular IoT Networks
Nan Jiang, Yansha Deng, Arumugam Nallanathan +1
Cellular-based networks are expected to offer connectivity for massive Internet of Things (mIoT) systems. However, their Random Access CHannel (RACH) procedure suffers from unrelia…
Traffic Prediction and Random Access Control Optimization: Learning and Non-learning based Approaches
Nan Jiang, Yansha Deng, Arumugam Nallanathan
Random access schemes in modern wireless communications are generally based on the framed-ALOHA (f-ALOHA), which can be optimized by flexibly organizing devices' transmission and r…
Online Supervised Learning for Traffic Load Prediction in Framed-ALOHA Networks
Nan Jiang, Yansha Deng, Osvaldo Simeone +1
Predicting the current backlog, or traffic load, in framed-ALOHA networks enables the optimization of resource allocation, e.g., of the frame size. However, this prediction is made…
Deep Reinforcement Learning for Real-Time Optimization in NB-IoT Networks
Nan Jiang, Yansha Deng, Arumugam Nallanathan +1
NarrowBand-Internet of Things (NB-IoT) is an emerging cellular-based technology that offers a range of flexible configurations for massive IoT radio access from groups of devices w…
Cooperative Deep Reinforcement Learning for Multiple-Group NB-IoT Networks Optimization
Nan Jiang, Yansha Deng, Osvaldo Simeone +1
NarrowBand-Internet of Things (NB-IoT) is an emerging cellular-based technology that offers a range of flexible configurations for massive IoT radio access from groups of devices w…