The research team’s paper, “Environment-Aware Link Quality Prediction for Millimeter-Wave Wireless LANs,” proposes a millimeter-wave (mmWave) wireless LAN link quality prediction scheme based on knowledge of the environment. mmWave wireless LANs are targeted for use with emerging bandwidth-intensive applications such as virtual/augmented reality and real-time high-definition video. The data set generated through the study was used to train a machine learning model that captures the relationship between environment features and link quality. Evaluation shows that the model accurately predicts link quality at arbitrary locations, even for cases not represented in the training data set. This approach paves the way to design anticipatory networking approaches for future wireless systems. The research was supported in part by the National Science Foundation through Awards CNS–1813242 and CNS–2016381.

Blough is the associate chair for Faculty Development in the School of Electrical and Computer Engineering (ECE), and served as the Interim Steve W. Chaddick School Chair for five months in 2021. Blough is the director of the Critical Networking Laboratory, where his research primarily focuses on wireless networks.

Liu is a tenure-track assistant professor in the Department of Computer Science at North Carolina State University (NCSU). His research covers broad areas of networking, computing, and communication including networking and systems, mobile computing, machine learning, new communication paradigms, and software development and simulation.

This year’s MOBIWAC symposium was held October 24-28 in Montreal, Canada. It serves as a forum where researchers from academy and industry gather to discuss novel advances in mobility, wireless access, and related topics, aiming at advancing knowledge and identifying new directions for future research and development.