Join us in exploring the future of energy-efficient in-building networks! As demand for high-performance wireless connectivity grows, optimizing Access Point (AP) placement is critical to reducing energy consumption and operational costs.

In this work, you will:

• Measure power consumption of WiFi and LiFi networks under different AP placement strategies.
• Use planning tools to simulate and evaluate network layouts.
• Compare energy efficiency and cost per bit for various deployment scenarios.
• Develop recommendations for optimizing AP placement to improve sustainability and reduce costs.

Prerequisites

Providing reliable voice communication over LDACS using IP-based networking

The primary goal of the thesis is to design and implement a FPGA-based system that enables multi-protocol support, automatic detection, and point-to-multipoint communication and contributes to scalable VLC solutions.

Are you ready to dive into cutting-edge technology that merges LiFi and WiFi networks? Imagine your work enabling devices to seamlessly connect across multiple interfaces, pushing the boundaries of what's possible in wireless communication. With multipath solutions like MPTCP and MPQUIC, the potential is immense—but the challenge is real.

We are looking for a motivated student to design and implement a state-of-the-art wireless-channel-aware packet scheduler. You'll tackle the complex task of scheduling data packets across multiple network paths, each with unique characteristics like delay and packet loss.

Related Reading:

1. W. Yang, L. Cai, S. Shu, J. Pan and A. Sepahi, "MAMS: Mobility-Aware Multipath Scheduler for MPQUIC," in IEEE/ACM Transactions on Networking, vol. 32, no. 4, pp. 3237-3252, Aug. 2024, doi: 10.1109/TNET.2024.3382269.

If you are interested in this work, please send me an email with a short introduction of yourself along with your CV and grade transcript.

Prerequisites

The goal of the internship would be to design and implement a new dynamic traffic steering policy for MLO (Multi-Link Operation) in WiFi-8. The focus of WiFi-8 will be Ultra High Reliability (UHR) so the traffic steering policy should also have this goal and be implemented using reinforcement learning.