Emerging mobile applications give rise to new bandwidth-hungry and latency-sensitive traffic classes that challenge existing wireless systems. Addressing them requires innovative approaches such as simultaneous data transmission across multiple Radio Access Technologies (RATs), e.g., WiFi and WiGig. However, existing transport layer multi-RAT traffic aggregation schemes, e.g., multi-path TCP, suffer from Head-of-Line (HoL) blocking and sub-optimal traffic splitting across the RATs that severely penalize their performance. In this paper, we investigate the design of FBDT, a novel multi-path transport layer solution that for the first time can achieve the sum of the throughput rates across the individual RATs network paths, despite their channel conditions' dynamics. We have implemented FBDT in the Linux kernel and show substantial improvement in throughput relative to state-of-the-art schemes, e.g, 2.5x gain in a dual-RAT scenario (WiFi and WiGig) when the client is mobile. Second, we extend FBDT to more than two radios and demonstrate that its throughput performance scales linearly with the number of RATs, in contrast to multi-path TCP, whose performance degrades with an increase in the number of RATs. We evaluate the performance of FBDT on different traffic classes and demonstrate: (i) 2-3 times shorter file download times, (ii) up to 10 times shorter streaming times and 10 dB higher video quality for progressive download video applications, and (iii) up to 9 dB higher viewport quality for interactive mobile VR applications, when our viewport quality maximization framework is employed along with FBDT.

The metaverse encompasses many virtual universes and relies on streaming high-quality 360° videos to VR/AR headsets. This type of video transmission requires very high data rates to meet the desired Quality of Experience (QoE) for all clients. Simultaneous data transmission across multiple Radio Access Technologies (RATs) such as WiFi and WiGig is a key solution to meet this required capacity demand. However, existing transport layer multi-RAT traffic aggregation schemes suffer from Head-of-Line (HoL) blocking and sub-optimal traffic splitting across the RATs, particularly when there is a high fluctuation in their channel conditions. As a result, state-of-the-art multi-path TCP (MPTCP) solutions can achieve aggregate transmission data rates that are lower than that of using only a single WiFi RAT in many practical settings, e.g., when the client is mobile. We make two key contributions to enable high quality mobile 360° video VR streaming using multiple RATs. First, we propose the design of FBDT, a novel multi-path transport layer solution that can achieve the sum of individual transmission rates across the RATs despite their system dynamics. We implemented FBDT in the Linux kernel and showed substantial improvement in transmission throughput relative to state-of-the-art schemes, e.g, 2.5x gain in a dual-RAT scenario (WiFi and WiGig) when the VR client is mobile. Second, we formulate an optimization problem to maximize a mobile VR client's viewport quality by taking into account statistical models of how clients explore the 360° look-around panorama and the transmission data rate of each RAT. We explore an iterative method to solve this problem and evaluate its performance through measurement-driven simulations leveraging our testbed. We show up to 12 dB increase in viewport quality when our optimization framework is employed.