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The highly directional nature of the millimeter wave (mmWave) beams pose several challenges in using that spectrum for meeting the communication needs of immersive applications. In particular, the mmWave beams are susceptible to misalignments and blockages caused by user movements. As a result, mmWave channels are vulnerable to large fluctuations in quality, which in turn, cause disproportionate degradation in end-to-end performance of Transmission Control Protocol (TCP) based applications. In this paper, we propose a reinforcement learning (RL) integrated transport-layer plugin, Millimeter wave based Immersive Agent (MIA), for immersive content delivery over the mmWave link. MIA uses the RL model to predict mmWave link bandwidth based on the real-time measurement. Then, MIA cooperates with TCP’s congestion control scheme to adapt the sending rate in accordance with the predictions of the mmWave bandwidth. To evaluate the effectiveness of the proposed MIA, we conduct experiments using a mmWave augmented immersive testbed and network simulations. The evaluation results show that MIA improves end-to-end immersive performance significantly on both throughput and latency.
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COded Taking And Giving (COTAG): Enhancing Transport Layer Performance over Indoor Millimeter Wave Access Networks
Millimeter wave (mmWave) access networks have the potential to meet the high-throughput and low-latency needs of immersive applications. However, due to the highly directional nature of the mmWave beams and their susceptibility to beam misalignment and blockage resulting from user movements and rotations, the associated mmWave links are vulnerable to large channel fluctuations. These fluctuations result in disproportion- ately adverse effects on performance of transport layer protocols such as Transmission Control Protocol (TCP). To overcome this challenge, we propose a network layer solution, COded Taking And Giving (COTAG) scheme to sustain low-latency and high- throughput end-to-end TCP performance in dually connected networks. In particular, COTAG creates network encoded packets at the network gateway and each access point (AP) aiming to adaptively take the spare bandwidth on each link for transmis- sion. Further, if one link bandwidth drops due to user movements, COTAG actively abandons the transmission opportunity by conditionally dropping packets. Consequently, COTAG actively adapts to link quality changes in mmWave access network and enhances the TCP performance without jeopardizing the latency of immersive content delivery. To evaluate the effectiveness of the proposed COTAG, we conduct experiments using off-the- shelf APs and network simulations. The evaluation results show that COTAG improves end-to-end TCP performance significantly on both throughput and latency.
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- Award ID(s):
- 1703389
- PAR ID:
- 10524679
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 978-1-5386-8347-7
- Page Range / eLocation ID:
- 3610 to 3616
- Format(s):
- Medium: X
- Location:
- Seoul, Korea, Republic of
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ICC45855.2022.9839289
