Scalable Multicast in Highly-Directional 60-GHz WLANs. Naribole, S. & Knightly, E. IEEE/ACM Transactions on Networking, 25(5):2844–2857, October, 2017. doi abstract bibtex The 60-GHz bands target multi-gigabit rate applications, such as high definition video streaming. Unfortunately, to provide multicast service, the strong directionality required at 60 GHz precludes serving all clients in a multicast group with a single transmission. Instead, a multicast transmission is comprised of a sequence of beam-formed transmissions (a beam group) that together cover all multicast group members. In this paper, we design, implement, and experimentally evaluate scalable directional multicast (SDM) as a technique to 1) train the access point with per-beam per-client RSSI measurements via partially traversing a codebook tree. The training balances the objectives of limiting overhead with collecting sufficient data to form efficient beam groups. 2) Using the available training information, we design a scalable beam grouping algorithm that approximates the minimum multicast group data transmission time. We implement the key components of SDM and evaluate with a combination of over-the-air experiments and trace-driven simulations. Our results show that the gains provided by SDM increase with group size and provide near-optimal group selection with significantly reduced training time, yielding up to 1.8 times throughput gains over exhaustive-search training and grouping.
@article{naribole_scalable_2017,
title = {Scalable {Multicast} in {Highly}-{Directional} 60-{GHz} {WLANs}},
volume = {25},
issn = {1063-6692},
doi = {10.1109/TNET.2017.2717901},
abstract = {The 60-GHz bands target multi-gigabit rate applications, such as high definition video streaming. Unfortunately, to provide multicast service, the strong directionality required at 60 GHz precludes serving all clients in a multicast group with a single transmission. Instead, a multicast transmission is comprised of a sequence of beam-formed transmissions (a beam group) that together cover all multicast group members. In this paper, we design, implement, and experimentally evaluate scalable directional multicast (SDM) as a technique to 1) train the access point with per-beam per-client RSSI measurements via partially traversing a codebook tree. The training balances the objectives of limiting overhead with collecting sufficient data to form efficient beam groups. 2) Using the available training information, we design a scalable beam grouping algorithm that approximates the minimum multicast group data transmission time. We implement the key components of SDM and evaluate with a combination of over-the-air experiments and trace-driven simulations. Our results show that the gains provided by SDM increase with group size and provide near-optimal group selection with significantly reduced training time, yielding up to 1.8 times throughput gains over exhaustive-search training and grouping.},
number = {5},
journal = {IEEE/ACM Transactions on Networking},
author = {Naribole, S. and Knightly, E.},
month = oct,
year = {2017},
keywords = {60 GHz, 802.11ad, Antenna arrays, MIMO, RSSI, Radio frequency, SDM, Training, Unicast, WLAN, array signal processing, beam-formed transmissions, codebook tree, codebook-based beamforming, data communication, exhaustive-search training, frequency 60.0 GHz, high definition video streaming, millimeter-wave, minimum multicast group data transmission time, multi-access systems, multicast, multicast communication, multicast group members, multicast service, multicast transmission, multigigabit rate applications, near-optimal group selection, over-the-air experiments, per-client RSSI measurements, scalable, scalable beam grouping algorithm, scalable directional multicast, scalable multicast, telecommunication network planning, wireless LAN},
pages = {2844--2857}
}
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In this paper, we design, implement, and experimentally evaluate scalable directional multicast (SDM) as a technique to 1) train the access point with per-beam per-client RSSI measurements via partially traversing a codebook tree. The training balances the objectives of limiting overhead with collecting sufficient data to form efficient beam groups. 2) Using the available training information, we design a scalable beam grouping algorithm that approximates the minimum multicast group data transmission time. We implement the key components of SDM and evaluate with a combination of over-the-air experiments and trace-driven simulations. 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