Mobility resilience and overhead constrained adaptation in directional 60 GHz WLANs

Haider, Muhammad Kumail; Knightly, Edward W.

doi:10.1145/2942358.2942380

Cited by 70 publications

(13 citation statements)

References 18 publications

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“…2 Simulation result for a large room with no obstacles and a point-to-point link. [109] 385 µs BBS [111] 121 µs Reduced Search [129] 91 µs Adaptive Search [114] 70 µs MOCA [113] 20 µs 802.11ad Tracking [1] 11.04 µs σ = 0.32 Gbps Our approach 0 µs 802.11ad. To avoid rate adaptation errors resulting in high packet losses, maintaining a stable SNR is crucial.…”

Section: A4 Discussionmentioning

confidence: 99%

“…Recent work focuses on further reducing the duration of beamsweeps. This includes sending beacon and SLS frames via multi-lobe beam patterns [109,110], preceding each data frame with a very short control frame that probes neighboring sectors [113], using past steering information to only probe the most promising sectors [114], or resorting to beacons on lower-frequency bands for angle-of-arrival estimation [111]. The standard also defines basic beam tracking [1].…”

Section: Appendix a Device Tracking In 60 Ghz Wireless Networkmentioning

confidence: 99%

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Zero Overhead Device Tracking in 60 GHz Wireless Networks using Multi-Lobe Beam Patterns

Loch

Assasa

Palacios

et al. 2017

Proceedings of the 13th International Conference on Emerging Networking EXperiments and Technologies

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Millimeter wave (mmWave) technology is one of the main pillars of the next generation Wireless Local Area Networks (WLANs) and 5G mobile networks. The main reason lies in the quantum leap of capacity it provides with respect to wireless networks operating in the sub-6-GHz band. Nevertheless, efficient and reliable communication in the mmWave band demands novel techniques to tackle all the barriers associated with wireless propagation in this band. For

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Section: A4 Discussionmentioning

confidence: 99%

Section: Appendix a Device Tracking In 60 Ghz Wireless Networkmentioning

confidence: 99%

Zero Overhead Device Tracking in 60 GHz Wireless Networks using Multi-Lobe Beam Patterns

Loch

Assasa

Palacios

et al. 2017

Proceedings of the 13th International Conference on Emerging Networking EXperiments and Technologies

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“…By default, the IEEE 802.11ad protocol resorts to costly beamtraining when nodes move. Related work presents improvements on this behavior, such as short frames preceding data packets to assess the current state of the channel and react accordingly [48], or using the data packet preamble to slightly steer the main lobe to the sides [49]. Cacciapuoti [50] has designed a mobility-aware user association strategy for 5G-mmWave networks based on association strategies.…”

Section: Beam Steeringmentioning

confidence: 99%

Machine Learning Based Network Analysis Using Millimeter-Wave Narrow-Band Energy Traces

Scalabrin

Bielsa

Loch

et al. 2020

IEEE Trans. on Mobile Comput.

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“…• Minimize control overhead: Protocol overhead should be reduced as much as possible, especially for transmitting short packets [20][21][22]. Due to the large channel acquisition overhead, small packets have disproportionately high energy costs.…”

Section: State Of Artmentioning

confidence: 99%

An Adaptive Beamforming Time with Round Robin MAC Algorithm for Reducing Energy Consumption in MANET

Inzillo¹,

Rango²,

Quintana³

et al. 2018

Preprint

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The use of Smart Antenna Systems (SAS) in pervasive environments such the Mobile Ad hoc Networks (MANET) has been promoted as the best choice to improve Spatial Division Multiple Access (SDMA) and throughput. Although directional communications are expected to provide great advantages in terms of network performance, directional MAC (Medium Access Control) protocols introduce several issues. One of the most known problems in this context is represented by the fact that, attempting to solve or at least mitigate the problems introduced by these kinds of antennas especially at MAC layer, a large amount of energy consumption is achieved ; for example, due to excessive retransmissions introduced by very frequently issue such as deafness and handoff. The expedients proposed in order to reduce these drawbacks attempting to limit beamforming time of nodes in cooperation with a Round-Robin scheduling, can grant high performance in terms of fairness and throughput. However the overall energy consumption in the network is not efficent due to the static approach. In view of this, we propose an Adaptive Beamforming Time with Round-Robin MAC providing for a dynamic assignment of the beamforming time with the purpose to limit the waste of energy of nodes.

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Mobility resilience and overhead constrained adaptation in directional 60 GHz WLANs

Cited by 70 publications

References 18 publications

Zero Overhead Device Tracking in 60 GHz Wireless Networks using Multi-Lobe Beam Patterns

Zero Overhead Device Tracking in 60 GHz Wireless Networks using Multi-Lobe Beam Patterns

Machine Learning Based Network Analysis Using Millimeter-Wave Narrow-Band Energy Traces

An Adaptive Beamforming Time with Round Robin MAC Algorithm for Reducing Energy Consumption in MANET

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