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Energy-Efficient mm-Wave Backhauling via Frame Aggregation in Wide Area Networks

Wide area networks for surveying applications, such as seismic acquisition, have been witnessing a significant increase in node density and area, where large amounts of data have to be transferred in real-time. While cables can meet these requirements, they account for a majority of the equipment we...

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Bibliographic Details
Published in:IEEE transactions on wireless communications 2021-10, Vol.20 (10), p.6954-6970
Main Authors: Reddy, Varun Amar, Stuber, Gordon L., Al-Dharrab, Suhail, Mesbah, Wessam, Muqaibel, Ali Hussein
Format: Article
Language:English
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Summary:Wide area networks for surveying applications, such as seismic acquisition, have been witnessing a significant increase in node density and area, where large amounts of data have to be transferred in real-time. While cables can meet these requirements, they account for a majority of the equipment weight, maintenance, and labor costs. A novel wireless network architecture, compliant with the IEEE 802.11ad standard, is proposed for establishing scalable, energy-efficient, and gigabit-rate backhaul across very large areas. Statistical path-loss and line-of-sight models are derived using real-world topographic data in well-known seismic regions. Additionally, a cross-layer analytical model is derived for 802.11 systems that can characterize the overall latency and power consumption under the impact of co-channel interference. On the basis of these models, a Frame Aggregation Power-Saving Backhaul (FA-PSB) scheme is proposed for near-optimal power conservation under a latency constraint, through a duty-cycled approach. A performance evaluation with respect to the survey size and data generation rate reveals that the proposed architecture and the FA-PSB scheme can support real-time acquisition in large-scale high-density scenarios while operating with minimal power consumption, thereby enhancing the lifetime of wireless seismic surveys. The FA-PSB scheme can be applied to cellular backhaul and sensor networks as well.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2021.3079345