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Wireless Inference-based Notification (WIN) without Packet Decoding
Kevin Chen and H. T. Kung, Harvard University
We consider ultra-energy-efficient wireless transmission of notifications in sensor networks. We argue that the usual practice where a receiver decodes packets sent by a remote node to acquire its state or message is suboptimal in energy use. We propose an alternative approach where a receiver first (1) performs physical-layer matched filtering on arrived packets without actually decoding them at the link layer or higher layer, and then (2) based on the matching results infers the sender's state or message from the time-series pattern of packet arrivals. We show that hierarchical multi-layer inference can be effective for this purpose in coping with channel noise. Because packets are not required to be decodable by the receiver, the sender can reach a farther receiver without increasing the transmit power or, equivalently, a receiver at the same distance with a lower transmit power. We call our scheme Wireless Inference-based Notification (WIN) without Packet Decoding. We demonstrate by analysis and simulation that WIN allows a sender to multiply its notification distance. We show how senders can realize these energy-efficiency benefits with unchanged system and protocols; only receivers, which normally are larger systems than senders and have ample computing and power resources for WIN-related processing.
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author = {Kevin Chen and H. T. Kung},
title = {Wireless Inference-based Notification ({{{{{WIN}}}}}) without Packet Decoding},
booktitle = {10th International Conference on Autonomic Computing (ICAC 13)},
year = {2013},
isbn = {978-1-931971-02-7},
address = {San Jose, CA},
pages = {325--330},
url = {https://www.usenix.org/conference/icac13/technical-sessions/presentation/chen},
publisher = {USENIX Association},
month = jun
}
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