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    Rights statement: © ACM, 2018. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Sensor Networks, 14, 2, (2018)} http://doi.acm.org/10.1145/3209044

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Differentiating Clear Channel Assessment using Transmit Power Variation

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
Article number15
<mark>Journal publication date</mark>1/05/2018
<mark>Journal</mark>ACM Transactions on Sensor Networks
Issue number2
Volume14
Number of pages28
Publication StatusPublished
<mark>Original language</mark>English

Abstract

Clear Channel Assessment (CCA) is a core element of Wireless Sensor Network (WSN) Medium Access Control (MAC) protocols which is used on transmitter and receiver side. Current CCA implementations cannot determine the device type occupying the media, leaving nodes unable to differentiate between WSN traffic and interference. However, this would be valuable as MAC protocols benefit from reacting differently depending on the channel occupier. In this paper we describe a method called Power Differentiating Clear Channel Assessment (P-DCCA). Transmitters vary the output power of the radio while the packet is being sent. Receivers are able to identify signals with this characteristic, enabling a Differentiating Clear Channel Assessment (DCCA) check to reveal if the medium is currently occupied by WSN traffic other interference. We present an implementation and thorough evaluation of P-DCCA. Using ContikiMAC as example we describe how P-DCCA can be integrated within MAC protocols. We show via large-scale testbed experiments and deployments that P-DCCA enabled networks have a significant improved performance. For example, we show that a P-DCCA enabled network can improve Packet Reception Rate (PRR) by up to a factor of 10 while reducing energy usage by over 80% under heavy interference.

Bibliographic note

© ACM, 2018. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Sensor Networks, 14, 2, (2018)} http://doi.acm.org/10.1145/3209044