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Data-Aided Sensing Where Communication and Sensing Meet: An Introduction

conference contribution
posted on 2020-01-01, 00:00 authored by Jinho ChoiJinho Choi
© 2020 IEEE. Since there are a number of Internet-of-Things (IoT) applications that need to collect data sets from a large number of sensors or devices in real-time, sensing and communication need to be integrated for efficient uploading from devices. In this paper, we introduce the notion of data-aided sensing (DAS) where a base station (BS) utilizes a subset of data that is already uploaded and available to select the next device for efficient data collection or sensing. Thus, using DAS, certain tasks in IoT applications, including federated learning, can be completed by uploading from a small number of selected devices. Two different types of DAS are considered: one is centralized DAS and the other is distributed DAS. In centralized DAS, the BS decides the uploading order, while each device can decide when to upload its own local data set among multiple uploading rounds in distributed DAS. In distributed DAS, random access is employed where the access probability of each device is decided according to its local measurement for efficient uploading.



Wireless Communications and Networking. Conference Workshops (2020 : Seoul, South Korea)


1 - 6




Seoul, South Korea

Place of publication

Piscataway, N.J.

Start date


End date






Publication classification

E1 Full written paper - refereed

Title of proceedings

WCNCW 2020 : Proceedings of the 2020 IEEE Wireless Communications and Networking Conference Workshops