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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/15724

Title: Binary Data Gathering with a Helper in Internet of Things: Distortion Analysis and Performance Evaluation
Authors: Lin, Wensheng
He, Xin
Juntti, Markku
Matsumoto, Tad
Keywords: Binary CEO problem
binary data gathering
Internet of Things
rate-distortion
side information
Issue Date: 2019-01-15
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Magazine name: IEEE Access
DOI: 10.1109/ACCESS.2019.2893019
Abstract: This paper focuses on one-helper assisted binary data gathering networks, for example, such as in Internet of Things (IoT), where a destination makes estimates of binary data relying on a number of agents and one helper. Due to the noise, corrupting errors already exist in the agent observations. To analyze performance of this system, we formulate this system as a binary chief executive officer (CEO) problem with a helper. Initially, we use a successive decoding scheme to decompose the binary CEO problem with a helper into the multiterminal source coding and final decision problems. Then, we present an outer bound on the rate-distortion region for multiterminal source coding with binary sources and a helper. After solving a convex optimization problem formulated from the derived outer bound, we obtain the final distortion by substituting the minimized distortions of observation into the distortion propagating function (DPF), which is derived to bridge the relationship between the joint decoding results and final decision. Finally, we analyze the trade-off of rate-distortion through theoretical calculation and simulations. Both the theoretical and simulation results demonstrate that a helper can obviously reduce the signal-tonoise ratio (SNR) threshold. We also have an in-depth discussion on the differences of system performance improvement between locating a helper and including an additional agent.
Rights: This is the author's version of the work. Copyright (C) 2019 IEEE. IEEE Access, 2019, DOI:10.1109/ACCESS.2019.2893019. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
URI: http://hdl.handle.net/10119/15724
Material Type: author
Appears in Collections:b10-1. 雑誌掲載論文 (Journal Articles)

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