Greedy tree search for Internet of Things signal detection

Jaeseok Lee; Byonghyo Shim

doi:10.1109/ISIT.2015.7282919

Greedy tree search for Internet of Things signal detection

Jaeseok Lee, Byonghyo Shim

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we propose a greedy tree search algorithm for Internet of Things (IoT) signal detection. The proposed method, referred to as matching pursuit with integer tree search (MP-ITS), recovers integer sparse vector (sparse vector whose nonzero elements are chosen from a set of finite alphabets) using the tree search. In order to control the computational burden yet maintains the effectiveness of the tree search, MP-ITS employs two strategies, viz., pre-screening to put a limitation on columns of the channel matrix and tree pruning to eliminate unpromising candidates from the tree. We show from the restricted isometry property (RIP) analysis and empirical simulations on realistic IoT scenarios that the proposed method is effective in recovering the sparse vector with integer constraint.

Original language	English
Title of host publication	Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2563-2567
Number of pages	5
ISBN (Electronic)	9781467377041
DOIs	https://doi.org/10.1109/ISIT.2015.7282919
Publication status	Published - 2015 Sept 28
Event	IEEE International Symposium on Information Theory, ISIT 2015 - Hong Kong, Hong Kong Duration: 2015 Jun 14 → 2015 Jun 19

Publication series

Name	IEEE International Symposium on Information Theory - Proceedings
Volume	2015-June
ISSN (Print)	2157-8095

Other

Other	IEEE International Symposium on Information Theory, ISIT 2015
Country/Territory	Hong Kong
City	Hong Kong
Period	15/6/14 → 15/6/19

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

ASJC Scopus subject areas

Theoretical Computer Science
Information Systems
Modelling and Simulation
Applied Mathematics

Access to Document

10.1109/ISIT.2015.7282919

Cite this

Lee, J., & Shim, B. (2015). Greedy tree search for Internet of Things signal detection. In Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015 (pp. 2563-2567). Article 7282919 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2015-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2015.7282919

Greedy tree search for Internet of Things signal detection. / Lee, Jaeseok; Shim, Byonghyo.
Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 2563-2567 7282919 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2015-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lee, J & Shim, B 2015, Greedy tree search for Internet of Things signal detection. in Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015., 7282919, IEEE International Symposium on Information Theory - Proceedings, vol. 2015-June, Institute of Electrical and Electronics Engineers Inc., pp. 2563-2567, IEEE International Symposium on Information Theory, ISIT 2015, Hong Kong, Hong Kong, 15/6/14. https://doi.org/10.1109/ISIT.2015.7282919

@inproceedings{fd8ff68765994d8c978a8c54b38944e9,

title = "Greedy tree search for Internet of Things signal detection",

abstract = "In this paper, we propose a greedy tree search algorithm for Internet of Things (IoT) signal detection. The proposed method, referred to as matching pursuit with integer tree search (MP-ITS), recovers integer sparse vector (sparse vector whose nonzero elements are chosen from a set of finite alphabets) using the tree search. In order to control the computational burden yet maintains the effectiveness of the tree search, MP-ITS employs two strategies, viz., pre-screening to put a limitation on columns of the channel matrix and tree pruning to eliminate unpromising candidates from the tree. We show from the restricted isometry property (RIP) analysis and empirical simulations on realistic IoT scenarios that the proposed method is effective in recovering the sparse vector with integer constraint.",

author = "Jaeseok Lee and Byonghyo Shim",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Symposium on Information Theory, ISIT 2015 ; Conference date: 14-06-2015 Through 19-06-2015",

year = "2015",

month = sep,

day = "28",

doi = "10.1109/ISIT.2015.7282919",

language = "English",

series = "IEEE International Symposium on Information Theory - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2563--2567",

booktitle = "Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015",

}

TY - GEN

T1 - Greedy tree search for Internet of Things signal detection

AU - Lee, Jaeseok

AU - Shim, Byonghyo

PY - 2015/9/28

Y1 - 2015/9/28

N2 - In this paper, we propose a greedy tree search algorithm for Internet of Things (IoT) signal detection. The proposed method, referred to as matching pursuit with integer tree search (MP-ITS), recovers integer sparse vector (sparse vector whose nonzero elements are chosen from a set of finite alphabets) using the tree search. In order to control the computational burden yet maintains the effectiveness of the tree search, MP-ITS employs two strategies, viz., pre-screening to put a limitation on columns of the channel matrix and tree pruning to eliminate unpromising candidates from the tree. We show from the restricted isometry property (RIP) analysis and empirical simulations on realistic IoT scenarios that the proposed method is effective in recovering the sparse vector with integer constraint.

AB - In this paper, we propose a greedy tree search algorithm for Internet of Things (IoT) signal detection. The proposed method, referred to as matching pursuit with integer tree search (MP-ITS), recovers integer sparse vector (sparse vector whose nonzero elements are chosen from a set of finite alphabets) using the tree search. In order to control the computational burden yet maintains the effectiveness of the tree search, MP-ITS employs two strategies, viz., pre-screening to put a limitation on columns of the channel matrix and tree pruning to eliminate unpromising candidates from the tree. We show from the restricted isometry property (RIP) analysis and empirical simulations on realistic IoT scenarios that the proposed method is effective in recovering the sparse vector with integer constraint.

UR - http://www.scopus.com/inward/record.url?scp=84969784613&partnerID=8YFLogxK

U2 - 10.1109/ISIT.2015.7282919

DO - 10.1109/ISIT.2015.7282919

M3 - Conference contribution

AN - SCOPUS:84969784613

T3 - IEEE International Symposium on Information Theory - Proceedings

SP - 2563

EP - 2567

BT - Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - IEEE International Symposium on Information Theory, ISIT 2015

Y2 - 14 June 2015 through 19 June 2015

ER -

Greedy tree search for Internet of Things signal detection

Abstract

Publication series

Other

Bibliographical note

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this