SpecSense: Crowdsensing for efficient querying of spectrum occupancy

Ayon Chakraborty; Md Shaifur Rahman; Himanshu Gupta; Samir R. Das

doi:10.1109/INFOCOM.2017.8057113

SpecSense: Crowdsensing for efficient querying of spectrum occupancy

Ayon Chakraborty
, Md Shaifur Rahman
, Himanshu Gupta
, Samir R. Das

Computer Science

Stony Brook University

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

80 Scopus citations

Abstract

We describe an end-to-end platform called SpecSense to support large scale spectrum monitoring. SpecSense crowdsources spectrum monitoring to low-cost, low-power commodity SDR/embedded platforms and provides necessary analytics support in a central spectrum server. In this work, we describe SpecSense and address specific challenges related to accurately estimate spectrum occupancy on demand with low overhead. To address the accuracy question, we augment state-of-the-art spatial interpolation techniques to accommodate scenarios where RF propagation characteristics change across space. To address the overhead question, we solve the sensor selection problem to select the minimum number of spectrum sensors that can best estimate the spectrum at the requested locations.

Original language	English
Title of host publication	INFOCOM 2017 - IEEE Conference on Computer Communications
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509053360
DOIs	https://doi.org/10.1109/INFOCOM.2017.8057113
State	Published - Oct 2 2017
Event	2017 IEEE Conference on Computer Communications, INFOCOM 2017 - Atlanta, United States Duration: May 1 2017 → May 4 2017

Publication series

Name	Proceedings - IEEE INFOCOM
ISSN (Print)	0743-166X

Conference

Conference	2017 IEEE Conference on Computer Communications, INFOCOM 2017
Country/Territory	United States
City	Atlanta
Period	05/1/17 → 05/4/17

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10.1109/INFOCOM.2017.8057113

Cite this

@inproceedings{e03fb6d321b140799722093fdcb56bee,

title = "SpecSense: Crowdsensing for efficient querying of spectrum occupancy",

abstract = "We describe an end-to-end platform called SpecSense to support large scale spectrum monitoring. SpecSense crowdsources spectrum monitoring to low-cost, low-power commodity SDR/embedded platforms and provides necessary analytics support in a central spectrum server. In this work, we describe SpecSense and address specific challenges related to accurately estimate spectrum occupancy on demand with low overhead. To address the accuracy question, we augment state-of-the-art spatial interpolation techniques to accommodate scenarios where RF propagation characteristics change across space. To address the overhead question, we solve the sensor selection problem to select the minimum number of spectrum sensors that can best estimate the spectrum at the requested locations.",

author = "Ayon Chakraborty and Rahman, \{Md Shaifur\} and Himanshu Gupta and Das, \{Samir R.\}",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE Conference on Computer Communications, INFOCOM 2017 ; Conference date: 01-05-2017 Through 04-05-2017",

year = "2017",

month = oct,

day = "2",

doi = "10.1109/INFOCOM.2017.8057113",

language = "English",

series = "Proceedings - IEEE INFOCOM",

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

booktitle = "INFOCOM 2017 - IEEE Conference on Computer Communications",

}

Chakraborty, A, Rahman, MS, Gupta, H & Das, SR 2017, SpecSense: Crowdsensing for efficient querying of spectrum occupancy. in INFOCOM 2017 - IEEE Conference on Computer Communications., 8057113, Proceedings - IEEE INFOCOM, Institute of Electrical and Electronics Engineers Inc., 2017 IEEE Conference on Computer Communications, INFOCOM 2017, Atlanta, United States, 05/1/17. https://doi.org/10.1109/INFOCOM.2017.8057113

SpecSense: Crowdsensing for efficient querying of spectrum occupancy. / Chakraborty, Ayon; Rahman, Md Shaifur; Gupta, Himanshu et al.
INFOCOM 2017 - IEEE Conference on Computer Communications. Institute of Electrical and Electronics Engineers Inc., 2017. 8057113 (Proceedings - IEEE INFOCOM).

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

TY - GEN

T1 - SpecSense

T2 - 2017 IEEE Conference on Computer Communications, INFOCOM 2017

AU - Chakraborty, Ayon

AU - Rahman, Md Shaifur

AU - Gupta, Himanshu

AU - Das, Samir R.

PY - 2017/10/2

Y1 - 2017/10/2

N2 - We describe an end-to-end platform called SpecSense to support large scale spectrum monitoring. SpecSense crowdsources spectrum monitoring to low-cost, low-power commodity SDR/embedded platforms and provides necessary analytics support in a central spectrum server. In this work, we describe SpecSense and address specific challenges related to accurately estimate spectrum occupancy on demand with low overhead. To address the accuracy question, we augment state-of-the-art spatial interpolation techniques to accommodate scenarios where RF propagation characteristics change across space. To address the overhead question, we solve the sensor selection problem to select the minimum number of spectrum sensors that can best estimate the spectrum at the requested locations.

AB - We describe an end-to-end platform called SpecSense to support large scale spectrum monitoring. SpecSense crowdsources spectrum monitoring to low-cost, low-power commodity SDR/embedded platforms and provides necessary analytics support in a central spectrum server. In this work, we describe SpecSense and address specific challenges related to accurately estimate spectrum occupancy on demand with low overhead. To address the accuracy question, we augment state-of-the-art spatial interpolation techniques to accommodate scenarios where RF propagation characteristics change across space. To address the overhead question, we solve the sensor selection problem to select the minimum number of spectrum sensors that can best estimate the spectrum at the requested locations.

UR - https://www.scopus.com/pages/publications/85027285540

U2 - 10.1109/INFOCOM.2017.8057113

DO - 10.1109/INFOCOM.2017.8057113

M3 - Conference contribution

AN - SCOPUS:85027285540

T3 - Proceedings - IEEE INFOCOM

BT - INFOCOM 2017 - IEEE Conference on Computer Communications

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 1 May 2017 through 4 May 2017

ER -

SpecSense: Crowdsensing for efficient querying of spectrum occupancy

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