Fractional sequential sensing for energy efficient cooperative cognitive radio networks

Ahmed M. Salama; Ahmed Zahran; Tamer Elbatt

doi:10.1109/GlobalSIP.2014.7032333

Fractional sequential sensing for energy efficient cooperative cognitive radio networks

Ahmed M. Salama
, Ahmed Zahran
, Tamer Elbatt

Nile University
Cairo University

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

Abstract

In this paper, we propose fractional sequential sensing (FSS) as a novel cooperative sensing scheme for cognitive radio networks. FSS compromises a tradeoff between sensing accuracy and efficiency by formulating an optimization problem whose solution identifies FSS sensing parameters. These parameters include the sensing period and channels allocated for each user. Our simulation results show that FSS successfully improves the sensing accuracy while maintaining a low power profile. Additionally, we show that the sensing accuracy performance gap between FSS and other traditional schemes increases by optimizing decision engine.

Original language	English
Title of host publication	2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1301-1305
Number of pages	5
ISBN (Electronic)	9781479970889
DOIs	https://doi.org/10.1109/GlobalSIP.2014.7032333
Publication status	Published - 5 Feb 2014
Externally published	Yes
Event	2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014 - Atlanta, United States Duration: 3 Dec 2014 → 5 Dec 2014

Publication series

Name	2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014

Conference

Conference	2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
Country/Territory	United States
City	Atlanta
Period	3/12/14 → 5/12/14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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10.1109/GlobalSIP.2014.7032333

Cite this

Salama, A. M., Zahran, A., & Elbatt, T. (2014). Fractional sequential sensing for energy efficient cooperative cognitive radio networks. In 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014 (pp. 1301-1305). Article 7032333 (2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2014.7032333

Salama, Ahmed M. ; Zahran, Ahmed ; Elbatt, Tamer. / Fractional sequential sensing for energy efficient cooperative cognitive radio networks. 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 1301-1305 (2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014).

@inproceedings{11a28132f5e24858b092a01fb4a963d2,

title = "Fractional sequential sensing for energy efficient cooperative cognitive radio networks",

abstract = "In this paper, we propose fractional sequential sensing (FSS) as a novel cooperative sensing scheme for cognitive radio networks. FSS compromises a tradeoff between sensing accuracy and efficiency by formulating an optimization problem whose solution identifies FSS sensing parameters. These parameters include the sensing period and channels allocated for each user. Our simulation results show that FSS successfully improves the sensing accuracy while maintaining a low power profile. Additionally, we show that the sensing accuracy performance gap between FSS and other traditional schemes increases by optimizing decision engine.",

author = "Salama, \{Ahmed M.\} and Ahmed Zahran and Tamer Elbatt",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014 ; Conference date: 03-12-2014 Through 05-12-2014",

year = "2014",

month = feb,

day = "5",

doi = "10.1109/GlobalSIP.2014.7032333",

language = "English",

series = "2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014",

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

pages = "1301--1305",

booktitle = "2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014",

address = "United States",

}

Salama, AM, Zahran, A & Elbatt, T 2014, Fractional sequential sensing for energy efficient cooperative cognitive radio networks. in 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014., 7032333, 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014, Institute of Electrical and Electronics Engineers Inc., pp. 1301-1305, 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014, Atlanta, United States, 3/12/14. https://doi.org/10.1109/GlobalSIP.2014.7032333

Fractional sequential sensing for energy efficient cooperative cognitive radio networks. / Salama, Ahmed M.; Zahran, Ahmed; Elbatt, Tamer.
2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 1301-1305 7032333 (2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014).

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

TY - GEN

T1 - Fractional sequential sensing for energy efficient cooperative cognitive radio networks

AU - Salama, Ahmed M.

AU - Zahran, Ahmed

AU - Elbatt, Tamer

PY - 2014/2/5

Y1 - 2014/2/5

N2 - In this paper, we propose fractional sequential sensing (FSS) as a novel cooperative sensing scheme for cognitive radio networks. FSS compromises a tradeoff between sensing accuracy and efficiency by formulating an optimization problem whose solution identifies FSS sensing parameters. These parameters include the sensing period and channels allocated for each user. Our simulation results show that FSS successfully improves the sensing accuracy while maintaining a low power profile. Additionally, we show that the sensing accuracy performance gap between FSS and other traditional schemes increases by optimizing decision engine.

AB - In this paper, we propose fractional sequential sensing (FSS) as a novel cooperative sensing scheme for cognitive radio networks. FSS compromises a tradeoff between sensing accuracy and efficiency by formulating an optimization problem whose solution identifies FSS sensing parameters. These parameters include the sensing period and channels allocated for each user. Our simulation results show that FSS successfully improves the sensing accuracy while maintaining a low power profile. Additionally, we show that the sensing accuracy performance gap between FSS and other traditional schemes increases by optimizing decision engine.

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M3 - Conference proceeding

AN - SCOPUS:84949928867

T3 - 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014

SP - 1301

EP - 1305

BT - 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014

Y2 - 3 December 2014 through 5 December 2014

ER -

Salama AM, Zahran A, Elbatt T. Fractional sequential sensing for energy efficient cooperative cognitive radio networks. In 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 1301-1305. 7032333. (2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014). doi: 10.1109/GlobalSIP.2014.7032333

Fractional sequential sensing for energy efficient cooperative cognitive radio networks

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