Energy efficient multicasting in cognitive radio networks

Abdullah M. Almasoud; Ahmed E. Kamal

doi:10.1109/ICC.2017.7996474

Energy efficient multicasting in cognitive radio networks

Abdullah M. Almasoud
, Ahmed E. Kamal

Iowa State University

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

6 Scopus citations

Abstract

In this paper, we study the problem of energy minimization for multicasting in cognitive radio networks, using omnidirectional and directional antennas. Our objectives are to build the multicast routing tree and schedule the secondary users' transmissions such that the total energy consumption is minimized. We consider in this paper the energy consumption due to channels switching, and we study the channel switching and scheduling dependency. We model the problem as a MultiLayer Hyper Graph, then we formulate the optimization problem as Mixed Integer Linear Program (MILP). Moreover, we propose a heuristic algorithm to solve our problem in polynomial time. We also show how the primary users, directional antennas, the number of available channels and channel switching time per frequency jumping step affect the total energy consumption. The simulation results shows that our proposed algorithm achieves close performance to the optimal solution.

Original language	English
Title of host publication	2017 IEEE International Conference on Communications, ICC 2017
Editors	Merouane Debbah, David Gesbert, Abdelhamid Mellouk
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781467389990
DOIs	https://doi.org/10.1109/ICC.2017.7996474
State	Published - 28 Jul 2017
Externally published	Yes
Event	2017 IEEE International Conference on Communications, ICC 2017 - Paris, France Duration: 21 May 2017 → 25 May 2017

Publication series

Name	IEEE International Conference on Communications
ISSN (Print)	1550-3607

Conference

Conference	2017 IEEE International Conference on Communications, ICC 2017
Country/Territory	France
City	Paris
Period	21/05/17 → 25/05/17

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

cognitive radio network
directional antenna
Energy efficiency
multicast
routing
scheduling

Access to Document

10.1109/ICC.2017.7996474

Cite this

Almasoud, A. M., & Kamal, A. E. (2017). Energy efficient multicasting in cognitive radio networks. In M. Debbah, D. Gesbert, & A. Mellouk (Eds.), 2017 IEEE International Conference on Communications, ICC 2017 Article 7996474 (IEEE International Conference on Communications). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICC.2017.7996474

@inproceedings{fdd69f6d29724f74b3a1c06cc601f163,

title = "Energy efficient multicasting in cognitive radio networks",

abstract = "In this paper, we study the problem of energy minimization for multicasting in cognitive radio networks, using omnidirectional and directional antennas. Our objectives are to build the multicast routing tree and schedule the secondary users' transmissions such that the total energy consumption is minimized. We consider in this paper the energy consumption due to channels switching, and we study the channel switching and scheduling dependency. We model the problem as a MultiLayer Hyper Graph, then we formulate the optimization problem as Mixed Integer Linear Program (MILP). Moreover, we propose a heuristic algorithm to solve our problem in polynomial time. We also show how the primary users, directional antennas, the number of available channels and channel switching time per frequency jumping step affect the total energy consumption. The simulation results shows that our proposed algorithm achieves close performance to the optimal solution.",

keywords = "cognitive radio network, directional antenna, Energy efficiency, multicast, routing, scheduling",

author = "Almasoud, \{Abdullah M.\} and Kamal, \{Ahmed E.\}",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Communications, ICC 2017 ; Conference date: 21-05-2017 Through 25-05-2017",

year = "2017",

month = jul,

day = "28",

doi = "10.1109/ICC.2017.7996474",

language = "English",

series = "IEEE International Conference on Communications",

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

editor = "Merouane Debbah and David Gesbert and Abdelhamid Mellouk",

booktitle = "2017 IEEE International Conference on Communications, ICC 2017",

address = "United States",

}

Almasoud, AM & Kamal, AE 2017, Energy efficient multicasting in cognitive radio networks. in M Debbah, D Gesbert & A Mellouk (eds), 2017 IEEE International Conference on Communications, ICC 2017., 7996474, IEEE International Conference on Communications, Institute of Electrical and Electronics Engineers Inc., 2017 IEEE International Conference on Communications, ICC 2017, Paris, France, 21/05/17. https://doi.org/10.1109/ICC.2017.7996474

Energy efficient multicasting in cognitive radio networks. / Almasoud, Abdullah M.; Kamal, Ahmed E.
2017 IEEE International Conference on Communications, ICC 2017. ed. / Merouane Debbah; David Gesbert; Abdelhamid Mellouk. Institute of Electrical and Electronics Engineers Inc., 2017. 7996474 (IEEE International Conference on Communications).

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

TY - GEN

T1 - Energy efficient multicasting in cognitive radio networks

AU - Almasoud, Abdullah M.

AU - Kamal, Ahmed E.

PY - 2017/7/28

Y1 - 2017/7/28

N2 - In this paper, we study the problem of energy minimization for multicasting in cognitive radio networks, using omnidirectional and directional antennas. Our objectives are to build the multicast routing tree and schedule the secondary users' transmissions such that the total energy consumption is minimized. We consider in this paper the energy consumption due to channels switching, and we study the channel switching and scheduling dependency. We model the problem as a MultiLayer Hyper Graph, then we formulate the optimization problem as Mixed Integer Linear Program (MILP). Moreover, we propose a heuristic algorithm to solve our problem in polynomial time. We also show how the primary users, directional antennas, the number of available channels and channel switching time per frequency jumping step affect the total energy consumption. The simulation results shows that our proposed algorithm achieves close performance to the optimal solution.

AB - In this paper, we study the problem of energy minimization for multicasting in cognitive radio networks, using omnidirectional and directional antennas. Our objectives are to build the multicast routing tree and schedule the secondary users' transmissions such that the total energy consumption is minimized. We consider in this paper the energy consumption due to channels switching, and we study the channel switching and scheduling dependency. We model the problem as a MultiLayer Hyper Graph, then we formulate the optimization problem as Mixed Integer Linear Program (MILP). Moreover, we propose a heuristic algorithm to solve our problem in polynomial time. We also show how the primary users, directional antennas, the number of available channels and channel switching time per frequency jumping step affect the total energy consumption. The simulation results shows that our proposed algorithm achieves close performance to the optimal solution.

KW - cognitive radio network

KW - directional antenna

KW - Energy efficiency

KW - multicast

KW - routing

KW - scheduling

UR - https://www.scopus.com/pages/publications/85028295944

U2 - 10.1109/ICC.2017.7996474

DO - 10.1109/ICC.2017.7996474

M3 - Conference contribution

AN - SCOPUS:85028295944

T3 - IEEE International Conference on Communications

BT - 2017 IEEE International Conference on Communications, ICC 2017

A2 - Debbah, Merouane

A2 - Gesbert, David

A2 - Mellouk, Abdelhamid

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 IEEE International Conference on Communications, ICC 2017

Y2 - 21 May 2017 through 25 May 2017

ER -

Energy efficient multicasting in cognitive radio networks

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this