Multi-objective optimal resource allocation using particle swarm optimization in cognitive radio

Hamza Khan; Sang Jo Yoo

doi:10.1109/CCE.2018.8465749

Multi-objective optimal resource allocation using particle swarm optimization in cognitive radio

Hamza Khan, Sang Jo Yoo

Inha University

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

8 Scopus citations

Abstract

In multi-channel ad-hoc cognitive radio networks, each channel has different wireless channel gain and primary activity so that achievable data rate to secondary users (SUs) and required sensing parameter value are channel dependent. SUs also have different energy saving requirements and data traffic demands. In this paper, a dynamic MAC frame configuration and optimal resource allocation scheme for multi-channel ad-hoc cognitive radio network is proposed. We formulate our dynamic resource allocation model as a constrained optimization problem with multi-objective functions using particle swarm optimization (PSO) algorithm. The proposed PSO scheme guarantees that the allocation captures the individual traffic and energy saving demands and maximizes the objectives functions simultaneously.

Original language	English
Title of host publication	2018 IEEE 7th International Conference on Communications and Electronics, ICCE 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	44-48
Number of pages	5
ISBN (Electronic)	9781538636787
DOIs	https://doi.org/10.1109/CCE.2018.8465749
State	Published - 13 Sep 2018
Event	7th IEEE International Conference on Communications and Electronics, ICCE 2018 - Hue, Viet Nam Duration: 18 Jul 2018 → 20 Jul 2018

Publication series

Name	2018 IEEE 7th International Conference on Communications and Electronics, ICCE 2018

Conference

Conference	7th IEEE International Conference on Communications and Electronics, ICCE 2018
Country/Territory	Viet Nam
City	Hue
Period	18/07/18 → 20/07/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

Adaptive resource allocation
Cognitive radio networks
Particle swarm optimization

Access to Document

10.1109/CCE.2018.8465749

Cite this

Khan, H., & Yoo, S. J. (2018). Multi-objective optimal resource allocation using particle swarm optimization in cognitive radio. In 2018 IEEE 7th International Conference on Communications and Electronics, ICCE 2018 (pp. 44-48). Article 8465749 (2018 IEEE 7th International Conference on Communications and Electronics, ICCE 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCE.2018.8465749

Khan, Hamza ; Yoo, Sang Jo. / Multi-objective optimal resource allocation using particle swarm optimization in cognitive radio. 2018 IEEE 7th International Conference on Communications and Electronics, ICCE 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 44-48 (2018 IEEE 7th International Conference on Communications and Electronics, ICCE 2018).

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title = "Multi-objective optimal resource allocation using particle swarm optimization in cognitive radio",

abstract = "In multi-channel ad-hoc cognitive radio networks, each channel has different wireless channel gain and primary activity so that achievable data rate to secondary users (SUs) and required sensing parameter value are channel dependent. SUs also have different energy saving requirements and data traffic demands. In this paper, a dynamic MAC frame configuration and optimal resource allocation scheme for multi-channel ad-hoc cognitive radio network is proposed. We formulate our dynamic resource allocation model as a constrained optimization problem with multi-objective functions using particle swarm optimization (PSO) algorithm. The proposed PSO scheme guarantees that the allocation captures the individual traffic and energy saving demands and maximizes the objectives functions simultaneously.",

keywords = "Adaptive resource allocation, Cognitive radio networks, Particle swarm optimization",

author = "Hamza Khan and Yoo, {Sang Jo}",

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year = "2018",

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doi = "10.1109/CCE.2018.8465749",

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Khan, H & Yoo, SJ 2018, Multi-objective optimal resource allocation using particle swarm optimization in cognitive radio. in 2018 IEEE 7th International Conference on Communications and Electronics, ICCE 2018., 8465749, 2018 IEEE 7th International Conference on Communications and Electronics, ICCE 2018, Institute of Electrical and Electronics Engineers Inc., pp. 44-48, 7th IEEE International Conference on Communications and Electronics, ICCE 2018, Hue, Viet Nam, 18/07/18. https://doi.org/10.1109/CCE.2018.8465749

Multi-objective optimal resource allocation using particle swarm optimization in cognitive radio. / Khan, Hamza; Yoo, Sang Jo.
2018 IEEE 7th International Conference on Communications and Electronics, ICCE 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 44-48 8465749 (2018 IEEE 7th International Conference on Communications and Electronics, ICCE 2018).

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

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N2 - In multi-channel ad-hoc cognitive radio networks, each channel has different wireless channel gain and primary activity so that achievable data rate to secondary users (SUs) and required sensing parameter value are channel dependent. SUs also have different energy saving requirements and data traffic demands. In this paper, a dynamic MAC frame configuration and optimal resource allocation scheme for multi-channel ad-hoc cognitive radio network is proposed. We formulate our dynamic resource allocation model as a constrained optimization problem with multi-objective functions using particle swarm optimization (PSO) algorithm. The proposed PSO scheme guarantees that the allocation captures the individual traffic and energy saving demands and maximizes the objectives functions simultaneously.

AB - In multi-channel ad-hoc cognitive radio networks, each channel has different wireless channel gain and primary activity so that achievable data rate to secondary users (SUs) and required sensing parameter value are channel dependent. SUs also have different energy saving requirements and data traffic demands. In this paper, a dynamic MAC frame configuration and optimal resource allocation scheme for multi-channel ad-hoc cognitive radio network is proposed. We formulate our dynamic resource allocation model as a constrained optimization problem with multi-objective functions using particle swarm optimization (PSO) algorithm. The proposed PSO scheme guarantees that the allocation captures the individual traffic and energy saving demands and maximizes the objectives functions simultaneously.

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Khan H, Yoo SJ. Multi-objective optimal resource allocation using particle swarm optimization in cognitive radio. In 2018 IEEE 7th International Conference on Communications and Electronics, ICCE 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 44-48. 8465749. (2018 IEEE 7th International Conference on Communications and Electronics, ICCE 2018). doi: 10.1109/CCE.2018.8465749

Multi-objective optimal resource allocation using particle swarm optimization in cognitive radio

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