Optimization of spectrum-energy efficiency in heterogeneous communication network

Fangqing Gu; Ziquan Liu; Yiu Ming Cheung; Hai Lin Liu

doi:10.1007/978-3-319-68759-9_67

Optimization of spectrum-energy efficiency in heterogeneous communication network

Fangqing Gu
, Ziquan Liu
, Yiu Ming Cheung^*
, Hai Lin Liu

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

1 Citation (Scopus)

Abstract

Green communication has become a hot topic in the field of wireless communication. This paper aims to improve the Quality of Service (QoS) of the system and minimizes the energy consumption by the spectrum-energy cooperation between adjacent base stations. We formulate the proposed spectrum-energy cooperation model as a hybrid constrained many-objective optimization problem (MaOP). To improve the efficiency of optimization algorithm, an alternate optimization algorithm is presented to address the proposed complex MaOP. The evolutionary multiobjective algorithm is employed for spectrum cooperation optimization which is discrete optimization problem, meanwhile classical optimization method is employed for energy consumption optimization and energy cooperation optimization that are continuous optimization problems. Simulation results show the effectiveness of the algorithm.

Original language	English
Title of host publication	Simulated Evolution and Learning - 11th International Conference, SEAL 2017, Shenzhen, China, November 10–13, 2017, Proceedings
Editors	Yuhui Shi, Kay Chen Tan, Mengjie Zhang, Ke Tang, Xiaodong Li, Qingfu Zhang, Ying Tan, Martin Middendorf, Yaochu Jin
Publisher	Springer Verlag
Pages	821-832
Number of pages	12
Edition	1st
ISBN (Electronic)	9783319687599
ISBN (Print)	9783319687582
DOIs	https://doi.org/10.1007/978-3-319-68759-9_67
Publication status	Published - 14 Oct 2017
Event	11th International Conference on Simulated Evolution and Learning, SEAL 2017 - Shenzhen, China Duration: 10 Nov 2017 → 13 Nov 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10593 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	11th International Conference on Simulated Evolution and Learning, SEAL 2017
Country/Territory	China
City	Shenzhen
Period	10/11/17 → 13/11/17

UN SDGs

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

SDG 7 Affordable and Clean Energy

User-Defined Keywords

Evolutionary algorithm
Green communication
Spectrum-energy cooperation

Access to Document

10.1007/978-3-319-68759-9_67

Cite this

Gu, F., Liu, Z., Cheung, Y. M., & Liu, H. L. (2017). Optimization of spectrum-energy efficiency in heterogeneous communication network. In Y. Shi, K. C. Tan, M. Zhang, K. Tang, X. Li, Q. Zhang, Y. Tan, M. Middendorf, & Y. Jin (Eds.), Simulated Evolution and Learning - 11th International Conference, SEAL 2017, Shenzhen, China, November 10–13, 2017, Proceedings (1st ed., pp. 821-832). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10593 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-68759-9_67

Gu, Fangqing ; Liu, Ziquan ; Cheung, Yiu Ming et al. / Optimization of spectrum-energy efficiency in heterogeneous communication network. Simulated Evolution and Learning - 11th International Conference, SEAL 2017, Shenzhen, China, November 10–13, 2017, Proceedings. editor / Yuhui Shi ; Kay Chen Tan ; Mengjie Zhang ; Ke Tang ; Xiaodong Li ; Qingfu Zhang ; Ying Tan ; Martin Middendorf ; Yaochu Jin. 1st. ed. Springer Verlag, 2017. pp. 821-832 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{d590cb5e41604dd4afc9d79110f01bda,

title = "Optimization of spectrum-energy efficiency in heterogeneous communication network",

abstract = "Green communication has become a hot topic in the field of wireless communication. This paper aims to improve the Quality of Service (QoS) of the system and minimizes the energy consumption by the spectrum-energy cooperation between adjacent base stations. We formulate the proposed spectrum-energy cooperation model as a hybrid constrained many-objective optimization problem (MaOP). To improve the efficiency of optimization algorithm, an alternate optimization algorithm is presented to address the proposed complex MaOP. The evolutionary multiobjective algorithm is employed for spectrum cooperation optimization which is discrete optimization problem, meanwhile classical optimization method is employed for energy consumption optimization and energy cooperation optimization that are continuous optimization problems. Simulation results show the effectiveness of the algorithm.",

keywords = "Evolutionary algorithm, Green communication, Spectrum-energy cooperation",

author = "Fangqing Gu and Ziquan Liu and Cheung, \{Yiu Ming\} and Liu, \{Hai Lin\}",

note = "Funding Information: This work was supported by the National Natural Science Foundation of China under Grants 61672444, 61673121 and 61703108, in part by the Natural Science Foundation of Guangdong Province under Grant 2017A030310467, the Projects of Science and Technology of Guangzhou under Grant 201508010008, the SZSTI Grant: JCYJ20160531194006833, and the Faculty Research Grant of Hong Kong Baptist University (HKBU) under Project: FRG2/16-17/051.; 11th International Conference on Simulated Evolution and Learning, SEAL 2017 ; Conference date: 10-11-2017 Through 13-11-2017",

year = "2017",

month = oct,

day = "14",

doi = "10.1007/978-3-319-68759-9\_67",

language = "English",

isbn = "9783319687582",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "821--832",

editor = "Yuhui Shi and Tan, \{Kay Chen\} and Mengjie Zhang and Ke Tang and Xiaodong Li and Qingfu Zhang and Ying Tan and Martin Middendorf and Yaochu Jin",

booktitle = "Simulated Evolution and Learning - 11th International Conference, SEAL 2017, Shenzhen, China, November 10–13, 2017, Proceedings",

address = "Germany",

edition = "1st",

}

Gu, F, Liu, Z, Cheung, YM & Liu, HL 2017, Optimization of spectrum-energy efficiency in heterogeneous communication network. in Y Shi, KC Tan, M Zhang, K Tang, X Li, Q Zhang, Y Tan, M Middendorf & Y Jin (eds), Simulated Evolution and Learning - 11th International Conference, SEAL 2017, Shenzhen, China, November 10–13, 2017, Proceedings. 1st edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10593 LNCS, Springer Verlag, pp. 821-832, 11th International Conference on Simulated Evolution and Learning, SEAL 2017, Shenzhen, China, 10/11/17. https://doi.org/10.1007/978-3-319-68759-9_67

Optimization of spectrum-energy efficiency in heterogeneous communication network. / Gu, Fangqing; Liu, Ziquan; Cheung, Yiu Ming et al.
Simulated Evolution and Learning - 11th International Conference, SEAL 2017, Shenzhen, China, November 10–13, 2017, Proceedings. ed. / Yuhui Shi; Kay Chen Tan; Mengjie Zhang; Ke Tang; Xiaodong Li; Qingfu Zhang; Ying Tan; Martin Middendorf; Yaochu Jin. 1st. ed. Springer Verlag, 2017. p. 821-832 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10593 LNCS).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Optimization of spectrum-energy efficiency in heterogeneous communication network

AU - Gu, Fangqing

AU - Liu, Ziquan

AU - Cheung, Yiu Ming

AU - Liu, Hai Lin

N1 - Funding Information: This work was supported by the National Natural Science Foundation of China under Grants 61672444, 61673121 and 61703108, in part by the Natural Science Foundation of Guangdong Province under Grant 2017A030310467, the Projects of Science and Technology of Guangzhou under Grant 201508010008, the SZSTI Grant: JCYJ20160531194006833, and the Faculty Research Grant of Hong Kong Baptist University (HKBU) under Project: FRG2/16-17/051.

PY - 2017/10/14

Y1 - 2017/10/14

N2 - Green communication has become a hot topic in the field of wireless communication. This paper aims to improve the Quality of Service (QoS) of the system and minimizes the energy consumption by the spectrum-energy cooperation between adjacent base stations. We formulate the proposed spectrum-energy cooperation model as a hybrid constrained many-objective optimization problem (MaOP). To improve the efficiency of optimization algorithm, an alternate optimization algorithm is presented to address the proposed complex MaOP. The evolutionary multiobjective algorithm is employed for spectrum cooperation optimization which is discrete optimization problem, meanwhile classical optimization method is employed for energy consumption optimization and energy cooperation optimization that are continuous optimization problems. Simulation results show the effectiveness of the algorithm.

AB - Green communication has become a hot topic in the field of wireless communication. This paper aims to improve the Quality of Service (QoS) of the system and minimizes the energy consumption by the spectrum-energy cooperation between adjacent base stations. We formulate the proposed spectrum-energy cooperation model as a hybrid constrained many-objective optimization problem (MaOP). To improve the efficiency of optimization algorithm, an alternate optimization algorithm is presented to address the proposed complex MaOP. The evolutionary multiobjective algorithm is employed for spectrum cooperation optimization which is discrete optimization problem, meanwhile classical optimization method is employed for energy consumption optimization and energy cooperation optimization that are continuous optimization problems. Simulation results show the effectiveness of the algorithm.

KW - Evolutionary algorithm

KW - Green communication

KW - Spectrum-energy cooperation

UR - https://www.scopus.com/pages/publications/85034260296

U2 - 10.1007/978-3-319-68759-9_67

DO - 10.1007/978-3-319-68759-9_67

M3 - Conference proceeding

AN - SCOPUS:85034260296

SN - 9783319687582

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 821

EP - 832

BT - Simulated Evolution and Learning - 11th International Conference, SEAL 2017, Shenzhen, China, November 10–13, 2017, Proceedings

A2 - Shi, Yuhui

A2 - Tan, Kay Chen

A2 - Zhang, Mengjie

A2 - Tang, Ke

A2 - Li, Xiaodong

A2 - Zhang, Qingfu

A2 - Tan, Ying

A2 - Middendorf, Martin

A2 - Jin, Yaochu

PB - Springer Verlag

T2 - 11th International Conference on Simulated Evolution and Learning, SEAL 2017

Y2 - 10 November 2017 through 13 November 2017

ER -

Gu F, Liu Z, Cheung YM, Liu HL. Optimization of spectrum-energy efficiency in heterogeneous communication network. In Shi Y, Tan KC, Zhang M, Tang K, Li X, Zhang Q, Tan Y, Middendorf M, Jin Y, editors, Simulated Evolution and Learning - 11th International Conference, SEAL 2017, Shenzhen, China, November 10–13, 2017, Proceedings. 1st ed. Springer Verlag. 2017. p. 821-832. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-68759-9_67

Optimization of spectrum-energy efficiency in heterogeneous communication network

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UN SDGs

User-Defined Keywords

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