User clustering based on correlation in 5G using semidefinite programming

Chit Wutyee Zaw; Yan Kyaw Tun; Choong Seon Hong

doi:10.1109/APNOMS.2017.8094167

User clustering based on correlation in 5G using semidefinite programming

Chit Wutyee Zaw, Yan Kyaw Tun, Choong Seon Hong

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

8 Citations (Scopus)

Abstract

For 5G cellular networks, non-orthogonal multiple access (NOMA) has been recognized as a promising technique. NOMA allows multiple users to access the same channel by adapting successive interference cancellation (SIC) and multiplexing in power domain. This causes the clustering problem to become critical as higher channel gain users need to cancel out the signals of lower channel gain users while the latter has to receive less interference. In this paper, we formulate the user clustering as a correlation clustering problem. We transform the problem by relaxing the clustering variables, and solve using semidefinite programming (SDP). Moreover, a simple iterative power allocation algorithm is nominated. In the simulation results, it can be seen that the correlation clustering using semidefinite programming outperforms the random clustering of users.

Original language	English
Title of host publication	19th Asia-Pacific Network Operations and Management Symposium
Subtitle of host publication	Managing a World of Things, APNOMS 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	342-345
Number of pages	4
ISBN (Electronic)	9781538611012
DOIs	https://doi.org/10.1109/APNOMS.2017.8094167
Publication status	Published - 1 Nov 2017
Event	19th Asia-Pacific Network Operations and Management Symposium, APNOMS 2017 - Seoul, Korea, Republic of Duration: 27 Sept 2017 → 29 Sept 2017

Publication series

Name	19th Asia-Pacific Network Operations and Management Symposium: Managing a World of Things, APNOMS 2017

Conference

Conference	19th Asia-Pacific Network Operations and Management Symposium, APNOMS 2017
Country/Territory	Korea, Republic of
City	Seoul
Period	27/09/17 → 29/09/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

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10.1109/APNOMS.2017.8094167

Cite this

Zaw, C. W., Tun, Y. K., & Hong, C. S. (2017). User clustering based on correlation in 5G using semidefinite programming. In 19th Asia-Pacific Network Operations and Management Symposium: Managing a World of Things, APNOMS 2017 (pp. 342-345). Article 8094167 (19th Asia-Pacific Network Operations and Management Symposium: Managing a World of Things, APNOMS 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/APNOMS.2017.8094167

Zaw, Chit Wutyee ; Tun, Yan Kyaw ; Hong, Choong Seon. / User clustering based on correlation in 5G using semidefinite programming. 19th Asia-Pacific Network Operations and Management Symposium: Managing a World of Things, APNOMS 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 342-345 (19th Asia-Pacific Network Operations and Management Symposium: Managing a World of Things, APNOMS 2017).

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title = "User clustering based on correlation in 5G using semidefinite programming",

abstract = "For 5G cellular networks, non-orthogonal multiple access (NOMA) has been recognized as a promising technique. NOMA allows multiple users to access the same channel by adapting successive interference cancellation (SIC) and multiplexing in power domain. This causes the clustering problem to become critical as higher channel gain users need to cancel out the signals of lower channel gain users while the latter has to receive less interference. In this paper, we formulate the user clustering as a correlation clustering problem. We transform the problem by relaxing the clustering variables, and solve using semidefinite programming (SDP). Moreover, a simple iterative power allocation algorithm is nominated. In the simulation results, it can be seen that the correlation clustering using semidefinite programming outperforms the random clustering of users.",

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Zaw, CW, Tun, YK & Hong, CS 2017, User clustering based on correlation in 5G using semidefinite programming. in 19th Asia-Pacific Network Operations and Management Symposium: Managing a World of Things, APNOMS 2017., 8094167, 19th Asia-Pacific Network Operations and Management Symposium: Managing a World of Things, APNOMS 2017, Institute of Electrical and Electronics Engineers Inc., pp. 342-345, 19th Asia-Pacific Network Operations and Management Symposium, APNOMS 2017, Seoul, Korea, Republic of, 27/09/17. https://doi.org/10.1109/APNOMS.2017.8094167

User clustering based on correlation in 5G using semidefinite programming. / Zaw, Chit Wutyee; Tun, Yan Kyaw; Hong, Choong Seon.
19th Asia-Pacific Network Operations and Management Symposium: Managing a World of Things, APNOMS 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 342-345 8094167 (19th Asia-Pacific Network Operations and Management Symposium: Managing a World of Things, APNOMS 2017).

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

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T1 - User clustering based on correlation in 5G using semidefinite programming

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AU - Tun, Yan Kyaw

AU - Hong, Choong Seon

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N2 - For 5G cellular networks, non-orthogonal multiple access (NOMA) has been recognized as a promising technique. NOMA allows multiple users to access the same channel by adapting successive interference cancellation (SIC) and multiplexing in power domain. This causes the clustering problem to become critical as higher channel gain users need to cancel out the signals of lower channel gain users while the latter has to receive less interference. In this paper, we formulate the user clustering as a correlation clustering problem. We transform the problem by relaxing the clustering variables, and solve using semidefinite programming (SDP). Moreover, a simple iterative power allocation algorithm is nominated. In the simulation results, it can be seen that the correlation clustering using semidefinite programming outperforms the random clustering of users.

AB - For 5G cellular networks, non-orthogonal multiple access (NOMA) has been recognized as a promising technique. NOMA allows multiple users to access the same channel by adapting successive interference cancellation (SIC) and multiplexing in power domain. This causes the clustering problem to become critical as higher channel gain users need to cancel out the signals of lower channel gain users while the latter has to receive less interference. In this paper, we formulate the user clustering as a correlation clustering problem. We transform the problem by relaxing the clustering variables, and solve using semidefinite programming (SDP). Moreover, a simple iterative power allocation algorithm is nominated. In the simulation results, it can be seen that the correlation clustering using semidefinite programming outperforms the random clustering of users.

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Zaw CW, Tun YK, Hong CS. User clustering based on correlation in 5G using semidefinite programming. In 19th Asia-Pacific Network Operations and Management Symposium: Managing a World of Things, APNOMS 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 342-345. 8094167. (19th Asia-Pacific Network Operations and Management Symposium: Managing a World of Things, APNOMS 2017). doi: 10.1109/APNOMS.2017.8094167

User clustering based on correlation in 5G using semidefinite programming

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