Optimal dynamic power management for green coordinated multipoint systems

Xin Wang; Tianyi Chen; Yu Zhang; Georgios B Giannakis

doi:10.1109/GLOCOM.2014.7416978

Optimal dynamic power management for green coordinated multipoint systems

Xin Wang, Tianyi Chen, Yu Zhang, Georgios B Giannakis

Electrical and Computer Engineering

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

Abstract

The paper deals with dynamic energy management for smart-grid powered coordinated multi-point (CoMP) transmissions. Aiming to minimize the expected energy transaction cost while guaranteeing the worst-case users' quality of service (QoS), an infinite-horizon optimization problem is formulated to obtain the optimal downlink transmit beamformers that are robust to channel uncertainties. Capitalizing on the virtual-queue based relaxation technique and the stochastic dual-subgradient method, an efficient online algorithm is developed in this context. Without a-priori knowledge of any statistics of the underlying random processes, it is rigorously established that the proposed algorithm is able to yield a feasible and asymptotically optimal solution.

Original language	English (US)
Title of host publication	2015 IEEE Global Communications Conference, GLOBECOM 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479959525
DOIs	https://doi.org/10.1109/GLOCOM.2014.7416978
State	Published - 2015
Event	58th IEEE Global Communications Conference, GLOBECOM 2015 - San Diego, United States Duration: Dec 6 2015 → Dec 10 2015

Publication series

Name	2015 IEEE Global Communications Conference, GLOBECOM 2015

Other

Other	58th IEEE Global Communications Conference, GLOBECOM 2015
Country/Territory	United States
City	San Diego
Period	12/6/15 → 12/10/15

Keywords

CoMP systems
Downlink beamforming
Highpenetration renewables
Stochastic optimization

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10.1109/GLOCOM.2014.7416978

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Wang, X., Chen, T., Zhang, Y., & Giannakis, G. B. (2015). Optimal dynamic power management for green coordinated multipoint systems. In 2015 IEEE Global Communications Conference, GLOBECOM 2015 Article 7416978 (2015 IEEE Global Communications Conference, GLOBECOM 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GLOCOM.2014.7416978

Optimal dynamic power management for green coordinated multipoint systems. / Wang, Xin; Chen, Tianyi; Zhang, Yu et al.
2015 IEEE Global Communications Conference, GLOBECOM 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7416978 (2015 IEEE Global Communications Conference, GLOBECOM 2015).

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

Wang, X, Chen, T, Zhang, Y & Giannakis, GB 2015, Optimal dynamic power management for green coordinated multipoint systems. in 2015 IEEE Global Communications Conference, GLOBECOM 2015., 7416978, 2015 IEEE Global Communications Conference, GLOBECOM 2015, Institute of Electrical and Electronics Engineers Inc., 58th IEEE Global Communications Conference, GLOBECOM 2015, San Diego, United States, 12/6/15. https://doi.org/10.1109/GLOCOM.2014.7416978

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abstract = "The paper deals with dynamic energy management for smart-grid powered coordinated multi-point (CoMP) transmissions. Aiming to minimize the expected energy transaction cost while guaranteeing the worst-case users' quality of service (QoS), an infinite-horizon optimization problem is formulated to obtain the optimal downlink transmit beamformers that are robust to channel uncertainties. Capitalizing on the virtual-queue based relaxation technique and the stochastic dual-subgradient method, an efficient online algorithm is developed in this context. Without a-priori knowledge of any statistics of the underlying random processes, it is rigorously established that the proposed algorithm is able to yield a feasible and asymptotically optimal solution.",

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AB - The paper deals with dynamic energy management for smart-grid powered coordinated multi-point (CoMP) transmissions. Aiming to minimize the expected energy transaction cost while guaranteeing the worst-case users' quality of service (QoS), an infinite-horizon optimization problem is formulated to obtain the optimal downlink transmit beamformers that are robust to channel uncertainties. Capitalizing on the virtual-queue based relaxation technique and the stochastic dual-subgradient method, an efficient online algorithm is developed in this context. Without a-priori knowledge of any statistics of the underlying random processes, it is rigorously established that the proposed algorithm is able to yield a feasible and asymptotically optimal solution.

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KW - Highpenetration renewables

KW - Stochastic optimization

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Optimal dynamic power management for green coordinated multipoint systems

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