Distributed fractional programming in matched multiple access channels

Alessio Zappone; Eduard Jorswieck; Amir Leshem

doi:10.1109/SAM.2016.7569619

Distributed fractional programming in matched multiple access channels

Alessio Zappone, Eduard Jorswieck, Amir Leshem

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

1 Scopus citations

Abstract

This work deals with the problem of distributed resource allocation in MIMO MC MAC networks. The assignment between users and subcarriers is allocated together with the users' transmit powers for energy efficiency maximization, by means of a novel approach which merges the popular Dinkelbach's algorithm with stable matching. A distributed algorithm is presented, which can be implemented in a fully decentralized way. The algorithm has low computational complexity which comes at the price of weaker optimality properties. Additionally, a novel energy consumption model, which explicitly accounts for the energy consumption due to feedback transmissions, is employed and it is shown that the proposed distributed algorithm can improve the energy efficiency compared to state of the art centralized resource allocation algorithms.

Original language	English
Title of host publication	2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016
Publisher	IEEE Computer Society
ISBN (Electronic)	9781509021031
DOIs	https://doi.org/10.1109/SAM.2016.7569619
State	Published - 15 Sep 2016
Externally published	Yes
Event	2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016 - Rio de Rio de Janeiro, Brazil Duration: 10 Jul 2016 → 13 Jul 2016

Publication series

Name	Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
Volume	2016-September
ISSN (Electronic)	2151-870X

Conference

Conference	2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016
Country/Territory	Brazil
City	Rio de Rio de Janeiro
Period	10/07/16 → 13/07/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

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10.1109/SAM.2016.7569619

Cite this

Zappone, A., Jorswieck, E., & Leshem, A. (2016). Distributed fractional programming in matched multiple access channels. In 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016 Article 7569619 (Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop; Vol. 2016-September). IEEE Computer Society. https://doi.org/10.1109/SAM.2016.7569619

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author = "Alessio Zappone and Eduard Jorswieck and Amir Leshem",

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doi = "10.1109/SAM.2016.7569619",

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Zappone, A, Jorswieck, E & Leshem, A 2016, Distributed fractional programming in matched multiple access channels. in 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016., 7569619, Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop, vol. 2016-September, IEEE Computer Society, 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016, Rio de Rio de Janeiro, Brazil, 10/07/16. https://doi.org/10.1109/SAM.2016.7569619

Distributed fractional programming in matched multiple access channels. / Zappone, Alessio; Jorswieck, Eduard; Leshem, Amir.
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016. IEEE Computer Society, 2016. 7569619 (Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop; Vol. 2016-September).

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

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AB - This work deals with the problem of distributed resource allocation in MIMO MC MAC networks. The assignment between users and subcarriers is allocated together with the users' transmit powers for energy efficiency maximization, by means of a novel approach which merges the popular Dinkelbach's algorithm with stable matching. A distributed algorithm is presented, which can be implemented in a fully decentralized way. The algorithm has low computational complexity which comes at the price of weaker optimality properties. Additionally, a novel energy consumption model, which explicitly accounts for the energy consumption due to feedback transmissions, is employed and it is shown that the proposed distributed algorithm can improve the energy efficiency compared to state of the art centralized resource allocation algorithms.

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Distributed fractional programming in matched multiple access channels

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