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Conference Paper: Optimal Power Control for Over-the-Air Computation

TitleOptimal Power Control for Over-the-Air Computation
Authors
KeywordsPower control
Fading channels
Noise reduction
Wireless communication
Distortion
Issue Date2019
PublisherInstitute of Electrical and Electronics Engineers.
Citation
Proceedings of 2019 IEEE Global Communications Conference (GLOBECOM), Waikoloa, Hawaii, USA, 9-13 December 2019, p. 1-6 How to Cite?
AbstractOver-the-air computation (AirComp) of a function (e.g., averaging) has recently emerged as an efficient multi-access scheme for fast aggregation of distributed data at devices (e.g., sensors) to fusion centers (FCs) over wireless channels. To realize reliable AirComp in practice, it is crucial to control the devices' transmit power for coping with channel distortion to achieve the desired magnitude alignment of simultaneous signals. % to strike a balance between enforcing signal-magnitude alignment for overcoming heterogenous channel fading and suppressing noise. In this paper, we study the power control problem for AirComp over fading channels. Our objective is to minimize the computation error by jointly optimizing the transmit power at devices and a signal scaling factor at the FC, called denoising factor, subject to the individual average power constraints at devices. The problem is generally non-convex due to the coupling of transmit power over devices and denoising factor. To optimally solve this problem, we apply the Lagrange duality method via exploiting its ''time-sharing'' property. The derived optimal power control exhibits a regularized channel inversion structure where the regularization has the function of balancing the tradeoff between the signal-magnitude alignment and noise suppression. Moreover, for the special case that only one device is power-limited, we show that the optimal power control for the power-limited device has an interesting channel-inversion water- filling structure, while those for other devices (with sufficiently large power budgets) reduce to channel-inversion power control over all fading states. Numerical results show that the optimal power control remarkably reduces the computation error as compared with other heuristic designs.
Persistent Identifierhttp://hdl.handle.net/10722/291028
ISSN

 

DC FieldValueLanguage
dc.contributor.authorCao, X-
dc.contributor.authorZhu, G-
dc.contributor.authorXu, J-
dc.contributor.authorHuang, K-
dc.date.accessioned2020-11-02T05:50:32Z-
dc.date.available2020-11-02T05:50:32Z-
dc.date.issued2019-
dc.identifier.citationProceedings of 2019 IEEE Global Communications Conference (GLOBECOM), Waikoloa, Hawaii, USA, 9-13 December 2019, p. 1-6-
dc.identifier.issn2334-0983-
dc.identifier.urihttp://hdl.handle.net/10722/291028-
dc.description.abstractOver-the-air computation (AirComp) of a function (e.g., averaging) has recently emerged as an efficient multi-access scheme for fast aggregation of distributed data at devices (e.g., sensors) to fusion centers (FCs) over wireless channels. To realize reliable AirComp in practice, it is crucial to control the devices' transmit power for coping with channel distortion to achieve the desired magnitude alignment of simultaneous signals. % to strike a balance between enforcing signal-magnitude alignment for overcoming heterogenous channel fading and suppressing noise. In this paper, we study the power control problem for AirComp over fading channels. Our objective is to minimize the computation error by jointly optimizing the transmit power at devices and a signal scaling factor at the FC, called denoising factor, subject to the individual average power constraints at devices. The problem is generally non-convex due to the coupling of transmit power over devices and denoising factor. To optimally solve this problem, we apply the Lagrange duality method via exploiting its ''time-sharing'' property. The derived optimal power control exhibits a regularized channel inversion structure where the regularization has the function of balancing the tradeoff between the signal-magnitude alignment and noise suppression. Moreover, for the special case that only one device is power-limited, we show that the optimal power control for the power-limited device has an interesting channel-inversion water- filling structure, while those for other devices (with sufficiently large power budgets) reduce to channel-inversion power control over all fading states. Numerical results show that the optimal power control remarkably reduces the computation error as compared with other heuristic designs.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers.-
dc.relation.ispartofIEEE Global Communications Conference (GLOBECOM) Proceedings-
dc.rightsIEEE Global Communications Conference (GLOBECOM) Proceedings. Copyright © Institute of Electrical and Electronics Engineers.-
dc.rights©2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.subjectPower control-
dc.subjectFading channels-
dc.subjectNoise reduction-
dc.subjectWireless communication-
dc.subjectDistortion-
dc.titleOptimal Power Control for Over-the-Air Computation-
dc.typeConference_Paper-
dc.identifier.emailHuang, K: huangkb@eee.hku.hk-
dc.identifier.authorityHuang, K=rp01875-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/GLOBECOM38437.2019.9013170-
dc.identifier.scopuseid_2-s2.0-85081950073-
dc.identifier.hkuros318019-
dc.identifier.spage1-
dc.identifier.epage6-
dc.publisher.placeUnited States-

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