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Harvested power maximization in QoS-Constrained MIMO SWIPT with generic RF harvesting model
Department of Electrical Engineering, Indian Institute of Technology Delhi, India.ORCID iD: 0000-0002-3225-6495
Mathematical and Algorithmic Sciences Lab, Paris Research Center, Huawei Technologies France SASU, France.
2018 (English)In: 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1-5Conference paper, Published paper (Refereed)
Abstract [en]

We consider the problem of maximizing the harvested power in Multiple Input Multiple Output (MIMO) Simultaneous Wireless Information and Power Transfer (SWIPT) systems with power splitting reception. Different from recently proposed designs, we target with our novel problem formulation at the jointly optimal transmit precoding and receive uniform power splitting (UPS) ratio maximizing the harvested power, while ensuring that the Quality-of-Service (QoS) requirement of the MIMO link is satisfied. We assume generic practical Radio Frequency (RF) Energy Harvesting (EH) receive operation that results in a non-convex optimization problem for the design parameters, which we then solve optimally after formulating it in an equivalent generalized convex form. Our representative results including comparisons of achievable EH gains with benchmark schemes provide key insights on various system parameters.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 1-5
Keywords [en]
Array processing; Convex optimization; Energy harvesting; Energy transfer; MIMO systems; Uninterruptible power systems, Design parameters; Nonconvex optimization; Power splitting; Problem formulation; Qualityof-service requirement (QoS); Radio-frequency energy harvesting; Simultaneous wireless information and power transfer (SWIPT); Transmit precoding, Quality of service
National Category
Communication Systems Signal Processing Computer and Information Sciences
Identifiers
URN: urn:nbn:se:liu:diva-155741DOI: 10.1109/CAMSAP.2017.8313150ISBN: 9781538612514 (electronic)ISBN: 9781538612507 (electronic)ISBN: 9781538612521 (electronic)OAI: oai:DiVA.org:liu-155741DiVA, id: diva2:1299133
Conference
7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 10-13 December, Curacao, Netherlands Antilles
Available from: 2019-03-26 Created: 2019-03-26 Last updated: 2019-03-26Bibliographically approved

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Mishra, Deepak

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
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  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
  • rtf