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Optimal Transmit Strategy for MISO Channels with Joint Sum and Per-antenna Power Constraints
KTH, School of Electrical Engineering (EES), Communication Theory.ORCID iD: 0000-0002-0108-0749
KTH, School of Electrical Engineering (EES), Communication Theory.ORCID iD: 0000-0002-0036-9049
The Information Theory and Applications Chair, Technische Universitat Berlin.
KTH, School of Electrical Engineering (EES), Communication Theory.ORCID iD: 0000-0002-7926-5081
2016 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476Article in journal, Letter (Refereed) Published
Abstract [en]

In this paper, we study an optimal transmit strategy for multiple-input single-output (MISO) Gaussian channels with joint sum and per-antenna power constraints. We study in detail the interesting case where the sum of the per-antenna power constraints is larger than sum power constraint. A closed-form characterization of an optimal beamforming strategy is derived.It is shown that we can always find an optimal beamforming transmit strategy that allocates the maximal sum power with phases matched to the complex channel coefficients. The main result is a simple recursive algorithm to compute the optimal power allocation. Whenever the optimal power allocation of the corresponding problem with sum power constraint only exceeds per-antenna power constraints, it is optimal to allocate maximal per-antenna power to those antennas to satisfy the per-antenna power constraints. The remaining power is divided amongst the other antennas whose optimal allocation follows from a reduced joint sum and per-antenna power constraints problem of smaller channel coefficient dimension and reduced sum power constraint. Finally, the theoretical results are illustrated by numerical examples.

Place, publisher, year, edition, pages
IEEE , 2016.
Keyword [en]
Sum power constraint, per-antenna power constraint, MISO, beamforming, transmit strategy, transmission rate.
National Category
Engineering and Technology
URN: urn:nbn:se:kth:diva-187650DOI: 10.1109/TSP.2016.2563382ISI: 000380117400016ScopusID: 2-s2.0-84980395633OAI: diva2:930870

QC 20160607

Available from: 2016-05-25 Created: 2016-05-25 Last updated: 2016-08-30Bibliographically approved

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