A scalable-low cost architecture for high gain beamforming antennas

Omar Bakr*, Mark Johnson, Jungdong Park, Ehsan Adabi, Kevin Jones, Ali Niknejad

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Many state-of-the-art wireless systems, such as long distance mesh networks and high bandwidth networks using mm-wave frequencies, require high gain antennas to overcome adverse channel conditions. These networks could be greatly aided by adaptive beamforming antenna arrays, which can significantly simplify the installation and maintenance costs (e.g., by enabling automatic beam alignment). However, building large, low cost beamforming arrays is very complicated. In this paper, we examine the main challenges presented by large arrays, starting from electromagnetic and antenna design and proceeding to the signal processing and algorithms domain. We propose 3-dimensional antenna structures and hybrid RF/digital radio architectures that can significantly reduce the complexity and improve the power efficiency of adaptive array systems. We also present signal processing techniques based on adaptive filtering methods that enhance the robustness of these architectures. Finally, we present computationally efficient vector quantization techniques that significantly improve the interference cancellation capabilities of analog beamforming architectures. © 2010 IEEE.
Original languageEnglish (US)
Title of host publication2010 IEEE International Symposium on Phased Array Systems and Technology
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages806-813
Number of pages8
ISBN (Print)9781424451272
DOIs
StatePublished - Oct 2010
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: Omar Bakr’s research is sponsored by a fellowship fromKing Abdullah University of Science and Technology. Theauthors would also like to acknowledge the students, facultyand sponsors of the Berkeley Wireless Research Center, andthe National Science Foundation Infrastructure Grant No.0403427.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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