TY - GEN
T1 - A scalable-low cost architecture for high gain beamforming antennas
AU - Bakr, Osman
AU - Johnson, Mark
AU - Park, Jungdong
AU - Adabi, Ehsan
AU - Jones, Kevin
AU - Niknejad, Ali
N1 - 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.
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=78649269978&partnerID=8YFLogxK
U2 - 10.1109/ARRAY.2010.5613269
DO - 10.1109/ARRAY.2010.5613269
M3 - Conference contribution
AN - SCOPUS:78649269978
SN - 9781424451272
T3 - IEEE International Symposium on Phased Array Systems and Technology
SP - 806
EP - 813
BT - 2010 IEEE International Symposium on Phased Array Systems and Technology, Array 2010
T2 - 4th IEEE International Symposium on Phased Array Systems and Technology, Array 2010
Y2 - 12 October 2010 through 15 October 2010
ER -