Feed-forward neural networks for analog impairment mitigation in high power RF transceivers

Jüschke P, Brendel J, Fischer G, Pascht A (2011)


Publication Type: Conference contribution

Publication year: 2011

Publisher: IEEE

Pages Range: 1650-1653

Conference Proceedings Title: Asia-Pacific Microwave Conference (APMC)

Event location: Melbourne, Australia

URI: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6174084

Abstract

Constantly rising capacity and increasing complexity of mobile communication systems as well as the general demand to reduce the power consumption to get the systems greener, are a big challenge especially for radio frontends. Complex modulated signals of mobile communication standards like LTE have high demands on radio frontends regarding signal requirements. the numerous variety of different standards in different frequency bands have further demands on radio transceivers and its architecture. Flexible radios, suitable for different standards, signals and frequencies with highest efficiency and dynamic are required. This paper shows possibilities to enhance the flexibility of RF transceivers and how to enable future standards and handle high requirements while relaxing configuration using neural networks for signal processing in RF transceivers.

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How to cite

APA:

Jüschke, P., Brendel, J., Fischer, G., & Pascht, A. (2011). Feed-forward neural networks for analog impairment mitigation in high power RF transceivers. In Asia-Pacific Microwave Conference (APMC) (pp. 1650-1653). Melbourne, Australia: IEEE.

MLA:

Jüschke, Patrick, et al. "Feed-forward neural networks for analog impairment mitigation in high power RF transceivers." Proceedings of the Asia-Pacific Microwave Conference (APMC), Melbourne, Australia IEEE, 2011. 1650-1653.

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