Environment-Adaptable Fast Multi-Resolution (EAF-MR) optimization in large-scale RF-FPGA systems

Published

Journal Article

© 2018, The Author(s). Software-defined radio (SDR) can have high communication quality with a reconfigurable RF front-end. One of the main challenges of a reconfigurable RF front-end is finding an optimal configuration among all possible configurations. In order to efficiently find an optimal configuration, Environment-Adaptable Fast (EAF) optimization utilizes calculated signal-to-interference-and-noise ratio (SINR) and narrows down the searching space (Jun et al., Environment-adaptable efficient optimization for programming of reconfigurable Radio Frequency (RF) receivers, 2014). However, we found several limitations for applying the EAF optimization to a realistic large-scale Radio Frequency-Field Programmable Gate Array (RF-FPGA) system. In this paper, we first investigated two estimation issues of RF impairments: a saturation bias of nonlinearity estimates and limited resources for RF impairment estimation. Using the estimated results, the SINR formula was calculated and used for the Environment-Adaptable Fast Multi-Resolution (EAF-MR) optimization, which was designed by applying the EAF optimization to multi-resolution optimization. Finally, our simulation set-up demonstrated the efficiency improvement of the EAF-MR optimization for a large-scale RF-FPGA.

Full Text

Duke Authors

Cited Authors

  • Jun, M; Negi, R; Yin, S; Alawieh, M; Wang, F; Sunny, M; Mukherjee, T; Li, X

Published Date

  • December 1, 2018

Published In

Volume / Issue

  • 2018 / 1

Electronic International Standard Serial Number (EISSN)

  • 1687-1499

International Standard Serial Number (ISSN)

  • 1687-1472

Digital Object Identifier (DOI)

  • 10.1186/s13638-018-1042-4

Citation Source

  • Scopus