| Autor: |
Minhee Jun, Rohit Negi, Shihui Yin, Mohamed Alawieh, Fa Wang, Megha Sunny, Tamal Mukherjee, Xin Li |
| Jazyk: |
angličtina |
| Rok vydání: |
2018 |
| Předmět: |
|
| Zdroj: |
EURASIP Journal on Wireless Communications and Networking, Vol 2018, Iss 1, Pp 1-17 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
1687-1499 |
| DOI: |
10.1186/s13638-018-1042-4 |
| Popis: |
Abstract 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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