Experimental Analysis and FPGA Implementation of the Real Valued Time Delay Neural Network Based Digital Predistortion

Date

2019-01-01

Author

Yesil, Soner
Sen, Cansu
Yılmaz, Ali Özgür

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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This paper presents an FPGA implementation of the Real Valued Time Delay Neural Network (RVTDNN) based digital predistortion with a very low resource utilization and high throughput. The implementation exploits efficient utilization of FPGA primitives and approximation of activation functions that can be realized with simple logic operations. The proposed modifications and constraints on the algorithms have been decided and verified based on a closed-loop adaptive hardware setup including RFHIC RWP03040-1H PA as the unit under test together with injected RF impairments. Over 20dB of in-band performance gain has been reported with a (4,8,2) RVTDNN configuration utilizing only 52 DSP48 blocks, 224 LUTs and 120 FFs.

Subject Keywords

RVTDNN, Activation function, DPD

URI

https://hdl.handle.net/11511/41038

DOI

https://doi.org/10.1109/icecs46596.2019.8964743

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

S. Yesil, C. Sen, and A. Ö. Yılmaz, “Experimental Analysis and FPGA Implementation of the Real Valued Time Delay Neural Network Based Digital Predistortion,” 2019, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/41038.