MUMBAI, India, July 31 -- Intellectual Property India has published a patent application (202541005276 A) filed by Tejas Networks Limited on January 22, 2025, for Neural Network Based Power Amplifier Linearization System.
Inventors include Dr. Girish Chandra Tripathi; Shrinivas Bhat; Ratnesh Kumar Gaur; Anindya Saha; and Ramesh S.
The application for the patent was published on July 24, 2026, under issue no. 30/2026.
Abstract: Abstract 5 10 15 20 The invention provides a method and system for linearizing a nonlinear power amplifier (PA) in a radio frequency (RF) transmitter. The method begins with splitting the input RF signal into magnitude and phase components. The phase component is then processed using zero-phase digital filtering (ZPDF) in both forward and reverse directions to remove phase distortion. Following this, the phase-processed signal and its magnitude are transformed into in-phase (I) and quadrature (Q) components. These I and Q components are fed into a Time-Delay Feed Forward Neural Network (TDFFNN), which models the nonlinear behavior of the PA. The trained TDFFNN generates a linearized output signal that compensates for the PA’s nonlinear distortions, ensuring improved signal fidelity and transmission quality. The method includes performance evaluation to verify the linearization's effectiveness, including key metrics such as Adjacent Channel Leakage Ratio (ACLR), Normalized Mean Square Error (NMSE), and Error Vector Magnitude (EVM). This approach optimizes RF signal transmission in modern communication systems. Figure 2 (Publication)
Disclaimer: Curated by HT Syndication.
