EVM Testing of Wireless OFDM Transceivers Using Intelligent Back-End Digital Signal Processing Algorithms

摘要

In production testing of wireless systems, measurement of EVM (a critical spec that is directly related to bit error rate) incurs significant test time due to the large numbers of symbols that need to be transmitted for reasons of accuracy. In our approach, EVM is modeled as a function of the system static non-idealities (IQ mismatch, gain, IIP3 parameters) and dynamic non-idealities (system noise, VCO phase noise). Using a selected subset of the OFDM tones, the static parameters are calculated first. These are then used to facilitate noise estimation using a back-end constellation compensation and noise amplification procedure. The data generated is used to predict EVM using machine learning methods. Significant reduction in test time is achieved with little loss in test accuracy.