Kernel-based performance evaluation of coded QAM systems
Abstract
Kernel Bit Error Rate (BER) estimators are of recent interest for Monte Carlo sample size reduction. Until now, they mainly addressed binary modulation systems. In this paper, a kernelbased BER estimator is designed for coded M-ary Quadrature Amplitude Modulation (QAM) systems. The observations from which estimations are made are defined in the form of bounded soft bits. An Epanechnikov kernel function is selected and its smoothing parameter is derived based on the concept of canonical bandwidth. Simulations are run for 4-QAM and 16-QAM systems, involving additive white Gaussian noise and frequency-selective Rayleigh fading channels respectively. Simulation results show that the proposed estimator yields significative sample savings that grow with Eb/N0.