Nonlinear Complex Support Vector Regression for Fading Channel Estimation in FBMC-OQAM System

Most channel estimation techniques for orthogonal frequency division multiplexing system are not directly applicable to filter bank multi-carrier with offset quadrature amplitude modulation (FBMC-OQAM) system because of the imaginary interference of FBMC-OQAM system. Thus, a novel support vector regression (SVR) algorithm for fading channel estimation in FBMC-OQAM system is proposed. We propose a nonlinear complex SVR algorithm (NCSVR) adapted to two auxiliary pilots (AP)-based FBMC-OQAM signal, namely as AP-NCSVR. The practicality of our method is proved by simulation results obtained for Jakes fading model and vehicular A model. Simulation results reveal the accuracy of the proposed AP-NCSVR algorithm to estimate channel frequency response coefficients and show that the bit error rate performance of the proposed AP-NCSVR algorithm is better than the conventional interpolation method for Jakes fading model and vehicular A model.

I. Introduction

Orthogonal frequency division multiplexing (OFDM) is widely applied in wireless communications. However, OFDM system leads to high out-of-band interference and low spectral efficiency, moreover it is sensitive to frequency shift of the carrier. In this context, filter bank multi-carrier with offset quadrature amplitude modulation (FBMC-OQAM) system has become a research interest recently [1]. Compared with the OFDM system, the FBMC-OQAM system offers many advantages such as low out-of-band interference [2], high spectral efficiency and flexible bandwidth. However, most of channel estimation techniques for OFDM system cannot be directly applied to FBMC-OQAM system because of the intrinsic imaginary interference [3] of FBMC-OQAM system. Thus, the channel estimation is a challenging task for FBMC-OQAM system.