Carrier-frequency offsets estimation based on ML and ESPRIT method for OFDMA uplink

Abstract

Carrier frequency offsets (CFOs) in orthogonal frequency division multiplexing access (OFDMA) system will introduce intercarrier interference (ICI) and consequently degrade the system performance. A new frequency offsets estimation algorithm based on the combination of ESPRIT (estimation of signal parameters by rotational invariance techniques) and the maximum likelihood (ML) estimation methods for OFDMA system is proposed. The subset of the frequency offsets is first estimated by ESPRIT then the frequency offset of each user is identified in the subset by ML estimation method. The complexity of the combination algorithm is significantly decreased compared with the ML estimator. The algorithm efficiently solves the problem of multi-frequency offsets estimation.