Studies On Carrier Frequency Offset Estimation And Phase Noise Mitigation In OFDM/MIMO-OFDM Systems

Orthogonal Frequency Division Multiplexing (OFDM) and multiple-input multiple-output OFDM (MIMO-OFDM) is a promising technique for broadband wireless communication currently. However, one of the main drawbacks of OFDM and MIMO-OFDM is that it is highly sensitive to carrier frequency offset (CFO) and phase noise (PHN). It is a significant challenge to suppress the effect of CFO and PHN in implementation of OFDM and MIMO-OFDM systems. This dissertation focuses on CFO estimation and PHN mitigation methods for implementation of OFDM and multiple-input multiple-output (MIMO) OFDM systems. The main contributions of the dissertation are as follows:1. A blind CFO estimation algorithm with low complexity was proposed for OFDM in quasi-static multipath channel. The likelihood function of CFO was extracted from signal covariance matrices in frequency domain, which could gave accurate CFO estimation. A closed-form solution could be manipulated with proposed algorithm, so it was computational efficient.2. A decision directed (DD) joint CFO and channel estimator was proposed for OFDM system in time-variant multipath channel. Based on space-alternating generalized expectation-maximization (EM) algorithm, CFO and channel state information were estimated iteratively. Furthermore, a close-form solution for CFO updating was derived by approximation.3. In quasi-static multipath channel, an iterative intercarrier interference (ICI) mitigation algorithm based on decision data was proposed for OFDM system with PHN. By using Huber filter, the conventional maximum likelihood feedback function in iteration was reformed, which could suppress the performance impairment due to decision error. So ICI estimation became more accurate and PHN mitigation has better performance. To reduce complexity in ICI mitigation based on ML criterion, a Majorization Minimize (MM) iterative algorithm for ICI mitigation was derived. By replacing ML cost function for ICI estimation with surrogate function, which is the majorization function of the ML cost function, the proposed PHN mitigation reduced orders of matrix to be inverted and has a lower complexity than the conventional ML PHN mitigation.4. Focus on V-BLAST space diversity multiplexing model in MIMO-OFDM systems, a blind CFO estimator was derived based on the subspace projection approach in quasi-static multipath channel. The proposed algorithm built sub-space of received signal and DFT based on Hadamard product concept. The projection cost function was obtained by analyzing the effect between CFO and Hadamard product sub-space of received signals and time-frequency domain transforming, then CFO was estimated accurately by maximization the Frobenius norm of projection. The proposed estimator has better performance than existing algorithms in literature.5. The performance analysis for OFDM and MIMO-OFDM systems with CFO were discussed detailedly in many literatures, but the effect and performance analysis of PHN were waiting for being studied deeply. The dissertation analyzed BER performance for MIMO-OFDM systems with PHN especially. Then, by reasonable approximate, a closed-form expression of BER was presented, which provided a simple and direct reference for choosing mitigation methods for implementation of MIMO-OFDM system.6. The PHN mitigation methods for MIMO-OFDM systems were focused on common phase error (CPE) mitigation up to now. CPE mitigation only for MIMO-OFDM systems could not give satisfying performance due to neglecting ICI component. To improving PHN mitigation performance further, the dissertation extended the ICI mitigation from OFDM systems to MIMO-OFDM systems based on V-BLAST system model. Compared with CPE mitigation method, the proposed mitigation algorithm can significantly improve the performance of PHN mitigation for MIMO-OFDM.