Scattered Pilots and Virtual Carriers Based Frequency Offset Tracking for OFDM Systems: Algorithms, Identifiability, and Performance Analysis

In this paper, we propose a novel carrier frequency offset (CFO) tracking algorithm for orthogonal frequency division multiplexing (OFDM) systems by exploiting scattered pilot carriers and virtual carriers embedded in the existing OFDM standards. Assuming that the channel remains constant during two consecutive OFDM blocks and perfect timing, a CFO tracking algorithm is proposed using the limited number of pilot carriers in each OFDM block. Identifiability of this pilot based algorithm is fully discussed under the noise free environment, and a constellation rotation strategy is proposed to eliminate the c-ambiguity for arbitrary constellations. A weighted algorithm is then proposed by considering both scattered pilots and virtual carriers. We find that, the pilots increase the performance accuracy of the algorithm, while the virtual carriers reduce the chance of CFO outlier. Therefore, the proposed tracking algorithm is able to achieve full range CFO estimation, can be used before channel estimation, and could provide improved performance compared to existing algorithms. The asymptotic mean square error (MSE) of the proposed algorithm is derived and simulation results agree with the theoretical analysis

CFO estimation in OFDM systems under timing and channel length uncertainties with model averaging

In this letter, we investigate the problem of CFO estimation in OFDM systems when the timing offset and channel length are not exactly known. Instead of explicitly estimating the timing offset and channel length, we employ a multi-model approach, where the timing offset and channel length can take multiple values with certain probabilities. The effect of multimodel is directly incorporated into the CFO estimator. Results show that the proposed estimator outperforms the estimator selecting only the most probable model and the method taking the maximal model. © 2006 IEEE.published_or_final_versio

Estimation of Channel Transfer Function and Carrier Frequency Offset for OFDM Systems with Phase Noise

The joint estimation of carrier frequency offset (CFO) and channel transfer function (CTF) for orthogonal frequency-division multiplexing (OFDM) systems with phase noise is discussed in this paper. A CFO estimation algorithm is developed by exploring the time-frequency structure of specially designed training symbols, and it provides a very accurate estimation of the CFO in the presence of both unknown frequency-selective fading and phase noise. Based on the estimated CFO, phase noise and frequency-selective fading are jointly estimated by employing the maximum a posteriori (MAP) criterion. Specifically, the fading channel is estimated in the form of the frequency-domain CTF. The estimation of the CTF eliminates the requirement of a priori knowledge of channel length, and it is simpler compared with the time-domain channel impulse response (CIR) estimation methods used in the literature. Theoretical analysis with the Cramer-Rao lower bound (CRLB) demonstrates that the proposed CFO and CTF estimation algorithms can achieve near-optimum performance

Bayesian CFO estimation in OFDM systems

This paper addresses the problem of carrier frequency offset (CFO) estimation in orthogonal frequency division multiplexing (OFDM) systems using Bayesian method. Depending on the availability of the noise variance, two general CFO estimators are derived. Furthermore, the two general maximum a posteriori (MAP) estimators are developed into several special cases based on different degrees of prior information on parameters. The relationships between the proposed estimators and existing estimators are comprehensively investigated. Finally, numerical results demonstrate the effects of employing different prior information on the estimation performances. © 2009 IEEE.published_or_final_versionThe IEEE Conference on Wireless Communications and Networking (WCNC 2009), Budapest, Hungary, 5-8 April 2009. In Proceedings of IEEE WCNC, 2009, p. 1-