2012
DOI: 10.1109/tsp.2011.2174053
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Joint Carrier Frequency Offset and Channel Estimation for OFDM Systems via the EM Algorithm in the Presence of Very High Mobility

Abstract: Abstract-In this paper, the problem of joint Carrier Frequency Offset (CFO) and channel estimation for OFDM systems over the fast time-varying frequency-selective channel is explored within the framework of the expectation-maximization (EM) algorithm and parametric channel model. Assuming that the path delays are known, a novel iterative pilot-aided algorithm for joint estimation of the multi-path Rayleigh channel Complex Gains (CG) and the Carrier Frequency Offset (CFO) is introduced. Each CG time-variation, … Show more

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Cited by 100 publications
(68 citation statements)
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“…The channels are assumed to be time-invariant, thus the normalized Doppler frequency is selected as f D T = 0.0001. Two Rayleigh channel model [9,10] are chosen as shown in Tables 1 and 2. Figures 3 and 4 show the MSE performances of the Kalman channel estimation algorithms compared to LS and MMSE estimation algorithms in channel model A and model B.…”
Section: Simulation Resultsmentioning
confidence: 99%
“…The channels are assumed to be time-invariant, thus the normalized Doppler frequency is selected as f D T = 0.0001. Two Rayleigh channel model [9,10] are chosen as shown in Tables 1 and 2. Figures 3 and 4 show the MSE performances of the Kalman channel estimation algorithms compared to LS and MMSE estimation algorithms in channel model A and model B.…”
Section: Simulation Resultsmentioning
confidence: 99%
“…Therefore, there is a strong requirement to evaluate the Doppler effects. Current work concerning Doppler estimation pays more attention to the direct DFS estimate in OFDM systems [11,12]. It has been pointed out that multipath effects in high-speed railway channels are not so serious, due to the dominant existence of line-of-sight (LOS) components [12].…”
Section: Related Workmentioning
confidence: 99%
“…As a consequence, the estimation algorithms, which are based on the exact knowledge of the model parameters, can be no longer accurate in this context. Thus the joint state and parameter estimation (i.e., state estimation in the presence of model uncertainty) for linear/nonlinear dynamical systems is a challenging problem in many practical areas, such as target tracking [2], satellite positioning [3] and communication systems [4].…”
Section: Introductionmentioning
confidence: 99%