Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
ML estimation of time and frequency offset in OFDM systems
IEEE Transactions on Signal Processing
Joint estimation of channel response, frequency offset, and phase noise in OFDM
IEEE Transactions on Signal Processing
BER of OFDM systems impaired by carrier frequency offset in multipath fading channels
IEEE Transactions on Wireless Communications
SNR Analysis of OFDM Systems in the Presence of Carrier Frequency Offset for Fading Channels
IEEE Transactions on Wireless Communications
Ml joint CFO and channel estimation in OFDM systems with timing ambiguity
IEEE Transactions on Wireless Communications
Pilot tone selection for channel estimation in a mobile OFDM system
IEEE Transactions on Consumer Electronics
Channel quality estimation and rate adaptation for cellular mobile radio
IEEE Journal on Selected Areas in Communications
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Orthogonal frequency division multiplexing (OFDM) systems require the knowledge of signal-to-noise ratio (SNR) at the receiver in order to optimize the system performance. In general, the noise variance is required by the SNR estimator and the knowledge of noise variance also improves the performance of carrier frequency offset (CFO) and channel state estimations. This paper commences by investigating the maximum likelihood noise variance estimator (ML-NVE) in OFDM systems with imperfect synchronization. Theoretical derivations show that both the mean and the variance of the ML-NVE are functions of the CFO and the advanced timing offset (ATO). In particular, it is demonstrated that the mean of the ML-NVE converges to a CFO-independent value as the ATO increases, while the variance converges to a CFO-dependent value. By exploiting the analytical results of the ML-NVE, we further investigate the SNR estimator. It is mathematically demonstrated that the SNR estimate is biased in the presence of CFO and ATO. Finally, the validity of the theoretical observations is confirmed by simulation experiments.