Data-Aided Joint Estimation of Carrier Frequency Offset and Frequency-Selective Time-Varying Channel

Ricklin, N.; Zeidler, J.R.

doi:10.1109/icc.2008.116

Cited by 9 publications

(11 citation statements)

References 14 publications

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“…The initial CFO and channel estimator in (29) and (31) reduce to the optimal estimators proposed in [18].…”

Section: Initializationmentioning

confidence: 99%

“…The performance of the proposed initial CFO and channel estimators is marked as 'Iter=0'. The BCRB derived with full training and the performance of the CFO and channel estimation with full training [18] are also shown for comparison. It can be seen that the performance of combined CFO and channel estimation improves significantly in the first iteration.…”

Section: B Performance Of the Proposed Algorithmmentioning

confidence: 99%

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Semiblind Iterative Data Detection for OFDM Systems with CFO and Doubly Selective Channels

He¹,

Ma²,

Wu³

et al. 2010

IEEE Trans. Commun.

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Abstract-Data detection for OFDM systems over unknown doubly selective channels (DSCs) and carrier frequency offset (CFO) is investigated. A semiblind iterative detection algorithm is developed based on the expectation-maximization (EM) algorithm. It iteratively estimates the CFO, channel and recovers the unknown data using only limited number of pilot subcarriers in one OFDM symbol. In addition, efficient initial CFO and channel estimates are also derived based on approximated maximum likelihood (ML) and minimum mean square error (MMSE) criteria respectively. Simulation results show that the proposed data detection algorithm converges in a few iterations and moreover, its performance is close to the ideal case with perfect CFO and channel state information.Index Terms-Carrier frequency offset (CFO), orthogonal frequency division multiplexing (OFDM), doubly selective channel (DSC), data detection, expectation-maximization (EM).

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“…The initial CFO and channel estimator in (29) and (31) reduce to the optimal estimators proposed in [18].…”

Section: Initializationmentioning

confidence: 99%

Section: B Performance Of the Proposed Algorithmmentioning

confidence: 99%

Semiblind Iterative Data Detection for OFDM Systems with CFO and Doubly Selective Channels

He¹,

Ma²,

Wu³

et al. 2010

IEEE Trans. Commun.

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“…The signal is then transmitted through a multi-path time-varying channel which has L independent taps with average power of the l th tap denoted by σ 2 l . The auto-correlation of the l th channel tap follows the classical Jakes' model [6] given by…”

Section: System Modelmentioning

confidence: 99%

“…200811159094. [6], [7]. Unfortunately, a whole OFDM symbol is required for training, which decreases the transmission efficiency.…”

Section: Introductionmentioning

confidence: 99%

Semi-blind CFO, channel estimation and data detection for OFDM systems over doubly selective channels

et al. 2010

Proceedings of 2010 IEEE International Symposium on Circuits and Systems

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Semi-blind joint CFO, channel estimation and data detection for OFDM systems over doubly selective channels (DSCs) is investigated in this work. A joint iterative algorithm is developed based on the maximum a posteriori expectationmaximization (MAP-EM) algorithm. In addition, a novel algorithm is also proposed to obtain the initial estimates of CFO and channels. Simulation results show that the performance of the proposed CFO and channel estimators approaches to that of the estimators with full training at high SNRs. Moreover, after convergence, the performance of data detection is close to the ideal case with perfect CFO and channel state information.

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“…Many approaches that employ NCFSK receivers use training symbols to perform various receiver functions, like channel estimation and start of packet synchronization, e.g., [3]. Also the problem of CFO is highly non-linear in nature and many other approaches can be found in literature that try to estimate the CFO using training sequences, e.g., [4] and [5]. In many cooperative communication applications, the estimator can use the detected data as training sequence for SNR estimation and is reasonable in a multi-hop broadcast application [6], where every node must decode the entire message; the detected data are all assumed to be correct regardless of the value of SNR.…”

Section: Introductionmentioning

confidence: 99%

Pilot assisted SNR estimation in a non-coherent M-FSK receiver with a carrier frequency offset

Hassan¹,

Ingram

2012

2012 IEEE International Conference on Communications (ICC)

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Pilot-assisted estimation of signal-to-noise ratio (SNR) is considered for an orthogonal non-coherent M-ary FSK receiver having a carrier frequency offset (CFO) at the front end. The received signal is also corrupted by symbol-rate Rayleigh fading and additive white Gaussian noise. A two-step estimation procedure is designed by observing received data in the receiver. In the first step, an asymptotically unbiased estimate of CFO is obtained using a moments based approach. This estimate is then used to derive a maximum-likelihood estimator for the SNR. The Cramer Rao Bound for SNR has been derived to compare the overall estimator performance in terms of its variance.

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Data-Aided Joint Estimation of Carrier Frequency Offset and Frequency-Selective Time-Varying Channel

Cited by 9 publications

References 14 publications

Semiblind Iterative Data Detection for OFDM Systems with CFO and Doubly Selective Channels

Semiblind Iterative Data Detection for OFDM Systems with CFO and Doubly Selective Channels

Semi-blind CFO, channel estimation and data detection for OFDM systems over doubly selective channels

Pilot assisted SNR estimation in a non-coherent M-FSK receiver with a carrier frequency offset

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