VSSO Kalman-usage of Barhumi's pilot pattern for channel estimation in MIMO-OFDM systems

Karthik, M.; Sreedhar, D.

doi:10.1049/el.2012.0666

Cited by 4 publications

(4 citation statements)

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“…These results are obtained with approximations that are detailed hereafter. In (30), L is first replaced byL, then |1 −L(e j2πf T )| 2 is approximated by a linear function of (f /f n ) 2r (asymptote) in the low frequency region (f f n ):…”

Section: Asymptotic Mse Of the Rw-ls-catlmentioning

confidence: 99%

On the use of tracking loops for low-complexity multi-path channel estimation in OFDM systems

2015

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International audience—This paper treats pilot aided multi-path channel estimation with tracking loops for OFDM systems under slow to moderate fading conditions. Recent works have presented theoretical results for the tuning of second-order and third-order tracking loops in the particular context of Jakes's Doppler spectrum channel. The method for getting the loop coefficients resorted either to the use of a given constraint, which made the obtained coefficients sub-optimal, or was obtained in part by simulations. Here, we perform a global optimization of the coefficients without constraints to get the optimal coefficients, and analytical formulas are provided. One remarkable result of this optimization is that only the natural frequency depends on the transmission parameters, i.e., the channel Doppler spectrum, the power delay profile, and the noise variance. Consequently, only one parameter has to be tuned. Moreover, asymptotic performance is formulated in a more general way as a function of the 2rth moments of the Doppler spectrum (r is the loop order). Hence, all our derivations are usable for any Doppler spectrum and are not specific to Jakes's Doppler spectrum. A complete table sums up for the three orders the theoretical results of the optimal coefficients together with the asymptotic performance. The performance is also compared with that of the asymptotic Kalman filter

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Section: Asymptotic Mse Of the Rw-ls-catlmentioning

confidence: 99%

On the use of tracking loops for low-complexity multi-path channel estimation in OFDM systems

2015

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“…However, the joint multi-path KF in Equation (21) does not process each path independently, due to the presence of (F H p F p ) −1 in K eq(k) (see Equation (20)). This matrix depends on the power delay profile of the channel.…”

Section: A Joint Multi-path Kfsmentioning

confidence: 99%

“…Reference [19] converts the vector of pilot subcarriers into L multi-path values where L is the number of multi-paths and applies a KF to each path. The VSSO approach (Vector State -Scalar Observation) is proposed in [20]- [23], where single-path KFs are used to separately track each tap of the discrete-time-equivalent (DTE) channel. This has the advantage of reducing the complexity of the joint estimation given by the VSVO (Vector State -Vector Observation) approach, reported in [24] and [25,Equations (18)- (21)].…”

Section: Introductionmentioning

confidence: 99%

“…• is developed in the framework of parametric (physical) channel model with the assumption of primary acquisition of the path delays as in [7], [11], [12], [26]- [28], instead of the DTE channel framework in [20]- [23], • provides analytic results on the tuning and performance of the proposed estimator, • is based on the RW model-based KF (instead of the AR1 model). Our study also permits to shed new light on the behavior of per-path Kalman estimators (per-path RW-KF) and their link with joint multi-path Kalman estimators, this additionally corroborates previous results of [22].…”

Section: Introductionmentioning

confidence: 99%

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Simplified Random-Walk-Model-Based Kalman Filter for Slow to Moderate Fading Channel Estimation in OFDM Systems

Shu

Ros

Simon³

2014

IEEE Trans. Signal Process.

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Abstract-This study deals with multi-path channel estimation for orthogonal frequency division multiplexing systems under slow to moderate fading conditions. Advanced algorithms exploit the channel time-domain correlation by using Kalman Filters (KFs) based on an approximation of the time-varying channel. Recently, it was shown that under slow to moderate fading, near optimal channel multi-path complex amplitude estimation can be obtained by using the integrated Random Walk (RW) model as the channel approximation. To reduce the complexity of the high-dimensional RW-KF for joint estimation of the multi-path complex amplitudes, we propose using a lower dimensional RW-KF that estimates the complex amplitude of each path separately. We demonstrate that this amounts to a simplification of the joint multi-path Kalman gain formulation through the Woodbury's identities. Hence, this new algorithm consists of a superposition of independent single-path single-carrier KFs, which were optimized in our previous studies. This observation allows us to adapt the optimization to the actual multi-path multi-carrier scenario, to provide analytic formulae for the mean-square error performance and the optimal tuning of the proposed estimator directly as a function of the physical parameters of the channel (Doppler frequency, Signal-to-Noise-Ratio, Power Delay Profile). These analytic formulae are given for the first-, second-, and thirdorder RW models used in the KF. The proposed per-path KF is shown to be as efficient as the exact KF (i.e., the joint multipath KF), and outperforms the autoregressive-model-based KFs proposed in the literature.

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Parametric estimation of rapidly varying channels in OFDM systems

Muralidhar¹,

Budavarapu²,

Das

et al. 2015

2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES)

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VSSO Kalman-usage of Barhumi's pilot pattern for channel estimation in MIMO-OFDM systems

Cited by 4 publications

References 4 publications

On the use of tracking loops for low-complexity multi-path channel estimation in OFDM systems

On the use of tracking loops for low-complexity multi-path channel estimation in OFDM systems

Simplified Random-Walk-Model-Based Kalman Filter for Slow to Moderate Fading Channel Estimation in OFDM Systems

Parametric estimation of rapidly varying channels in OFDM systems

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