Estimation of Fast-Fading Channels for Turbo Receivers With High-Order Modulation

Movahedian, Alireza; McGuire, Michael

doi:10.1109/tvt.2012.2227345

Cited by 16 publications

(7 citation statements)

References 21 publications

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“…The receiver realizes an iterative process of channel estimation, symbol equalization and decoding as described in [5], also described in more detail below. A fast-fading channel with L + 1 taps and normalized Doppler frequency of f D is considered.…”

Section: System Modelmentioning

confidence: 99%

“…Iterative channel estimation and decoding has been the subject of interest of many authors (see, e.g., [1]- [5]). A fundamental question is concerned with the capacity advantage offered by an iterative channel estimation scheme over a purely pilot-based one.…”

Section: Introductionmentioning

confidence: 99%

“…Most digital radio receivers use linear minimum mean square (LMMSE) estimators to estimate the radio channel [5], [6]. In this paper, a lower bound on channel LMMSE estimation error for iterative radio receivers is derived.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Capacity of iteratively estimated channels using LMMSE estimators

Movahedian

McGuire

2013

2013 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)

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This paper explores how iterative channel estimation, symbol detection and decoding at the receiver affects the achievable capacity compared with a non-iterative, purely pilotsbased scheme. First, a bound is put on the linear minimum mean-square error (LMMSE) estimator of doubly selective radio channels. Subsequently, a bound on the capacity using an LMMSE estimator is found. These bounds take into account the uncertainty in symbol detection on channel estimation, and incorporate the effect of channel estimation error on channel capacity. The paper describes how bounds can be calculated for typical multipath and fast fading radio channels. The interaction between the symbol detector and the decoder is depicted by exploiting an extrinsic information transfer (EXIT) chart, where a bound on the detector curve is found. With optimal LMMSE pilot-based channel estimation, the bounds demonstrate that iterative channel estimation has little advantage except at fading rates greater than 1% of the symbol rate. To make the results more concrete, finite order modulations are also investigated and compared with the case of Gaussian distributed symbols, showing that the latter can be used to approximate the performance of the former in a more convenient way.

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Section: System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Capacity of iteratively estimated channels using LMMSE estimators

Movahedian

McGuire

2013

2013 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)

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“…Furthermore, to reduce the computational complexity, channel estimation using banded structure of the channel matrix in the frequency domain is used to reduce the dimensionality of the parameter estimation space in [9]. In comparison with the joint channel estimation and data detection, the performance of bit error rate is improved in the iterative scheme using turbo receivers [10][11][12]. However, this performance improvement is achieved at the cost of complexity increasing and data rate decreasing.…”

Section: Introductionmentioning

confidence: 99%

Iterative Channel Estimation and Detection for High-Mobility MIMO-OFDM Systems: Mitigating Error Propagation by Exploiting Error Information

Teng

et al. 2015

Wireless Pers Commun

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Joint channel estimation and data detection are always challenging problems for high mobility multiple-input multiple-output orthogonal frequency division multiplexing systems. Existing iterative schemes focus on the performance improvement from the correct ones, ignoring error propagation from the incorrect ones. To deal with this problem, we propose a new iterative channel estimation and detection scheme that reduces the unexpected effects of both detection errors and channel estimation errors. The interference in channel estimation induced by detection errors is analyzed and transformed as part of the noise, which is filtered out by Kalman estimator using the derived covariance of both the channel and data errors in detection. Besides, to minimize the detection error caused by channel estimation errors, we propose a new detection algorithm with an optimized weight, which is obtained by the error covariance of the estimated channels and the detected data. Furthermore, matrix calculations and parameter approximations are performed to reduce computational complexity. Extensive simulation results are also presented to demonstrate the significant performance improvement in joint channel estimation and data detection with the proposed iterative schemes.

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“…The problem of fast-fading channel estimation for extremely high fading rates up to 1% of the symbol rate has been tackled by several authors, most notably in [1] and [2], where extended Kalman filters(EKF) are proposed, and in [3] and [4] where a zero phase filter (ZPF) is used to de-noise the channel estimates, and thereby combat the computational complexity. Using sufficiently large state vectors, these methods may be applied to higher order modulation schemes, but the computational cost becomes prohibitive, particularly when the radio channel entails a large number of taps.…”

Section: Introductionmentioning

confidence: 99%

Low complexity estimation of fast fading radio channels for higher order modulation

Movahedian

McGuire

2013

2013 IEEE International Conference on Communications (ICC)

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This paper proposes a technique for near optimal estimation of doubly selective fast-fading radio channels with low computational cost. The channel is characterized by an autoregressive (AR) model. A Kalman filter combined with a zero phase filter smoother is used to estimate the channel gains using the detected symbols in a turbo equalization and decoding scheme. It is demonstrated that, compared to other methods, this technique provides a superior bit error rate performance with a low computational cost for fast fading channels. The proposed technique is applied to higher order modulation schemes and the error-rate performance is evaluated. In contrast to other techniques for fast fading channels, the error floor for this technique is at a much higher SNR level.

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Estimation of Fast-Fading Channels for Turbo Receivers With High-Order Modulation

Cited by 16 publications

References 21 publications

Capacity of iteratively estimated channels using LMMSE estimators

Capacity of iteratively estimated channels using LMMSE estimators

Iterative Channel Estimation and Detection for High-Mobility MIMO-OFDM Systems: Mitigating Error Propagation by Exploiting Error Information

Low complexity estimation of fast fading radio channels for higher order modulation

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